Vol. 1 No. 1 (2025): First Volume and Issue of IJAIC Journal
Articles

Application of K-Means Clustering in the Prevention and Complaint System of Sexual Violence at Politeknik Negeri Lhokseumawe

PDF
  • Muhammad Rizka,
  • Hendrawaty,
  • Sepkha Ayunda Sari
Muhammad Rizka
Politeknik Negeri Lhokseumawe

Published 23-10-2025

Keywords

  • Sexual Violence,
  • Prevention,
  • K-Means,
  • Clustering

Copyright (c) 2025 mulyadi, Zulfan Khairil Simbolon, Iqbal Panutan

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Abstract

Sexual violence on campus, particularly at Politeknik Negeri Lhokseumawe, is an issue that requires serious attention and effective handling. To improve the current manual complaint management system, the application of information technology through the K-Means Clustering method is necessary for the prevention and complaint system of sexual violence. This approach is expected to assist in grouping complaint data from victims, making it easier to identify levels of sexual violence and to design more targeted responses. This research was conducted by developing and managing a sexual violence complaint system, where the complaints were grouped into three clusters based on the calculation of the data. The clusters were validated using the silhouette method, resulting in a score of 0.50 for cluster 0 (moderate level), 0.20 for cluster 1 (moderate level), and 0.58 for cluster 2 (low level). These results indicate that the K-Means Clustering method is effective in categorizing complaint data and can support more effective handling of sexual violence cases on campus.

PDF

Downloads

Download data is not yet available.

References

  1. U. Marfu’ah, S. Rofi’ah, and Maksun, “Sistem Pencegahan Dan Penanganan Kekerasan Seksual Di Kampus,” Kafa’ah J., vol. 11, no. 1, pp. 96–106, 2021, [Online]. Available: http://kafaah.org/index.php/kafaah/index
  2. N. Sudjud and Mohamad Ali Akbar, “Rancang Bangun Aplikasi Pelaporan Anti Kekerasan Seksual (AKAS) Berbasis Android,” Inf. (Jurnal Inform. dan Sist. Informasi), vol. 14, no. 2, pp. 162–169, 2022, doi: 10.37424/informasi.v14i2.182.
  3. I. Firdiyansyah, R. Riki, and ..., “Rancang Bangun Sistem Pengaduan Penanganan Kekerasan Seksual Di Universitas Maritim Raja Ali Haji,” Jursima …, vol. 10, no. 3, 2022, [Online]. Available: https://ejournal.indobarunasional.ac.id/index.php/jursima/article/view/499%0Ahttps://ejournal.indobarunasional.ac.id/index.php/jursima/article/download/499/308
  4. R. A. Faujia, E. S. Setianingsih, and H. Pratiwi, “Analisis Klaster K-Means Dan Agglomerative Nesting Pada Indikator Stunting Balita Di Indonesia,” Semin. Nas. Off. Stat., vol. 2022, no. 1, pp. 1249–1258, 2022, doi: 10.34123/semnasoffstat.v2022i1.1511.
  5. A. K-means, A. Fadilah, M. N. P, S. Lumbanbatu, and S. Defiyanti, “Pengelompokan kabupaten/kota di indonesia berdasarkan faktor penyebab stunting pada balita menggunakan algoritma k-means,” vol. 6, no. 2, pp. 223–230, 2022.
  6. J. P. Tanjung, B. A. Wijaya, and M. Ridho, “Implementasi Algoritma K-Means Dalam Mengukur Tingkat Kepuasan Siswa Terhadap Pelayanan Pada SMA Swasta Bani Adam AS,” Data Sci. Indones., vol. 3, no. 1, pp. 1–11, 2023, doi: 10.47709/dsi.v3i1.2775.
  7. M. Y. Matdoan, F. Y. Risdiana, and G. Haumahu, “Application of the K-Means Cluster for the Classification of Disadvantaged Districts/Cities in Maluku Province,” JRST (Jurnal Ris. Sains dan Teknol., vol. 6, no. 1, p. 61, 2022, doi: 10.30595/jrst.v6i1.11637.
  8. M. Naomi, H. Noprisson, F. I. Komputer, U. Mercu, and B. Jakarta, “Analisa Dan Perancangan Sistem Pengaduan Mahasiswa Berbasis Web ( Studi Kasus : Universitas Mercu Buana Kranggan ),” 2, vol. 1, no. 5, pp. 185–193, 2020.
  9. Haviluddin, “Memahami Penggunaan UML ( Unified Modelling Language ),” Memahami Pengguna. UML (Unified Model. Lang., vol. 6, no. 1, pp. 1–15, 2011, [Online]. Available: https://informatikamulawarman.files.wordpress.com/2011/10/01-jurnal-informatika-mulawarman-feb-2011.pdf
  10. A. Septianingsih, “Analisis K-Means Clustering Pada Pemetaan Provinsi Indonesia Berdasarkan Indikator Rumah Layak Huni,” J. Lebesgue J. Ilm. Pendidik. Mat. Mat. dan Stat., vol. 3, no. 1, pp. 224–241, 2022, doi: 10.46306/lb.v3i1.116.