Konsistensi Ranking pada Sistem Rekomendasi Resep Masakan dengan Simple Additive Weighting - Ratih Kartika Dewi; Komang Candra Brata; Nabila Nabila (Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada, 2019)
Along with the development of internet technology, recipes can easily be obtained from various sources, such as websites, mobile applications, and social media. The variety of recipes that available in various media still have one disadvantage: it can not accommodate user preferences. In this kind of problem, the role of a Decision Support System (DSS) is needed by people who actively cook using recipes in daily cooking activities. DSS recommendations for recipes can be built by using Simple Additive Weighting (SAW) algorithm. The variables chosen as criteria for recipe recommendations are duration of cooking, level of complexity, and calories. The ranking consistency test aims to see if there is a ranking reversal (the first ranking is swapped with the latest ranking) when there is a change in the number of recipes (alternatives). The purpose of this research is to find out the reliability of the SAW algorithm in the issue of recipe recommendations. The ranking consistency test result shows consistency of 100% and there is no rank reversal (last recommendation becomes first recommendation) for this case.