RULE MINING UNTUK KLASIFIKASI DATA MENGGUNAKAN SEARCH TREE
DOI:
https://doi.org/10.29407/inotek.v1i1.445Abstract
Penelitian ini adalah kajian teori dalam penerapan search tree untuk proses rule mining. Klasifikasi merupakan proses untuk menyatakan suatu objek ke salah satu kategori yang sudah didefinisikan sebelumnya. Search tree bekerja dengan pendekatan berbasis ruang solusi (State Space). Dalam kajian ini, search tree digunakan untuk menterjemahkan bobot hasil training dalam Jaringan Syaraf Tiruan (JST) menjadi set aturan konjungsi (IF-THEN). Proses ini disebut dengan rule mining. Dalam pembahasan akan dijelaskan proses training pada dataset yang cukup populer yaitu permasalahan “Playing Tennis”. Proses pelatihan (training) dilakukan dengan JST Metode Backpropagation. Dataset “playing tennis" memiliki 4 input atribut dan satu output atribut (atribut kelas). Untuk kepentingan rule mining, nantinya dataset akan dimodelkan menjadi 10 input atribut dan 2 output atribut. Formulasi permasalahan ke dalam jaringan syaraf dengan menggunakan 10 input neuron yang masing-masing mewakili value atribut non kelas dan dua output neuron yang mewakili value atribut kelas.
Keywords:
Klasifikasi, jaringan syaraf tiruan, backpropagation, search tree, ekstraksi rule##plugins.themes.default.displayStats.downloads##
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