Klasifikasi Multi-Label Hadis Terjemahan Shahih Bukhari Berdasarkan Kategori Anjuran, Larangan, dan Informasi Menggunakan Metode Extreme Gradient Boosting (XGBoost)

Abstrak

Hadith is one of the sources of Islamic teachings that contains meanings such as recommendations, prohibitions, andinformation. The large number of hadiths makes manual classifications time consuming, therefore an automatic classification methodis needed. This study aims to perform multi-label classifications on translated Shahih Bukhari hadiths using the XGBoost method withthe Binary Relevence approach and hyperparameter tuning using GridSearchCV. the result showed that the implementation ofhyperparameter tuning improved model performance, especially in recall and F1-score values. In addition, the hamming loss valuedecraesed from 9.19% to 9.10%, indicating that hyperparameter tuning was able to reduce prediction errors in the model.

Identifier

• OpenAlex: https://openalex.org/W7166725283
• DOI: https://doi.org/10.47065/bulletinds.v5i3.10142