Penerapan Reinforcement Learning untuk Penentuan Lokasi Optimal Usaha Minimarket
-
Nur Idil Fitri Idris
*
Universitas Teknologi Akba Makassar, Makassar,
Indonesia
- Mashud Mashud Universitas Teknologi Akba Makassar, Makassar, Indonesia
- Maysaro Maysaro Universitas Teknologi Akba Makassar, Makassar, Indonesia
- Rosmini Rosmini Universitas Teknologi Akba Makassar, Makassar, Indonesia (*) Corresponding Author
Abstract
Determining a minimarket business location is a strategic decision in the modern retail sector because it is influenced by population density, accessibility, competition level, and market potential. This study aims to develop an artificial intelligence-based adaptive system to recommend optimal minimarket business locations in Tamalanrea District using the Reinforcement Learning method. The main problem addressed in this study is how the system can dynamically assess location feasibility based on field data and provide recommendations relevant to business environmental conditions. The research method includes location data collection, data normalization, criteria weighting, and reward value calculation based on four main criteria: population density, traffic intensity, distance to other branches, and distance to competitors. The test results show that the location with the highest reward value is Indomaret Poros BTP at 0.9981, the medium category is Indomaret KM 12 No.16 at 0.9278, and the lowest category is Indomaret Poros Kapassa Raya at 0.1457. These results indicate that the developed system is able to provide adaptive, objective, and data-driven business location recommendations to support strategic decision-making in minimarket business development.
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