Weighing of Performance Indicator Components National Road Condition Program in Maluku Province
DOI:
https://doi.org/10.59188/eduvest.v5i2.50821Keywords:
performance indicators, component weights, national roads, MalukuAbstract
The Program Performance Indicator (IKP) stipulated in the Guidelines for the Road and Bridge Sector No.07/P/BM/2021 is an indicator to measure the fulfillment of the level of road network services. The IKP consists of four components where the IKP value is the average value of the four components. The four components of the IKP are unevenness (IRI), pavement surface condition (PCI), remaining pavement life (RSL), and drainage effectiveness with the weight of each component set in the guidelines, namely IRI 60%, PCI 10%, RSL 15%, and drainage effectiveness 15%. The weight can also be adjusted to the specifics of each Center or Province. This study aims to examine the components of IKP in West Papua and West Java Provinces. The research was conducted using the Analytical Hierarchy Process (AHP) method to obtain a ranking of each IKP component. The results of the study were obtained that the weight of the IKP component based on the guidelines could be accepted and applied to the review area, except for the weight of the PCI for Maluku Province where less than 75% of respondents stated that it was appropriate. The weight of the components obtained based on the AHP analysis for the Maluku region is IRI 28%, PCI 27%, RSL 23%, and drainage effectiveness 22%. The results of the study can be considered as a reference for the preparation of component weights for other provinces in Indonesia.
References
Faisal, R. (2020). Perbandingan Metode Bina Marga Dan Metode PCI (Pavement Condition Index) Dalam Mengevaluasi Kondisi Kerusakan Jalan (Studi Kasus Jalan Tengku Chik Ba Kurma, Aceh). Teras Jurnal: Jurnal Teknik Sipil, 10(1), 110–122.
Hanandeh, S. (2022). Introducing mathematical modeling to estimate pavement quality index of flexible pavements based on genetic algorithm and artificial neural networks. Case Studies in Construction Materials, 16, e00991.
Ibrahim, E. M., El-Badawy, S. M., Ibrahim, M. H., & Elbeltagi, E. (2020). A modified pavement condition rating index for flexible pavement evaluation in Egypt. Innovative Infrastructure Solutions, 5, 1–17.
Jannat, G. E., & Tighe, S. L. (2015). Performance based evaluation of overall pavement condition indices for Ontario highway systems. TAC 2015: Getting You There Safely-2015 Conference and Exhibition of the Transportation Association of Canada//ATC: Destination Sé Curité Routiè Re-2015 Congrè s et Exposition de l’Association Des Transports Du Canada.
Kheirati, A., & Golroo, A. (2022). Machine learning for developing a pavement condition index. Automation in Construction, 139, 104296.
Setiawan, F. D. (2023). Analisis Pemanfaatan Filler Tanah Merah Sebagai Campuran Aspal Hrs-Wc Terhadap Karakteristik Hasil Uji Marshall. Institut Teknologi Sepuluh Nopember Surabaya.
Sholevar, N., Golroo, A., & Esfahani, S. R. (2022). Machine learning techniques for pavement condition evaluation. Automation in Construction, 136, 104190.
Shtayat, A., Moridpour, S., Best, B., & Rumi, S. (2022). An overview of pavement degradation prediction models. Journal of Advanced Transportation, 2022(1), 7783588.
Sihombing, S., Rodji, A. P., & Akbar, J. A. (2019). Analisis Penggunaan Serbuk Batu Karang sebagai Filler pada Campuran Asphalt Concrete-Wearing Course (AC-WC). Prosiding Seminar Nasional Teknologi Universitas Krisnadwipayana, 368–375.
Sowolino, B. O. (2023). Penentuan bobot komponen indikator kinerja Program Kondisi Jalan Nasional. Program Studi Teknik Sipil Program Doktor Fakultas Teknik-UNPAR.
Wibowo, P., & Mabui, D. S. S. (2023). Karakteristik Marshall pada Campuran Aspal HRS-WC dengan Menggunakan Filler Batu Karang. Prosiding Seminar Nasional Teknik Sipil, 1(1), 477–486.
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Burhanuddin Hasri, Buri Hartanto Susilo, Hamkah
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
