DEVELOPMENT OF IOT-BASED MOTORCYCLE ELECTRICAL LEARNING MEDIA - Ricki Ananda; Muhammad Amin; Febby Madonna Yuma; Adi Mas Afandi (JOURNAL OF SCIENCE AND SOCIAL RESEARCH, 2026)
Abstract: The development of Industry 4.0 toward Society 5.0 requires innovation in vocational learning media based on Internet of Things (IoT) for motorcycle electrical systems. This study aims to develop a learning media for real-time monitoring and fault diagnosis. The method used is Design Based Research (DBR) consisting of analysis, design, development, and testing stages. The system integrates an ADC voltage sensor (12.6 V normal; ADC ≈ 859 and 12.1 V weak; ADC ≈ 820), pull-up resistor switch detection (logic 0 = 0 V normal; logic 1 = 5 V fault), ACS712 current sensor (1.5 A lamp ON; ADC ≈ 568 and 0 A fuse fault; ADC ≈ 511), and INA219 charging sensor (14.0 V normal charging; ADCbus ≈ 3500 and 12.4 V not charging; ADCbus ≈ 3100). The results show that all sensors operate stably and accurately in detecting both normal and fault conditions. Integration into a web-based dashboard enables real-time monitoring via computers and smartphones. Therefore, the developed learning media effectively improves students’ understanding, visualization, and analytical skills in IoT-based motorcycle electrical systems. Keywords: ACS712; ADC; Design Based Research; INA219; IoT; Motorcycle Electrical System; Learning Media   Abstrak: Perkembangan Revolusi Industri 4.0 menuju Society 5.0 menuntut inovasi media pembelajaran vokasi berbasis Internet of Things (IoT) pada sistem kelistrikan sepeda motor. Penelitian ini bertujuan mengembangkan media pembelajaran untuk monitoring dan diagnosis kerusakan kelistrikan secara real-time. Metode yang digunakan adalah Design Based Research (DBR) melalui tahap analisis, perancangan, pengembangan, dan pengujian. Sistem menggunakan sensor ADC (12,6 V normal; ADC ≈ 859 dan 12,1 V lemah; ADC ≈ 820), pull-up resistor (logika 0 = 0 V normal; logika 1 = 5 V kerusakan), ACS712 (1,5 A lampu ON; ADC ≈ 568 dan 0 A saat sekring putus; ADC ≈ 511), serta INA219 (14,0 V charging normal; ADCbus ≈ 3500 dan 12,4 V tidak mengisi; ADCbus ≈ 3100). Hasil pengujian menunjukkan seluruh sensor bekerja stabil, akurat, dan sesuai fungsi dalam mendeteksi kondisi normal maupun fault pada sistem kelistrikan. Integrasi data sensor ke dashboard web memungkinkan pemantauan real-time melalui perangkat komputer dan smartphone. Dengan demikian, media pembelajaran yang dikembangkan efektif meningkatkan pemahaman, visualisasi, dan kemampuan analisis peserta didik pada sistem kelistrikan sepeda motor berbasis IoT.. Kata kunci: ACS712; ADC; Design Based Research; INA219; IoT; Kelistrikan Sepeda Motor; Media  Pembelajaran