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All Journal Jurnal Aplikasi Teknik Sipil
Hadid, Muhammad
Institut Teknologi Kalimantan
Civil Engineering, Building, Construction & Architecture

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Pengaruh Hambatan Samping terhadap Kapasitas Dasar Jalan Perkotaan Kota Balikpapan dengan Pendekatan Simulasi Mikroskopik Hadid, Muhammad; Putri, Arum Prastiyo
Jurnal Aplikasi Teknik Sipil Vol 19, No 1 (2021)
Publisher : Departemen Teknik Infrastruktur Sipil Institut Teknologi Sepuluh Nopember Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1018.656 KB) | DOI: 10.12962/j2579-891X.v19i1.8679

Abstract

The objective of this research is to show the impact of the side friction to ideal capacity on the urban road based on a microscopic simulation approach. Simulation using software PTV VISSIM. the kind of side frictions that use are parking/stop vehicle (PSV), slow vehicle (SMW), and entry/exit vehicle (EEV). Simulation divided into 2 steps are the first is to gain the basic model and the second is to gain the impact of side friction to ideal capacity. The result shows that the side friction that gives the highest impact to ideal capacity is entry/exit vehicle (EEV), especially on an undivided road. The other result shows that the combination of side friction is not give a cumulative impact on decreasing ideal capacity. That indicates that the combination side friction simulation has a proportional impact on the decreasing of ideal capacity. This research can be an alternative method to analyze the urban traffic characteristics in Indonesia.
Sistem Klasifikasi Dan Deteksi Kendaraan Otomatis Dengan Custom Dataset YOLOv8 (Studi Kasus: Kota Balikpapan) Hadid, Muhammad
Jurnal Aplikasi Teknik Sipil Vol 23, No 3 (2025)
Publisher : Departemen Teknik Infrastruktur Sipil Institut Teknologi Sepuluh Nopember Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j2579-891X.v23i3.19632

Abstract

Currently the counting survey is still being carried out manually using surveyors. The challenges include the need for high concentration, energy-draining tasks, and the requirement for a considerable number of surveyors, which are drawbacks in manual data collection. An approach can be taken by fully replacing it with the utilization of artificial intelligence. Using deep learning, research is conducted to design an automatic vehicle detection system by employing the YOLOv8 algorithm as a real-time based vehicle detection. Then, an analysis is performed to test the model's consistency in detecting six classified vehicle objects passing through one of the CCTV videos in Balikpapan's Transportation Agency (Dishub). Based on the analysis, the system's performance is obtained with the following accuracy rates: highest during the day, 96.92%–100%; lowest at night, 91.43%–100%. F1-Score values: highest at night, 80%–100% then in the morning and during the day, 67%–100%.
Co-Authors Putri, Arum Prastiyo