Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Suvriadi Panggabean
Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Medan, Indonesia
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
WEB BASED GEOGRAPHIC INFORMATION SYSTEM FOR OPTIMAL TOURIST ROUTE PLANNING IN NORTH SUMATRA USING THE ANT COLONY OPTIMIZATION ALGORITHM Faridawaty Marpaung; Mulyono Mulyono; K M A Fauzi; Eni Yuniastuti; Arnita Arnita; Suvriadi Panggabean
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss3pp2523-2534

Abstract

The transition toward Tourism 4.0 has redefined travel planning as a multifaceted optimization challenge, specifically the Personalized Tourist Trip Design Problem (PTTDP). While conventional navigation services offer basic routing, they frequently lack the capacity to integrate multi-objective constraints with interactive, preference-based spatial visualizations. This research addresses this gap by developing an integrated Spatial Decision Support System (SDSS) that merges the Ant Colony Optimization (ACO) metaheuristic with a Web-based Geographic Information System (WebGIS). The study employs a quantitative methodology, using a weighted-sum scalarization technique to harmonize divergent goals: maximizing destination attraction scores while simultaneously reducing travel distance and duration. Based on empirical validation in Berastagi City, North Sumatra, the results reveal that the ACO-WebGIS framework substantially outperforms traditional routing methods, achieving 17.84% reduction in total distance, 17.24% improvement in time efficiency, and 42.85% increase in the number of POIs visited within identical time constraints, all supported by a swift computational latency of only 1.45 seconds. The scientific value of this work lies in the seamless coupling of algorithmic optimization and dynamic spatial mapping, providing a scalable, robust tool for intelligent tourism management that delivers a mathematically sound yet practical solution for modern travelers.
Co-Authors Arnita Arnita Eni Yuniastuti Faridawaty Marpaung K M A Fauzi Mulyono Mulyono