Hyperparameter Tuning pada Model Stance Detection Menggunakan GridSearchCV

Authors

  • Arif Hamied Nababan Universitas Prima Indonesia
  • Mia Yovanca Hutagalung Universitas Prima Indonesia

Keywords:

Data Science, Stance Detection, Job Creation Bill, Hyperparameter tuning, gridsearch

Abstract

Tujuan dari penelitian ini adalah membangun model stance detection terhadap Undang-Undang Cipta Kerja yang memiliki performa lebih baik daripada model sebelumnya. Performa model stance detection ini penting untuk ditingkatkan agar dapat dilakukan penyerapan aspirasi masyarakat yang lebih baik terhadap Undang-Undang Cipta Kerja yang  terus menjadi kontroversi besar di Indonesia mulai dari tahun 2019 sampai di tahun 2023 ini. Dalam penelitian ini digunakan metode Hyperparamater Tuning yang diimplementasikan menggunakan kerangka kerja CRISP-DM. Hasil yang diperoleh adalah sebuah model stance detection menggunakan algoritma Support Vector Machine  yang memiliki nilai micro f1-score sebesar 78,4%. Hyperparameter model tersebut adalah  C bernilai 10, parameter max_features dari proses ekstraksi fitur menggunakan metode TF-IDF sebesar 10000, dan menggunakan fitur unigram. Disimpulkan bahwa model tersebut memiliki performa lebih baik dengan nilai micro f1-score yang lebih besar 6,6% daripada model stance detection pada penelitian sebelumnya.

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Published

2023-08-23

How to Cite

Nababan, A. H., & Hutagalung, M. Y. (2023). Hyperparameter Tuning pada Model Stance Detection Menggunakan GridSearchCV. Jurnal Sains Dan Teknologi, 5(1), 205-209. Retrieved from https://ejournal.sisfokomtek.org/index.php/saintek/article/view/1505

Issue

Vol. 5 No. 1 (2023): Jurnal Sains dan Teknologi

Section

Article

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Copyright (c) 2023 Arif Hamied Nababan, Mia Yovanca Hutagalung

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