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A Review: Information Technology-based Climate Data Dissemination Syalom Alfa Bazeleel Neonane; Adi Bagus Putrantio
Journal of Computation Physics and Earth Science (JoCPES) Vol 1 No 2 (2021): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/2mnwd629

Abstract

Changes in climate indicators can cause extreme weather and can trigger disasters, such as floods and droughts and even crop failure. it is difficult to predict because farmers and local governments do not understand the importance of climate information, the solution to the problem is to disseminate and disseminate information, but requires an information system that is also inseparable from software, IoT-based applications, and others. With the method used, namely by classifying the climate based on rainfall. In classifying the climate, the oldeman and schmidt-ferguson classifications are used. Then the dataset is formed to calculate the degree or probability of the rainfall category and the Data Normality test. The test results show that the classification of rainfall categories with light, normal, and heavy categories is 79.5%, 40.9%, and 86.4% respectively. While the precision is 96.4%, 42.6%, and 83.3% respectively. Therefore, in making applications as a medium for disseminating information, it is necessary to understand the process of seasonal occurrence, and how to turn these data into information that can be utilized by the wider community.