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6 results on '"Zakaria, Rasdiana"'

1. Road Traffic Noise Analysis at the U-Turn in Makassar City

Author

Hustim, Muralia, Zakaria, Rasdiana, Ramli, Muhammad Isran, Syafruddin, Nurul Azizah, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Mohammed, Bashar S., editor, Shafiq, Nasir, editor, Rahman M. Kutty, Shamsul, editor, Mohamad, Hisham, editor, and Balogun, Abdul-Lateef, editor

Published
2021
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2. Total Suspended Particulate Matter (TSP)-Bound Carbonaceous Components in a Roadside Area in Eastern Indonesia.

Author

Amin, Muhammad, Ramadhani, Andi Annisa Tenri, Zakaria, Rasdiana, Hanami, Zarah Arwieny, Putri, Rahmi Mulia, Phairuang, Worradorn, Hata, Mitsuhiko, and Furuuchi, Masami

Subjects
CARBONACEOUS aerosols, PARTICULATE matter, AIR quality standards, ROADSIDE improvement, AIR sampling apparatus
Abstract

To evaluate carbonaceous components in the ambient air in the eastern region of Indonesia, 35 Total Suspended Particulate Matter (TSP) samples were collected on four characteristic roadsides on Sultan Alauddin Street, in Makassar City, using a high-volume air sampler. The average TSP concentration was 279.7 μg/m3, which exceeded both the National Ambient Air Quality Standard (NAAQS) of Indonesia and the World Health Organization (WHO) standards. The highest concentration reached 838.6 μg/m3 in the GR (gravel) site, which had the highest number of vehicles and was near a U-turn. TSP concentration was higher during peak hours (morning and late afternoon) than off-peak hours (noon). The main component of the total carbon (TC) fraction was organic carbon (OC), which showed a strong correlation with elemental carbon (EC) (r values for the morning, noon, and late afternoon were 0.89, 0.87, and 0.97, respectively), indicating that the carbon components were derived from common sources. TSP had a strong correlation with carbon components, except for char-EC. OC vs. soot-EC and EC vs. soot-EC also correlated well, suggesting the dominant influence of vehicle exhaust emissions. Non-exhaust emissions had a slight influence during peak hours, particularly at the GR site. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Road traffic noise analysis at unsignalized intersection in Makassar City.

Author

Hustim, Muralia, Aly, Sumarni Hamid, Zakaria, Rasdiana, Gara, Fernando Magnis, and Widaryanti, Nadiyah

Subjects
TRAFFIC noise, NOISE pollution, NOISE measurement, PREDICTION models
Abstract

The transportation sector has become a very important part in supporting community activities. The development of existing transportation must be balanced with the growth of roads, otherwise several problems will arise, one of which is noise pollution as a problem. This study aims to analyze the noise level at 14 observation points and to predict the noise level using the CoRTN (Calculation of Road Traffic Noise) method. Noise level measurements were carried out for 12 hours from 07.00 to 18.00 with 10 minutes of sampling from each hour using SLM TM-103. Meanwhile, for the prediction of the CoRTN method, the variables of vehicle volume and vehicle speed are used. The results show the average of noise level for all measurement points is 80.62dB. This value has exceeded the technical limit of the road capacity, which is between 63.2 dB to 76.0 dB, although the minimum result of noise level measurement 77.6 dB is still higher than the standard. From the noise prediction result, the average noise level is 77.9 dB. The comparison showed the measurement and prediction had under 3 dB difference, so that the measurement data and prediction models can be well received based on the statistic test. [ABSTRACT FROM AUTHOR]

Published
2022
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6. The Effect of Speed Factors and Horn Sound to The RLS 90 Model Reliability on The Visum Program in Predicting Noise of Heterogeneous Traffic

Author

hustim, Muralia, Ramli, Muhammad Isran, Zakaria, Rasdiana, A R, Zulfiani, hustim, Muralia, Ramli, Muhammad Isran, Zakaria, Rasdiana, and A R, Zulfiani

Abstract

This study aimed to predict the noise generated by heterogeneous traffic using RLS 90 model on the Visum program, evaluating and looking for correction factor. Points of observation were taken at 37 points on the road side at 06.00 - 18.00 and 06.00 - 21.00 with research object are motorcycle, light vehicle and heavy vehicle. The observed data are traffic volume, vehicle speed, number of horn and traffic noise by using Sound Level Meter Tenmars TM-103. The result shows the prediction model of RLS 90 Visum program produces an average noise level value of 69.3 dB with Pearson’s correlation and RMSE of 0.71 and 9.97, the prediction model RLS 90 vehicle correction produces an average noise level value of 77.9 dB with Pearson’s correlation and RMSE of 0.75 and 2.02, whereas the prediction model RLS 90 vehicle and horn correction produces an average noise level value of 79.1 dB with Pearson’s correlation and RMSE of 0.83 and 1.29. So that, prediction model RLS 90 with vehicle and horn correction quite good which has a relationship of Y = 0.71 X + 29.65 to the prediction model RLS 90 with Visum program.

Published
2018

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