Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Armada Informatika
Alfin Akbar
Universitas Islam Indragiri
Computer Science & IT Control & Systems Engineering

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

Found 1 Documents
Search

 1 
Skin Disease Classification System and Drug Recommendation Based on Symptoms Using K-Nearest Neighbor (KNN) Algorithm Alfin Akbar; Dwi Yuli Prasetyo
Jurnal Armada Informatika Vol 10 No 1 (2026): Juni
Publisher : STMIK Methodist Binjai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36520/jai.v10i1.275

Abstract

Skin diseases are among the most common health problems affecting the community. This study aims to develop a skin disease classification system based on symptoms using the K-Nearest Neighbor (KNN) algorithm and to provide treatment recommendations. The dataset used consists of 405 records containing disease symptoms, disease location, disease shape, disease name, and treatment recommendations. Text-based symptom data were transformed into numerical representations using the Term Frequency-Inverse Document Frequency (TF-IDF) method before the classification process was carried out using the KNN algorithm. The experiments were conducted using K values of 3, 5, and 7. The results showed that the best performance was achieved with K=7, obtaining an accuracy of 90.12%, a precision of 0.91, a recall of 0.93, and an F1-score of 0.91. Meanwhile, K=5 achieved an accuracy of 88.89%, and K=3 achieved an accuracy of 87.65%. Furthermore, the system was successfully implemented using Streamlit, allowing users to interactively classify skin diseases and obtain treatment recommendations based on the symptoms entered.
Co-Authors Dwi Yuli Prasetyo