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Locating a Hub Port in Eastern Indonesia Using Network Analytics Armand Omar Moeis; Nur Faqih Wirawan; Arry Rahmawan Destyanto; Andri D. Setiawan; Bahy Helmi Hartoyo Putra; Teuku Yuri Zagloel; Akhmad Hidayatno
Jurnal Penelitian Transportasi Laut Vol 23, No 2 (2021): Jurnal Penelitian Transportasi Laut
Publisher : Puslitbang Transportasi Laut, Sungai, Danau, dan Penyeberangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25104/transla.v23i2.1695

Abstract

The main, current challenge to the maritime logistics system of Indonesia is the low level of freight transport from its eastern region. The transportation of goods to and from the eastern and western regions of Indonesia must be balanced if efficiency is to be enhanced and costs are to be reduced. One remedy to the current imbalance is increasing the existing economies of scale. This could be achieved by developing a hub port to enable goods to be consolidated and transported efficiently. The present study employs network analytics to determine the best site for a hub port in the eastern region of Indonesia. The coordinates of the ports in that region were analyzed using centrality algorithms and the NetworkX library. Based on analysis result, in perspective of relative distance between ports then Bitung port will be recommended as hub port in eastern Indonesia.
Indonesian Port Cluster Simulation Game: Understanding Complex System Through Simulation Game Armand Omar Moeis; Shara Marcheline; Arry Rahmawan Destyanto; Teuku Yuri Zagloel; Akhmad Hidayatno
Jurnal Penelitian Transportasi Laut Vol 22, No 1 (2020): Jurnal Penelitian Transportasi Laut
Publisher : Puslitbang Transportasi Laut, Sungai, Danau, dan Penyeberangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25104/transla.v22i1.1548

Abstract

Port Cluster is a collection of interdependent and involved companies in related activities in the same port area. Port clusters can be categorized as infrastructure. One of the characteristics of infrastructure is the number of parties involved in a problem, referred to as a Multi-Actor System. In a multi-actor system, policymaking becomes more complicated because it cannot be based on only one party's interests. Policymaking in this domain requires contemporary approaches where one of them is Simulation Gaming. This paper shows how Simulation Gaming can serve as an approach to comprehend the Indonesian Port Cluster, a multi-actor system.
Designing Indonesian Liner Shipping Network Armand Omar Moeis; Teuku Yuri Zagloel; Akhmad Hidayatno; Komarudin Komarudin; Sonny Guo
Jurnal Teknik Industri Vol. 19 No. 1 (2017): JUNE 2017
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (367.252 KB) | DOI: 10.9744/jti.19.1.47-54

Abstract

As the largest archipelago nation in the world, Indonesia’s logistics system has not shown excellence according to the parameters of logistics performance index and based on logistics costs percentages from overall GDP. This is due to the imbalances of trading on the western and eastern regions in Indonesia, which impacts the transportation systems costs to and from the eastern regions. Therefore, it is imperative to improve the competitiveness of Indonesian maritime logistics through maritime logistics network design. This research will focus on three levels of decision making in logistics network design, which include type of ships in the strategic level, shipping routes in the tactical level, and container allocation in the operational level with implementing butterfly routes in Indonesia’s logistics networking problems. Furthermore, this research will analyze the impact of Pendulum Nusantara and Sea Toll routes against the company profits and percentages of containers shipped. This research will also foresee how demand uncertainties and multi-period planning should affect decision making in designing the Indonesian Liner Shipping Network.
Machine learning model for green building design prediction Mustika Sari; Mohammed Ali Berawi; Teuku Yuri Zagloel; Rizka Wulan Triadji
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i4.pp%p

Abstract

Green Building (GB) is a design concept that implements sustainable processes and green technologies in the building’s life cycle. However, the design process of GB tends to take longer than conventional buildings due to the integration of various green requirements and performances into the building design. Technological advances are continually improving the quality of human life by providing solutions to problems they encounter, such as the machine learning (ML) technique utilized to develop predictive and classification models. This study aims to develop a GB design prediction by employing an ML approach by considering four GB design criteria: energy efficiency, indoor environmental quality, water efficiency, and site planning. A dataset of GB projects collected from a private construction company based in Jakarta was used to train and test the ML model. Mean Square Error (MSE) was used to evaluate the model accuracy. The comparison of MSE results of the conducted experiments showed that the combination of the ANN method with the IF-ELSE algorithm resulted in the most accurate ML model for GB design prediction with an MSE of 1.3, creating a predictive model that improves the time efficiency of GB design process.