Local Community Involvement for Indonesian National Bridge Management Systems

More Info


Within the Indonesian national road network, Bina Marga, assisted by regional offices (Balai), manage nearly 18,000 bridges scattered across 34 provinces. Maintaining its reliability is vital as inland transportation remains the most effective mobility means for ± 270 million inhabitants. Therefore, as a road service provider under the Ministry of Public Work and Housing, they aim to achieve a high maturity level in public infrastructure asset management (PIAM) practices. It is done by improving the current Bridge Management Systems (BMS) 1992 guideline. However, managing such a vast network is challenging. The limited human resources in quality & quantity hinder Bina Marga and Balai to strive for reliable data and adequate routine maintenance. Inspired by Indonesian collectivism, the study explores local community involvement to improve bridge data quality and adequate routine maintenance, i.e., BMS x Locals. Its objective is to recommend Bina Marga to improve the current BMS practices through a BMS x Locals guideline. The study sketches the current state of BMS, identifies drivers in outsourcing locals, identifies the type of works and groups, identifies locals’ willingness to be outsourced, and generates situational strategies. The research question is formulated as: How can the local community be involved as the external resources to assist Bina Marga’s in Indonesian Bridge Management Systems (BMS). This study uses interviews and desk study to collect data on six Bina Marga & five Balai NTB officials, and five locals in West Nusa Tenggara province. In addition, various data analyses are performed, consisting of Causal Loop Diagram (CLD), Multi-criteria Decision-Making Analysis (MCDA), SWOT & TOWS analysis. The study results and the BMS x Locals guideline have been validated by a high-level Balai official. For the result, CLD reveals that Bina Marga is struggling for a high PIAM maturity level because of the absence of specific quadrennial strategic planning (RENSTRA) and limited human resources in BMS, making them unable to obtain reliable data and perform adequate routine maintenance within a year. It also identifies Bina Marga’s drivers to outsource locals: up-to-date data monitoring, additional human resources, economy, and public engagement. The MCDA, amounting to 4 analyses, identifies nine criteria: cost, time, bridge literacy, technological literacy, labouring skill, quality, continuity, level of education, and age. Such criteria generate inventory and condition data – conducted by local university elements and cleaning works (garbage, rubble, grass, and drainage) – by locals in the municipality’s list. Locals’ willingness to be outsourced is also unveiled through CLD, consisting of economy, i.e., additional income and knowledge & local pride. Moreover, SWOT & TOWS analysis identifies 11 strengths, 12 weaknesses, 9 opportunities, and 10 threats for BMS x Locals; and generates situational strategies (maxi-maxi: 7, maxi-mini: 7, mini-maxi: 6, and mini-mini: 7). Finally, synthesised situational strategies amounting to 1 to 2 items have been presented according to the empirical challenges. Based on the research outcome, BMS x Locals guideline is recommended to Bina Marga and Balai comprising six primary activities: screening, assessment of capacity, organisation forming & linking, planning & design, implementation, and monitoring & evaluation.