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All Journal Bulletin of Network Engineer and Informatics (BUFNETS)
Windu Antara Kesiman
Universitas Pendidikan Ganesha
Computer Science & IT

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Implementation of K-Means Clustering and Graph Methods to Enhance the Success Rate of the Bulan Bintang Application Ni Komang Sriasih; Windu Antara Kesiman; I Made Sunarya
Bulletin of Network Engineer and Informatics Vol. 4 No. 2 (2026): BUFNETS (Bulletin of Network Engineer and Informatics) October 2026
Publisher : PT. GWEX NET PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59688/vscwhj56

Abstract

The BULAN BINTANG (Fostering and Overcoming Bullying in Children) is an application used to find out cases of bullying between students at SMP Negeri 2 Ubud. This application utilizes Sociometery to detect social gaps between students by filling in questionnaires given by the guidance and counseling teacher in each class. The sociometric questionnaire contains the selection of 2 people who are liked in the class and 2 students who are not liked in the class along with their permission. The results of the sociometric questionnaire will be processed using the k-means clustering method to group students who are liked (popular) and students who are not liked (isolated). The results of student grouping will then be processed using the graph method. The graph methods used are directed graphs, combined graphs, weighted graphs and color graphs. From the color graph process, it can be indicated which students are speculated to be potential bullies and targets of bullying. From implementing the k-means clustering and graph method in the BULAN BINTANG application, the BK teacher received 95% satisfaction from the respondents and then obtained an accuracy of 80% matching data for problematic students.
Co-Authors I Made Sunarya Ni Komang Sriasih