Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Building of Informatics, Technology and Science
Yayan Sopyan
STMIK LIKMI, Bandung
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analisis Sistem Pendukung Keputusan Penerima Beasiswa Terbaik Menerapkan Metode Weight Aggregated Sum Product Assesment (WASPAS) dengan Pembobotan Rank Order Centroid (ROC) Sopyan, Yayan; Lesmana, Agria Dwi
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2525

Abstract

KIP Kuliah is one of the government's education equity programs. The KIP Kuliah program is intended for students who graduate from high school or its equivalent, but not all students can benefit from the KIP Kuliah program. Students who are entitled to benefit from the KIP Kuliah program are those who have academic potential but whose economic circumstances do not allow them to continue their education at tertiary institutions. The process of selecting scholarship recipients is a new problem for tertiary institutions, where quotas and the number of applicants are sometimes unbalanced, so a rigorous selection process is needed based on an assessment of the economic condition of the family and the achievements of the scholarship recipient candidates. Therefore, a Decision Support System (DSS) is needed to overcome this problem using the Weighted Aggregated Sum Product Assessment (WASPASS) and rank order centroid (ROC) methods to find the best alternative scholarship recipients. The results obtained from this study are the recipients of the best alternative scholarship A6, with the highest score of 0.57, followed by other alternatives based on the ranking results in this DSS calculation.
Analisis Algoritma K-Means dan Davies Bouldin Index dalam Mencari Cluster Terbaik Kasus Perceraian di Kabupaten Kuningan Sopyan, Yayan; Lesmana, Agrian Dwi; Juliane, Christina
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2697

Abstract

In marriage, the thing that is most avoided is a divorce. Divorce is the termination of the husband and wife relationship which is carried out legally at the time of trial. From year to year, there is an increase in the number of divorces in Indonesia, including the number of divorces in Kuningan Regency. This study analyzes divorce cases in villages in Kuningan Regency, the analysis is carried out by using data mining clustering methods using the K-Means algorithm. The clustering method is grouping data based on the same characteristics. In determining the number of clusters by using the value of the smallest Davies Bouldin Index, it is hoped that the number of clusters formed can be more optimal. The results of this study are that there are 4 clusters consisting of villages or sub-districts with different divorce rates, namely the highest divorce rate, high divorce rate, medium divorce rate, low divorce rate, and lowest divorce rate
Co-Authors Christina Juliane, Christina Lesmana, Agria Dwi Lesmana, Agrian Dwi