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Prasetyo, Ilham Bagus
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Mechanical Engineering Transportation

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RANCANGAN ALAT PEMBATASAN PENGGUNAAN HANDPHONE PADA PENGEMUDI BUS BERBASIS INTERNET OF THINGS Prasetyo, Ilham Bagus; Pratindy, Raka; Srianto
Jurnal Transportasi Vol. 23 No. 2 (2023): Jurnal Transportasi
Publisher : Forum Studi Transportasi antar Perguruan Tinggi (FSTPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jtrans.v23i2.7363.146 - 156

Abstract

The phenomenon of bus drivers still using mobile phones while driving is still prevalent today. This happens because bus drivers have the opportunity to reach for their mobile phones while driving, making it necessary to restrict the use of mobile phones by bus drivers. This research aims to develop an Internet of Things (IoT)-based device that can monitor the use of mobile phones by bus drivers while driving. Using the Research and Development method, this study resulted in a design for a device that restricts the use of mobile phones by bus drivers. This device detects the installation of a mobile phone, ownership of the mobile phone, and the vehicle's speed. Through the data input and data processing in the device's design, it produces warnings in the form of text and sound, as well as violation reports sent to the bus company supervisor. This helps the bus company in monitoring bus drivers. This device's design can serve as a reference for the development of a device that can be implemented in buses to restrict the use of mobile phones while driving. ABSTRAK Fenomena pengemudi bus mengemudi sambil mengoperasikan handphone masih dijumpai hingga saat ini. Hal tersebut terjadi karena pengemudi bus memiliki kesempatan untuk menjangkau handphone pada saat mengemudi, sehingga diperlukan upaya pembatasan kesempatan penggunaan handphone pada pengemudi bus. Penyusunan karya ilmiah ini menggunakan metode penelitian Research & Development (R&D). Penelitian ini menghasilkan sebuah rancangan alat pembatasan penggunaan handphone pada pengemudi bus berbasis Internet of Things (IoT). Alat ini mendeteksi pemasangan handphone, kepemilikan handphone, dan kecepatan kendaraan. Output yang dihasilkan yaitu berupa peringatan dalam bentuk tulisan dan suara serta laporan pelanggaran yang dikirimkan kepada pengawas perusahaan otobus. Rancangan alat ini bertujuan untuk meminimalisir kesempatan pengemudi untuk dapat menjangkau handphone pada saat mengemudi. Selain itu, alat ini juga dapat membantu perusahaan otobus dalam melakukan pengawasan terhadap pengemudi bus.
Short-Term Prediction of Bus Station Fleet Number Using a Combination of BiLSTM Models Siswanto, Joko; Rahmawati, Ainun; Rahardja, Untung; Putra, Nanda Dwi; Hakim, Muhammad Iman Nur; Pinandita, Tito; Prasetyo, Ilham Bagus
Automotive Experiences Vol 8 No 1 (2025)
Publisher : Automotive Laboratory of Universitas Muhammadiyah Magelang in collaboration with Association of Indonesian Vocational Educators (AIVE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.13402

Abstract

Predicting the number of bus station fleets requires a holistic approach, using sophisticated data analysis techniques and appropriate predictive modeling. Short-term predictions of bus station fleet numbers are proposed based on the best MAPE evaluation values ​​from the comparison of the Bi-LSTM, BiLSTM-CNN, BiLSTM-Transformer, BiLSTM-Informer, and BiLSTM-Reformer models. The dataset used is in the form of a CSV consisting of 6 types of arrivals and departures of the Giwangan City Yogyakarta type A bus station fleet from 01/01/2021 to 09/30/2023. The best prediction model was found in BiLSTM-Transformers based on a MAPE value of 0.2211 with a relatively fast time (00:00:52) compared to BiLSTM, BiLSTM-CNN, BiLSTM-Informer, and BiLSTM-Reformer. The BiLSTM-Transformer model can short-term predict 6 types of fleet arrivals and departures at the bus station in the next 30 days. The peak of the bar and curve is at 0 which means the proposed prediction model is very accurate. There is 1 strong positive correlation, 2 weak positive correlations, 2 strong negative correlations, 8 weak negative ones, and 2 uncorrelated ones. Prediction results can be used to support short-term decision making in fleet planning and management based on the dynamics of community mobility.
Co-Authors Ainun Rahmawati Joko Siswanto Muhammad Iman Nur Hakim Pratindy, Raka Putra, Nanda Dwi Srianto Tito Pinandita Untung Rahardja