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Application of Transportation Methods in Optimizing Transportation Cost for Fleet Product Distribution Radhiah, Radiah; Rusdiana, Siti; Marzuki, Marzuki; Saputra, T. Murdani; Mukhra, Uly Handayani
Transcendent Journal of Mathematics and Applications Vol 2, No 1 (2023)
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/tjoma.v2i1.31741

Abstract

Motor vehicle distribution companies which are the source of this research data are located in Banda Aceh and Medan. The vehicles will then be sent to several areas, namely Lhokseumawe, Panton Labu, Meulaboh, Takengon, Subulussalam, Kuta Binjei, Kutacane, Aceh Singkil, Rimo and North Aceh. The problem in the process of sending vehicles is that if the inventory of vehicles in one of the warehouses is empty, then the supply of vehicles is obtained from warehouses that are still available in the warehouse regardless of distance. This paper describes the optimization of transportation costs for Fleet product distribution. Products are distributed from two sources to ten destinations. The cost of sending the vehicle incurred by the company is Rp 152,994,625. By using the Vogel's Approximation Method (VAM) and Modified Distribution Method (MODI), the total cost generated is Rp 142.728.100. Solving transportation problems with the transportation method can minimize and optimize the cost of sending a vehicle of Rp 10.266.525 or 6.71% and it can increase company profits.
Does Social Assistance Expenditure Reduce Poverty? Panel Evidence from Indonesian Provinces Thahira, Zia; Agustina, Maulidar; Zikra, Naswatun; Amalina, Faizah; Mukhra, Uly Handayani
Jurnal Samudra Ekonomika Vol 9 No 2 (2025): Jurnal Samuka
Publisher : Fakultas Ekonomi dan Bisnis Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/jse.v9i2.13180

Abstract

This study investigates the determinants of poverty across Indonesian provinces with a particular focus on the role of social assistance expenditure. Using provincial panel data from 2015 to 2024, the analysis combines information on poverty headcount ratios with fiscal, economic, and political variables, namely social assistance per capita, gross regional domestic product (GRDP) per capita, unemployment rate, and election years. The study employs a fixed effects panel regression model, selected on the basis of specification tests, and incorporates one-year lagged values of social assistance and GRDP per capita to capture the delayed effects of fiscal and economic policies. The results reveal that social assistance has a negative but modest effect on poverty, indicating its limited yet relevant role in supporting vulnerable households. GRDP per capita emerges as the strongest determinant, confirming the importance of inclusive growth in driving poverty reduction, while unemployment significantly worsens poverty outcomes. In addition, poverty rates tend to fall in election years, reflecting the influence of political cycles on welfare spending. Overall, the findings underscore that poverty reduction in Indonesia requires multidimensional strategies that combine sustained economic growth, labor market improvements, and well-targeted social assistance, supported by institutional safeguards that ensure consistency beyond short-term political incentives.