The people of Indonesia have a wide range of traditions and customs, as well as religious activities. The public's interest in Indonesian religious activities has grown as a result of the diversity of religious activities carried out by Indonesians. Multimedia has an essential role in allowing individuals to obtain information fast, especially as technology advances. As a result, in order to obtain information centrally, the public must search for appropriate information, which takes time. In circumstances like these, the issue is creating and developing an android-based multimedia system application that may assist the public in learning about the Indonesian people's religious activities. This study intends to assist Indonesians in obtaining information on their religious activities, so that they may quickly obtain information and learn about and comprehend their religious activities. The Luther–Sutopo version of the Multimedia Development Life Cycle (MDLC) was utilised, including stages for idea, design, material gathering, assembly, testing, and dissemination. This study led to the development of an Android-based multimedia system for religious activities among Indonesians.
This research method uses CRISP-DM with emerging pattern supervision modeling and EPM Algorithm. The contribution of the research is to assist the Government in overcoming the problem of the spread of the COVID-19 cluster in several regions in Indonesia. The research aims to implement information on the COVID-19 data mining pattern in the DKI Jakarta area. The problems faced are the difficulty of identifying the pattern of COVID-19 data in one area, it is difficult to dig up data on the http://corona.jakarta.go.id website. It is not easy to decide on the handling of COVID-19. The output of the research results in a cluster of information on COVID-19 in the DKI Jakarta area based on Significance level depends on the Covid Map In terms of Region, Status, Gender, & age And Signification can be the basis for determining covid OTG, DTG, and Positive. The theoretical and practical implications can be stated as follows: The use of supervised emerging pattern methods can affect the processing of COVID-19 data. For 5 Regions in DKI Jakarta and distribution to determine covid OTG, DTG, and Positive. The result of the development of this data mining system is to produce pattern reports to produce Supervised Emerging Patterns technology for decision making at the COVID-19 Task Force in DKI Jakarta.
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