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Kombinasi Multi Factor Evalution Process (MFEP) Dan Equal Weight Dalam Penentuan Tingkat Kesejahteraan Masyarakat Sudipa, I Gede Iwan; Aryati, Komang Sri
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i1.300

Abstract

Community welfare reflects the equal distribution of social life in society. Various government assistance is provided to support the process of equal distribution of welfare. By knowing each community's level of welfare, aid can be provided on the right target principle. There are 21 assessment indicators used in determining the level of community welfare. In determining the level of community welfare, it is necessary to apply multicriteria decision-making techniques to determine the grouping of each category of community level. This study used a combination of the Multi-Factor Evaluation Process (MFEP) method to calculate the final evaluation value of 21 assessment indicators and determine the level of community welfare categories. Equal Weight method for determining the weight according to the number of assessment criteria with the same criterium importance. Combining the two methods above is to produce an alternative evaluation value and a category of community welfare level based on the final value of each alternative to the assessment indicator.
Kombinasi Multi Factor Evalution Process (MFEP) Dan Equal Weight Dalam Penentuan Tingkat Kesejahteraan Masyarakat Sudipa, I Gede Iwan; Aryati, Komang Sri
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i1.300

Abstract

Community welfare reflects the equal distribution of social life in society. Various government assistance is provided to support the process of equal distribution of welfare. By knowing each community's level of welfare, aid can be provided on the right target principle. There are 21 assessment indicators used in determining the level of community welfare. In determining the level of community welfare, it is necessary to apply multicriteria decision-making techniques to determine the grouping of each category of community level. This study used a combination of the Multi-Factor Evaluation Process (MFEP) method to calculate the final evaluation value of 21 assessment indicators and determine the level of community welfare categories. Equal Weight method for determining the weight according to the number of assessment criteria with the same criterium importance. Combining the two methods above is to produce an alternative evaluation value and a category of community welfare level based on the final value of each alternative to the assessment indicator.
Sistem Informasi Akademik Serta Penentuan Kelas Unggulan Dengan Algoritama K-Means di SMP Negeri 3 Ubud Kusuma, Aniek Suryanti; Aryati, Komang Sri
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 1 No 3 (2019): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (730.697 KB) | DOI: 10.33173/jsikti.29

Abstract

SMP Negeri 3 Ubud is educational establishments located at Silungan Lotunduh Ubud. SMP Negeri 3 Ubud has excellent class, to define the student entry into superior class using a manual system that is using Microsoft Excel. This system is inefficient because it requires a lot of time when creating. In addition to the data processing of academic, especially a student's scores are still manually so difficult when creating repot. Based on the problems it created an Academic Information System as well as the determination of class excellent using clustering method with K-Means algorithm. with the academic information system and determination superior class computerized then administrative staff easier and faster in processing student data, teacher data and employee data. The method used to determine which class superior that is Clustering K-Means algorithm. With the K-Means algorithm will process the value system and grouping students according to the value closest to the cluster center point. With this system superior class determination more quickly and efficiently
Optimasi Pendistribusian Kelas Pada Dosen di STMIK STIKOM Indonesia Menggunakan Algoritma Genetika Kusuma, Aniek Suryanti; Aryati, Komang Sri
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 2 No 1 (2019): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (419.33 KB) | DOI: 10.33173/jsikti.49

Abstract

The stage of class scheduling starts from scheduling courses in classes, then distributing the class to lecturers. The process of distributing classes to lecturers becomes an obstacle for the STMIK STIKOM Indonesia academic body because the academic body must adjust the existing class with the lecturer who is interested in it as well as the lecturer chosen to support a class so that it does not have classes that have a time conflict. One method for solving these problems is by using genetic algorithms that work by generating a number of random solutions and then processing the collection of solutions in a genetic process. There are eight genetic algorithm procedures, which are random chromosome generation procedures, chromosome repair to validate chromosomes from their limits, fitness function to calculate the feasibility of a solution, crossover, mutation, child repair and elitism. The output of this research is in the form of an analysis and determination of the system requirements that must exist. In addition, it produces a trial report on the effect of genetic parameters to determine the effect of changes in the value of genetic parameters on the fitness value and the time used to carry out the distribution process.