Klasifikasi Data Pariwisata Berkelanjutan Menggunakan Decision Tree dengan Equal Width dan Logaritma Binning : Decision Tree Classification Using Equal Width and Logarithmic Binning for Sustainable Tourism Data

Fahri Alviansyah; Mukti Adi Azhari; Attar Raihan Nazhif; Suharto Suharto; Denny Saryanto; Kusrini Kusrini

doi:10.57152/malcom.v6i1.2520

Authors

Fahri Alviansyah Universitas Amikom Yogyakarta
Mukti Adi Azhari Universitas Amikom Yogyakarta
Attar Raihan Nazhif Universitas Amikom Yogyakarta
Suharto Suharto Universitas Amikom Yogyakarta
Denny Saryanto Universitas Amikom Yogyakarta
Kusrini Kusrini Universitas Amikom Yogyakarta

DOI:

https://doi.org/10.57152/malcom.v6i1.2520

Keywords:

Decision Tree, Equal Width Binning, Logarithmic Binning, Pra-Proses Data

Abstract

Pengelolaan data rekomendasi pariwisata memerlukan pemodelan prediktif yang akurat untuk mengklasifikasikan target rekomendasi berdasarkan perilaku wisatawan. Namun, variabel numerik seperti Rekomendasi Score seringkali memiliki distribusi data yang tidak merata (skewed), yang dapat memengaruhi performa algoritma pembelajaran mesin seperti Decision Tree. Penelitian ini bertujuan untuk membandingkan efektivitas dua teknik preprocessing dengan diskritisasi, yaitu Equal Width Binning (EWB) dan Logarithmic Binning (LB), dalam meningkatkan kinerja model klasifikasi. Metodologi penelitian ini mencakup beberapa tahapan preprocessing data, antara lain handling missing value, serta ekstraksi fitur temporal dari data tanggal perjalanan. Data kemudian diproses menggunakan dua skenario binning yang berbeda sebelum dilatih menggunakan algoritma Decision Tree. Hasil penelitian dievaluasi menggunakan metrik Akurasi, Presisi, Recall, dan F1-Score. Hasil perbandingan menunjukkan bahwa Equal Width Binning nilai akurasi sebesar 82 %, dan Logarithmic Binning memberikan nilai akurasi sebesar 90%. Diskritisasi melalui logaritma bining mampu mengurangi kedalaman pohon (tree depth) dan mencegah overfitting, sehingga menghasilkan model yang lebih tangguh dalam memprediksi target rekomendasi pariwisata.

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