Hamkah, Godfried Lewakabessy, Icha Hest

Determination of the Effectiveness of Drainage of National Road Sections Based on DIS Data in Maluku Province

Introduction

Determination of the effectiveness of drainage of national road sections based on dis data in maluku province. Determine national road drainage effectiveness in Maluku Province using DIS and PCI data. This research provides ED index & ranking for road maintenance by BPJN/Bina Marga.

Abstract

Every five years, periodic maintenance is required for damage to parts of the road, where samples are taken from each location every year to measure the damage weight value and obtain the PPI value, in order to determine whether parts of the road or other supporting buildings need to be preserved periodically or not. IRI survey to measure unevenness components, PCI/SDI survey to measure pavement surface conditions, Benkelmen beam to measure remaining pavement life, Topographic survey, drainage effectiveness ranking to measure ED components and other surveys that support the availability of primary data and secondary data which of course require a lot of time and cost. To determine the ED index value (Effectiveness of Drainage), an approach is needed through PCI data and ED (Effectiveness of Drainage) will be determined or analyzed using the data that has been collected/downloaded, then the data that has been processed after that will be useful for BPJN agencies or the Bina Marga Service/sub- service related to roads/bridges or road implementation because the ED component is an important part of the PPI component. Based on the research results, the ranking is obtained from the calculation of the ED (Effectiveness of Drainage) ranking range

Review

This paper addresses a highly relevant issue in infrastructure management: the effectiveness of road drainage systems, specifically focusing on national road sections in Maluku Province. The stated objective is to determine drainage effectiveness based on "DIS Data," aiming to provide valuable insights for periodic road preservation and management. Given that poor drainage is a primary contributor to pavement deterioration, the research topic holds significant practical importance for road agencies like BPJN and Bina Marga, potentially leading to more targeted and efficient maintenance strategies. The abstract effectively highlights the extensive time and cost typically associated with traditional road surveys, implying that the proposed approach offers a more streamlined and cost-effective method. The methodology outlined in the abstract proposes determining the Effectiveness of Drainage (ED) index value by leveraging existing data, particularly PCI (Pavement Condition Index) data, and other "collected/downloaded" information. While the abstract lists various surveys (IRI, PCI/SDI, Benkelman beam, topographic) that contribute to primary and secondary data, the precise connection of "DIS Data" from the title to these specific datasets, and exactly how PCI data is used to *derive* or *analyze* ED, remains somewhat underspecified. A clearer articulation of the analytical model or approach used to translate PCI values into an ED ranking would significantly enhance the understanding and replicability of the proposed method. The emphasis on utilizing readily available data, however, is a strong point, suggesting a pragmatic approach to data-driven decision making. The research concludes with the generation of a ranking based on the calculated ED (Effectiveness of Drainage) ranking range. While the abstract states that these results will be useful for relevant agencies due to ED being an important part of the PPI (Pavement Performance Index) component, further elaboration on the nature of this ranking and its direct implications would be beneficial. For instance, what does the ranking reveal about the current state of drainage effectiveness in Maluku, and how can these specific findings guide future maintenance interventions? A more detailed discussion of the *significance* of the ranking, beyond its mere existence, would strengthen the abstract. Overall, this research promises a valuable contribution to optimizing road maintenance practices by focusing on a critical yet often resource-intensive aspect of infrastructure management. The full paper would benefit from a more explicit definition of the "DIS Data" and a detailed explanation of the analytical process.

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