Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Universitas Batanghari Jambi
Jody, Pradithia
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Law, Crime, Criminology & Criminal Justice

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Implementasi Machine Learning Tanpa Label (Unsupervised) dalam Identifikasi dan Klasifikasi Penyakit Berdasarkan Data Medis Pasien Jody, Pradithia; Sucahyo, Muhamad Yusuf; Setiawan, Rizqi; Prasetyo, Dwi Bagus; Amsury, Fachri; Fahlapi, Riza
Jurnal Ilmiah Universitas Batanghari Jambi Vol 26, No 1 (2026): Februari
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/jiubj.v26i1.6402

Abstract

This study aims to implement an unsupervised learning method using the K-Means Clustering algorithm to group patients based on medical data without requiring prior disease labels. The dataset used consists of 300 simulated patient data (synthetic data) with variables of blood pressure, blood sugar, cholesterol, and symptoms of fever, cough, shortness of breath, and muscle pain. The results show that the model can divide patients into four main clusters: hypertension, diabetes, hypercholesterolemia, and respiratory infections, which are consistent with realistic clinical conditions. Analysis of the average feature per cluster, scatter plots, and heatmaps strengthen the interpretation of the characteristics of each group. This approach proves that the K-Means method can be an efficient early diagnostic tool even though the data is unlabeled.
Co-Authors Fachri Amsury Fahlapi, Riza Prasetyo, Dwi Bagus Setiawan, Rizqi Sucahyo, Muhamad Yusuf