Spatial Evaluation of 3kg LPG Distribution Points: Analysis of Availability, Coverage, and Development Potential in Minggir Sub-district, Sleman

by. Fabiola Larasati

Introduction

Background

Equitable energy distribution serves as a fundamental pillar supporting economic activities and community welfare. Liquified Petroleum Gas (LPG) represents one such critical energy source. LPG is a liquefied gas fuel derived from petroleum products that is environmentally friendly and widely utilized by households and industries (Nurdin et al., 2020). As one of the most extensively used energy sources in Indonesia, 3kg LPG plays a vital role in meeting community living needs (Helvira et al., 2023). However, the distribution of 3kg LPG distribution points is often uneven, creating potential service gaps between regions.

In LPG distribution, there are several key terms including agents and distribution points (pangkalan). According to Sinaga et al. (2023), agents are parties appointed by Pertamina to distribute LPG gas according to their designated areas. Meanwhile, distribution points or sub-agents serve as extensions of agents that sell LPG gas to retailers such as shops or directly to consumers. Currently, 3kg LPG is no longer sold through retailers, so consumers must purchase through official distribution points. According to data from the Department of Industry and Trade of Sleman Regency (2024), Minggir Sub-district has the lowest number of official 3kg LPG distribution points in Sleman Regency. This condition indicates potential access difficulties for residents compared to other sub-districts with more distribution points. To understand this issue comprehensively, a spatial evaluation was conducted to analyze the service level of distribution points in Minggir Sub-district.

This research, titled "Spatial Evaluation of 3kg LPG Distribution Points: Analysis of Availability, Coverage, and Development Potential in Minggir Sub-district, Sleman," aims to provide a comprehensive evaluation of distribution point spread in the area. The analysis begins by measuring distribution point availability through calculating the ratio between the number of distribution points and population in each village. Subsequently, mapping is conducted to understand the spatial coverage of existing distribution points and their effective service area extent. Results from both evaluations are then used to identify development potential by mapping underserved areas. This is expected to serve as strategic guidance for stakeholders to ensure more equitable energy distribution for the community in Minggir Sub-district.

Objectives

Based on the background above, this research has the following objectives:

1. Map distribution point availability by calculating the ratio of distribution points to population in each village
2. Analyze spatial coverage of existing distribution points to understand their effective service area extent
3. Identify distribution point development potential by mapping underserved areas

Benefits

1. For Government: Provide spatial data as a foundation for more effective energy distribution equity policies
2. For Agent Business Operators: Offer strategic location recommendations for distribution point network expansion in areas with minimal competition
3. For Distribution Point Business Operators: Help understand potential market areas and customer numbers in their vicinity
4. For Consumers: Provide information to locate the nearest distribution points from their residences

Research Methodology

1. Spatial Join: Calculate the number of distribution points in each village using Spatial Join features in ArcGIS, then compare with population data to obtain ratios per 1,000 residents
2. Radius (Buffer): Use Radius tools on Geomapid with 10km distance parameters from market gravity points
3. Weighted Mean Center: Use village center points as input and population data as weight fields to find the geographic average location of total market demand
4. Network Analyst (Service Area): Use network analyst features, specifically service areas with distance tiers (500, 1,000, and 2,000 meters) around each existing distribution point
5. Overlay & Erase: Use overlay analysis, specifically Erase features by subtracting sub-district administrative polygons with service coverage polygons to produce "blank spots" as potential distribution point areas

Study Location

Minggir Sub-district is located in the western part of Sleman Regency, Special Region of Yogyakarta Province. According to the Central Statistics Agency of Sleman Regency (2024), Minggir Sub-district has a total population of 32,677 people and a total area of 27.27 km², resulting in a population density of 1,197.91 people/km². Minggir Sub-district borders Tempel Sub-district to the north, Seyegan and Godean Sub-districts to the east, Moyudan Sub-district to the south, and Kulonprogo Regency to the west. The sub-district is divided into five villages: Sendangagung, Sendangsari, Sendangrejo, Sendangmulyo, and Sendangarum.

Results and Discussion

Distribution Point Spread in Minggir Sub-district

Distribution point data for 3kg LPG gas was obtained through the Department of Industry and Trade of Sleman Regency in 2024. Initially, this data was only in tabular form with information such as distribution point names, addresses, and coordinate points. Through coordinate point information, all distribution points in Minggir Sub-district were visualized.

Based on the distribution point spread visualization, Minggir Sub-district has a total of 40 distribution points spread across each village. The distribution pattern is irregular with several distribution points located close to each other. Heatmap features on the Geomapid platform help understand the density of distribution point concentrations in the area. Two red-colored spots are visible in Sendangsari and Sendangmulyo Villages, indicating these areas have several closely located distribution points. Overall distribution point spread in Minggir Sub-district is not yet evenly distributed across villages, particularly in Sendangmulyo Village where some areas still lack distribution points.

Distribution Point Ratio Per 1,000 Residents by Village

The distribution point ratio per 1,000 residents is a figure showing how many distribution points are available to serve every 1,000 people in a village. This figure is used to fairly compare distribution point availability levels between villages without being influenced by population differences. The number of distribution points in each village was calculated using Spatial Join features in ArcGIS. Population data for each village was obtained through the publication "Minggir Sub-district in Figures 2024" published by the Central Statistics Agency (BPS) of Sleman Regency.

Calculation results show that higher ratio values indicate better service in that village, while lower ratio values indicate the village lacks distribution points. The minimum ratio value belongs to Sendangarum Village at 0.83, while the maximum ratio value belongs to Sendangsari Village at 1.36.

The calculated ratios were then visualized and classified into five classes based on minimum and maximum values. The visualization shows that three villages have the highest ratio class: Sendangsari, Sendangrejo, and Sendangmulyo. The second-highest ratio class is in Sendangagung Village, while Sendangarum Village has the lowest ratio class among other villages. This indicates that the number of distribution points in Sendangarum Village needs to be increased to improve service ratios.

Distribution of 3kg LPG Distribution Point Supply Agents in Minggir Sub-district

Agents play a role in distributing 3kg LPG gas to sub-agents or distribution points. Agent data in Sleman Regency was obtained from the "Agent Address List July 2024 Realization Update". This data was initially in tabular form requiring geotagging for spatial visualization.

The visualization shows that there are no agents located within Minggir Sub-district itself. There are 12 agents in Sleman Regency distributing gas to each distribution point. The supply agent distribution pattern is irregular and tends to cluster in certain areas. Heatmap features show no red-colored classes, indicating agent locations are not densely packed.

Identification of Agent Coverage from Market Gravity Center Point

The market gravity center point was obtained based on population numbers in each village in Minggir Sub-district using the Weighted Mean Center method. The calculation process takes the center point (centroid) of each village administrative polygon, then weights each point based on population data. Population numbers serve as the primary basis for 3kg LPG market demand since areas with higher populations logically have greater consumption potential.

Using a 10-kilometer radius buffer from the market gravity center point, 6 agents were identified as having the closest locations to the market gravity center in Minggir Sub-district: PT Padma Duta Sentosa, PT Dutagas Sinar Abadi, PT Cipta Mandiri Bhakti, PT Arza Putra Mandiri, PT Wirata Andela Lasmana, and PT Rafano Putra Mandiri. These six agents are expected to maximize distribution point networks in Minggir Sub-district due to their proximity advantage to the market gravity center.

Service Area Determination Based on Distance

Service areas were processed using Network Analyst methods in ArcGIS software based on road data obtained through OpenStreetMap (OSM). Distance classes of 500 meters, 1,000 meters, and 2,000 meters were determined as ideal since consumers typically choose to purchase gas at locations not too far from their residences.

The visualization shows that predetermined service areas have not yet covered most areas in Minggir Sub-district, with only small portions currently covered by service areas. Road accessibility becomes crucial for gas trading processes, indirectly encouraging relevant authorities to maintain and repair existing road networks in Minggir Sub-district.

Determining Distribution Point Potential in Inadequately Served Areas

Potential distribution point areas were determined using overlay and erase methods in ArcGIS software. Two datasets were overlaid: distribution point ratio per 1,000 residents shapefiles with previously processed service area shapefiles. After overlaying, areas with existing service coverage were removed, leaving only areas not yet covered by service areas in Minggir Sub-district.

The visualization shows five priority classes based on distribution point ratios per 1,000 residents in each village. New distribution point development priority focuses on areas or villages with low distribution point ratio values, namely Sendangarum Village. However, other villages can also undergo potential distribution point development.

Conclusion

Based on results and discussion, several conclusions can be drawn:

1. Availability Analysis: Distribution point service levels in Minggir Sub-district are spatially uneven. Ratio thematic maps show clear disparities between villages, with Sendangarum Village identified as having the lowest distribution point availability per 1,000 residents, visually indicating significant service gaps.
2. Spatial Coverage Analysis: Service area analysis using 500, 1,000, and 2,000-meter methods shows that effective service areas from 40 existing distribution points only cover a small portion of total Minggir Sub-district area. This indicates most residents must travel relatively far distances to access the nearest distribution points.
3. Development Potential: Combining availability and coverage analyses successfully identified potential areas for new distribution point development. Generated blank spot maps show that primary priority areas for distribution point development are in Sendangarum Village, which not only has the lowest service ratio but also has the largest area not covered by existing distribution point services.

Recommendations

1. For Regional Government: Ratio service data visualization can serve as a foundation for formulating energy distribution equity policies, especially by encouraging distribution point establishment in Sendangarum Village
2. For Agent Business Operators: Potential vacant area visualization can function as strategic guidance for planning network expansion and opening new distribution points in proven underserved areas
3. For Distribution Point Business Operators: Distribution point owners can use distribution spread and service coverage visualization to understand competition levels around their locations and identify untapped potential market areas
4. For Consumers: Communities can utilize official distribution point spread visualization from this research as guidance to find the nearest distribution points from their residences

References

Bibliography

Central Statistics Agency. (2024). Minggir Sub-district in Figures 2024. Central Statistics Agency Publisher of Sleman Regency.

Helvira, R., Nurjannah, S., & Widiati, A. (2023). Consumer Behavior Analysis in the Use of 3 Kilogram Liquified Petroleum Gas (LPG) Subsidies from an Islamic Economic Perspective. Jurnal Adz-Dzahab: Jurnal Ekonomi Dan Bisnis Islam, 8(1), 43-54.

Nurdin, N., Darmansyah, A., & Fajriana, F. (2020). 3 Kg LPG Gas Distribution Location Mapping Application Using Android-Based Ant Colony Algorithm. Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi, 6(1), 30-36.

Sinaga, D. M., Widiarty, W. S., & Tobing, G. L. (2023). Legal Analysis Regarding Default in Cooperation Agreements Between 3 Kg LPG Distribution Points and Pertamina 3 Kg LPG Agents. Jurnal Cahaya Mandalika ISSN 2721-4796 (online), 3(2), 1317-1328.

Image Sources

Department of Cooperatives and SMEs of Sleman Regency. Minggir Sub-district Office. https://dinkopukm.slemankab.go.id/event-location/kantor-kapanewon-minggir/ (Accessed July 30, 2025).

Hartati, E. R. (2024). Pertamina Threatens to Close Distribution Points Selling 3kg LPG Not According to Regulations. Investor.id. https://investor.id/business/350207/pertamina-ancam-tutup-pangkalan-yang-jual-lpg-3kg-tak-sesuai-aturan (Accessed July 30, 2025).

Data Sources

Geospatial Information Agency. National Geospatial Portal of the Republic of Indonesia. https://tanahair.indonesia.go.id/portal-web/ (Accessed July 30, 2025).

Central Statistics Agency. (2024). Minggir Sub-district in Figures 2024. Central Statistics Agency Publisher of Sleman Regency.

Department of Industry and Trade of Sleman Regency. (2024). Department of Industry and Trade of Sleman Regency. https://perindag.slemankab.go.id/ (Accessed July 30, 2025).

Directorate General of Oil and Gas, Ministry of Energy and Mineral Resources. (2024). Agent Address List July 2024 Realization Update. https://migas.esdm.go.id/ (Accessed July 30, 2025).

OpenStreetMap contributors. OpenStreetMap. https://www.openstreetmap.org/ (Accessed July 30, 2025).