Decision Tree Methodology (C4.5) for Predicting Students' Reading Interest in the Library SMK Negeri 1 Kota Cirebon
DOI:
https://doi.org/10.58421/misro.v4i1.359Keywords:
C4.5 Algorithm, Data Mining, Decision Tree, Library, Reading InterestAbstract
Reading is one aspect of language skills that is actively receptive. The media used in reading is written language media. Reading is seeing and understanding the content of what is written, either spelling or pronouncing what is written. Reading activities are often socialised in education because reading is a very important activity to support teaching and learning activities at school. The facility provided by the school as a support in socialising reading activities for students is the library. Many students often utilise the SMK Negeri 1 Kota Cirebon library to carry out the borrowing process and read books there. Reading activities are an obligation that students must carry out, but students who carry out reading activities cannot be categorised as students with an interest in reading. The problem faced by the SMK Negeri 1 Cirebon City library is that it has not been able to predict or know the reading interests of students in the school library. This study uses data mining techniques with the C4.5 algorithm to predict student reading interest. This research produces rules to help SMK N 1 Cirebon City predict student reading interest in the school library. This step is done by designing a system model that uses the C4.5 algorithm to form a decision tree to produce a rule for predicting student reading interest. This research will produce valuable information about predicting student reading interest in the SMK Negeri 1 Cirebon City library using the C4.5 algorithm method.
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