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Journal : Integra: Journal of Integrated Mathematics and Computer Science

Products Distribution from Suppliers to Retailers in Bandarlampung City (Case Study: Retailers location in Teluk Betung) Salsabila, Annisa; Nikmah, Nadhir Rotun; Bakhtiananda, Rafif Syadid; Aswin, Micelle Yap; Nurvazly, Dina Eka
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 1 (2024): March
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.2024116

Abstract

Traveling Salesman Problem(TSP) is a problem where a salesman visits cities, each city is connected, and there are weights to move between cities, thus forming a complete weighted graph. The objective of the TSP is to determine all city routes with the lowest total weight. Cheapest Insertion Heuristic (CIH), one of the algorithms to solve TSP. This algorithm provides different travel routes depending on the order of city elimination on the subtour in question. In this study, the CIH algorithm will be discussed to determine the shortest route for distribution of goods from suppliers to several retailers in the city of Bandarlampung, especially for 23 retailers whose locations in Teluk Betung sub-district. The result shows that the total distance travel from the supplier to the 23 retailers and then back to the supplier location is 34.84 km.
Application of GSTARMA Spatial-Temporal Model for Inflation Analysis in South Sulawesi Province Sari, Dede Ratna; Widiarti; Nurvazly, Dina Eka; Usman, Mustofa; Loves, Luvita
Integra: Journal of Integrated Mathematics and Computer Science Vol. 1 No. 3 (2024): November
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20241322

Abstract

The Generalized Space-Time Autoregressive Moving Average (GSTARMA) model is a development of the time series model that can capture both spatial and temporal dynamics simultaneously. This study uses the GSTARMA model to analyze inflation data in five cities in South Sulawesi Province from January 2017 to October 2024. The GSTARMA model obtained is GSTARMA (1,0,1) with a cross-correlation normalization spatial weight matrix. The results of the analysis indicate a spatial influence between locations and temporal relationships in the inflation data.