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PERANCANGAN SISTEM INFORMASI PENCARIAN KERUSAKAN SEPEDA MOTOR SISTEM ELECTRONIC FUEL IGNATION (EFI) Muhammad Isnaini; Saut Matedius Situmorang
JURNAL TEKNISI Vol. 1 No. 1 (2021): February 2021
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/teknisi.v1i1.490

Abstract

Have researched a sistym information about malfunction problems sitem search motor cycle which the device uses advanced methods of reasoning in expert systems . Troubelshooting on motor cycle generally used manually, by determining the symptoms theoretically derived from the experiences so that a technician and student / student often neglected problem finding time and accuracy in solving the problems of motor cycle with EFI sistem repair problems .The method used is the observation on trouble shooting to EFI sensor sistem and collect data from any symptoms of damage to television later in the evaluation of the raw data is entered into a database to an expert system by utilizing visual basic programming .The results will produce a search expert software system that can damage on EFI sensor sparepart can help the technicians and users of the motor cycle itself to recognize and deal damage that occurs EFI component sistem .
Performance Evaluation of a Mobile Attendance System Using Dual-Factor Dynamic Qr Code and Gps Geofencing Rosma Siregar; Bagoes Maulana; Muhammad Isnaini; Elsa Sabrina; Harvei Desmon Hutahaean
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 06 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i06.2281

Abstract

This study develops and evaluates an Android-based attendance system integrating dual-factor authentication using dynamic QR codes and GPS geofencing to prevent proxy attendance in higher education. The system was developed using the Waterfall model and evaluated through quantitative experiments measuring response time, GPS accuracy drift, and security robustness via Black-Box testing. Results show high efficiency with an average response time below 1.5 seconds. GPS validation achieved an average drift of 4.2 meters outdoors and 12.5 meters indoors, remaining within the 30-meter geofencing threshold. The system successfully rejected unauthorized attempts, including out-of-range scans and fake GPS spoofing. These findings demonstrate that combining dynamic QR codes with GPS validation significantly improves attendance authenticity and system reliability compared to single-factor methods. The study provides empirical evidence of a robust and scalable solution for secure mobile-based attendance systems in higher education.
V-LAMOT: A Cognitive-Load Optimized Virtual Lab for Three-Phase Motor Control Muhammad Isnaini; Sukarman Purba; Mega Silfia Dewy; Muhammad Dani Solihin; Agnes Irene Silitonga
Journal of Educational Technology and Learning Creativity Vol. 4 No. 1 (2026): June
Publisher : Cahaya Ilmu Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37251/jetlc.v4i1.2766

Abstract

Purpose of the study: This study aims to design and validate V-LAMOT, a web-based virtual laboratory for three-phase motor starting simulation. The system is intended to address limitations of physical laboratories by providing an accessible and safe environment while maintaining conceptual accuracy and supporting the development of practical motor control skills. Methodology: The study adopted the Systems Development Life Cycle (SDLC) to develop the V-LAMOT platform using HTML5, CSS, JavaScript, and state-machine modeling. The design was guided by Cognitive Load Theory principles. Data were obtained through expert validation instruments and the System Usability Scale (SUS), and analyzed using Shapiro–Wilk tests, one-sample t-tests, Cohen’s d, and Pearson correlation with 30 students. Main Findings: Expert validation indicated high feasibility, with conceptual accuracy reaching a mean score of 4.50/5. SUS evaluation produced an overall score of 78.83 (“Good”), with learnability scoring highest at 82.00. All usability measures were significantly above the benchmark (p < 0.001) with large effect sizes (d > 0.8). A strong correlation between usability and learnability (r = 0.823) suggested effective cognitive load reduction. Novelty/Originality of this study: This study presents an integrated virtual laboratory that combines state-machine modeling with Cognitive Load Theory-based interface design for three-phase motor control. Unlike conventional simulations, V-LAMOT integrates multiple motor starting methods in one environment and empirically links usability, learnability, and cognitive load reduction, advancing virtual laboratory development through systematic integration of technical accuracy and pedagogical principles.