Implementasi Data Mining Menentukan Game Android Paling Diminati Dengan Algoritma Apriori - Yulianti Yulianti; Dwi Yuni Utami; Noer Hikmah (Paradigma, 2019)
Abstract - Game play at this time is greatly increased among children, teenagers and Parents . various types of games continue to emerge and steal the hearts of enthusiasts. he role of the game quite effective to eliminate saturation, fatigue, sadness, or just want to fill the free time, From starting paid games to free games. To meet The  desire of gamers needs to be made an information So that fans can find out. A priori algorithm includes the type of association rules in Mining data. One stage of association analysis, which attracts many researchers to produce an efficient algorithm is the analysis of high frequency patterns (frequent pattern mining). Important or not a buffer association that is known by two benchmarks, namely: support and confidence. Support (support value) presents a combination of items in the database, while confidence (recognition capacity) is a strong correlation between items and a priori algorithm association rules can help determine specialization in a class or group. It can be concluded that the algorithm can facilitate the researcher apriosi to produce output that is measured accurately with the value of the value that has been set. The game support support value is 50%, and the results of the study can produce 80% confidence value for game Shadowrun (Dragonfall) dah Knight of pen & paper 2 , while for game women the support value is 50% and the results of the research can be 66,7% for game Candy Crush Saga and other games in demand. From these data it is stated that more men like game-and-woman games. Keywords: specialization, game type, priori algorithmi