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All Journal Elkom: Jurnal Elektronika dan Komputer INFOKAM Jurnal Informatika dan Teknik Elektro Terapan Jurnal Sains dan Informatika Journal of Information Systems and Informatics JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Digit : Digital of Information Technology Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Education Technology Information Social Sciences and Health JAMU : Jurnal Abdi Masyarakat UMUS Innovative: Journal Of Social Science Research Jurnal Teknik Indonesia Jurnal Multidisiplin Teknologi dan Arsitektur Journal of Citizen Research and Development
Otong Saeful Bachri
Program Studi Teknik Informatika, Fakultas Teknik, Universitas Muhadi Setiabudi, Brebes, Indonesia
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Penerapan Algoritma C4.5 untuk Prediksi Prioritas Relokasi Rumah Terdampak Bencana Tanah Gerak di Kabupaten Brebes Apriliani, Rosema Dina; Ramdhan, Nur Ariesanto; Bachri, Otong Saeful
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.20672

Abstract

Bencana tanah gerak di Kabupaten Brebes menyebabkan kerusakan parah pada hunian, sehingga diperlukan sistem pendukung keputusan untuk menentukan prioritas relokasi rumah secara cepat dan akurat. Penelitian ini mengembangkan aplikasi berbasis web menggunakan metode Waterfall dan algoritma Decision Tree C4.5. Data diperoleh dari DINPERWASKIM Brebes dengan atribut seperti jenis bencana, lokasi, status kepemilikan rumah, dan kondisi bangunan (atap, kolom/balok, struktur). Implementasi dilakukan menggunakan Flask dan PostgreSQL, sedangkan evaluasi mencakup pengujian fungsional (Black-Box) dan performa model. Hasil pengujian menunjukkan aplikasi berfungsi sesuai kebutuhan dan model C4.5 mencapai akurasi 98,89% setelah penyeimbangan kelas dengan SMOTE. Atribut kondisi kolom/balok dan kondisi atap menjadi faktor utama dalam penentuan prioritas. Sistem ini diharapkan mendukung pengambilan keputusan pemerintah daerah dalam program relokasi rumah terdampak bencana secara lebih tepat dan efisien.
Sistem Pendukung Keputusan Menentukan Beasiswa di SMKS Maarif Nu 03 Larangan Menggunakan Metode Weighted Aggregatedsum Product Assessment (WASPAS) Nurfikri, Muhammad Ihsan; Bhakti, R M Herdian; Bachri, Otong Saeful
Jurnal Multidisiplin Teknologi dan Arsitektur Vol 3, No 1 (2025): Mei 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/motekar.v3i1.6032

Abstract

Penelitian ini bertujuan untuk mempermudah proses seleksi penerima beasiswa di SMKS Maarif Nahdhotul Ulama 03 Larangan, yang diperuntukkan bagi siswa berprestasi namun memiliki keterbatasan ekonomi. Mengingat banyaknya jumlah siswa, penilaian manual terhadap berbagai kriteria seperti nilai akademik, prestasi ekstrakurikuler, dan kondisi ekonomi dinilai kurang efektif. Oleh karena itu, diterapkan Sistem Pendukung Keputusan (SPK) berbasis Metode Weighted Aggregated Sum Product Assessment (WASPAS) yang memberikan bobot pada setiap kriteria, sehingga menghasilkan perankingan yang lebih tepat dan objektif. Hasil penelitian menunjukkan bahwa alternatif A7 memperoleh nilai tertinggi sebesar 1,279662 dan menduduki peringkat pertama, disusul oleh A1 dengan nilai 1,266194 di peringkat kedua, A64 dengan nilai 1,168183 di peringkat ketiga, A95 dengan nilai 1,154944 di peringkat keempat, dan A5 dengan nilai 1,143422 di peringkat kelima. Diharapkan, SPK berbasis WASPAS ini dapat mendukung pengambilan keputusan yang lebih efisien dan adil dalam menentukan penerima beasiswa di sekolah tersebut.
Global Research Trends and Map on Machine Learning Applications in Stunting Detection in Vulnerable Populations: A Bibliometric Analysis Bachri, Otong Saeful; Widodo, Catur Edi; Nurhayati, Oky Dwi
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1248

Abstract

Stunting and malnutrition continue to be significant public health challenges, particularly in low-income and rural populations. With the growing reliance on data-driven strategies in public health, machine learning (ML) has emerged as a promising tool for identifying, classifying, and predicting conditions related to undernutrition. This study presents a bibliometric analysis of global research from 2019 to 2025, focusing on the application of ML techniques—such as clustering, support vector machines (SVM), and random forest—in addressing malnutrition and stunting. A total of 417 Scopus-indexed publications were analyzed using Biblioshiny (R) to assess research trends, key themes, influential authors, prominent journals, and thematic evolution. The analysis reveals a consistent growth rate of 10.72% in publications, with notable contributions from China and other low- and middle-income countries. Keyword mapping highlights that “machine learning,” “spatial analysis,” and “stunting” are central to the research, although they remain areas for further development. Thematic evolution indicates a shift towards more integrated, context-aware approaches, with a growing focus on built environments and vulnerable populations. The study concludes that while ML holds significant promise for advancing decision-making in child health and nutrition, its impact will depend on continued methodological refinement and effective implementation within public health systems.
Co-Authors Abdi R, Aulia Agung Permana, Tegar Agyztia Premana Ahmad Najmi Fuadi Andi Yulianto Anin, Anindia Anindia Ardiani Apriliani, Rosema Dina Ariestanto Ramdhan, Nur Badruzzaman, Ni'am Bagus W, Teguh Bambang Irawan /E21207042 Bhakti, Herdian Bhakti, R M Herdian Budiasih, Kristanti Catur Edi Widodo Dumadi Dumadi Elis Afriyani Fery Sofian Efendi Fitro, Achmad Gagas Prasetya Gian Fitralisma Harliana Harliana Harliana Harliana Herdian Bhakti, RM Irmansyah, Teguh Bagus Wicaksono Iza Azkiah Khalid Iskandar Khalid Iskandar Muhami, Rizal Muhammad Bagus Irwana Aji Muhammad Lutfi Jamaludina Mukson Mukson Nur Ariesanto Ramdhan Nur Ariesanto Ramdhan Nurfikri, Muhammad Ihsan Oky Dwi Nurhayati Pandhu Wijaya, Akhmad Pratama Putra, Rizki Premana, Agyztia R.M Herdian Bhakti R.M. Herdian Bhakti Raden Mohamad Herdian Bhakti Raden Mohamad Herdian Bhakti Raden Mohamad Herdian Bhakti Ramdhan, Nur Ariesanto Rifqoh Febriyanti Putri Riono, Slamet Bambang Rizky Esa Riyanto Roby Setiadi Roby Setiadi Rohman, Aulia Abdi Rudianto Rudianto Shahib, M Umar Sri Yulianti Susilo, Bayu Tegar Agung Permana Teuku Rizal Adi Pangestu Tri S, Wananda Wahyuningsih, Puji Yenny Ernitawati Yuhano Yuhano