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All Journal snimed Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI J I M P - Jurnal Informatika Merdeka Pasuruan PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Sistem Informasi dan Sistem Komputer Djtechno: Jurnal Teknologi Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Artificial Intelligence and Digital Business
Fadil Indra Sanjaya
Universitas Teknologi Yogyakarta
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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Classification of Nutritional Status Using the Fuzzy Mamdani Method : Case Study at Banjar City Hospital Nugraha, Muhammad Satria; Sanjaya, Fadil Indra
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9893

Abstract

The problem of nutritional status in adults requires accurate and adaptive classification methods. This study aims to develop a decision support system using the Fuzzy Mamdani method to classify nutritional status based on Body Mass Index (BMI). A dataset consisting of 237 anthropometric records from Banjar City Regional General Hospital was utilized. The system applies five fuzzy rules to map BMI values into nutritional categories: malnutrition, underweight, normal, overweight, and obesity. The classification process involves fuzzification, inference, and defuzzification using the centroid method. System performance evaluation shows an overall accuracy of 91.13%, with the highest classification precision achieved in the normal category (98.54%) and the lowest in the malnutrition category (30.77%). The results demonstrate that the Fuzzy Mamdani method is effective for nutritional classification, although refinement is needed for underrepresented categories. This system can serve as a useful tool for supporting clinical decision-making in public health services.
Co-Authors Anna Dina Kalifia Aryanto, Fajar Hanggoro Dwi Astrianty, Ledy Elsera Baraputri, Jennie Nadia Dadang Heksaputra Dadang Heksaputra Dini Erlinawati Elfan Fanhas Khoeri Fariddudin Ar-Razi Ab Febri Liantoni Heksaputra, Dadang Jayanegara, Adi Prabu Kalifia, Anna Dina Mabruri, Abdul Basith Mahardika, Setiawan Putra Muhammad Fachrie Muhammad Nurjaman Mulia Sulistiyono Novianto, Amrizal Nugraha, Muhammad Satria Nuzula Afini Pramudwiatmoko, Arif Pratama, Mohammad Bayu Putra, Fajar Permana Rahmatullah, Andi Ramadhan, Religius Ristianto, Andika Sulistyo Dwi Sancoko Syuhada, Arya Firgi Taufik Hidayah Yuliana Rizki Ikhsanty Zahra Septa Hati