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Pengukuran Kedalaman dan Koordinat Jalan Berlubang Menggunakan Sensor Ultrasonik dan GPS Berbasis Internet Of Things (IoT) Phisca Aditya Rosyady; Fadil Fajeri; Muhammad Andika Agustian
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Vol 4, No 1 (2022): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v4i1.1061

Abstract

The development of the world of transportation in Indonesia is growing very rapidly, especially in the field of land transportation. This can be seen from the number of motorized vehicles, both cars, and motorcycles in Indonesia, which continues to increase from year to year. According to data from Badan Pusat Statistik (BPS), the number of motorized vehicles reached 126,508,776 units, the data increased 5.9 percent from the previous year 2017 wherein that year the number of motorized vehicles was 118,922,708 units. The problem that still often occurs for land transportation infrastructure is that there are still many damaged roads such as potholes, so prevention is needed by recording road damage data such as the depth of holes during manual recording, so in this study, we discuss how to measure these holes using ultrasonic sensors. integrated with GPS data to record the location of potholes. The result is that the measurement error using ultrasonic is 4.9 %. Meanwhile, for the results of testing the GPS data, the error in latitude data is 0.00061 %, the data for longitude error is 0.00004 %..
Prototipe Sistem Deteksi Kemacetan Jalan Raya Berbasis Internet Of Things (IoT) Phisca Aditya Rosyady; Muslih Rayullan Feter; Zakky Ahmad Ikhsan M
Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Vol 4, No 2 (2022): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v4i2.1270

Abstract

Along with the progress of the times and technology is currently increasing the number of motorized vehicles on the highway. However, this increase in the number of motorized vehicles is not matched by an increase in road volume capacity, causing traffic congestion. The purpose of this study was to find out information about traffic conditions at highway intersections. This research is a prototype that describes a four-way intersection that has infrared sensors in each path. This infrared sensor is used as a vehicle detector. Tests on the prototype made various traffic conditions that are relevant to the actual situation. This research utilizes the concept of the Internet of things (IoT) prototype which is made to be connected to the internet network so that users can find out traffic conditions remotely and in real time. One of the information media used in this research is Twitter. The results of this study indicate that the prototype made can work well. The infrared sensor used can work optimally and can detect vehicles precisely at a sensitivity range of 4.5 cm. The average delay in sending notification tweets is 18 seconds.
Elevator Energy Consumption and Upward Travel Load Patterns in A University Lecture Building Erika Wulandari; Phisca Aditya Rosyady
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 2 (2026): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i2.3949

Abstract

This study analyzes passenger elevator operation patterns and their contribution to building electricity consumption in a university lecture building. Previous research has mainly focused on system simulations or control optimization, resulting in limited empirical studies that integrate large-scale directional passenger movement data with aggregated building-level electricity consumption, especially in academic settings. To address this gap, the study examines elevator usage patterns based on 31,265 observed trips and links directional travel with building-level electricity consumption. Data were collected over a two-week period (13–24 October 2025) through direct observation and MDP-based energy measurements, then analyzed using Pearson correlation and linear regression. Results show that 44.6% of total traffic occurred in the morning, with 83.0% concentrated during peak periods. Upward trips accounted for 52.7% of movements, indicating directional asymmetry associated with increased traction motor load during peak hours. Pearson correlation analysis revealed a significant positive relationship between elevator usage intensity and daily electricity consumption (r = 0.813, p = 0.004, 95% CI [0.35–0.96]). Linear regression showed that 66.1% of variation in daily energy consumption could be explained by elevator usage intensity. This study provides a context-specific empirical analysis by integrating directional elevator travel data with aggregated building-level electricity consumption in a university lecture building, based on real-world observations. These findings demonstrate that dominant upward travel during academic transition periods is measurably associated with overall building energy consumption dynamics.