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All Journal Indonesian Journal of Information System Jurnal INFOTEL
Norshahila Ibrahim
Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak, Malaysia
Computer Science & IT Electrical & Electronics Engineering

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Integrating Gamification in Expert Systems: A Novel Approach for Stress Disorder Diagnosis in Digital Mental Health putri taqwa prasetyaningrum; Norshahila Ibrahim; Reny Yuniasanti; Ibnu Rivansyah Subagyo
JURNAL INFOTEL Vol 17 No 2 (2025): May
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i2.1324

Abstract

The increasing prevalence of stress disorders highlights the need for innovative, accessible, and engaging diagnostic tools in mental health services. This study presents the design and implementation of a gamified expert system for diagnosing stress disorders, integrating gamification elements to enhance user engagement and reduce stigma. The system employs the forward chaining method to deliver high-accuracy, rule-based diagnoses while incorporating features such as points, rewards, and leaderboards to motivate user interaction.The system's development followed a user-centered design approach to ensure an intuitive interface aligned with user needs. Evaluation results demonstrated a diagnostic accuracy rate of 92%, validated by mental health professionals, alongside significant improvements in user engagement metrics, including session frequency and duration. Qualitative feedback indicated that gamification effectively reduced stigma and increased motivation for mental health assessments.These findings suggest that gamified expert systems can bridge gaps in accessibility and engagement in mental health services. This research contributes to the advancement of digital health technologies by providing practical insights into integrating gamification into expert systems to foster proactive mental health management.
Optimizing Sentiment Analysis of Hotel Reviews Using PCA and Machine Learning for Tourism Business Decision Support PUTRI TAQWA PRASETYANINGRUM; Norshahila Ibrahim; Ozzi Suria
Indonesian Journal of Information Systems Vol. 8 No. 1 (2025): August 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v8i1.10978

Abstract

Sentiment analysis of hotel reviews provides valuable insights for improving customer satisfaction and service quality in the tourism industry. However, the high dimensionality and unstructured nature of review data pose challenges in extracting meaningful insights. This study optimizes sentiment analysis by applying Principal Component Analysis (PCA) for dimensionality reduction and utilizing machine learning models for classification. The proposed approach involves data preprocessing, feature selection using PCA, model training, and performance evaluation. Experimental results show that PCA enhances classification accuracy and computational efficiency by eliminating redundant features, improving sentiment prediction. The comparative analysis demonstrates that the Voting classifier achieves the highest accuracy (95.29%) and F-score (97.50%), while the BiLSTM-FNN model attains the highest recall (99.95%). These findings highlight the potential of PCA-based sentiment analysis in supporting data-driven decision-making for hotel management, enabling enhanced service quality, improved customer experience, and effective marketing strategies.
Co-Authors Ibnu Rivansyah Subagyo Ozzi Suria PUTRI TAQWA PRASETYANINGRUM putri taqwa prasetyaningrum Reny Yuniasanti