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Journal : IJISCS (International Journal of Information System and Computer Science)

SYSTEM USABILITY EVALUATION OF THE DIGITAL AUTOMATIC WEATHER SYSTEM AT BMKG LAMPUNG PROVINCE Rintiana, Rintiana; Triloka, Joko
IJISCS (International Journal of Information System and Computer Science) Vol 9, No 2 (2025): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v9i2.1848

Abstract

The Digital Automatic Weather System (AWS) is a vital tool for real-time meteorological data collection, utilized by the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) to support weather monitoring activities. However, the effectiveness of this technology largely depends on its perceived usability among users. This study aims to evaluate the usability level of the Digital AWS implemented at BMKG Lampung Province by applying the System Usability Scale (SUS) method. Data were collected through SUS questionnaires completed by AWS users within the BMKG environment. The analysis revealed an average SUS score of 59.9, which falls into the Marginal Low category and below the industry standard benchmark of 68. These findings suggest that, although the Digital AWS is functional, several aspects require improvement, particularly in interaction simplicity, interface consistency, and usage efficiency. Recommendations are directed toward enhancing interface design, simplifying navigation, and providing user training to ensure that the Digital AWS can optimally support BMKG’s operational activities.
DEVELOPMENT OF AN EYE-CONTROLLED MOBILE ROBOT SYSTEM USING EOG SIGNALS Triloka, Joko; Fauzi, Adi Ahmad
IJISCS (International Journal of Information System and Computer Science) Vol 9, No 3 (2025): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v9i3.1859

Abstract

The development of an eye-controlled mobile robot system using Electrooculography (EOG) signals is presented in this study. The proposed system enables robot motion control through eye movement detection, providing an alternative interaction method for individuals with limited physical mobility. The EOG sensor captures eye movement potentials, which are processed by a microcontroller to generate motion commands. A threshold-based detection algorithm was implemented to classify eye movements into four directional commands: left, right, forward, and backward. The system was tested to evaluate movement accuracy and response time. Experimental results show that the proposed system achieved an average directional detection accuracy of 88.3% and an average response time of 218 milliseconds, indicating reliable and real-time performance. The findings demonstrate that EOG-based control provides a feasible and responsive approach for human–robot interaction. Future improvements may involve noise filtering techniques and machine learning models to enhance signal stability and classification precision.