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Journal : Jurnal Computech

Digital Revolution: Using the Naive Bayes Algorithm for Automatic Classification of Archives in a Public Institution in Bandung City Supriatna, Haris; Sambani, Egi Badar; Kautsar, Ray Jati
Jurnal Computech & Bisnis (e-journal) Vol. 19 No. 2 (2025): Jurnal Computech & Bisnis (e-Journal)
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56447/38hhf382

Abstract

The application of the Naive Bayes algorithm in an automatic digital archive classification system at a public institution in Bandung City is covered in this study.  The institution's biggest problem is the growing volume of records, which makes it challenging to manage and find archives rapidly.  To automatically categorize digital archives into predefined categories, a system was developed.  The Naive Bayes algorithm, which provides excellent accuracy, simplicity, and efficiency in processing text data, is the technique employed.  Digital documents that have undergone text-preprocessing steps, including tokenization, stopword removal, and stemming, prior to categorization make up the archive data.  This system uses MySQL, PHP, and the Laravel framework.  According to test results, the system can satisfactorily classify archives while facilitating user location by category.  As a result, this system can improve the institution's digital archive management effectiveness and efficiency.
Implementation Of The Case Based Reasoning (CBR) Expert System Method For Heart Disease Diagnosis Based On Patient Symptom History: Case Study Of Mitra Lewo Clinic Jamaludin, Ikbal; Baehaqi, Ahmad; Sambani, Egi Badar
Jurnal Computech & Bisnis (e-journal) Vol. 19 No. 2 (2025): Jurnal Computech & Bisnis (e-Journal)
Publisher : LPPM STMIK Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56447/vhke3d34

Abstract

Cardiovascular disease ranks among the primary causes of mortality in Indonesia.  An expedient and precise diagnostic method is crucial, particularly in primary healthcare settings such as Klinik Mitra Lewo, which face constraints on medical personnel.  This research aims to develop a web-based expert system using the Case-Based Reasoning (CBR) methodology to support preliminary diagnosis of heart disease based on a patient's symptom history.  The CBR approach functions by juxtaposing new patient symptoms with historical cases via the stages of Retrieve, Reuse, Revise, and Retain.  This system is developed using an Object-Oriented Software Engineering (OOSE) methodology and implemented in PHP using the CodeIgniter framework.  System testing employs black-box testing techniques to verify that each functionality satisfies user requirements.  The research findings demonstrate that the system can offer pertinent initial diagnostic recommendations and assist medical professionals in decision-making.  Consequently, an expert system can be a valuable asset in healthcare, especially when medical resources are constrained.