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Journal : RISTEC : Research in Information Systems and Technology

Implementation of the Simple Additive Weighting (SAW) Method for Supplier Selection Muhyidin, Yusuf; Iman Hermanto, Teguh; Raymond Ramadhan, Yudhi; Irmayanti, Dede; Angga Permana, Muhammad
RISTEC : Research in Information Systems and Technology Vol. 5 No. 1 (2024): JURNAL RISTEC : Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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Abstract

Supplier selection is a critical part of purchasing activities in a company because it has an impact on the quality and availability of raw materials, production cost efficiency and the smooth circulation of company finances. Determining suppliers based on certain criteria can be supported by a decision support system (DSS). The method used is the Simple Additive Weighting (SAW) method. The criteria used in selecting suppliers are speed of delivery, discount level, service, quality of goods and payment tempo. The final result obtained from the calculation process is a ranking table which shows the assessment of each supplier using the weight criteria determined by the company and recommends the supplier with the highest score as the best supplier. By implementing a decision support system using the Simple Additive Weighting (SAW) method, it can help companies determine and select suppliers who are able to provide good products. Keywords : Simple Additive Weighting Method; selection of supplier
Decision Support System To Determine The Best Cafe Recommendations In Purwakarta Using MOORA Method Dede Irmayanti; Ismi Kaniawulan; Mawar Wiliyanti
RISTEC : Research in Information Systems and Technology Vol. 5 No. 2 (2024): RISTEC: Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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Abstract

The growing cafe industry in Purwakarta presents challenges for customers in choosing the right cafe due to various factors such as distance, food prices, and service quality. This research aims to develop a Decision Support System using the MOORA method to efficiently recommend the best cafes based on predefined criteria. The research involved collecting data about cafes, analyzing the problem, and applying the MOORA method to rank cafes according to relevant criteria, such as distance, price, facilities, and service quality. The findings show that the MOORA method is effective in ranking cafés in Purwakarta, with cafés that get the highest score fulfilling the criteria of distance, price, facilities, and service quality, thus being recommended as the best choice for the community. This study concluded that the best café recommendation in Purwakarta is café salbeans park with the highest score of 0.093. In other words, café salbeans park is the best alternative. and it is recommended that this system be widely implemented and updated regularly to include the latest information about cafes, improving user experience in decision making.