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Sawali Wahyu
Esa Unggul University
Computer Science & IT

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IMPLEMENTATION BLOCKCHAIN IN MOBILE APPLICATIONS SEMINAR ON E-CERTIFICATE VERIFICATION USING SMART CONTRACTS Sahri Ramadan; Sawali Wahyu; Budi Tjahjono; Riya Widayanti
JIKO (Jurnal Informatika dan Komputer) Vol 9 No 1 (2026)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v9i1.11356

Abstract

The increasing adoption of electronic certificates in academic and professional environments raises critical challenges related to authenticity, data integrity, and verification reliability. Conventional certificate management systems commonly rely on centralized architectures and manual validation procedures, which are vulnerable to manipulation, duplication, and single points of failure (SPoF). This study proposes a blockchain-based electronic certificate verification system implemented on a private Hyperledger Fabric network using smart contracts. The system records certificate verification metadata on a distributed ledger to ensure integrity and traceability while maintaining storage efficiency. Smart contracts automate the issuance and validation lifecycle, enabling transparent and tamper-resistant certificate management. The verification process is conducted by comparing document authentication data with records stored on the blockchain. Experimental evaluation demonstrates that the proposed system can accurately identify document alterations and consistently distinguish between valid and invalid certificates. The results indicate that the integration of blockchain and smart contracts as an active validation mechanism enhances transparency, reduces dependence on centralized authorities, and improves trust in mobile-based digital credential systems. Therefore, the proposed approach provides a secure and reliable framework for electronic certificate verification in academic environments.
MOBILE APPLICATION FOR IDENTIFICATION OF EMPLOYEE STRESS PATTERN USING DEEP LEARNING APPROACH Sawali Wahyu; Silvia Ratna Juwita; Ryan Putra Laksana; Lista Meria
JIKO (Jurnal Informatika dan Komputer) Vol 9 No 1 (2026)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v9i1.11527

Abstract

Employee stress has become a critical issue affecting organizational productivity, well-being, and performance, especially in dynamic work environments. This study proposes an integrated mobile-based stress prediction and recommendation system that combines Long Short-Term Memory (LSTM) and Neural Collaborative Filtering (NCF) to identify employee stress levels and provide personalized improvement recommendations. Experimental evaluation using 1000 datasets was used to test the LSTM and NCF models. The LSTM model was used to predict stress levels due to its ability to capture complex patterns in multidimensional data, while NCF was used to generate personalized recommendations based on collaborative patterns. The results showed that the LSTM model achieved superior classification performance with 98% accuracy and the recommendation evaluation showed good convergence performance, with a Hit Ratio reaching 0.92 and a Normalized Discounted Cumulative Gain (NDCG) reaching 0.89, indicating high recommendation relevance. Furthermore, the system usability evaluation using the System Usability Scale (SUS) involving 30 respondents resulted in an average score of 80.81, which is categorized as excellent usability. The integration of deep learning and collaborative filtering into a mobile platform provides an effective and intelligent solution for employee stress prediction and intervention. This study contributes to the development of an adaptive occupational health monitoring system and demonstrates the potential of AI-based mobile applications in supporting mental health management in the workplace.
Co-Authors Budi Tjahjono Meria, Lista Riya Widayanti Ryan Putra Laksana Sahri Ramadan Silvia Ratna Juwita