Smart Commuter Line (KRL) using IoT and SOA in Indonesia
B. Junedi Hutagaol1, Dennis, Matius Richard2, Nilo Legowo3
1B. Junedi Hutagaol Information Systems Management Department, BINUS Graduate Program, Master of Information Systems Management, Bina Nusantara University Jakarta, Indonesia.
2Dennis Information Systems Management Department, BINUS Graduate Program, Master of Information Systems Management, Bina Nusantara University Jakarta, Indonesia.
3Matius Richard Information Systems Management Department, BINUS Graduate Program, Master of Information Systems Management, Bina Nusantara University Jakarta, Indonesia.
4Nilo Legowo Information Systems Management Department, BINUS Graduate Program, Master of Information Systems Management, Bina Nusantara University Jakarta, Indonesia.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 485-488 | Volume-8 Issue-5, January 2020. | Retrieval Number: E4976018520/2020©BEIESP | DOI: 10.35940/ijrte.E4976.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Commuter line (KRL) one of the better public transportation for commuter people in Indonesia especially in Jabodetabek (Jakarta, Bogor, Depok, Tangerang, Bekasi). Passenger satisfaction is the one of the service quality factor in KRL. There is no real time passenger information in both train and station, the situation make an unpredictable activity for passenger that want to use or wait the commuter line (KRL). Most of passenger cannot enter the train because the crowded passenger. KRL management cannot manage train capacity and train time management to meet passenger needs. This paper proposed a smart commuter line system to provide real time passenger information using IoT by count people using Markov Random Field framework and integrate all KRL enterprise system using SOA to support data integration.
Keywords: Commuter Line, IoT, SOA, Passenger Satisfaction, Markov Random Field, Public Transportation.
Scope of the Article: Approximation And Randomized Algorithms.