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All Journal ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH TIN: TERAPAN INFORMATIKA NUSANTARA Bulletin of Computer Science Research
Triase Triase
Universitas Islam Negeri Sumatera Utara, Medan
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Analisis Komparasi Algoritma KNN dan Naive Bayes untuk Klasifikasi Pasien Rehabilitasi Narkoba di XYZ Putri Khairunnisa Nabilah; Triase Triase
JURIKOM (Jurnal Riset Komputer) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9553

Abstract

The development of information technology in the field of data mining opens up significant opportunities to optimize data classification in the healthcare and rehabilitation sectors. LRPPN BI Medan currently faces challenges in determining rehabilitation programs because the decision-making process is still subjective and has not yet systematically utilized historical data. Inaccuracies in determining these programs can reduce recovery effectiveness and increase the potential for patient relapse. This study aims to apply and test the effectiveness of the KNN and Naïve Bayes algorithms in classifying rehabilitation programs based on patient criteria, such as duration of drug use, URICA test results, medical history, and addiction level. This study uses a quantitative approach with the Waterfall development method. This solution is proposed to overcome subjectivity through a data-based classification system that complements each other in accuracy and processing speed. The results of this study show that the Naive Bayes algorithm has a higher accuracy rate of 96.43%, while KNN has an accuracy of 94.29%.
Co-Authors Abdul Razaq Adnan Buyung Nasution Della Widyati Donas Putra Hafizah Safwani Khairuna Khairuna Meidy Alfarazi Lubis Muhamad Alda Muhammad Farhan Azmi Darus Muhammad Faris Adira Muhammad Rivaldi Nazrah Namira Siregar Putri Khairunnisa Nabilah Raissa Amanda Putri Sriani Sriani Suendri, Suendri