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All Journal Teknika Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Building of Informatics, Technology and Science Vocatech : Vocational Education and Technology Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE G-Tech : Jurnal Teknologi Terapan Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology ARRUS Journal of Engineering and Technology Instal : Jurnal Komputer Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Ilmu Komputer dan Informatika Brilliance: Research of Artificial Intelligence TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 Electronic Journal of Education, Social Economics and Technology MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Jurnal Pengabdian Masyarakat Ilmu Komputer Journal Serambi Engineering (JSE) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Lidya Rosnita
Universitas Malikussaleh
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Journal : JINAV: Journal of Information and Visualization

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Classification of Stunting Status Using the Naive Bayes Classifier Algorithm with Backward Elimination Feature Selection Pasaribu, Hafni Maya Sari; Abdullah, Dahlan; Rosnita, Lidya
JINAV: Journal of Information and Visualization Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav4100

Abstract

Stunting is one of the major health issues affecting toddlers that can influence their physical growth and developmental progress, ultimately impacting their quality of life. It is characterized by a child’s height being below the standard for their age. To address this issue, a method is needed to classify the stunting status in toddlers. This study aims to classify stunting status in toddlers using the Naive Bayes Classifier algorithm, with feature selection performed using the Backward Elimination method to improve classification accuracy.The dataset used in this research was collected in 2023 from the Lueng Daneun Public Health Center, located in Peusangan Simblah Krueng Subdistrict, Bireun District. The dataset includes several features such as age, gender, family income, height, weight, sanitation, clean water access, and formula milk consumption. The application of the backward elimination feature selection method is intended to identify the most significant and relevant features for the target variable. The Naive Bayes Classifier was implemented using the Python programming language. The analysis results indicated that the remaining feature, namely the sanitation condition, had a significant contribution to the classification process. The dataset consisted of 244 entries, divided into 195 training data and 49 testing data with an 80:20 ratio. The initial classification results showed an accuracy of 77.55%, a precision of 60.00%, a recall of 64.29%, and an F1-score of 62.07%. After feature selection, the accuracy increased to 81.63%, precision to 63.16%, recall to 85.71%, and the F1-score slightly improved to 72.73%. These results indicate that feature selection in the Naive Bayes model demonstrates good performance.
Co-Authors Afif, Muhammad Athallah Afridah, Rita Aidilof, Hafizh Al Kausar Aidilof, Hafizh Al Kautsar Al Kautsar Aidilof, Hafizh Amelia, Ulva Amir Fauzi Ansyari, Taufik Habib Armaya, Devira Yuda Asrianda Asrianda Azzahra Iskandar, Farah Bancin, Udurta Bustami Bustami Dahlan Abdullah Deassy Siska Dela, Monisa Dian Putri, Yohana Diana, Mhd. Arief Efendi, Syahril Efendi, Syahril Elma Fitria Ananda Eva Darnila Eva Darnila Fachry Abda El Rahman Fadlisyah Fadlisyah Fasdarsyah Fasdarsyah Fidyatun Nisa Fuadi, Wahyu Furqan, Hafizul Habib Muharry Yusdartono Hafidh Rafif, Teuku Muhammad Hamsi, Widia Harahap, Ilham Taruna Harahap, Lina Mardiana Ikramina ikramina ikramina, Ikramina Jange, Beno Khairul Amna, Khairul Kurniawati Kurniawati Lina Mardiana Harahap Mara Wahyu Alamsyah Pane Micola Azwir, Andrea Muhammad Azhari Muhammad Fajri Muhammad Fikry Muhammad Ikhwani Muhammad Muaz Munauwar Muhammad Muhammad Muhammad Zarlis Muhammad Zarlis, Muhammad Muharry Yusdartono, Habib Mukti Qamal Mulyadi, Rizki Munirul Ula Muzaffar Rigayatsyah Nanda Sitti Nurfebruary Nasution, Wahidatunnisa Naturizal, Rayhan Naza Amarianda Nur Ismiza Nurdin Nurfebruary, Nanda Sitti Nurhaliza Bin Aras Nurqamarina Nurul Aula Nurwijayanti Pasaribu, Hafni Maya Sari Pratiwi, Dinda Pulungan, Fauzi Irham Putri, Sri Raihan Rachman, Aulia Rachmat Triandi Tjahjanto Rahmadani Sari, Putri Dwi Rahmat Triandi Rangkuti, Haris Yunanda Rian Kelana Putra Rini Meiyanti Risawandi, Risawandi Rizal Rizal Rizal Rizal Rizal S.Si., M.IT, Rizal Rizky Putra Fhonna Safriana Safriana Safwandi Safwandi, Safwandi Said Fadlan Anshari salamah salamah Samosir, Dini Kairiyah Saputri, Rifa Andriani Siti Maimunah Sujacka Retno Syahputra, M Oriza Ulva Ilyatin Wahyu Fuadi Yesy Afrillia Yunanda Rangkuti, Haris Zalfie Ardian Zara Yunizar Zulfadli Zulfadli