Kajian Kausalitas Permintaan Trafik Terhadap Kapasitas Bandara Berdasarkan Persepsi Pengelola Bandara (Studi Kasus: Bandara Internasional Soekarno-Hatta)

Anwar, Fadrinsyah · 2017 · Crossref

DOI: 10.25104/wa.v41i1.140.11-18

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Summary

This study investigates the causal relationship between air traffic demand and airport capacity, specifically examining how variables influencing traffic demand affect the expansion of airport facilities. The research is motivated by the significant growth in air travel in Indonesia, which has outpaced capacity development, leading to congestion at major commercial airports. The primary objective is to determine which demand factors drive the need for specific capacity enhancements to inform better airport planning and development strategies. The study employs a probabilistic causality approach using Bayesian Networks (BN) to analyze uncertainty and causal links. Data were collected through primary surveys using Likert-scale questionnaires administered to airport managers and experts at Soekarno-Hatta International Airport, Indonesia’s largest commercial airport. The methodology involved purposive sampling to gather conditional perceptions regarding capacity strategies. The analysis utilized the Belief Network PowerConstructor algorithm for structure learning and Netica 4.16 software for probabilistic inference. The model incorporated five key demand variables—economy, population, deregulation, ticket prices, and flight routes—and ten capacity variables representing airside facilities (runway, taxiway, apron) and terminal facilities (gate, baggage claim, curbside, check-in, security screening, and departure lounge). The results indicate that increases in the probability of traffic demand variables generally lead to increases in the probability of airport capacity variables. Specifically, the analysis identified three capacity variables with significantly increased probabilities: runway, apron, and curbside. When individual demand factors were tested, flight routes had the strongest impact on runway capacity (9.59% increase), deregulation most significantly affected curbside capacity (9.54% increase), and economic factors drove the highest increase in apron capacity (6.75%). When all demand variables were simultaneously set to high probability, curbside showed the highest probability increase (11.3%), followed by apron (10.5%) and runway (9.6%). Conversely, the departure lounge showed the least sensitivity to demand changes, with probability increases below 0.2%. The study concludes that route expansion, regulatory changes, and economic growth are the dominant drivers for capacity expansion at Soekarno-Hatta International Airport. The significance of this research lies in its application of Bayesian Networks to quantify the causal links between traffic demand and infrastructure needs. By identifying that runway, apron, and curbside facilities are most responsive to demand fluctuations, the study provides airport operators with evidence-based insights for prioritizing capacity investments. This approach helps mitigate the risks associated with both excess capacity and insufficient infrastructure, offering a structured method for planning airport development that accounts for the complex interplay of economic, demographic, and regulatory factors.

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• traffic density