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All Journal Jurnal Penelitian Infotekmesin Journal of Energy and Electrical Engineering (JEEE) Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Jurnal Teknologi dan Manajemen Industri Terapan Information Technology Education Journal Jurnal Polimesin Jurnal Keselamatan Transportasi Jalan Journal of Renewable Energy and Smart Device Journal of Current Studies in SDGs
Helmi Wibowo
Politeknik Keselamatan Transportasi Jalan
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Transportation Other

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PENGUKURAN KECEPATAN KENDARAAN BERBASIS MIKROKONTROLER GUNA MENUNJANG KESELAMATAN DALAM BERKENDARAN I Gede Indra Perdana; Helmi Wibowo; Asep Ridwan
Jurnal Penelitian 237-246
Publisher : Politeknik Penerbangan Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46491/jp.v6i4.813

Abstract

Tingkat kecelakaan di Indonesia masih tergolong sangat tinggi sampai saat ini, Berdasarkan sumber dari Kepolisian tingkat kecelakaan lalu lintas dari tahun 2018 sampai 2019 paling banyak disebabkan oleh faktor kendaraan terkait dengan pemenuhan persyaratan teknis dan laik jalan hingga mencapai 61%. Setelah dilakukan analisa untuk kendaraan yang beroperasi di jalan ternyata banyak terdapat kegagalan atau malfungsi pada skala speedometer yang terdapat di kendaraan. Metode analisis yang digunakan pada penelitian yaitu teknik analisis t-tes deskriptif. Peneltian ini juga menggunakan 3 (tiga) kendaraan sampel dengan masing-masing kendaraan di uji putaran roda dan propeller shaft dengan kecepatan konstan 10 km/jam. Berdasarkan penelitian ini diketahui bahwa Alat Uji Speedometer ini menggunakan bahan-bahan seperti infrared sensor, LCD, baterai 9 V, jumper serta mikrokontroler kemudian dikemas ke dalam bentuk akrilik yang sudah dibuat agar lebih menarik, Dari 6 percobaan yang dilakukann, didpatkan hasil bahwa alat uji pengukur kecepatan belum bekerja secara optimal kelebihan dari alat ini yaitu Bahan-bahan yang digunakan untuk pembuatan Rancang Bangun Alat Uji Speedometer ini tergolong murah serta Alat ini bisa digunakan untuk pengujian speedometer di UPT PKB dan untuk kelemahannya sendiri yaitu Sensor infrared yang digunakan pada alat uji speedometer ini sangat rentan terhadap cahaya, sehingga mempengaruhi hasil pembacaan putaran, Diameter roda maupun propeller shaft sangat berpengaruh pada hasil kecepatan serta Posisi letak penanda untuk pembacaan sensor juga mempengaruhi kecepatan yang dihasilkan.
Traffic Light Maintenance Training at The Transportation Office of Kulon Progo Regency Helmi Wibowo; Riza Pahlevi; Hanif Adhi Yudhitami; Dhi Astuti
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 3, No 2 (2022): REKA ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v3i2.116-123

Abstract

In traffic regulation, Maintenance of Traffic Light Signaling Devices (APILL) is a competency that must be possessed by every employee of the Department of Transportation, so that every APILL at road intersections is able to regulate the speed of vehicles in an orderly manner. The method used was to provide education and training to employees of the Kulonprogo Department of Transportation for 5 (five) days. To measure the level of understanding of the training participants, pre-test and post-test were conducted. The average value of pre-test and post-test was 68 and 83 with an average increase of 16%. The conclusion of the APILL Maintenance Training at the Transportation Office of Kulon Progo Regency is said to be successful as indicated by the increase of the post test scores of all training participants. This shows the training participants understand the material well.
PURWARUPA HAZARD PINTAR PADA KENDARAAN MPV Helmi Wibowo; Sabrina Sabrina; Srianto Srianto
Journal of Energy and Electrical Engineering (JEEE) Vol 4, No 2: 13 April 2023
Publisher : Teknik Elektro Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jeee.v4i2.6372

Abstract

The use of Hazard lights on vehicles is not in accordance with traffic rules so that it often results in accidents. Hazard lights are widely misused and often confuse the driver behind. Based on this, the study made a smart Hazard tool to minimize the number of accidents. The research method used in this study is an experimental method. This smart Hazard makes the Hazard lights turn off automatically without pressing the Hazard light switch when the right and left turn signals are turned on.  This tool can be simulated in Multi Purpose Vehicle (MPV) type vehicles with negative controllers and only requires a very small power of 0.398 Watts when the hazard lights are on and the turn signal is on so as not to make the battery consumption large and the voltage considered reasonable so as not to affect other electricity.
Development of a YOLO- and MQTT-Based Overtaking Warning System for Intelligent Driver Safety Education Muhammad Faris Haidar; Helmi Wibowo
Information Technology Education Journal Vol. 5, No. 2, May (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i2.269

Abstract

Purpose – This study aims to develop an intelligent overtaking warning system based on YOLOv8 object detection and Vehicle-to-Vehicle (V2V) communication using MQTT, designed as a prototype with the potential to serve as an interactive learning medium for driver safety and vehicular communication concepts. The study is motivated by the limited availability of practical educational tools for understanding overtaking processes and real-time communication in the Internet of Vehicles (IoV) context. Design – The research adopts a research and development (R&D) approach, including system design, implementation, and testing stages. The system is built using Raspberry Pi and ESP32, integrating GPS and LiDAR sensors with OCR-based recognition, and is evaluated through technical performance testing and user perception analysis using a Likert-scale questionnaire with validity and reliability testing. Findings – The results show that the system achieves an average end-to-end detection and processing delay of 0.911 seconds, while MQTT communication latency averages approximately 0.1269 seconds under controlled network conditions, with stable bidirectional communication. The YOLOv8 model performs optimally at a confidence threshold of 0.4, and the GPS and LiDAR sensors produce average error rates of 3.99% and 2.86%, respectively, while MQTT communication achieves a 100% success rate under tested conditions. Questionnaire results indicate that respondents reported positive perceptions regarding system usefulness, with most questionnaire items meeting validity criteria (r > 0.31) and a Cronbach’s Alpha of 0.952, indicating high reliability. Research Implication – These findings suggest that the system is technically feasible and demonstrates perceived educational potential as an interactive learning medium. However, this study is limited by the number of respondents and simulation-based testing; therefore, future work should include real-world traffic testing and larger-scale evaluations to improve system robustness and applicability. Originality – This study integrates YOLOv8-based object detection with MQTT-based V2V communication to develop an intelligent overtaking warning system as an interactive learning medium in IoV contexts.
Analisis dan Redesain Kursi Pengemudi Truk Pertamina Ditinjau dari Aspek Ergonomi Agung Tri Febrianto; Rifano; Helmi Wibowo; Sugiyarto
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 5 No. 2 (2026): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v5i2.1748

Abstract

Pengemudi truk tangki PT Pertamina (Persero) menghadapi risiko gangguan muskuloskeletal akibat penggunaan kursi pengemudi yang belum sepenuhnya memenuhi prinsip ergonomi. Penelitian ini bertujuan menganalisis tingkat ergonomis kursi pengemudi truk Pertamina berbasis sasis Hino di Fuel Terminal Rewulu serta merumuskan rekomendasi redesain berbasis antropometri. Metode yang digunakan meliputi pengukuran sudut postur dengan goniometer pada 58 responden, kuesioner Nordic Body Map (NBM) dengan skala Likert, serta simulasi software Jack versi 8.4 menggunakan metode Posture Evaluation Index (PEI) yang mengintegrasikan Low Back Analysis (LBA), Ovako Working Posture Analysis System (OWAS), dan Rapid Upper Limb Assessment (RULA). Hasil menunjukkan bahwa sudut torso tidak memenuhi standar rekomendasi, nilai PEI tertinggi sebesar 2,100 dan terendah 1,408, serta keluhan muskuloskeletal terbesar terdapat pada batang tubuh dan leher. Rekomendasi redesain kursi berbasis data antropometri Perhimpunan Ergonomi Indonesia berhasil menurunkan nilai PEI hingga 1,835 pada responden dengan risiko tertinggi, membuktikan bahwa penyesuaian dimensi kursi secara ergonomis efektif meningkatkan kenyamanan dan keselamatan pengemudi.
Multimodal vehicle security system based on internet of things: integration of fingerprint authentication, face recognition, and GPS tracking Dodik Wahyu Wiratama; Muhammad Iman Nur Hakim; Helmi Wibowo; Arief Novianto
Jurnal Polimesin Vol 24, No 3 (2026): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i3.9032

Abstract

The surge in vehicle theft in Indonesia has exposed the weaknesses of conventional security systems such as mechanical keys and immobilizers. This study aims to develop an IoT-based vehicle security system integrating fingerprint authentication, facial recognition, and GPS tracking, and evaluates its performance quantitatively. The system was tested on a Toyota Avanza with six users. Facial recognition used a MobileNetV2 CNN model trained with 1,200 local images across four classes (registered, unregistered, masked, and sunglasses) using a learning rate of 0.001, batch size of 32, and 50 epochs. Fingerprint authentication employed minutiae extraction with Euclidean distance matching. The system successfully implemented two-factor authentication. Facial recognition achieved an accuracy of 94.2%, with a False Acceptance Rate (FAR) of 2.1% and a False Rejection Rate (FRR) of 3.7%. Fingerprint authentication reached 91.5% accuracy, with FAR of 4.3% and FRR of 4.2% under dry finger conditions, while FRR increased to 18.5% for scratched fingers. The system detected unregistered users and triggered engine shutdown while sending photos and GPS coordinates through Telegram. GPS tracking achieved 99.3% positional accuracy. The results demonstrate the feasibility of multimodal IoT-based vehicle security, although performance remains sensitive to lighting conditions, face coverings, and finger surface conditions.
The Smart Battery Safety and Anti-Theft Monitoring System for Electric Bicycles with Automatic Cut-Off and Dual-Channel Notification Andhika Putra Perdana; Mokhammad Rifqi Tsani; Helmi Wibowo; Nanang Okta Widiandaru
Journal of Renewable Energy and Smart Device Vol. 3 No. 2 April 2026
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/joresd.v3i2.685

Abstract

The rapid growth of electric bicycle usage in Indonesia has been accompanied by rising safety incidents, particularly those related to battery thermal runaway and theft. This research presents the design and implementation of an integrated monitoring and security system for electric bicycles using the ESP32 microcontroller, PZEM-017, DS18B20, and Neo-6M GPS module, combined with a web-based dashboard and Telegram bot notification. The system was developed using the Research and Development (R&D) method with a four-parameter monitoring scheme covering voltage, current, temperature, and geospatial coordinates. Experimental results from twenty data points per sensor demonstrated excellent accuracy: DS18B20 achieved an average error of 1.133%, PZEM-017 achieved 1.224% for voltage and 1.787% for current, while the Neo-6M module achieved 0.000575% and 0.000042% for latitude and longitude respectively. The automatic cut-off mechanism successfully operated in all six tested scenarios, and the Telegram-website integration delivered notifications with an average delay of two seconds. These findings confirm that the proposed system improves safety and security of electric bicycles through real-time multi-parameter monitoring and remote intervention capability. Unlike prior systems that address monitoring or security in isolation, this work is the first to unify real-time multi-parameter battery protection, automatic cut-off, geofencing, and dual-channel notification within a single low-cost ESP32-based platform tailored for urban electric bicycle users in Indonesia. The practical relevance of this integration is particularly significant given the accelerating adoption of electric bicycles as primary short-distance transportation in densely populated Indonesian cities, where charging-related fire incidents and theft cases have reached critical levels.  
Studi Eksperimen Penggunaan Diesel Particulat Filter Terhadap Temperatur Oli Mesin, Air Radiator, Dan Exhaust Manifold Mesin Diesel Moch. Aziz Kurniawan; Helmi Wibowo; Aat Eska Fahmadi; Nasrul Amin; Muhammad Farras
Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Vol. 12 No. 2 (2025): JURNAL KESELAMATAN TRANSPORTASI JALAN (INDONESIAN JOURNAL OF ROAD SAFETY)
Publisher : Pusat Penelitian dan Pengabdian Masyarakat (P3M)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46447/ktj.v12i2.771

Abstract

The use of vehicles using diesel engines is increasing and has a direct impact on increasing exhaust emissions, especially particulate matter (PM), which is harmful to health and the environment. This study aims to analyze the installation of a honeycomb Diesel Particulate Filter (DPF) made of galvalum on exhaust emissions and engine temperature in a Mitsubishi L300 vehicle. The DPF was designed using galvalum material with a square honeycomb configuration and glasswool variations of 50, 100, and 150 grams. The test was conducted experimentally by comparing conditions without DPF and after DPF installation, including testing exhaust emissions, engine oil temperature, radiator water temperature, and exhaust manifold temperature. The installation of a diesel particulate filter (DPF) can reduce exhaust emissions by up to 37.1% at DPF 150 variations. DPF installation also relatively increases the temperature of radiator water, engine oil, and exhaust manifold in diesel engines. The largest temperature increase in exhaust manifold temperature is up to 8.02% compared to without using DPF at idle conditions. This temperature increase is caused by the honeycomb and glasswool structures that can create obstacles to the flow of exhaust gases. When the engine speed reaches 2000 rpm, there is an increase in exhaust manifold temperature of up to 15.09% compared to idle speed. This increase is due to faster engine speed so that combustion heat also increases.
Sistem Pengawasan Perilaku Pengemudi Berbasis IoT Dengan Pemanfaatan LiDAR dan GPS Untuk Meningkatkan Keselamatan Berkendara Helmi Wibowo; Faza Asfarin Ajrun Adhim
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2823

Abstract

In 2022, a total of 139,258 traffic accidents occurred in Indonesia, encompassing all types of incidents, from minor to fatal. The high number of accidents, particularly those caused by speeding and unsafe following distances, highlights the need for a system capable of automatically monitoring and intervening in driver behavior. This study aims to develop an IoT-based control and monitoring system that not only detects violations such as overspeeding and insufficient following distance but also provides direct intervention in vehicle speed. The system utilizes an Arduino Mega and ESP32, equipped with GPS and LiDAR sensors, along with a DAC output to limit the accelerator pedal voltage when repeated violations are detected. Testing was conducted to evaluate sensor accuracy, IoT performance, and the effectiveness of speed intervention. The results showed a 100% success rate in five speed intervention tests, good sensor accuracy, and IoT notifications successfully delivered with an average delay of 5.9 seconds. The system proved to be effective and feasible as a technology-based solution to enhance driving safety.
Object Detection of Motor Vehicle Suspension Systems Based on the YOLOv8 Algorithm: Supporting Sustainable Industry and Innovation (SDG 9) Helmi Wibowo; Nurul Muzakki Rihhadatul ‘Aisy; Muhammad Iman Nur Hakim; Mokhammad Rifqi Tsani; Setya Wijayanta
Journal of Current Studies in SDGs Vol. 3 No. 2 (2027): June
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.3.2.192

Abstract

Objective: To develop an object detection system for identifying motor vehicle suspension system components using the YOLOv8 algorithm. Specifically, this study focused on improving the efficiency and accuracy of undercarriage inspection processes, which are commonly conducted manually and require technical knowledge to recognize suspension components and detect potential damage. This research contributes to automotive inspection innovation and supports the development of sustainable industrial technology in accordance with Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure). Method: The study employed a computer vision-based approach using the YOLOv8 object detection algorithm for recognizing suspension system components in motor vehicles. The dataset consisted of 1000 suspension system images collected from mandatory vehicle inspection activities at motor vehicle testing facilities. Results: The results showed that the YOLOv8-based detection model could identify suspension system components with an accuracy of up to 95%. Furthermore, the trained model successfully detected oil leakage damage on shock absorber components with an accuracy of 92%. The evaluation results indicate that the proposed system can effectively recognize suspension components under different inspection conditions and provide reliable assistance for vehicle undercarriage inspection processes. Novelty: The study provides a novel implementation of the YOLOv8 deep learning algorithm for automated suspension system inspection in motor vehicles by integrating computer vision technology into the vehicle testing process. The developed system contributes to automotive technology innovation and supports the advancement of smart inspection infrastructure in line with SDG 9 (Industry, Innovation, and Infrastructure).
Co-Authors Aat Eska Fahmadi Agung Tri Febrianto Andhika Putra Perdana Asep Ridwan Dhi Astuti Dodik Wahyu Wiratama Faza Asfarin Ajrun Adhim Hanif Adhi Yudhitami I Gede Indra Perdana MOCH. AZIZ KURNIAWAN Mokhammad Rifqi Tsani Muhammad Faris Haidar Muhammad Farras Muhammad Iman Nur Hakim Nasrul Amin Novianto, Arief Nurul Muzakki Rihhadatul ‘Aisy Rifano Riza Pahlevi Sabrina Sabrina Setya Wijayanta Srianto Srianto Sugiyarto Widiandaru, Nanang Okta