Article Per Year (5 Year)
p-Index From 2021 - 2026
1.564
P-Index
This Author published in this journals
All Journal JURTEKSI Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Pengabdian Masyarakat IPTEK Journal of Information Systems and Technology Research Jurnal Sistem Informasi Triguna Dharma (JURSI TGD)
riansah, wahyu
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Journal of Information Systems and Technology Research

 1 
Analysis Of Promethee Methods On Assistance Recipients Family Of Hope Program In Poor People Hendrik Koto, Muhammad; Riansah, Wahyu
Journal of Information Systems and Technology Research Vol. 4 No. 1 (2025): January 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i01.1003

Abstract

The Family of Hope Program (PKH) managed by the Ternate City Social Service is a critical social assistance initiative aimed at reducing poverty and improving the welfare of underprivileged families. However, the program's implementation is not optimal due to the lack of a systematic approach in the selection of beneficiaries. Currently, the process relies on manual home visits and subjective visual assessments, which are time-consuming and prone to inaccuracies. This research aims to develop a decision support system (DSS) that utilizes the Promethee method to enhance the objectivity and efficiency of the beneficiary selection process. The Promethee method was chosen for its ability to rank alternatives based on multiple criteria, making it suitable for handling complex decision-making scenarios. Four criteria—age, marital status, education, and disability—were used to evaluate and prioritize potential beneficiaries. This research involved data collection from the Ternate City Social Service, followed by system design and analysis using the Promethee approach. The findings indicate that the Promethee-based DSS provides a structured and transparent mechanism for evaluating candidates, enabling the Social Service to make more accurate and equitable decisions. This system significantly reduces the time required for the selection process while improving its reliability. The study concludes that integrating the Promethee method into the Family of Hope Program can address existing inefficiencies and support the Social Service in achieving its goal of targeted poverty alleviation
Intelligent System for Mental Health Disorder Diagnosis Using Certainty Factor Method Sari , Kartika; Winata, Hendri; Riansah, Wahyu
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1308

Abstract

Mental health issues are increasingly recognized as a global challenge, affecting more than 450 million people worldwide, with a significant treatment gap in developing countries such as Indonesia. The limited number of mental health professionals highlights the need for alternative solutions to support early diagnosis. This study aims to design and implement an intelligent expert system for the diagnosis of mental disorders using the Certainty Factor (CF) method. The CF approach was selected for its ability to handle uncertainty and subjectivity in expert reasoning, particularly in cases where symptoms overlap across different disorders. The research methodology includes problem analysis, data collection, system design, implementation, and evaluation. The system was tested using a dataset of mental disorder symptoms, including depression, anxiety, schizophrenia, and bipolar disorder. The results indicate that the system can diagnose bipolar disorder with the highest CF value (0.951), followed by depression (0.883), anxiety disorder (0.853), and schizophrenia (0.510). These findings demonstrate that the CF-based system can provide accurate and realistic initial diagnoses that approximate expert judgment. This research contributes to the field of health informatics by providing a decision-support tool that can be integrated into telehealth platforms, enabling communities to gain faster access to mental health screening.
Co-Authors Amin, Faridho Dedi Setiawan Devri Suherdi, Devri Hendri Winata, Hendri Hendrik Koto, Muhammad Hutabarat, Mutiara Kusnasari, Sri Lumban Gaol, Nur Yanti Maha, Shinta Lestari Br S. Martupa Sihaloho, Vanleus Panjaitan, Zaimah Rafli, Muhammad Fikhri Ramadhan, Puji Sari Saniman Sari , Kartika Saripurna, Darjat Syahputra, Trinanda Winata, Hendryan Zulkifli Lubis