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Ibrahim, Irawan
Universitas Muhammadiyah Gorontalo
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Penerapan Algoritma Naive Bayes Untuk Sistem Klasifikasi Status Gizi Bayi Balita Mohamad Ilyas Abas; Rizal Lamusu; Widya Eka Pranata; Syahrial Syahrial; Irawan Ibrahim; Wahyudin Hasyim; Verliana Kiayi
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.508

Abstract

Infants and toddlers are in a critical period of rapid growth and development, often referred to as the "golden age." During this stage, regular nutritional assessments are essential to monitor health status and detect potential nutritional problems early. This study aims to classify the nutritional status of infants and toddlers using the Naïve Bayes algorithm, a probabilistic classification method based on Bayes' theorem with a strong assumption of attribute independence. The main attributes used in the classification system include age, weight, and height. The dataset consists of 700 records of infants and toddlers collected from previous observations. The results show that the Naïve Bayes algorithm can be effectively implemented for nutritional status classification, achieving a system accuracy of 88.14%. This indicates that the method performs well and has the potential to be utilized in decision support systems for child health monitoring.
PENERAPAN METODE MULTI OBJECTIVE OPTIMIZATION ON THE BASIC OF RATIO ANALYSIS (MOORA) UNTUK PEMILIHAN PENERIMA BANTUAN LANGSUNG TUNAI DI DESA ILOMANGGA Handayani, Tri Pratiwi; Pratiwi I Wantu; Irawan Ibrahim; Hilmansyah Gani
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 3 No. 2 (2023): Juli: 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.v3i2.1724

Abstract

Penelitian ini bertujuan untuk mengimplementasikan algoritma Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) sebagai Pendukung Keputusan dalam memilih penerima Bantuan Tunai Langsung di Desa Ilomangga, Gorontalo. Dengan dataset sebanyak 169 calon penerima, penelitian ini berfokus pada pengembangan pendekatan yang efisien untuk membantu kepala desa dalam proses pemilihan penerima manfaat. Dengan menggabungkan optimisasi multi-obyektif dan analisis rasio, algoritma MOORA secara objektif mengevaluasi dan mengurutkan penerima berdasarkan kelayakan dan kesesuaian. Temuan penelitian ini menunjukkan efektivitas MOORA dalam menyederhanakan proses seleksi, memastikan transparansi, dan mengoptimalkan alokasi sumber daya bagi mereka yang paling membutuhkan. Penelitian ini memberikan kontribusi pada sistem pendukung keputusan dengan memperlihatkan implementasi praktis MOORA.
Co-Authors Alter Lasarudin Daulima, Mohamad Rizki Fathir Adisyar Gani, Hilmansyah Ghani, Hilmasyah Gobel, Alvian Van Handayani, Tri Pratiwi Kango, Riklan Lamusu, Rizal Lasaruddin, Alter Lestari, Gita Maku, Rubiyanto Masri, Muhamad Moh. Nasrul Arief Setiawan Adam Mohamad Ilyas Abas Muslim Panigoro Nur'aini Mufaidhah Tangahu Nursetiawati Nursetiawati Panigoro, Muslim Poha, Rahmad A Pranata, Widya Eka Pratiwi I Wantu Pratiwi I Wantu Pratiwi I Wantu Rizal Lamusu Rizal Lamusu Rubiyanto Maku Salahudin Pakaya Syahrial Syahrial SYAHRIAL SYAHRIAL Syahrial Syahrial Syahrial Syahrial Tri Pratiwi Handayani Tri Pratiwi Handayani Umar Sako, Umar Verliana Kiayi Wahyudin Hasyim Widya Eka Pranata Widya Eka Pranata Yulan Humolungo Yulanda Yunus