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Segmentasi Risiko Kesehatan Bayi dan Balita Menggunakan Algoritma K-Means Lalu Mutawalli; Mohammad Taufan Asri Zaen; Ahmad Tantoni; Indi Febriana Suhriani
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.504

Abstract

Urban disparities in maternal and child health remain a critical challenge in achieving the Sustainable Development Goals (SDGs). This study aims to map the disparity of health risks among infants and toddlers across 44 subdistricts in DKI Jakarta by analyzing three key indicators: prevalence of low birth weight (LBW), infant mortality, and undernutrition. Cross-sectional data from 2024 (n=176) were normalized using Min-Max scaling to minimize scale bias. The clustering process using the K-Means algorithm was conducted after determining the optimal number of clusters (k=5) through the Elbow method. Cluster validation employed three metrics—Silhouette Score (0.65), Davies-Bouldin Index (0.45), and Calinski-Harabasz Index (82.2)—demonstrating the model's consistency. Stability analysis through subsampling further confirmed the reliability of the results (standard deviation <0.1). Five risk patterns were identified: (1) two low-risk clusters (LBW <1.0%; undernutrition <2%), (2) two moderate-risk clusters (LBW 1.0–1.75%; infant mortality 0.5–3%), and (3) one high-risk cluster (LBW >1.75%; undernutrition >8%). The subdistricts of Jagakarsa and Kepulauan Seribu were identified as priority intervention hotspots due to high comorbidity risks. The findings indicate that the K-Means approach is effective in supporting evidence-based resource allocation policies, particularly in optimizing NICU services and nutrition supplementation programs in high-risk areas. This spatially based approach also facilitates more intuitive visualization for targeted and efficient planning of local health programs.
IMPLEMENTASI EXTREME PROGRAMMING DALAM SISTEM PENDAFTARAN TUGAS AKHIR DI STMIK LOMBOK Kahpi, Khairul Kahpi; Lalu Mutawalli; Maemun Saleh; Hasyim Asyari
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 2 No. 1 (2022): Maret: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v2i1.273

Abstract

Tugas Akhir merupakan salah satu karya ilmiah mahasiswa sebagai syarat menyelesaikan pendidikan Strata Satu (S1) di STMIK Lombok. Sistem pengajuan judul tugas akhir dan dosen pembimbing di STMIK Lombok masih menggunakan sistem konvensional sehingga proses pendaftaran pengajuan tugas akhir menjadi lebih lama dan memperlambat penyusunan proposal. Peneliti menggunakan beberapa Metodologi penelitian dalam Perancangan sistem ini. Untuk metode pengumpulan data peneliti menggunakan metode Observasi dan metode Wawancara pada Mahasiswa, Akademik dan Kaprodi. Sedangkan untuk metode analisis metode yang digunakan adalah metode PIECES. Pada penilitian ini dikembangkan sistem pendaftaran Tugas Akhir di STMIK Lombok dengan metodologi extereme programming. Sistem digunakan oleh 4 user yaitu mahasiswa, akademik, dosen, dan kaprodi. Interface dibangun berdasarakan form cetak yang berlaku. Sistem diintegrasikan dengan Database SIAKAD STMIK Lombok. Berdasarkan hasil pengujian fungsional yang dilakukan dengan metode white box. Setiap fitur dapat berjalan dengan baik dan sistem dapat mengelola data pengajuan judul, pendaftaran seminr proposal dan pendaftaran sidang Tugas Akhir.