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All Journal REKAYASA JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) IJISTECH (International Journal Of Information System & Technology) Indonesian Journal of Applied Informatics Industri Inovatif : Jurnal Teknik Industri Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika JATI (Jurnal Mahasiswa Teknik Informatika) SKANIKA: Sistem Komputer dan Teknik Informatika IJISTECH Jurnal Informatika Teknologi dan Sains (Jinteks) Prosiding Seminar Nasional Pengabdian Masyarakat The Journal of Enhanced Studies in Informatics and Computer Applications International Journal of Computer Science and Information Technology
Joseph Dedy Irawan
Institut Teknologi Nasional Malang
Agriculture, Biological Sciences & Forestry Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Physics Social Sciences

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PENERAPAN METODE K-MEANS ++ UNTUK PENGELOMPOKAN WILAYAH RAWAN KEKERASAN ANAK DAN PEREMPUAN DI KABUPATEN NAGEKEO Marshella Angela Merici Poa; Ahmad Fahrudi Setiawan; Joseph Dedy Irawan
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 9 No 1 (2026): Jurnal SKANIKA Januari 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v9i1.3633

Abstract

Violence against women and children in Nagekeo Regency is a crucial social issue requiring targeted intervention. The Department of PMD-P3A faces challenges in analyzing regional vulnerability, which has historically been manual and subjective. This research aims to develop a web-based vulnerability grouping system implementing the K-Means++ Clustering method. This method was strategically selected for its ability to optimize initial centroid selection through distance probability calculations, resulting in more stable and accurate clustering compared to the standard K-Means algorithm. The system was developed using the Laravel framework and MySQL database, utilizing historical data from 2020 to 2025. The clustering process is based on two key parameters: Type of Violence and Place of Occurrence, mapping regions into three levels: Highly Vulnerable, Vulnerable, and Non-Vulnerable. The results demonstrate excellent system performance with a Silhouette Score of 0.6633 and a Davies-Bouldin Index (DBI) of 0.4520, indicating a solid and optimally separated cluster structure. Beyond statistical data, the system provides interactive digital mapping visualizations. This implementation is expected to serve as a decision-support tool for the local government in formulating more effective and efficient social protection policies in Nagekeo Regency.
Co-Authors Ahmad Bahrul Ilmi Ahmad Fahrudi Setiawan AHMAD FAISOL Alfin Ardiansyah Betty Dewi Puspasari Deddy Rudhistiar Dhayal Gustopo Dimas Rizky Pratama Eko Heri Susanto Emmalia Adriantantri F. Yudi Limpraptono Faisol , Ahmad Hafid Zulkarnain Hirarki Ardi Pratama I Made Paundra D.W Wisesa Ida Bagus Suardika Iftitah Ruwana Indyastuti, Desi Ivano, Kevin Majesta Kahpi Harhab Ludytio Akhsanul In'am M. Zainuri Hasan Maqila Sulaiman Abu Zakaria Marshella Angela Merici Poa Michael Jordan Mira Orisa Muhammad Farhan Alauddin Munasih Primaswara Prasetya , Renaldi Renaldi P. P Renaldi P. P. Renaldi Primaswara Prasetya Renaldi Primaswara Prasetya Ridho Arif Wicaksono Ridho Arif Wicaksono Rivaldi, Arrealdo Roy Mahendra Pedro Pratama Sentot Achmadi Sentot Achmadi Sixtus Yoebel Augusto Sonny Prasetio Sony Prasetio Sri Indriani Sumanto Suryo Adi Suryo Adi Wibowo Suryo Adi Wibowo Susanto, Eko Heri Thomas Priyasmanu Thomas Priyasmanu Vikar Teguh Yudistira Yohanes Yudha Saputra Bangko Yosep Agus Pranoto Yudi Arta Trirensila