<![CDATA[The variety of Point of Sale (POS) applications available on the market with different features, prices, and advantages means that business owners often face challenges in choosing the POS application that best suits their needs and budget. To choose a POS application, a business owner must know, one by one, the characteristics of the application to be chosen. This makes business owners experience difficulties, and it takes a long time to determine which application to choose. Although POS applications promise great benefits, selecting the right application can be a complicated and crucial task. So, this research was carried out with the aim of building a Decision Support System (DSS) for selecting Point of Sale (POS) applications using a combination of ARAS (Additive Ratio Assessment) and ROC (Rank Order Centroid) methods. The ROC approach in this research functions to determine weight values based on priority levels. Meanwhile, the ARAS method compares and ranks alternatives based on attribute utility performance to determine the best alternative. The SPK software was developed on a website basis, with features including managing criteria data, alternatives, alternative values, ARAS method calculations, and viewing alternative ranking results. From the case studies carried out, the highest to lowest utility values were obtained, namely: Majoo (A2) got a value of 0.8626, Moka POS (A2) got a value of 0.8412, Loyverse POS (A1) got a value of 0.8078, Smart Kasir (A5) got a value of 0.7546, and Olsera POS (A3) obtained a value of 0.7136. The output produced by the system obtains the same value as the manual calculation, meaning that the implementation of the ARAS method in the system is declared valid. In terms of testing, usability testing produces an average score of 87.5%. This shows that this system is suitable for use because it has functionality that is considered to be in accordance with user requirements.]]>
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