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All Journal INOVTEK Polbeng - Seri Informatika INOVTEK Seri Elektro
M. Afridon
Politeknik Negeri Bengkalis
Computer Science & IT

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RANCANG BANGUN ALAT UJI EMISI KENDARAAN BERMOTOR DENGAN PENGAMBILAN KEPUTUSAN FUZZY LOGIC Muhammad Arifin; M. Afridon
INOVTEK - Seri Elektro Vol. 7 No. 2 (2025): Desember
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/ise.v7.i2.1328

Abstract

Peningkatan jumlah kendaraan bermotor di Indonesia secara signifikan telah menjadi penyumbang utama polusi udara di kawasan perkotaan. Untuk menanggulangi hal ini, uji emisi kendaraan menjadi langkah penting guna mengontrol tingkat pencemaran udara. Penelitian ini bertujuan untuk merancang dan membangun alat uji emisi kendaraan bermotor yang mampu mendeteksi gas buang seperti karbon monoksida (CO), karbon dioksida (CO₂), hidrokarbon (HC), dan nitrogen oksida (NOx). Sistem ini mengintegrasikan sensor berbasis mikrokontroler ESP32 dengan konektivitas Wi-Fi dan Bluetooth, serta memanfaatkan metode fuzzy logic untuk mengevaluasi hasil pengukuran emisi. Proses fuzzifikasi, inferensi, dan defuzzifikasi digunakan untuk menentukan status emisi kendaraan dalam kategori 'Aman', 'Perlu Diperiksa', atau 'Berbahaya'. Hasil pengujian menunjukkan sistem ini bekerja secara real-time dan dapat digunakan secara praktis di lapangan.
Implementation of Fuzzy Logic on Motorcycle Emission Testing Device Using Multi-Gas Sensors M. Afridon; Khairudin Syah; Marzuarman; Heri Susanto; Muhammad Arifin; M. Andrian Syindau Abdillah; M. Zaki Nawaf Ramadhan
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/w1802r28

Abstract

Manual motorcycle emission inspection often leads to inconsistent interpretation due to operator dependency. This study developed a motorcycle emission testing system using multi-gas sensors, consisting of ZE07-CO for CO, an infrared CO₂ sensor for CO₂, TGS2602 for VOC, and O₂ I2C DFRobot for oxygen concentration, integrated with an ESP32 microcontroller. Sensor data are transmitted in real-time via Bluetooth to a computer for processing and visualization on a graphical user interface. The measurement ranges were adjusted to match actual exhaust gas characteristics: CO 0–5000 ppm, CO₂ 0–50000 ppm, VOC 0–500 ppm, and O₂ 0–5%. Emission level classification was performed using the Mamdani fuzzy logic method with three triangular membership functions for each parameter and three output categories: low, medium, and dangerous. Tests on nine motorcycles showed four units classified as low emission (CO <1000 ppm; O₂ >2.4%), three as medium (CO 1100–2500 ppm; O₂ 1.5–2.0%), and two older vehicles classified as dangerous (CO >3500 ppm; VOC >350 ppm; O₂ <1%). The system successfully provides automatic and real-time emission assessment, although verification against standard emission testers and environmental compensation is required for broader practical implementation.
Co-Authors Heri Susanto Khairudin Syah M. Andrian Syindau Abdillah M. Zaki Nawaf Ramadhan Marzuarman, Marzuarman Muhammad Arifin MUHAMMAD ARIFIN