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All Journal Jurnal Teknik dan Science (JTS)
Viliananda Tripita Claur
Universitas Gunadarma
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Penggunaan Kecerdasan Buatan untuk Menganalisis Faktor Risiko Diabetes dengan menggunakan Random Forest Classifier Tri Sulistyorini; Nelly Sofi; Dwi Widiastuti; Viliananda Tripita Claur
Jurnal Teknik dan Science Vol. 4 No. 3 (2025): Oktober: Jurnal Teknik dan Science
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jts.v4i3.2453

Abstract

Diabetes is a non-communicable disease that deserves attention and poses a significant public health challenge. Although not a contagious disease, preventive measures and early detection of diabetes risk are crucial. This study used machine learning-based artificial intelligence to identify diabetes risk factors. The model was created using the Random Forest Classifier (RFC) algorithm, which has 16 variables as parameters. The model was built using the Python programming language, with data collection spanning from 2015 to 2018. The research included needs analysis, data collection, data preprocessing, model training, predictive model creation, system design, implementation, and testing. The final results showed that, with an accuracy of 89%, the model could be used effectively to predict diabetes risk. Furthermore, the model identified more pre-diabetes classes than other classes.
Co-Authors Dwi Widiastuti Nelly Sofi Tri Sulistyorini