PEMETAAN LOKASI TEMPAT KULINER YANG SUDAH BERSERTIFIKAT HALAL DI KOTA PADANG MENGGUNAKAN DATA APLIKASI GOOGLE MAPS

Authors

  • Muhamad Ihsan Universitas Negeri Padang

DOI:

https://doi.org/10.23969/jp.v11i03.61405

Keywords:

Halal Culinary; Halal Certification; Google Maps; Geographic Information Systems (GIS); Spatial Analysis

Abstract

The rapid growth of the culinary industry in Padang City has not been accompanied by the availability of comprehensive spatial information regarding culinary businesses with official halal certification. This condition makes it difficult for the public, particularly Muslim tourists, to obtain accurate information about certified halal culinary destinations. This study aims to identify the categories of halalcertified culinary businesses, analyze their spatial distribution patterns, and map their locations in Padang City using Google Maps data. This research employed a quantitative descriptive method with a spatial analysis approach based on Geographic Information Systems (GIS). A saturated sampling technique (census) was applied, in which all identified halal-certified culinary businesses were included as research objects. Data were collected through observations using Google Maps, recording geographic coordinates, and verifying halal certification data from the Halal Product Assurance Agency (BPJPH) and the Indonesian Ulema Council (MUI). Data analysis included descriptive analysis, Nearest Neighbor Analysis (NNA), buffer analysis, and Kernel Density Estimation. The results showed that of the 668 culinary businesses identified on Google Maps, 450 businesses (67.36%) had obtained halal certification, while 218 businesses (32.64%) had not. The Nearest Neighbor Analysis index (R = 0.7) indicates that the spatial distribution of halal-certified culinary businesses in Padang City follows a clustered pattern. Density and buffer analyses further revealed that halal culinary businesses are concentrated in the city center and along major road corridors, whereas suburban areas exhibit a lower distribution density. The findings were visualized through an interactive Web GIS map using Google My Maps, providing accessible spatial information for the public.

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Published

2026-07-26