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All Journal IJMST Scientific Journal of Engineering Research
Insyroh, Nazaruddin
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Computer Science & IT Engineering

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Classification of Stunting in Toddlers using Naive Bayes Method and Decision Tree Maulana, Adrian; Ilham, Muhammad; Lonang, Syahrani; Insyroh, Nazaruddin; Sherly da Costa, Apolonia Diana; B. Talirongan, Florence Jean; Furizal, Furizal; Firdaus, Asno Azzawagama
Indonesian Journal of Modern Science and Technology Vol. 1 No. 1 (2025): January
Publisher : CV. Abhinaya Indo Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64021/ijmst.1.1.28-33.2025

Abstract

Child stunting is a health problem that has a major impact on their physical growth and brain development. This study aims to create a model that can predict the risk of stunting using machine learning technology, in order to provide assistance quickly. Using data from 7,573 children, which included information such as age, weight, height gender and breastfeeding status, we tried two methods, Naive Bayes and Decision Tree. As a result, Naive Bayes was more accurate and the success rate reached 92%, compared to Decision tree which was only 88%. With this model, it is hoped that health workers will find it easier to find children at risk of stunting, so that preventive action can be taken earlier. This research aims to provide technology-based solutions to overcome the problem of stunting in the community.
Implementation of Data Mining Using Simple Linear Regression Algorithm to Predict Export Values Fawait, Aldi Bastiatul; Rahmah, Sitti; Costa, Apolonia Diana Sherly da; Insyroh, Nazaruddin; Firdaus, Asno Azzawagama
Scientific Journal of Engineering Research Vol. 1 No. 1 (2025): January
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v1i1.2025.11

Abstract

This study aims to analyze the trends in export value in East Kalimantan. The research utilizes secondary data sourced directly from the Central Statistics Agency of East Kalimantan Province. A simple linear regression algorithm for data mining is employed as the analytical method. The findings indicate a decline in East Kalimantan's export value from January 2022 to April 2024, as well as in the forecasted export value from May 2024 to December 2024. The prediction model achieved a Root Mean Square Error (RMSE) value of 3.182%, demonstrating a high level of accuracy in estimating export values. This research is expected to serve as a valuable reference for stakeholders in formulating strategies to enhance East Kalimantan's export performance and contribute to the region's future economic development.
Co-Authors Aldi Bastiatul Fawait Fawait Asno Azzawagama Firdaus B. Talirongan, Florence Jean Costa, Apolonia Diana Sherly da Furizal, Furizal Maulana, Adrian Muhammad Ilham Sherly da Costa, Apolonia Diana Sitti Rahmah Syahrani Lonang