IMPLEMENTATION OF THE EDAS (DISTANCE FROM AVERAGE SOLUTION) ALGORITHM FOR CLASSIFICATION OF MID-RANGE SMARTPHONE RECOMMENDATIONS

Abstract

This research aims to help people choose the best smartphones at affordable prices in the range of 2-5 million using the EDAS (DISTANCE FROM AVERAGE SOLUTION) method. Visual language modeling such as UML is used to input smartphone lists and judgments from experts or smartphone brand sales regarding features such as brand, type, 3G, 4G, 5G, battery, RAM, ROM, camera size, and others. The EDAS calculation process was carried out with 34 smartphone data samples from various brands such as VIVO, OPPO, Realme, Xiaomi, Samsung and Infinix which were taken from the GSM Arena API as the main source of data. To achieve this goal, visual language modeling is first carried out using UML (Unified Modeling Language) such as Class Diagrams, Use Case diagrams, and Activity diagrams. The concept of this application is to input a list of smartphones that interest the user and assess the specifications of the smartphone using the assessment of experts or parties experienced in selling and evaluating smartphones, such as assessments from sales of a smartphone brand. Weighting is also carried out by evaluating each specification such as brand, type, 3G, 4G, 5G, battery, RAM, ROM, camera megapixel size, telephoto, depth sensor, macro camera, monochrome camera, screen, screen type, processor, and processor type. Weighting is done on a scale from 0 to 10. Weighting from 0-10 is done to assess each specification. The results of the EDAS implementation are the 5 most recommended smartphones and the 5 least recommended smartphones. namely for the 5 most recommended smartphones Redmi 8 with a score of 1.2431, Infinix S5 Lite with a score of 1.2143, Infinix S5 with a score of 1.2143, Tecno i7 with a score of 1.1344 and Oppo F3 Plus with a score of 1.0397. also the least recommended smartphones are Infinix Zero 5 with a score of -2.0970, Redmi Note 7 Pro with a score of 0.2334, Vivo Z1 Pro with a score of 0.2628, LG W30 Pro with a score of 0.2922, Xiaomi Mi A3 with a score of 0.3120.