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Valentina, Cecilia
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering

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Perancangan Sistem Pakar Penyakit Demam Berdarah Menggunakan Metode Gradient Boosting Decision Tree Valentina, Cecilia; Tjen, Jimmy
MDP Student Conference Vol 4 No 1 (2025): The 4th MDP Student Conference 2025
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v4i1.11200

Abstract

Dengue fever is a disease transmitted through mosquito bites and can cause high death rates in several countries . This disease is most commonly found in countries with a tropical climate. Therefore, technology utilization has been implemented to help people to predict dengue fever. This research design an expert system using the Gradient Boosting Decision Tree (GBDT) method to classification a symptoms of dengue fever. This research used a dataset from Kaggle website and this data was analyzed and resulted in accuracy of 89%, a recall of 88,79%, and a precision of 69,96%. So, it was able to provide an accurate prediction of dengue fever through the GBDT method. The classification result was then adapted into mobile based application with a UI/UX design so that it can directly interact with users.
Co-Authors Jimmy Tjen