Jurnal Infortech
type: channel
description: The first Infortech journal was published in 2019, with ISSN: 2715-8160. Jurnal Infortech (Information Technology) is an open access, periodical, and peer-reviewed journal published by LPPM Universitas Bina Sarana Informatika. Infortech Journal is published electronically twice a year in June and December. The editors accept manuscripts in the form of scientific articles and research in the fields of Computer Networks, Software Computing, Information Systems and Technology, Human-Computer Interaction, Knowledge Engineering, Decision Support Systems, Fuzzy Systems, Big Data, Information Security, etc. Infortech does not serve requests for fast track methods. Only articles of high quality and originality will be processed. Please click here to view the history of the Infortech journal. ----------------------------------------------------------------------------------- Indexed: Crossref, Google Scholar, PKP Index, Garuda, etc.
publisher: LPPM Universitas Bina Sarana Informatika
language: en
publication name: Jurnal Infortech
issn: 2715-8160
items: Analysis of Grab Online Motorcycle Taxi Application Usability in Jakarta Using PLS-SEM Approach Model
items: Risk Assessment of Inventory Information Systems Using NIST SP 800-30 at PT XYZ
items: Design of a Smart Chili Mini Greenhouse with ESP32 and Model Predictive Control
items: Evaluation of Intensity Transformation and Histogram-Based Methods for Image Enhancement
items: SMART and CVSS-Based System Vulnerability Prioritization Model
items: Development of a Web-Based Smart Ecosystem Platform for Sustainable Public Service Automation
items: Analysis and Implementation of the PCQ Method in MikroTik-Based Bandwidth Management
items: User Satisfaction Analysis of the LEAD.CO.ID News Portal Performance Using WebQual 4.0
items: Energy Efficiency Optimization in Smart Buildings Using NodeMCU and Cloud Monitoring
items: Analysis Prevalence and Effectiveness of the Stunting Management Intervention Program for Toddlers in Bogor City
items: Optimization of Entropy and MOORA Methods for Comparison of Family Vehicles in Indonesia
items: Implementation of Local Network Access Restriction security on L2TP VPN with Firewall Filter Method
items: Behind the Black Box: Improving Stunting Determinants Analysis Through Explainable Artificial Intelligence
items: Breast Cancer Prediction Optimization Using Support Vector Machine and Naive Bayes Algorithms
items: Analisis Tingkat Kepuasan Pengguna Aplikasi Alpukat Betawi Menggunakan Metode End User Computing Satisfaction (EUCS)
items: Klasifikasi Diagnosis Penyakit Diabetes Menggunakan Algoritma C4.5
items: Implementasi Metode Naïve Bayes Pada Ulasan Pengguna Aplikasi Dana Di Google Play Store
items: Implementasi Sistem Monitoring Jaringan Real-Time Berbasis Open Source Dengan Integrasi Zabbix Dan Telegram
items: Analisis Klasifikasi Dan Prediksi Pola Publikasi Berita Pemprov DKI Jakarta Menggunakan Machine Learning
items: Pieces Framework Untuk Analisis Kepuasan Pengguna Website SMA
items: Analisis dan Evaluasi Usability Website Bank Woori Saudara Indonesia Menggunakan Metode Usability Testing
items: Sistem Informasi Geografis Desa Kaputihan: Implementasi dan Pengelolaan Wilayah dengan Metode Waterfall
items: Peringkat Kepuasan Pelanggan WLAN Lintas jaringan Nusantara menggunakan metode Survei Pengalaman Pengguna
items: Analisis Design UI/UX Pada Aplikasi Let it Flo Menggunakan Metode Design Thinking
items: Implementasi Algoritma C4.5 Untuk Klasifikasi Tingkat Kenaikan Jabatan Pada PT Siprama Cakrawala Depok
items: Penerapan Algoritma Naive Bayes Pada Penerimaan Santri Baru Pendidikan Pondok Pesantren
items: Audit Tata Kelola Teknologi Informasi Sistem ITMS dengan COBIT 5 di Kantor Pertanahan Jakarta Selatan
items: Inovasi Artificial Intelligence dalam Mengidentifikasi Pneumonia Anak untuk Meningkatkan Efisiensi Diagnostik Menggunakan Model CNN
items: Algoritma Random Forest Sebagai Uplift Modeling pada Prediksi Retensi Pelanggan Layanan Telekomunikasi
items: Penerapan Naïve Bayes Berbasis SMOTE Dan Decision Tree Untuk Analisis Sentimen Timnas Indonesia

Analysis of Grab Online Motorcycle Taxi Application Usability in Jakarta Using PLS-SEM Approach Model
type: item
description: Founded in Singapore in 2012, Grab is one of the biggest online transportation companies in Southeast Asia. In Jakarta, GrabBike is part of this service. Even while technology advancements are driving the rise of these apps, issues including poor map accuracy, ugly UI, and frequently missed advertising still exist. Thus, the purpose of this study is to use the Technology Acceptance Model (TAM) to examine the variables that affect how simple it is to use the GrabBike service in Jakarta. Ease of use (Perceived Ease of Use), advantages (Perceived Usefulness), user attitude (Attitude Toward Using), user intention (Behavioral Intention to Use), and actual users (real System Usage) are the five study variables used in this method. Likert scale questionnaires were utilized to gather data from 106 individuals using a descriptive quantitative technique. The partial least squares (PLS)-based structural equation modeling (SEM) technique is used to assess the relationship between variables. The study's findings demonstrate that advantages (perceived usefulness) and usability (perceived ease of use) have a major impact on users' attitudes (attitude toward using). The intention to use (Behavioral Intention to Use) and Actual System Usage are subsequently impacted by this attitude.
subject: Articles
  topic: section
subject: analysis
  topic: keywords
subject: TAM
  topic: keywords
subject: PLS-SEM
  topic: keywords
subject: GrabBike Jakarta
  topic: keywords
subject: User Acceptance
  topic: keywords
creator: Elin Panca Saputra
creator: Adila Faisal
creator: Siti Nurajizah
creator: Aryo Tunjung Kusumo
creator: Tino Dwiantoro
rights: Copyright (c) 2026 Elin Panca Saputra, Adila Faisal; Siti Nurajizah; Aryo Tunjung Kusumo, Tino Dwiantoro https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 63
ending page: 69
doi: 10.31294/infortech.v8i1.12766

Risk Assessment of Inventory Information Systems Using NIST SP 800-30 at PT XYZ
type: item
description: Inventory information systems are vital for automotive dealership operations, but their web-based implementation increases exposure to cybersecurity risks that can disrupt stock management and business continuity. This study aims to identify and evaluate cybersecurity risks in PT XYZ Bandung’s inventory information system using the NIST Special Publication 800-30 Revision 1 framework. A descriptive quantitative approach with a case study method was employed, collecting data through observation, interviews, documentation review, and questionnaires from 20 respondents. The 9-step NIST SP 800-30 process was applied to characterize the system, identify threats and vulnerabilities, assess likelihood and impact, and determine risk levels using the formula Risk = Likelihood × Impact. The results show that PT XYZ faces 4 high-level risks with a score of 9: unauthorized access, stock manipulation, human error, and system downtime. Three medium-level risks were also identified: data loss, malware/ransomware, and DoS/DDoS attacks. Major vulnerabilities include weak passwords, absence of audit logs, inadequate backup, unpatched systems, lack of training, and no server redundancy. Recommended controls include OpenVPN with multi-factor authentication, audit logging, role-based access control, automated backup, regular updates, cybersecurity training, and server redundancy. This study confirms that NIST SP 800-30 provides a structured and practical method for SMEs to assess and prioritize cybersecurity risks, offering actionable recommendations to improve data confidentiality, integrity, and availability at PT XYZ Bandung.
subject: Articles
  topic: section
subject: Cybersecurity Risk Assessment
  topic: keywords
subject: NIST SP 800-30
  topic: keywords
subject: Inventory System
  topic: keywords
subject: Risk Management
  topic: keywords
subject: Automotive Dealership
  topic: keywords
creator: Nanang Hunaifi
creator: Phitsa Mauliana
rights: Copyright (c) 2026 Nanang Hunaifi, Phitsa Mauliana https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 49
ending page: 56
doi: 10.31294/infortech.v8i1.12750

Design of a Smart Chili Mini Greenhouse with ESP32 and Model Predictive Control
type: item
description: Chili cultivation requires stable environmental conditions to achieve optimal plant growth. However, conventional control methods such as On-Off control are reactive and less efficient in handling dynamic environmental changes. This study develops a mini greenhouse system based on the Internet of Things (IoT) integrated with Model Predictive Control (MPC) to maintain the stability of the microclimate for chili plants. The system uses an ESP32 microcontroller as the main controller, DHT22 and soil moisture sensors to monitor temperature, air humidity, and soil moisture, as well as actuators in the form of a fan and water pump. The MPC algorithm is applied to predict system conditions and determine optimal control actions. The system is also integrated with an IoT platform and Telegram notifications for real-time monitoring. Simulation results show that the MPC method provides more stable temperature control compared to the On-Off control method, with overshoot reduced from approximately ±2°C to ±0.5°C and a faster settling time. Therefore, the developed system can improve microclimate control stability and operational efficiency in a mini greenhouse.
subject: Articles
  topic: section
subject: Internet of Things
  topic: keywords
subject: Model Predictive Control
  topic: keywords
subject: Mini Greenhouse
  topic: keywords
subject: Control System
  topic: keywords
subject: Chili plant
  topic: keywords
creator: Salsabila Aurellia Zabrina
creator: Faisal Muttaqin
creator: Agus Salim
rights: Copyright (c) 2026 Salsabila Aurellia Zabrina; Faisal Muttaqin, S.Kom, M.T, Dr. Eng Agussalim, S.Pd., M.T https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 88
ending page: 92
doi: 10.31294/infortech.v8i1.12825

Evaluation of Intensity Transformation and Histogram-Based Methods for Image Enhancement
type: item
description: Digital image enhancement is an important process in image processing because it improves visual quality and supports further image analysis. Images captured by digital devices often suffer from degradation caused by sensor limitations, uneven illumination, low contrast, and non-uniform intensity distribution. This study evaluates several grayscale image enhancement techniques based on intensity transformation and histogram analysis using an interactive Python-based application. The methods include image negative transformation, power-law transformation (gamma correction), gray level slicing, histogram equalization, histogram matching, and Contrast Limited Adaptive Histogram Equalization (CLAHE). Evaluation was performed through visual comparison, histogram analysis, and quantitative measurements, including mean intensity, entropy, Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), standard deviation, and Contrast Improvement Index (CII). The dataset consisted of six standard grayscale images from the Gonzalez and Woods image database: Lena, Cameraman, Boat, House, Peppers, and Baboon. All images were converted to grayscale and resized to 512 × 512 pixels.The results show that each method has different characteristics depending on the image condition. Histogram equalization effectively enhances global contrast but may cause over-enhancement. CLAHE provides more stable local contrast improvement and preserves image details. Power-law transformation offers flexible brightness adjustment, while gray level slicing highlights specific intensity ranges. The developed application supports real-time parameter adjustment and visualization of processed images, histograms, and evaluation metrics, providing an effective framework for image enhancement analysis and learning digital image processing
subject: Articles
  topic: section
subject: Digital Image Processing
  topic: keywords
subject: Intensity Transformation
  topic: keywords
subject: Histogram Analysis
  topic: keywords
subject: Histogram Equalization
  topic: keywords
subject: CLAHE
  topic: keywords
subject: Interactive Application
  topic: keywords
creator: Adhitya Januarizky Hadi Putra
rights: Copyright (c) 2026 Adhitya Januarizky Hadi Putra https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 70
ending page: 81
doi: 10.31294/infortech.v8i1.12786

SMART and CVSS-Based System Vulnerability Prioritization Model
type: item
description: The increasing number of cybersecurity system vulnerabilities each year makes it difficult for organizations to determine the priority scale for remediation. Information system security is an essential aspect of maintaining the continuity of digital services against cyber threats. Poorly managed system vulnerabilities can increase the risk of exploitation by unauthorized parties. This study aims to develop a system vulnerability prioritization model using the SMART (Simple Multi-Attribute Rating Technique) and CVSS (Common Vulnerability Scoring System) methods. CVSS is used to measure the severity level of vulnerabilities based on technical characteristics such as the impact on the confidentiality, integrity, and availability of the system. Furthermore, the SMART method is applied to perform multi-criteria weighting processes in order to generate a more objective ranking of vulnerability handling priorities. The result of this model is a prioritized list of system vulnerabilities intended to assist system administrators in determining mitigation actions more effectively and efficiently. Through this approach, the vulnerability management decision-making process is expected to become more structured, measurable, and targeted.
subject: Articles
  topic: section
subject: Cybersecurity in auto
  topic: keywords
subject: Vulnerability Prioritization
  topic: keywords
subject: SMART
  topic: keywords
subject: CVSS
  topic: keywords
subject: Risk Management
  topic: keywords
creator: Sari Hartini
creator: Rosi Kusuma Serli
rights: Copyright (c) 2026 Sari Hartini, Rosi Kusumasari https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 103
ending page: 108
doi: 10.31294/infortech.v8i1.12867

Development of a Web-Based Smart Ecosystem Platform for Sustainable Public Service Automation
type: item
description: Public service delivery in Indonesia continues to face fundamental challenges including inefficient manual administrative processes, error-prone document validation, and the absence of real-time tracking systems. This research aims to develop the PANDU (Pelayanan Publik Digital Terpadu) platform as a web-based smart ecosystem that automates public services sustainably. The platform is built using the Waterfall development method with Model-View-Controller architecture based on Laravel 12 framework, Filament 4.0 administration panel, and Tailwind CSS 4.0 responsive interface. Four main smart features are integrated: automatic document validation, duplicate request detection within a 30-day window, category-based related service recommendations, and automatic priority calculation using multi-criteria scoring algorithm. The platform produces three separate panels for citizens, officers, and administrators, equipped with real-time tracking system through public API and configurable multi-step approval workflows. Black box testing results using equivalence partitioning technique demonstrate one hundred percent functional success rate, while usability evaluation using System Usability Scale yields an average score in the Excellent category with Acceptable acceptability level. The PANDU platform successfully bridges the gap between smart government theoretical frameworks and operational implementation, providing significant contribution to accelerating sustainable digital transformation of public services in Indonesia.
subject: Articles
  topic: section
subject: Digital Public Service
  topic: keywords
subject: Service Automation
  topic: keywords
subject: Smart Platform
  topic: keywords
subject: E-Government
  topic: keywords
subject: Automatic Document Validation
  topic: keywords
creator: Shoffan Saifullah
creator: Muhammad Iqbal
creator: Lisnawanty Lisnawanty
creator: Weiskhy Steven Dharmawan
creator: Fahmi Raditya
rights: Copyright (c) 2026 Shoffan Saifullah, Muhammad Iqbal, Lisnawanty Lisnawanty, Weiskhy Steven Dharmawan, Fahmi Raditya https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 93
ending page: 102
doi: 10.31294/infortech.v8i1.12830

Analysis and Implementation of the PCQ Method in MikroTik-Based Bandwidth Management
type: item
description: This study aims to implement bandwidth management using the Per Connection Queue (PCQ) method on a MikroTik router to overcome uneven bandwidth distribution. The main problem frequently encountered is the lack of optimal network traffic management, which impacts network performance and work productivity. The research method used is the Network Development Life Cycle (NDLC) with data collection techniques through observation, interviews, and literature studies. The analysis results indicate that the network does not yet have a bandwidth management system and priority allocation among departments. The proposed solution is the implementation of Simple Queue combined with the PCQ method to distribute bandwidth fairly according to the needs of each floor or department. The testing results show that the PCQ method can distribute bandwidth more systematically and stably, with achieved bandwidth values close to the predetermined targets, such as the 17th floor achieving 68.97/69.53 Mbps from a target of 70 Mbps. The study concludes that the combination of Simple Queue and PCQ on a MikroTik router is effective in creating fair, measurable, and efficient bandwidth management that supports business activities.
subject: Articles
  topic: section
subject: Bandwidth Management
  topic: keywords
subject: Per Connection Queue
  topic: keywords
subject: Quality of Service
  topic: keywords
subject: MikroTik Router
  topic: keywords
subject: simple queue
  topic: keywords
creator: Anton
creator: Mochamad Wahyudi
creator: Corleon Adonay Theofilus
creator: Hendra Supendar
creator: Hilda Amalia
creator: Salman Alfarizi
creator: Lise Pujiastuti
rights: Copyright (c) 2026 anton, Corleon Adonay Theofilus, hendra supendar, hilda amalia, salman alfarizi https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 57
ending page: 62
doi: 10.31294/infortech.v8i1.12752

User Satisfaction Analysis of the LEAD.CO.ID News Portal Performance Using WebQual 4.0
type: item
description: The quality of online media platforms is critical for competitiveness in the digital media industry. This study evaluates the quality of LEAD.CO.ID news portal using WebQual 4.0 method with a quantitative approach. Data were obtained from 100 participants using an online survey and subsequently processed with SPSS software employing multiple linear regression analysis. The t-test results show all three variables affect user satisfaction significantly, with usability as the dominant factor (β = 0.512, p < 0.001). The F-test confirms simultaneous significant influence (F = 23.215, p < 0.001). An R² coefficient of 0.420 demonstrates that 42% of the variance in user satisfaction is attributable to the factors incorporated in the proposed model, during 58% is influenced by other factors such as access speed, branding, and exclusive content. Overall, LEAD.CO.ID’s website quality is in the “good” category. However, to increase reader engagement and competitive advantage, managers should implement layered source verification to improve information credibility, and optimize mobile loading time below 3 seconds to strengthen usability. This study contributes to WebQual 4.0 application in local digital media and provides data-driven recommendations for improving reader loyalty.
subject: Articles
  topic: section
subject: WebQual 4.0
  topic: keywords
subject: User Satisfaction
  topic: keywords
subject: Online News Portal
  topic: keywords
subject: Usability
  topic: keywords
subject: LEAD.CO.ID
  topic: keywords
creator: Adjat Sudradjat
creator: Ridho Oktrian Pamungkas
creator: Rahdian Kusuma Atmaja
creator: Yana Iqbal Maulana
creator: Rachman Komarudin
rights: Copyright (c) 2026 Adjat Sudradjat, M.Kom, Ridho Oktrian Pamungkas, S.Kom, Rahdian Kusuma Atmaja, M.Kom, Yana Iqbal Maulana, M.Kom, Rachman Komarudin, M.Kom https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 41
ending page: 48
doi: 10.31294/infortech.v8i1.12737

Energy Efficiency Optimization in Smart Buildings Using NodeMCU and Cloud Monitoring
type: item
description: Inefficient energy management in modern building infrastructure is often caused by a lack of real-time visibility of power consumption and reliance on manual controls that are unresponsive to environmental dynamics. This study proposes the design of an integrated Internet of Things (IoT)-based Smart Building system for energy efficiency optimization. This system was developed using the NodeMCU ESP8266 microcontroller architecture, which orchestrates DHT11 and ACS712 sensors for the acquisition of precise data related to environmental parameters and electrical loads. The main contribution of this research lies in the implementation of a non-blocking programming algorithm to ensure stable sensor readings without interruption, as well as the application of a hysteresis control method in air conditioning (AC) units with thresholds of 30°C (ON) and 28°C (OFF). This hysteresis approach is designed to mitigate compressor short-cycling, which wastes energy. System testing shows that the integration of the RemoteXY mobile interface and OLED display is capable of presenting data telemetry with a response latency of less than 2 seconds. This system has proven effective in providing stable hybrid (automatic and manual) control, offering a low-cost but significant solution for reducing the operational energy consumption of buildings.
subject: Articles
  topic: section
subject: Smart Building
  topic: keywords
subject: Energy Efficiency
  topic: keywords
subject: IoT
  topic: keywords
subject: NodeMCU
  topic: keywords
subject: ESP8266
  topic: keywords
subject: Hysteresis Control
  topic: keywords
creator: Sandro Arnesto
creator: Muhammad Rizqi Saputra
creator: Sujiliani Heristian
creator: Jordy Lasmana Putra
creator: Musriatun Napiah
creator: Rachmat Adi Purnama
rights: Copyright (c) 2026 Sandro Arnesto, Muhammad Rizqi Saputra, Sujiliani Heristian, Jordy Lasmana Putra, Musriatun Napiah, Rachmat Adi Purnama https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 82
ending page: 87
doi: 10.31294/infortech.v8i1.12819

Analysis Prevalence and Effectiveness of the Stunting Management Intervention Program for Toddlers in Bogor City
type: item
description: Stunting remains a major public health challenge in Indonesia. Although various intervention programs have been implemented, more effective strategies are needed to achieve the targeted reduction in prevalence. Based on the findings of this study, the City of Bogor reduced its stunting prevalence from 3.32% in 2022 to 2.35% in 2024. This study aimed to identify the key factors contributing to the success of stunting intervention programs using a Root Cause Analysis (RCA) approach, focusing on program implementation at the sub-district level. The methods included Exploratory Data Analysis (EDA) to examine spatial-temporal trends in stunting prevalence and RCA based on secondary data, program documents, and interpretation of EDA findings. Potential causes affecting program performance were categorized using a fishbone (Ishikawa) framework. The results showed that the decline in stunting prevalence was accompanied by an increase in child weighing coverage from 88.83% to 99.49% and a reduction in disparities across sub-districts. RCA identified six key factors influencing program effectiveness: (1) the number and competence of Posyandu cadres relative to community awareness; (2) standardization of procedures and cross-sectoral coordination; (3) availability of anthropometric measurement equipment; (4) targeted distribution of supplementary feeding (PMT) and vitamins; (5) family participation and nutritional literacy; and (6) data accuracy and timely follow-up of cases. These factors were derived from program documents, secondary data interpretation, and fishbone-based categorization. The findings provide evidence-based recommendations for sustaining stunting reduction through more targeted interventions.
subject: Articles
  topic: section
subject: Prevalence of stunting in Bogor City
  topic: keywords
subject: Program Effectiveness
  topic: keywords
subject: Root Cause Analysis (RCA)
  topic: keywords
subject: Exploratory Data Analysis (EDA)
  topic: keywords
subject: Stunting Reduction
  topic: keywords
creator: Binta Agung Putra Wibawa
creator: Afida Nurul Yasmin
creator: Fauzan Syahrul Jihad
creator: Karlena Indriani
creator: Monikka Nur Winnarto
rights: Copyright (c) 2026 Binta Agung Putra Wibawa, Afida Nurul Yasmin, Fauzan Syahrul Jihad, Karlena Indriani, Monikka Nur Winnarto https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 25
ending page: 34
doi: 10.31294/infortech.v8i1.12671

Optimization of Entropy and MOORA Methods for Comparison of Family Vehicles in Indonesia
type: item
description: This study addresses the issue of subjectivity in determining criteria weights within multi-criteria decision-making for selecting family vehicles in Indonesia. Decision-making in this context often involves multiple factors such as comfort, accommodation, design, features, and fuel consumption, which can lead to biased results if weights are assigned subjectively. To overcome this limitation, this research proposes a combination of the Entropy method and the MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) method within a decision support system framework. The Entropy method is utilized to objectively calculate the weights of each criterion based on data variability, thereby minimizing human bias, while the MOORA method is applied to rank the available vehicle alternatives. The research adopts a quantitative approach by analyzing several popular family vehicles, including Honda BR-V, Mitsubishi Xpander, Suzuki Ertiga, Hyundai Stargazer, and Toyota Avanza. The results indicate that the integration of Entropy and MOORA methods produces more objective and consistent rankings. Based on the calculated preference values, Toyota Avanza achieved the highest rank, followed by Mitsubishi Xpander and Hyundai Stargazer, while Suzuki Ertiga and Honda BR-V ranked lower. In conclusion, the Entropy–MOORA combination proves to be effective in enhancing the objectivity and accuracy of decision-making. This approach can be applied to other multi-criteria problems, providing a systematic and reliable decision support model.
subject: Articles
  topic: section
subject: Decision Support System
  topic: keywords
subject: Entropy Method
  topic: keywords
subject: MOORA
  topic: keywords
subject: Multi-Criteria Decision Making
  topic: keywords
subject: Vehicle Selection
  topic: keywords
creator: Santoso Setiawan
creator: Syamsul Bahri
creator: Wahyudin
creator: Popon Handayani
rights: Copyright (c) 2026 Santoso Setiawan, Syamsul Bahri, Wahyudin, Popon Handayani https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 8
ending page: 16
doi: 10.31294/infortech.v8i1.12652

Implementation of Local Network Access Restriction security on L2TP VPN with Firewall Filter Method
type: item
description: The use of L2TP/IPSec-based Virtual Private Networks (VPNs) has become a common solution for providing remote access to local networks. However, VPN implementations without adequate access restrictions can potentially pose security risks, such as unauthorized access to internal resources, including shared directories on servers. This study aims to implement and analyze a local network access restriction strategy using a firewall filter with an accept-few-drop-any approach on an L2TP VPN network. The research method used is an experiment with the PPDIOO (Prepare, Plan, Design, Implement, Operate, Optimize) model approach. Testing was conducted in two scenarios: before and after the firewall filter implementation. The parameters analyzed included security aspects (access to shared directories) and network performance (latency, throughput, and packet loss). The results showed that before the firewall filter implementation, VPN users could access shared directories without restrictions. After the whitelisting strategy was implemented, access to file sharing services was effectively blocked, while other network services continued to run normally. In terms of performance, the firewall filter implementation did not have a significant impact on network performance.
subject: Articles
  topic: section
subject: VPN
  topic: keywords
subject: Inteconnection
  topic: keywords
subject: Mobile Network
  topic: keywords
subject: Firewall Strategy
  topic: keywords
subject: Network Security
  topic: keywords
creator: Tommi Alfian Armawan Sandi
creator: Firmansyah
creator: Eka Kusuma Pratama
creator: Rian Septian Anwar
rights: Copyright (c) 2026 Tommi Alfian Armawan Sandi, Firmansyah, Eka Kusuma Pratama, Rian Septian Anwar https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 35
ending page: 40
doi: 10.31294/infortech.v8i1.12698

Behind the Black Box: Improving Stunting Determinants Analysis Through Explainable Artificial Intelligence
type: item
description: Stunting is a public health problem that has a long-term impact on the quality of human resources. This study aims to analyze the performance of machine learning algorithms and identify the dominant factors of stunting using the Explainable Artificial Intelligence (XAI) approach. The dataset used was 120,999 toddlers with age, height, gender, and nutritional status attributes. The research stages include data pre-processing, normalization, separation of training and testing data (80:20), modeling using C4.5 algorithms, Support Vector Machine (SVM), and Random Forest, and evaluation using accuracy, precision, recall, and F1-score. The results showed that Random Forest and C4.5 achieved the best performance with an accuracy of 99.93%, while SVM achieved 98.37%. Interpretive analysis using SHAP revealed that height and age were the most dominant factors in the stunting classification with a contribution of 0.59 and 0.41, respectively, while gender contributed relatively small. These findings show that the integration of multi-algorithmic evaluation and XAI not only results in accurate prediction models, but also transparent and interpretive, thus supporting data-driven decision-making in efforts to accelerate stunting reduction in Indonesia
subject: Articles
  topic: section
subject: Stunting
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Explainable AI
  topic: keywords
subject: SHAP
  topic: keywords
subject: Random Forest
  topic: keywords
creator: Wawan Nugroho
creator: Heribertus Ary Setyadi
creator: Supriyanta Supriyanta
creator: Galih Setiawan Nurohim
creator: Annida Purnamawati
rights: Copyright (c) 2026 Wawan Nugroho, Heribertus Ary Setyadi, Supriyanta Supriyanta, Galih Setiawan Nurohim, Annida Purnamawati https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 17
ending page: 24
doi: 10.31294/infortech.v8i1.12656

Breast Cancer Prediction Optimization Using Support Vector Machine and Naive Bayes Algorithms
type: item
description: Breast cancer is ranked as the second most common cause of death for women worldwide. Breast cancer is often found when it has entered the final stage. In general, this is due to slow handling and treatment, so it is very necessary to detect the disease early. The purpose of this study is to determine the performance of the two algorithms, namely Naïve Bayes and Support Vector Machine (SVM) in classifying breast cancer types which will then be analysed and compared the accuracy of the two algorithms. The dataset used in this study, Breast Cancer Wisconsin, is public data originating from UCI Machine Learning, has a total of 683 data with 10 attributes and has two classes, namely benign class with 458 data and malignant class with 241 data. The dataset was split 80:20, with 80% used as training data and 20% as testing data, and then evaluated using cross-validation. The results of the study show that Support Vector Machine (SVM) has the best performance with an accuracy of 96.89% while Naïve Bayes 96.15%. With this accuracy, These results indicate that the SVM model provides better classification performance than Naïve Bayes for the Breast Cancer Wisconsin dataset.
subject: Articles
  topic: section
subject: Data Mining
  topic: keywords
subject: Breast Cancer
  topic: keywords
subject: Naive Bayes
  topic: keywords
subject: Support Vector Machine
  topic: keywords
subject: Machine Learning
  topic: keywords
creator: Devi Wulandari
creator: Qudsiah Azizah
creator: Diah Puspitasari
creator: Kresna Ramanda
creator: Erma Delima Sikumbang
creator: Sulaeman Hadi Sukmana
rights: Copyright (c) 2026 Devi Wulandari, Qudsiah Azizah, Diah Puspitasari, Kresna Ramanda, Erma Delima Sikumbang, Sulaeman Hadi Sukmana https://creativecommons.org/licenses/by-sa/4.0
date: 2026-06-22
publication date: 2026-06-22
starting page: 1
ending page: 7
doi: 10.31294/infortech.v8i1.12629

Analisis Tingkat Kepuasan Pengguna Aplikasi Alpukat Betawi Menggunakan Metode End User Computing Satisfaction (EUCS)
type: item
description: Layanan administrasi dan informasi berbasis daring kini menjadi kebutuhan esensial bagi masyarakat perkotaan, termasuk penduduk DKI Jakarta. Perkembangan teknologi menghadirkan peluang besar dalam menyediakan akses layanan administrasi publik yang lebih cepat, praktis, dan efisien. Salah satu bentuk layanan tersebut adalah aplikasi Alpukat Betawi, yang memberikan kemudahan bagi warga DKI Jakarta untuk mengajukan layanan administrasi kependudukan secara langsung. Namun, dalam pelaksanaannya, masih ditemukan sejumlah kendala dan permasalahan. Oleh karena itu, diperlukan analisis lebih mendalam guna mengevaluasi sejauh mana aplikasi Alpukat Betawi mampu memenuhi kebutuhan penggunanya. Penelitian ini dilakukan dengan pendekatan secara kuantitatif untuk menghimpun dan menganalisis data secara objektif, serta untuk mengukur tingkat kepuasan pengguna aplikasi Alpukat Betawi. Pengukuran dilakukan menggunakan metode End User Computing Satisfaction (EUCS), yang menunjukkan nilai signifikansi uji F sebesar 0,000. Karena nilai tersebut lebih kecil dari ambang batas 0,05, maka hipotesis nol (Ho) ditolak. Dengan demikian, dapat disimpulkan bahwa variabel Content (X1), Accuracy (X2), Format (X3), Ease of Use (X4), dan Timeliness (X5) secara simultan berpengaruh terhadap kepuasan pengguna aplikasi Alpukat Betawi (Y).
subject: Articles
  topic: section
subject: End User Computing Satisfication
  topic: keywords
subject: Kepuasan Pengguna
  topic: keywords
subject: Alpukat Betawi
  topic: keywords
creator: Sayid Ghiazzuddin Ahmad
creator: Tika Adilah M
rights: Copyright (c) 2025 Sayid Ghiazzuddin Ahmad, Tika Adilah M https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 76
ending page: 83
doi: 10.31294/infortech.v7i1.12368

Klasifikasi Diagnosis Penyakit Diabetes Menggunakan Algoritma C4.5
type: item
description: Kesehatan memiliki peranan yang sangat penting untuk menunjang kehidupan manusia, dengan memiliki kesehatan yang baik, manusia dapat melakukan aktifitas dengan produktif dalam sosialisasi atau ekonomi untuk mecapai tujuan hidup. Salah satu penyakit yang dapat mengakibatkan komplikasi bahkan kematian adalah penyakit diabetes. Angka kematian yang tinggi yang diakibatkan oleh penyakit diabetes sangat mengkhawatirkan, diagnosis dini begitu penting dilakukan untuk menekan angka kematian. Selain itu diagnosis dini juga merupakan titik awal penderita untuk mencegah terjadinya diabetes lebih parah dengan melakukan pola hidup sehat agar tidak mengalami komplikasi. Diagnosa penyakit diabetes pada manusia salah satunya dapat dilakukan dengan menerapkan algoritma Machine Learning yaitu C4.5. Penelitian ini bertujuan melakukan diagnosa penyakit diabetes untuk menghindari keterlambatan diagnosis yang dapat mengakibatkan komplikasi pada pasien pengidap penyakit diabetes dengan menggunakan Algoritma C4.5 dalam mendiagnosa dan membuat model prediksi yang menghasilkan sebuah pohon keputusan serta pengujian terhadap hasil diagnosa penyakit diabetes. Dalam penelitian ini terdapat beberapa atribut klasifikasi yaitu gender, age, urea, creatinine, HbA1c, cholesterol, trigeliserida, HDL, LDL, VLDL, dan BMI. Hasil dari penelitian ini dijadikan sebagai acuan untuk dapat melihat apakah seseorang terkena diabetes atau tidak. Hasil akhir dari penelitian ini yaitu menghasilkan nilai akurasi sebesar 99.47%, dimana nilai ini menandakan bahwa algoritma C4.5 mampu melakukan diagnosis penyakit diabetes dengan baik.
subject: Articles
  topic: section
subject: Diabetes
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Algoritma C4.5
  topic: keywords
creator: Indah Sagita Cahyani
creator: Karlena Indriani
creator: Monikka Nur Winnarto
rights: Copyright (c) 2025 Indah Sagita Cahyani, Karlena Indriani, Monikka Nur Winnarto https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 70
ending page: 75
doi: 10.31294/infortech.v7i1.12367

Implementasi Metode Naïve Bayes Pada Ulasan Pengguna Aplikasi Dana Di Google Play Store
type: item
description: Studi ini bertujuan untuk mengalisis sentimen dengan mengimplementasikan metode naive bayes pada ulasan pengguna aplikasi DANA yang terdapat di Google Play Store. Implementasi merupakan proses atau tindakan dalam menerapkan suatu ide, teori, atau rencana ke dalam bentuk yang dapat dijalankan atau digunakan secara nyata. Pendapat pada ulasan aplikasi DANA berjumlah sangat besar. Tujuan dari penelitian ini adalah untuk melakukan analisis sentimen terhadap aplikasi Dana yang ada di Google Play Store menggunakan metode Naive Bayes Classifier. Metode Naïve Bayes adalah salah satu metode klasifikasi yang populer dalam analisis sentimen karena kemampuannya yang tinggi dalam mengklasifikasikan teks berdasarkan probabilitas dari kata-kata yang terdapat di dalamnya. Pengambilan data ulasan dilakukan menggunakan teknik scraping yang dilakukan dengan Google Collab lalu data diolah hingga menhasilkan 500 data. Dari hasil Confusion Matrix menghasilkan akurasi sebesar 80.80%. Hasil penelitian ini membuktikan bahwa algoritma Naive Bayes Classifier memiliki performa yang tinggi dalam menganalisis sentimen ulasan pengguna aplikasi DANA.
subject: Articles
  topic: section
subject: Implementasi
  topic: keywords
subject: DANA
  topic: keywords
subject: metode Naive Bayes
  topic: keywords
subject: scraping
  topic: keywords
subject: google play
  topic: keywords
creator: Raenaldi Ferryan Chandra
creator: Dwi Andini Putri
rights: Copyright (c) 2025 Raenaldi Ferryan Chandra, Dwi Andini Putri https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 64
ending page: 69
doi: 10.31294/infortech.v7i1.12366

Implementasi Sistem Monitoring Jaringan Real-Time Berbasis Open Source Dengan Integrasi Zabbix Dan Telegram
type: item
description: <span style="font-size: 10.0pt; line-height: 107%; font-family: 'Calibri',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; mso-font-kerning: 0pt; mso-ligatures: none; mso-ansi-language: EN-ID; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Pemantauan jaringan secara real-time merupakan kebutuhan penting dalam menjaga kinerja dan keandalan infrastruktur Teknologi Informasi (TI) pada perusahaan modern. Ketika terjadi gangguan pada sistem jaringan atau server, keterlambatan dalam mendeteksi dan menindaklanjuti masalah tersebut dapat berdampak pada penurunan produktivitas, bahkan gangguan layanan bisnis. PT Indo Mutu Makmur menghadapi tantangan serupa, di mana belum tersedianya sistem monitoring otomatis menyebabkan keterbatasan dalam mengelola infrastruktur TI secara efisien. Penelitian ini mengusulkan integrasi antara Zabbix sebagai sistem monitoring jaringan berbasis open source dan Telegram sebagai media pengiriman notifikasi real-time kepada administrator. Sistem ini dirancang untuk memantau parameter penting seperti penggunaan CPU, memori, kapasitas disk, dan lalu lintas jaringan. Apabila terdeteksi adanya anomali seperti layanan SNMP yang tidak aktif, sistem secara otomatis akan mengirimkan peringatan melalui bot Telegram. Metode yang digunakan adalah metode model Network Development Life Cycle. Hasil pengujian menunjukkan bahwa sistem mampu mendeteksi gangguan dengan akurat dan mengirimkan notifikasi dalam waktu kurang dari lima detik, memungkinkan respons cepat dari tim teknis. Dengan demikian, implementasi sistem ini memberikan solusi monitoring yang efisien, terjangkau, dan mudah diadopsi oleh perusahaan berskala kecil hingga menengah. Sistem ini juga meningkatkan visibilitas infrastruktur TI dan mempercepat pengambilan keputusan dalam penanganan insiden.
subject: Articles
  topic: section
subject: Zabbix
  topic: keywords
subject: Network Monitoring
  topic: keywords
subject: Telegram
  topic: keywords
creator: Anton Anton
creator: Hendra Supendar
rights: Copyright (c) 2025 Anton, Hendra Supendar https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 56
ending page: 63
doi: 10.31294/infortech.v7i1.12365

Analisis Klasifikasi Dan Prediksi Pola Publikasi Berita Pemprov DKI Jakarta Menggunakan Machine Learning
type: item
description: Dalam era digital, akses informasi melalui berbagai platform online semakin meningkat, termasuk melalui situs web resmi pemerintah. Pemerintah Provinsi DKI Jakarta secara rutin menyampaikan kebijakan, program, dan berita melalui situs webnya. Namun, volume data yang besar dan keragaman topik berita menghadirkan tantangan dalam pengelolaan dan analisis informasi secara efisien. Penelitian ini mengembangkan model klasifikasi dan prediksi pola publikasi berita menggunakan tiga algoritma machine learning yaitu: Support Vector Machine (SVM), Naïve Bayes, dan Random Forest. Dataset yang digunakan berupa berita yang dipublikasikan oleh Pemprov DKI Jakarta selama tahun 2023. Pra-pemrosesan data meliputi pembersihan teks, case folding, tokenizing, normalisasi, penghapusan stopword, dan stemming. Model SVM dan Naïve Bayes diterapkan untuk klasifikasi berita, sedangkan Random Forest digunakan untuk memprediksi pola publikasi berita harian. Proses tuning hyperparameter dilakukan menggunakan GridSearchCV guna meningkatkan kinerja model. Penilaian terhadap klasifikasi dilakukan dengan diukur dari beberapa parameter yaitu akurasi, precision, recall, dan F1-score, sedangkan evaluasi prediksi menggunakan MAE, MSE, dan R². Temuan dari penelitian ini mengindikasikan bahwa SVM menunjukkan performa yang baik dengan akurasi 95%, sedangkan Random Forest berhasil memprediksi pola publikasi berita dengan R² sebesar 0,82. Penelitian ini diharapkan dapat mendukung pengelolaan informasi publik secara lebih efisien dan menyediakan wawasan mengenai pola publikasi berita oleh Pemprov DKI Jakarta.
subject: Articles
  topic: section
subject: Klasifikasi Berita
  topic: keywords
subject: Prediksi Pola Publikasi
  topic: keywords
subject: Machine Learning
  topic: keywords
creator: Rifky Permana
creator: Febby Ariyanti Herdiana
rights: Copyright (c) 2025 Rifky Permana, Febby Ariyanti Herdiana https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 50
ending page: 55
doi: 10.31294/infortech.v7i1.12364

Pieces Framework Untuk Analisis Kepuasan Pengguna Website SMA
type: item
description: Website merupakan salah satu dari perkembangan di bidang teknologi informasi yang dapat menyediakan informasi secara cepat untuk para pengguna website, Website juga terhubung dengan jaringan internet sehingga mudah di akses dari manapun. SMA KORPRI Bekasi merupakan sekolah menengah atas swasta yang telah menggunakan website sebagi sarana untuk menyebarkan informasi kepada penguna website dan membantu proses belajar para siswa-siswi. Untuk melihat seberapa efektif penggunaan website SMA KORPRI Bekasi akan dilakukan analisis tentang kepuasan pengguna dalam menggunakan website. Ada beberapa Teknik analisis yang dapat digunakan dalam melakukan analisis salah satunya adalah dengan metode Pieces Framework. Pieces Framework merupakan metode yang memiliki 6 variabel yaitu : performance, Information and Data, Economy, Control and Securty,Eficiency dan service untuk menganalisis kelemahan. Tujuan penelitian ini untuk melihat tingkat kepuasan pengguna website SMA KORPRI Bekasi. Hasil dari analisis menunjukan bahwa rata-rata siswa-siswi merasa puas. Dengan nilai rata dari setiap variable performace (3,40), information (3,77), economic (3,63), control (3,84), effeciency (3,82), dan service (3,78). Pengguna situs web SMA Korpri rata-rata puas dengan situs web sekolah tersebut.
subject: Articles
  topic: section
subject: Pieces Framework
  topic: keywords
subject: Analisis Kepuasan Pengguna
  topic: keywords
subject: Website SMA
  topic: keywords
creator: Apri Adiyantoro
creator: Sri Muryani
rights: Copyright (c) 2025 Apri Adiyantoro, Sri Muryani https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 43
ending page: 49
doi: 10.31294/infortech.v7i1.12363

Analisis dan Evaluasi Usability Website Bank Woori Saudara Indonesia Menggunakan Metode Usability Testing
type: item
description: Website Bank Woori Saudara (BWS) yang mulai aktif sejak 2014 hingga penelitian ini dilakukan masih dalam tahap pengembangan dan belum pernah dievaluasi dengan menyeluruh. Sebagai platform digital yang mendukung aktivitas perbankan, website BWS menyediakan berbagai informasi dan layanan. Salah satu aspek terpenting yang menentukan kualitas sebuah website adalah usability atau kegunaan. Evaluasi terhadap kegunaan dan efektivitas website menjadi penting untuk meningkatkan kemudahan serta loyalitas pengguna. Penelitian ini bertujuan untuk mengidentifikasi masalah pada website BWS dengan menerapkan metode Usability Testing berdasarkan lima aspek, yaitu aspek Learnability (kegunaan), Memorability (kemudahan dalam mengingat), Efficiency (efisiensi), Error (pencegahan kesalahan) dan Satisfaction (kepuasan pengguna). Metode pengumpulan data dilakukan melalui pengamatan langsung, wawancara, dan angket secara daring. Penentuan jumlah sampel menggunakan teknik Simple Random Sampling dengan jumlah responden sebanyak 100 user, sementara analisis data dilakukan dengan statistik deskriptif dan uji Independent Sample T-Test menggunakan SPSS. Hasil evaluasi usability pada website BWS mengindikasikan bahwa variabel Learnability, Efficiency, dan Errors memiliki pengaruh signifikan terhadap tingkat kepuasan pengguna. Sebaliknya, Memorability tidak menunjukkan pengaruh signifikan dan perlu ditingkatkan. Untuk meningkatkan usability secara keseluruhan, disarankan agar website BWS memperbarui informasi, memperbaiki fitur yang ada, menambahkan fitur “Daftar” dan “Search Engine”, serta meningkatkan aspek Efficiency dan mengurangi kesalahan (Errors), sambil tetap menjaga aspek Memorability. Evaluasi juga perlu dilakukan secara berkala dengan melibatkan pengguna secara langsung. Dapat disimpulkan penelitian ini menekankan bahwa peningkatan aspek usability seperti pembaruan informasi, efisiensi navigasi, dan minimisasi kesalahan dapat meningkatkan kepuasan pengguna, sehingga website BWS dapat m…
subject: Articles
  topic: section
subject: Analisis
  topic: keywords
subject: evaluasi
  topic: keywords
subject: usability testing
  topic: keywords
subject: website
  topic: keywords
creator: Mutiara Putri Anjani
creator: Ika Kurniawati
creator: Fachri Amsury
creator: Heriyanto Heriyanto
rights: Copyright (c) 2025 Mutiara Putri Anjani, Ika Kurniawati, Fachri Amsury, Heriyanto https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 34
ending page: 42
doi: 10.31294/infortech.v7i1.12362

Sistem Informasi Geografis Desa Kaputihan: Implementasi dan Pengelolaan Wilayah dengan Metode Waterfall
type: item
description: Pemerintah desa seringkali menghadapi tantangan dalam memetakan batas wilayah dan menentukan titik lokasi bangunan fasilitas umum. Ketidakakuratan dan keterlambatan dalam pemetaan tersebut tidak hanya mengganggu proses administrasi, tetapi juga menyulitkan pengunjung dari luar desa dalam menemukan lokasi tujuan. Dampak ini berpotensi menghambat berbagai aspek pengembangan desa, mulai dari perencanaan infrastruktur hingga penyediaan layanan publik yang efektif. Saat ini, aplikasi peta daring seperti Google Maps telah banyak digunakan untuk kebutuhan navigasi. Namun, aplikasi tersebut memiliki keterbatasan, seperti waktu yang diperlukan untuk meng-update titik lokasi baru dan kesulitan dalam menampilkan lokasi yang kurang populer atau dinamis. Akibatnya, data yang disajikan tidak selalu mencerminkan kondisi lapangan secara real-time atau spesifik terhadap kebutuhan warga desa. Oleh karena itu, diperlukan sebuah sistem informasi geografis (SIG) yang dirancang khusus untuk kebutuhan desa. Tujuan dibuatnya Aplikasi SIG ini diharapkan mampu memetakan batas wilayah secara akurat, menandai titik lokasi fasilitas umum, serta menyediakan informasi detail mengenai jaringan jalan dan lokasi pemukiman. Metode yang digunakan dalam penelitian ini yaitu metode waterfall.Dengan solusi ini, diharapkan akses informasi bagi pengunjung dan perencanaan administratif oleh pemerintah desa dapat berjalan lebih efisien dan responsif terhadap perubahan kondisi di lapangan.
subject: Articles
  topic: section
subject: SIG
  topic: keywords
subject: Google Maps
  topic: keywords
subject: Metode Waterfall
  topic: keywords
creator: Yani Sri Mulyani
rights: Copyright (c) 2025 Yani Sri Mulyani https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 26
ending page: 33
doi: 10.31294/infortech.v7i1.12361

Peringkat Kepuasan Pelanggan WLAN Lintas jaringan Nusantara menggunakan metode Survei Pengalaman Pengguna
type: item
description: Untuk mengetahui Kepuasan Pelanggan penggunan Wifi Lintas Jaringan Nusantara dilakukan penelitian agar diketahui variabel-variabel yang mempengaruhi kepuasan klien terhadap layanan wifi PT Lintas Jaringan Nusantara. Penyebaran kuesioner menggunakan metode User Experience Questionnaire (kuesioner yang digunakan untuk mengukur pengalaman pengguna terhadap sebuah produk atau sistem), dengan memeriksa kualitas layanan dan loyalitas pelanggan sebagai variabel berpengaruh untuk kepuasan pelanggan. Identifikasi dengan pengalaman pelanggan. Analisis perilaku partisipan melibatkan beberapa langkah, seperti yang dijelaskan dalam metodologi investigasi. Sebagai informasi digunakan data kuantitatif nominal atau numerik, diproses, dan digunakan untuk menghasilkan kesimpulan penelitian. Informasi ini dianggap mendasar karena berasal dari ringkasan awal atau asli. Pemeriksaan validitas dan reliabilitas digunakan untuk menganalisis data untuk penyebaran kuesioner. Masing-masing kategori berikut memiliki skor rata-rata di atas rata-rata: kebaruan 1,18, akurasi 1,29, kejelasan 1,19, efisiensi 1,43), daya tarik 1,44, dan stimulasi 1,29. Diharapkan bahwa temuan studi ini akan memberikan informasi yang berguna bagi PT Lintas Jaringan Nusantara dalam meningkatkan kualitas layanan dan loyalitas pelanggan mereka.
subject: Articles
  topic: section
subject: Kepuasan Pelanggan
  topic: keywords
subject: Wifi
  topic: keywords
subject: UEQ
  topic: keywords
creator: TB Didi Aswadi
creator: Yuli Komalasari
creator: Chalimatusadiah Chalimatusadiah
creator: Diah Wijayanti
creator: Indria Widyastuti
rights: Copyright (c) 2025 TB Didi Aswadi, Yuli Komalasari, Chalimatusadiah, Diah Wijayanti, Indria Widyastuti https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 20
ending page: 25
doi: 10.31294/infortech.v7i1.12360

Analisis Design UI/UX Pada Aplikasi Let it Flo Menggunakan Metode Design Thinking
type: item
description: PT.Jasamarga Tollroad Operator telah melakukan pengembangan pada sistem transaksi jalan tol yang disebut Single Lane Free Flow atau pembayaran nir sentuh pada gerbang tol. Untuk mendukung sistem pembayaran nir sentuh PT.Jasamarga Tollroad Operator meluncurkan Aplikasi “Let It Flo” yang dapat di install pada Android dan juga IOS. Aplikasi Let It Flo ini pada rating Playstore dan Appstore dinilai masih terdapat beberapa kendala tampilan yang kurang menarik, pengalaman pengguna yang buruk dapat menyebabkan berkurangnya pengguna atau kegagalan produk, pewarnaan pada aplikasi Let It Flo yang kurang menarik perhatian pengguna, tata letak button yang membingungkan pengguna. Dengan penerapan Design Thingking untuk meningkatkan usability dilakukan design ulang Prototype dan System Usability Scale untuk pengujian Prototype mendapatkan pengalaman positif dengan nilai 74% dan disimpulkan acceptable, grade scale B dan adjective good, serta acceptable pada Prototype Aplikasi Let It Flo.
subject: Articles
  topic: section
subject: UI/UX/ Design
  topic: keywords
subject: Design Thingking
  topic: keywords
subject: System Usability Scale
  topic: keywords
creator: Dimas Primadani
creator: Siti Nurlela
rights: Copyright (c) 2025 Dimas Primadani, Siti Nurlela https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 14
ending page: 19
doi: 10.31294/infortech.v7i1.12359

Implementasi Algoritma C4.5 Untuk Klasifikasi Tingkat Kenaikan Jabatan Pada PT Siprama Cakrawala Depok
type: item
description: Dalam era modern, kenaikan jabatan menjadi tantangan bagi perusahaan karena proses promosi yang sering kali dianggap subjektif. Penelitian ini bertujuan untuk membangun model klasifikasi kenaikan jabatan menggunakan Algoritma C4.5 guna meningkatkan objektivitas keputusan promosi karyawan. Data dikumpulkan dari database karyawan PT Siprama Cakrawala serta melalui kuesioner kepada manajer, supervisor, dan karyawan. Variabel yang digunakan mencakup kinerja, pengalaman kerja, tingkat pendidikan, sikap kerja, dan keterlibatan dalam proyek. Data dianalisis menggunakan RapidMiner dengan teknik Decision Tree, kemudian divalidasi menggunakan metode Cross Validation untuk mengukur akurasi model. Hasil penelitian menunjukkan bahwa model yang dihasilkan memiliki tingkat akurasi sebesar 88.91%, dengan classification error sebesar 11.09%. Variabel pengalaman kerja memiliki pengaruh paling dominan dengan nilai information gain tertinggi dan menjadi root node dalam pohon keputusan. Precision model menunjukkan bahwa algoritma C4.5 cukup andal dalam mengklasifikasikan karyawan yang layak dan belum layak mendapatkan promosi jabatan, dengan nilai precision kelayakan sebesar 91.11% dan precision belum layak sebesar 87.50%. Dengan hasil ini, model yang dikembangkan dapat digunakan sebagai alat bantu dalam proses pengambilan keputusan promosi karyawan.
subject: Articles
  topic: section
subject: Algoritma C4.5
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Klasifikasi Karyawan
  topic: keywords
creator: Rahayu Ningsih
creator: Muhammad Devan Basunanda
creator: Wati Erawati
rights: Copyright (c) 2025 Rahayu Ningsih, Muhammad Devan Basunanda, Wati Erawati https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 6
ending page: 13
doi: 10.31294/infortech.v7i1.12358

Penerapan Algoritma Naive Bayes Pada Penerimaan Santri Baru Pendidikan Pondok Pesantren
type: item
description: Penerimaan santri baru merupakan tahapan penting dalam sistem pendidikan di sekolah formal maupun di pondok pesantren. Di beberapa pondok pesantren proses penerimaan santri baru sering kali dilakukan secara manual, sehingga rentan terhadap kesalahan data dan penilaian subjektif, yang menyebabkan hasil dari tes seleksi tidak akurat. Seperti yang terjadi di pesantren Shalahuddin Al-Ayyubi Kabupaten Bekasi. Penelitian ini bertujuan untuk membantu pengelola pesantren menetapkan kelulusan tes seleksi santri baru dengan menerapkan algoritma naïve bayes dalam proses penerimaan santri baru, supaya hasil dari tes seleksi bisa lebih akurat dan terkomputerisasi. Penelitian menggunakan pendakatan kuantitatif dengan memanfaatkan data awal sebanyak 47 record, yang dibagi menjadi data testing, 80% untuk data pelatihan dan 20% untuk data pengujian. Hasil penelitian menunjukkan bahwa algoritma naïve bayes mampu memberikan akurasi sebesar 88.89%, dengan precision sebesar 66,67%, recall sebesar 100% dan nilai AUC sebesar 1,000. Dari hasil prediksi, 7 santri dinyatakan diterima dan 2 santri tidak diterima. Terbukti bahwa algoritma Naïve Bayes memiliki tingkat akurasi yang tinggi serta mampu memberikan hasil prediksi yang valid dan terukur.
subject: Articles
  topic: section
subject: Penerimaan Santri Baru
  topic: keywords
subject: Pesantren
  topic: keywords
subject: Algoritma Naïve Bayes
  topic: keywords
creator: Yopi Handrianto
creator: Muadz Zidan AlWafi
rights: Copyright (c) 2025 Yopi Handrianto, Muadz Zidan AlWafi https://creativecommons.org/licenses/by-sa/4.0
date: 2025-06-16
publication date: 2025-06-16
starting page: 1
ending page: 5
doi: 10.31294/infortech.v7i1.12357

Audit Tata Kelola Teknologi Informasi Sistem ITMS dengan COBIT 5 di Kantor Pertanahan Jakarta Selatan
type: item
description: Kantor Pertanahan Kota Administrasi Jakarta Selatan merupakan unit pelaksana teknis dari Kementerian Agraria dan Tata Ruang/BPN yang memanfaatkan Sistem Manajemen Talenta ASN (ITMS) untuk mendukung pengelolaan data kepegawaian dan pengembangan kompetensi aparatur. Namun, efektivitas tata kelola teknologi informasi pada sistem ini belum pernah dievaluasi secara formal. Penelitian ini bertujuan untuk menilai tingkat kapabilitas proses tata kelola TI pada sistem ITMS menggunakan kerangka kerja COBIT 5, khususnya pada domain DSS (Deliver, Service and Support) dan MEA (Monitor, Evaluate and Assess). Hasil audit menunjukkan bahwa MEA01 memperoleh tingkat kapabilitas tertinggi sebesar 5,52, menandakan sistem telah menyediakan informasi yang akurat dan transparan. Secara umum, rata-rata kapabilitas berada pada level 3,78, mendekati level 4 (Predictable Process). Proses DSS01, DSS03, DSS06, dan MEA01 telah mencapai atau melampaui target, sedangkan DSS02, DSS04, DSS05, dan MEA02 masih menunjukkan gap, dengan celah terbesar pada DSS04 sebesar -1,56. Rekomendasi perbaikan mencakup penguatan sistem pelaporan insiden, peningkatan kesiapan layanan melalui pelatihan berkala, serta penguatan kebijakan keamanan informasi. Evaluasi ini diharapkan dapat menjadi dasar pengambilan keputusan dalam peningkatan tata kelola TI yang lebih efektif dan berkelanjutan.
subject: Articles
  topic: section
subject: Audit TI
  topic: keywords
subject: COBIT 5
  topic: keywords
subject: ITMS
  topic: keywords
subject: Kantor Pertanahan
  topic: keywords
creator: Rani Irma Handayani
creator: Normah Normah
creator: Bakhtiar Rifai
creator: Nurmawati Nurmawati
rights: Copyright (c) 2025 Nurmawati, Rani Irma Handayani, Normah, Bakhtiar Rifai https://creativecommons.org/licenses/by-sa/4.0
date: 2025-12-24
publication date: 2025-12-24
starting page: 95
ending page: 103
doi: 10.31294/infortech.v7i2.11636

Inovasi Artificial Intelligence dalam Mengidentifikasi Pneumonia Anak untuk Meningkatkan Efisiensi Diagnostik Menggunakan Model CNN
type: item
description: Pneumonia adalah salah satu jenis infeksi yang paling sering ditemui dan berisiko tinggi di seluruh dunia, yang mengakibatkan angka penyakit dan kematian yang tinggi, khususnya di kalangan populasi yang rentan seperti anak-anak. Dengan demikian, penelitian ini bertujuan untuk menciptakan sistem pintar yang mampu mengidentifikasi pneumonia secara otomatis melalui gambar thorax dengan memanfaatkan arsitektur Convolutional Neural Networks (CNN). Dalam penelitian ini, beberapa arsitektur CNN, yaitu MobileNet V2, ResNet, dan EfficientNet diuji untuk mencari model terbaik, dengan mempertimbangkan risiko overfitting dan penggunaan optimizer yang tepat. Metode yang digunakan mencakup pengumpulan data, preprocessing, pembagian dataset menjadi data train, test dan validasi, serta penerapan teknik transfer learning. Evaluasi dilakukan berdasarkan parameter kinerja seperti akurasi, sensitivitas dan presisi untuk menilai performa model. Hasil penelitian menunjukkan bahwa arsitektur MobileNet V2 memberikan kinerja terbaik dengan akurasi mencapai 93%. Model ini kemudian diimplementasikan dalam sistem cerdas yang dapat mempercepat dan mempermudah proses diagnosis pneumonia sehingga memberikan manfaat signifikan bagi sektor kesehatan dan masyarakat luas. Penelitian ini juga menekankan pentingnya teknik optimasi yang tepat dalam memastikan model dapat bekerja secara optimal di aplikasi dunia nyata.
subject: Articles
  topic: section
subject: Pneumonia
  topic: keywords
subject: Arsitekture CNN
  topic: keywords
subject: MobileNet V2
  topic: keywords
creator: Kresna Ramanda
creator: Monikka Nur Winnarto
creator: Sucitra Sahara
rights: Copyright (c) 2025 Kresna Ramanda, Monikka Nur Winnarto, Sucitra Sahara https://creativecommons.org/licenses/by-sa/4.0
date: 2025-12-24
publication date: 2025-12-24
starting page: 124
ending page: 129
doi: 10.31294/infortech.v7i2.11383

Algoritma Random Forest Sebagai Uplift Modeling pada Prediksi Retensi Pelanggan Layanan Telekomunikasi
type: item
description: Persaingan penyedia layanan telekomunikasi mengakibatkan potensi pelanggan berpindah layanan ke penyedia lain atau disebut dengan customer churn. Hal ini dapat mengancam keberlangsungan hidup provider tersebut. Oleh karena itu perlu dilakukan upaya prediksi pelanggan yang mungkin akan melakukan churn agar perusahaan dapat mempersiapkan strategi untuk membuat pelanggan dapat kembali berlangganan pada provider tersebut atau disebut dengan customer retention. Oleh karena itu pada penelitian ini akan digunakan algoritma random forest sebagai uplift modeling untuk prediksi retensi pelanggan layanan telekomunikasi. Uplift modeling akan berfokus pada mereformulasi target variabel dari pelanggan yang akan melakukan churn menjadi pelanggan yang mungkin akan melakukan retensi. Sementara algoritma random forest dipilih karena mampu membagi kriteria pemecahan kedalam ruang/segmen yang sesuai dirancang untuk uplift modeling. Metode penelitian yang digunakan pada penelitian ini adalah CRISP-DM yang merupakan kerangka penelitian data mining untuk penelitian lintas industri. Hasil penelitian ini menunjukan bahwa algoritma yang diusulkan menghasilkan akurasi sebesar 91,87%.
subject: Articles
  topic: section
subject: customer churn
  topic: keywords
subject: customer retention
  topic: keywords
subject: uplift modeling
  topic: keywords
subject: random forest
  topic: keywords
creator: Rizki Tri Prasetio
creator: Yudi Ramdhani
creator: Vito Hafizh Cahaya Putra
creator: Pratiwi Pratiwi
rights: Copyright (c) 2025 Rizki Tri Prasetio, Yudi Ramdhani, Vito Hafizh Cahaya Putra, Pratiwi https://creativecommons.org/licenses/by-sa/4.0
date: 2025-12-24
publication date: 2025-12-24
starting page: 84
ending page: 88
doi: 10.31294/infortech.v7i2.11577

Penerapan Naïve Bayes Berbasis SMOTE Dan Decision Tree Untuk Analisis Sentimen Timnas Indonesia
type: item
description: Penelitian ini bertujuan menganalisis persepsi publik terhadap kinerja Tim Nasional Indonesia pada masa kepelatihan Patrick Kluivert melalui analisis sentimen komentar penggemar di Instagram. Media sosial dipilih karena menjadi wadah utama bagi penggemar untuk menyampaikan opini dan dukungan secara langsung. Sebanyak 300 komentar dikumpulkan dari akun resmi Timnas Indonesia menggunakan teknik data scraping. Data tersebut kemudian melalui proses pembersihan dan pelabelan sebelum dianalisis. Untuk menyeimbangkan distribusi data, digunakan metode Synthetic Minority Over-sampling Technique (SMOTE). Klasifikasi sentimen dilakukan dengan membandingkan dua algoritma machine learning, yaitu Naïve Bayes dan Decision Tree, guna menilai kinerja masing-masing dalam mengenali sentimen positif maupun negatif. Hasil penelitian menunjukkan bahwa model Decision Tree memiliki performa lebih baik, khususnya dengan nilai recall tinggi pada kelas positif, yang menunjukkan kemampuannya dalam mendeteksi sentimen positif secara akurat. Meskipun demikian, model ini masih lemah dalam mengidentifikasi sentimen negatif. Secara keseluruhan, temuan ini menggambarkan antusiasme dan kecintaan besar penggemar terhadap Timnas Indonesia, terlepas dari hasil pertandingan yang diperoleh.
subject: Articles
  topic: section
subject: Analisis Sentimen
  topic: keywords
subject: Naive Bayes
  topic: keywords
subject: Decision Tree
  topic: keywords
subject: SMOTE
  topic: keywords
creator: Ghudzamir 'Ammar Ibrahim Pasaribu
creator: Ghofar Taufik
creator: Giatika Chrisnawati
creator: Indarti
creator: Dewi Laraswati
creator: Dinda Ayu Muthia
rights: Copyright (c) 2025 Ghudzamir 'Ammar Ibrahim Pasaribu, Ghofar Taufik, Giatika Chrisnawati, Indarti, Dewi Laraswati, Dinda Ayu Muthia https://creativecommons.org/licenses/by-sa/4.0
date: 2025-12-24
publication date: 2025-12-24
starting page: 152
ending page: 160
doi: 10.31294/infortech.v7i2.11570