The existence of a smooth highway is needed to speed up the process of transporting people, goods and services and shortening the travel time. If the road is damaged, it will result in a decline in the economy in an area. In an effort to improve road performance, it is necessary to know the level of damage and the type of damage to the road. This study will discuss the existing conditions of Durian Anduonohu and Manunggal roads based on visual observations and analyzed using the Pavement Condition Index (PCI) method, specifically for measuring vehicle speed, the moving car observer method is used. The final result of this research is the level of damage and type of road damage on Durian Anduonohu road, quite severe with a PCI value ranging from 30-67 with an average damage of 39% meaning bad conditions, with the equation from the regression analysis the following regression model results are obtained: Y = (1,390)*(0.056) x which means that there is an effect of the level of damage to the road on the speed of the vehicle at each additional PCI value. Analysis of the level of damage and types of damage to the Manunggal road segment with PCI values ranging from 41-55 with an average damage of 42%, which means that the road damage is in moderate condition (Fair), with the equation of the regression analysis the following Regression model results are: Y=(1.356))(0.044) x which means that there is an effect of the level of damage to the road on the speed of the vehicle at each additional PCI value. This research is expected to be a barometer of the Kendari city government or related agencies in trying to overcome or repair the two roads so that the flow of people, goods and services runs smoothly and the economy of the city of Kendari can continue to increase.
CITATION STYLE
Ahmad, S. N., Azikin, M. T., Sukri, A. S., & Balaka, R. (2020). Aplikasi Metode PCI (Pavement Condition Index) Dalam Mengukur Tingkat Kerusakan Jalan dan Pengaruhnya Terhadap Kecepatan Kendaraan. REKONSTRUKSI TADULAKO: Civil Engineering Journal on Research and Development, 17–22. https://doi.org/10.22487/renstra.v1i2.25
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