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Journal : Internet of Things and Artificial Intelligence Journal

Analysis of Tourism Businesses Number in the Entertainment and Recreation Sector using Predictive Apriori Algorithm Manurung, Romarta Yemima; Sari, Dewi Purwita; Agustinah, Nabila; Syanahieskara, Razel; Tahyudin , Imam; Nurfaizah, Nurfaizah; Alvi Sholikhatin, Siti
Internet of Things and Artificial Intelligence Journal Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (801.3 KB) | DOI: 10.31763/iota.v2i4.550

Abstract

Data Analysis of the Number of Tourism Businesses in the Entertainment and Recreation Sector is used as data sources for extracting information. In this study, data on the number of tourism businesses in the entertainment and recreation sector will be mined to support decision-making information. This research purpose is to analyze the tourism business number in the entertainment and recreation sectors. The method is using predictive Apriori algorithm. The data has been tested using Knime software to process data on the number of tourism businesses in the entertainment and recreation sector at the domestic level by using business data whose numbers are increasing or decreasing. Starting from entering nodes 1, 2 and 3 to getting node 4, which is the final result. The results obtained show the data set that produces the final result for every 1 tourism business data. The result obtained that the tourism number in entertainment and recreation sectors are increasing. Furthermore, the prediction result of entertainment and recreation which have best accuracy are balls, discotheques, massage parlors, karaoke, live music, massage parlors, sports and physical fitness centers, family recreation facilities and spa