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All Journal Jurnal Teknik dan Science (JTS)
Kami Hari Basuki
Faculty of Engineering, Universitas Diponegoro
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Adi Soemarmo Airport Train Demand Modelling Based on Google Cloud Big Data Ma’ruf Tsaghani Purnomo; Amelia Kusuma Indriastuti; Kami Hari Basuki; Diondi Toto Kusuma; Radhevio Izza Aghna
Jurnal Teknik dan Science Vol. 4 No. 3 (2025): Oktober: Jurnal Teknik dan Science
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jts.v4i3.2358

Abstract

The development of the Adi Soemarmo Airport Train route is necessary to optimise its services by increasing the load factor. One of the efforts that can be made to enhance the load factor includes demand modelling. Big Data provided by Google Cloud Big Data is utilised for its capacity to provide fast and large-scale trip data. This approach supports demand modelling carried out across regencies and cities as study areas for route development. The data is modelled with a four-stage transportation model, adopting zones based on sub-districts within the regencies and cities in the study area. The results indicate the emergence of potential demand through changes in transit points to transfer points in zones along the Madiun, Klaten, Wonogiri, and Gundih. These zones that have potential demand are chosen as the guidelines for developing the Adi Soemarmo Airport Train route.
Co-Authors Amelia Kusuma Indriastuti Diondi Toto Kusuma Ma’ruf Tsaghani Purnomo Radhevio Izza Aghna