Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Kharisma Tech Journal of Technology Research in Information System and Engineering
Mohammad Sofyan S. Thayf
STMIK KHARISMA Makassar
Computer Science & IT Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Sistem Pakar Troubleshooting Kerusakan Hardware Komputer Berbasis Web Dengan Metode Forward Chaining Pada Laboratorium STMIK Kharisma Makassar Faisal T Supu; Sofyan S. Thayf; Marlina
JTRISTE Vol 13 No 1 (2026): JTRISTE
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/jtriste.v13i1.710

Abstract

This research aims to develop a web-based expert system designed to assist in troubleshooting computer hardware issues at the STMIK Kharisma Makassar Laboratory. The system employs a forward chaining method to diagnose problems based on symptoms reported by users. The research methodology utilized is R&D with a descriptive and quantitative approach. Test results indicate that this system can deliver accurate diagnoses and relevant solutions, thereby enhancing efficiency in addressing hardware damage issues.
PENGEMBANGAN FITUR PENCARIAN INFORMASI OBAT BERBASIS AI PADA APLIKASI POTIO Allycia Joshin; Moh. Sofyan S. Thayf; Zaenab Pontoh
KHARISMA Tech Vol 21 No 1 (2026): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v21i1.597

Abstract

Potio was a mobile-based alarm application that functioned as a medication reminder for users who often forgot their medication schedules, which consisted of several features, such as adding alarms, medication history, themes customization, and medicine information research. In its development, this application used a MySQL database to store the results of inputting alarm data and medicine information. However, with the increasing amount of data that needed to be managed, researchers faced challenges in data management, because the very large number of medicines needed to be inputted manually, so it took longer and there was the potential for errors in data input. Therefore, the development of a medicine information search feature in the Potio application was carried out using one of the models, namely Gemini AI, by obtaining an Application Programming Interface key to be implemented into the medicine information search feature, followed by a prompt technique to provide effective output. The results of testing using Blackbox Testing with test cases showed that Potio successfully utilized Gemini AI for the medicine information search feature, eliminating the need for manual input of medicine information into the MySQL database.
Co-Authors Allycia Joshin Faisal T Supu Marlina marlina Zaenab Pontoh