Sistem Rekomendasi Collaborative Filtering Sebagai Upaya Peningkatan Perekonomian di Pasar Tradisional

Herbert A. Tambunan(1*), Jimmi Hendrik Pangihutan Sitorus(2),

(1) AMIK Parbina Nusantara, Pematang Siantar, Indonesia
(2) AMIK Parbina Nusantara, Pematang Siantar, Indonesia
(*) Corresponding Author

Abstract


Traditional markets face significant challenges from the growth of modern markets and e-commerce, which can lead to reduced attractiveness, loss of competitiveness and decreased sales. Traditional markets have a key role in economic, social and cultural sustainability. Therefore, the preservation and transformation of this market is very important to support the economy, promote local products and maintain cultural heritage. This research aims to improve the economy of traditional markets by implementing collaborative filtering technology, which makes it easier for consumers to find the desired products. The Horas Market in Pematang Siantar City is the object of research. Collaborative filtering is a technique that uses user data to recommend products based on similarities to other users. The dataset includes the opinions of 2,114 consumers who purchased products from 10 kiosks, totalling 97 products and 5,948 product ratings. Test results using the RSME metric with 100 epochs show a value of 0.1832 on the training data and 0.1908 on the test data. These results show the suitability of the Matrix Factorization-based collaborative filtering method as an application recommendation system at the Horas Market. In the context of traditional markets, this technology can increase sales by recommending relevant products to customers, encouraging the economic growth of traditional markets. However, it is necessary to understand the long-term implications for local communities and the economy as the next step in this research.

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DOI: http://dx.doi.org/10.30645/j-sakti.v7i2.706

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