Open AccessImplementation of ID3 algorithm classification using web-based weka
Author(s) -
Arif Senja Fitrani,
Mochamad Alfan Rosid,
Yulian Findawati,
Yuli Rahmawati,
Adnan Anam
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1381/1/012036
Subject(s) - id3 , computer science , decision tree , data mining , division (mathematics) , process (computing) , id3 algorithm , class (philosophy) , decision tree learning , machine learning , artificial intelligence , incremental decision tree , mathematics , arithmetic , operating system
The Bangil District Court is an IB class court that handles a large number of case cases. Every year more and more case cases are included in the Bangil District Court, but not all case cases are in a mutation status. By using classification techniques that can process large amounts of data to find patterns that occur in case data. Data processing is used to predict case minutation with the decision tree method using ID3 algorithm. Case data has 8 attributes and has been classified into 6 parts, namely division based on Case Type, Register, Case Classification, Length of Process, Public Prosecutor and Decision with a goal of Mutation Status. Weka 3.6 is an API that is used to build rules / rule bases. The rule that was formed was then implemented in the making of a case status prediction application in the web-based Bangil District Court.