Improving Population Services with Application of Genetic Algorithm

- The computer system has now become one of the tools that can be used by everyone in doing work such as office work, managing family card applications, birth certificates, ID cards at the sub-district office. In this case, the problem that often occurs in the lurah office or sub-district office is the queue that is too long in the service of each community who will take care of submitting their file maker. So with that there needs to be a system that will help every employee who can minimize the performance of the person in charge of managing the file. In this research will use scheduling method with genetic algorithm. The results of the research succeeded in minimizing the waiting time by the community who would submit files at the Pancur Batu sub-district office. The time required for registration is 5 minutes per person.


INTRODUCTION
In an office company, it has become the main good service to every consumer as well as in an office in the community such as the sub-district office, to minimize the work of employees or employees, every few community services are processed into a software system (Sharma & Nelson, 2019). Improving services is one of the strategic ways to bind customers in a business world and if in an office, service is also very important, such as in subdistrict offices and other institutions related to public services (Karno et al., 2017). Genetic methods solve the problem in a good way. every process of natural evolution while looking for a good solution in solving problems is one of the advantages of genetic algorithms (Gautama, 2016), (Septyanto et al., 2018). In this research, try to solve the problems that exist in the sub-district office in community service in managing every letter needed. The algorithm to be used is a genetic algorithm. It is hoped that with this system, service problems at the sub-district office which always require a long time can be resolved with this scheduling method. The schedule is a setting of the number of hours that will be used both working and in the administrative queue, while scheduling is a structure of activities that have been arranged (Samaher & Firdaus Mahmudy, 2015), (Gunawan, 2021). A genetic algorithm is a search algorithm in which the mechanism of the system is based on genetics and natural selection. In contrast to conventional genetic algorithms, where the results are obtained randomly from the set of solutions. in a set-set algorithm called puplation, each individual is named a chrom some resulting from a solution. In the genetic algorithm, chromosomes are the most important part, because the chromosome model used will influence the quality of the solution given (al., 2018). Chrome-chromasone process that will continue which is called generation. in each generation, each kromson will be analyzed based on the evaluation function (Pane, Awangga, et al., will converge on the best chromosomes, which is expected to be the optimal solution (Yunus et al., 2018). Service scheduling in each institution becomes a problem if it is not managed properly, when the schedule is compiled in excel or manual form, there is a high probability that data input errors will occur. (Oktarina & Hajjah, 2019). Information systems help everyone's activities (Siddik & Sirait, 2018). The stages of the Genetic Algorithm ( (Jollyta et al., 2017) can be seen in the image below.

Data Collection Methods
This study will use the collection of information with literature studies from library sources to be the basis for problem analysis.

Flow of Analysis
The flow of this study begins with the collection of information processed by genetic methods as shown in the figure below. In order to work on the system, the author makes a research stage as follows 1. Data Collection In this study, it uses 3 data collection processes as follows: a. Literatur Review At this stage, the author seeks references in order to get better ideas in data collection, so the author looks for sources such as national and international journals, books, or sources that can support research. b. Interview At this stage, the author will conduct direct interviews with people related to the object of study so that the data can be more accurate. c. System Analysis At this stage, data analysis will be carried out in order to find out what kind of system the analyst will also know the limit to where. • Data Collection At this stage is the beginning of the research conducted by means of direct observation or interviews to obtain data such as the name of the head of the family and the names of family members.
• Individual Definition What is meant in the individual definition stage is naming the gene to be analyzed, which aims to make it easier when carrying out the genetic algorithm process. Looking for fitness value, probability value, and probability cumulative value. ▪ Crossover Crossover or called cross-breeding is to find new values. Combining two or more chromosomes to form a new chromosome (Pane, Maulana Awangga, et al., 2019). The purpose of crossover is to increase the diversity of strings in a population by crossing between the strings obtained from the previous reproduction. The results of the crossover of the next 2 parental chromosomes will produce 2 offspring, therefore, the number of populations is increased by 2 times from the initial population.

▪ Mutation Process
The mutation process is that the selected chromosome will be randomly mutated, then the mutation point on the chromosome is determined randomly as well.

▪ Chromosome Evaluation
In order to maximize the results of the daily scheduling, the objective function is used. The objective of the objective function is to maximize the fitness value. The value sought in the evaluation of chromosomes is the objective function of each chromosome where the value is obtained from the formula in the genetic algorithm and is generated as shown in the following

CONCLUSION
Based on the background of the problem, this research optimizes the waiting time for community services in managing letters at the sub-district office. The results of this study are based on data that each participant can save about 2 hours, where usually the sub-district office has to wait up to 3 hours and even up to 4 hours, or today it is no longer served.