Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Proceeding International Conference on Information Technology and Business JURIKOM (Jurnal Riset Komputer)
Romadona, Romadona
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Sistem Deteksi Dini Gangguan Mental Menggunakan Algoritma Random Forest 'Aziiz Alfarobi, Muhammad Ilham; Tariq, Tariq; Romadona, Romadona; Sari, Aprilisa Arum
JURIKOM (Jurnal Riset Komputer) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8857

Abstract

Early detection of mental health disorders poses a significant challenge in primary care, often hindered by conventional assessment methods that are subjective and time-consuming. This research aims to design and evaluate an intelligent system prototype for predicting mental health risks. Adopting the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework , this study utilized 1,000 medical record datasets from Clinic. A predictive model was developed using the Random Forest algorithm, which is known for its robustness in handling complex data. Evaluation results indicate exceptional model performance, achieving a weighted accuracy of 99.67% on the test dataset. Feature importance analysis confirmed that social support, sleep quality, and physical activity variables are the most significant predictors. The prototype was successfully implemented as an interactive web application using Streamlit, demonstrating the feasibility of using machine learning as a rapid and accurate clinical decision support tool for mental health screening at the primary care level.
Sistem Deteksi Dini Gangguan Mental Menggunakan Algoritma Random Forest 'Aziiz Alfarobi, Muhammad Ilham; Tariq, Tariq; Romadona, Romadona; Sari, Aprilisa Arum
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8857

Abstract

Early detection of mental health disorders poses a significant challenge in primary care, often hindered by conventional assessment methods that are subjective and time-consuming. This research aims to design and evaluate an intelligent system prototype for predicting mental health risks. Adopting the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework , this study utilized 1,000 medical record datasets from Clinic. A predictive model was developed using the Random Forest algorithm, which is known for its robustness in handling complex data. Evaluation results indicate exceptional model performance, achieving a weighted accuracy of 99.67% on the test dataset. Feature importance analysis confirmed that social support, sleep quality, and physical activity variables are the most significant predictors. The prototype was successfully implemented as an interactive web application using Streamlit, demonstrating the feasibility of using machine learning as a rapid and accurate clinical decision support tool for mental health screening at the primary care level.
Assessment of Usability and Acceptance of An Academic Information System Using SUS And TAM Adaptation Nurlistiani, Rini; Romadona, Romadona; Kurniawan, Hendra; Nursiyanto, Nursiyanto
Prosiding International conference on Information Technology and Business (ICITB) 2023: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 9
Publisher : Proceeding International Conference on Information Technology and Business

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Organizations, companies, and the world of education carry out all learning activities using e-learning. There is an important part that requires an academic system with structured data, namely the system at private universities in Indonesia, for example,Informatics and Business Institute Darmajaya. Darmajaya is one of the educational institutes that uses online learning media information technology called e-learning for students and lecturers. The newest information system used at IIB Darmajaya is the academic information system (AIS) which consists of Darmajaya students and lecturers. Result from the assessment showing of lecturers understand how to use AIS with value 56.92, and 65.93 from students of IIB Darmajaya. Keywords :SUS,TAM, Evaluation, Acceptance, Usability
Co-Authors 'Aziiz Alfarobi, Muhammad Ilham Aprilisa Arum Sari Hendra Kurniawan Nurlistiani, Rini Nursiyanto Tariq, Tariq