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All Journal Jiko (Jurnal Informatika dan komputer) SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Informatika: Jurnal Pengembangan IT
Sawali Wahyu
Esa Unggul University
Computer Science & IT Control & Systems Engineering Engineering

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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.
ANALISIS SENTIMEN OPINI PUBLIK TERHADAP KASUS KORUPSI BAHAN BAKAR MINYAK OPLOSAN PT PERTAMINA DENGAN HYBRID MODEL DEEP LEARNING Muhammad Ramdhan Awali; Sawali Wahyu; Anik Hanifatul Azizah
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 2 (2025): Jurnal SKANIKA Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i2.3525

Abstract

The corruption case related to oplosan fuel oil involving PT Pertamina has become a national issue that has drawn diverse responses from the public. Sentiment analysis of public opinion on social media can provide important insights for the government and stakeholders in understanding public perceptions of the case. This study aims to analyze public opinion sentiment regarding the alleged fuel adulteration corruption case involving PT Pertamina, using a hybrid deep learning model approach. Data were collected from the social media platform Twitter (X) between February 24 and March 19, 2025, resulting in 12,365 tweets after preprocessing. The study implements four model architectures: IndoBERT, CNN, LSTM, and a hybrid IndoBERT-CNN-LSTM model. Evaluation results show that IndoBERT achieved the highest accuracy at 90%, followed by CNN (86%), hybrid (84%), and LSTM with the lowest accuracy (69%). In addition, the K-Fold cross-validation scheme produced more stable model evaluation results than the Hold-Out method. Based on sentiment distribution analysis, public opinion was dominated by negative sentiment at 72%, while positive and neutral sentiments each accounted for 16%. These findings indicate that the public tends to respond negatively to the Pertamina fuel corruption issue. This study contributes to the understanding of public opinion on social media through a deep learning-based sentiment analysis approach and highlights the importance of selecting appropriate model architectures and validation strategies in the task of classifying Indonesian-language text.
Implementation of Augmented Reality Technology for Human Anatomy Learning Media Using Mobile-Based Gamification Models Bagus Rosyid Hamdani; Sawali Wahyu; Arief Ichwani; Popong Setiawati
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10264

Abstract

SMP Negeri 38 Bekasi is a junior high school that experiences low student learning outcomes in the Science subject, particularly in human body anatomy material. Based on the learning outcome data of eighth-grade students, the low achievement of the Minimum Mastery Criteria (MMC) is largely caused by the abstract nature of anatomy material, which requires strong visualization skills, while the learning process is still dominated by conventional methods based on text and two-dimensional images that are less engaging and interactive for students. To address this problem, the use of technology can be applied through the implementation of Augmented Reality (AR) with a gamification approach in learning media. This study aims to develop a mobile-based learning application on human body anatomy material to improve students’ learning interest and outcomes by presenting three-dimensional models of human body organs, as well as providing interactive quiz features, scoring systems, and leaderboards. The application was developed using a gamification approach and the Multimedia Development Life Cycle (MDLC) method. The results of application testing using the System Usability Scale (SUS) method indicate that the AR Human Body Anatomy application obtained a score of 84.05, which falls into the A or Excellent category, while the Management Dashboard application obtained a score of 80.5, which is also categorized as A. The results show that Science learning using Augmented Reality-based learning media with a gamification approach can facilitate students’ understanding of human body anatomy through three-dimensional visualization technology, increase learning motivation and enthusiasm, and improve student learning outcomes as well as the achievement of the Minimum Mastery Criteria (MMC).
Co-Authors Arief Ichwani Azizah, Anik Hanifatul Bagus Rosyid Hamdani Budi Tjahjono Meria, Lista Muhammad Ramdhan Awali Popong Setiawati Riya Widayanti Ryan Putra Laksana Sahri Ramadan Silvia Ratna Juwita