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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Ilomata International Journal of Management Ilomata International Journal of Management
Chuan-Kai Yang
National Taiwan University of Science and Technology
Computer Science & IT Decision Sciences, Operations Research & Management Social Sciences

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Temporal Exploration in 2D Visualization of Emotions on Twitter Stream Mochamad Nizar Palefi Ma'ady; Chuan-Kai Yang; Renny Pradina Kusumawardani; Hatma Suryotrisongko
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 1: February 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i1.6591

Abstract

As people freely express their opinions toward a product on Twitter streams without being bound by time, visualizing time pattern of customers emotional behavior can play a crucial role in decision-making. We analyze how emotions are fluctuated in pattern and demonstrate how we can explore it into useful visualizations with an appropriate framework. We manually customized the current framework in order to improve a state-of-the-art of crawling and visualizing Twitter data. The data, post or update on status on the Twitter website about iPhone, was collected from U.S.A, Japan, Indonesia, and Taiwan by using geographical bounding-box and visualized it into two-dimensional heat map, interactive stream graph, and context focus via brushing visualization. The results show that our proposed system can explore uniqueness of temporal pattern of customers emotional behavior.
Trucks Pooling and Allocation in TSE Concept Using GIS Spatial and Novel FFOA Batara Parada Siahaan; Togar Mangihut Simatupang; Liane Okdinawati; Chuan-kai Yang; Dinar Nugroho
Ilomata International Journal of Management Vol 3 No 4 (2022): October 2022
Publisher : Yayasan Ilomata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (620.78 KB) | DOI: 10.52728/ijjm.v3i4.571

Abstract

Strategic system logistics business entails the importance of regulating truck pooling facilities and allocating the trucks for cost optimization goals. Regulators and investors must consider spatial constraints such as the supply-demand gap and service distance. Little attention has been paid to developing decision logistics models, particularly truck pooling and allocation decisions. In this study, the FFOA and GIS were used to determine the spatial component of truck pooling decisions, providing a scenario for origin pooling and delivery distance. The model evaluates truck allocation to each city, a distance vector, a spatial factor, and city demand are used for the cost optimization goal. The results show that the FFOA model successfully defines the optimal truck allocation for each truck pooling site with a cost. The managerial implication in developing a sharing economy concept for truck logistics is to use the study's framework model result to solve challenges in truck logistics.
Trucks Pooling and Allocation in TSE Concept Using GIS Spatial and Novel FFOA Batara Parada Siahaan; Togar Mangihut Simatupang; Liane Okdinawati; Chuan-kai Yang; Dinar Nugroho
Ilomata International Journal of Management Vol 3 No 4 (2022): October 2022
Publisher : Yayasan Ilomata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52728/ijjm.v3i4.571

Abstract

Strategic system logistics business entails the importance of regulating truck pooling facilities and allocating the trucks for cost optimization goals. Regulators and investors must consider spatial constraints such as the supply-demand gap and service distance. Little attention has been paid to developing decision logistics models, particularly truck pooling and allocation decisions. In this study, the FFOA and GIS were used to determine the spatial component of truck pooling decisions, providing a scenario for origin pooling and delivery distance. The model evaluates truck allocation to each city, a distance vector, a spatial factor, and city demand are used for the cost optimization goal. The results show that the FFOA model successfully defines the optimal truck allocation for each truck pooling site with a cost. The managerial implication in developing a sharing economy concept for truck logistics is to use the study's framework model result to solve challenges in truck logistics.
Co-Authors Batara Parada Siahaan Dinar Nugroho Hatma Suryotrisongko Liane Okdinawati Mochamad Nizar Palefi Ma’ady Renny Pradina Kusumawardani Togar Mangihut Simatupang