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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JUSTIN (Jurnal Sistem dan Teknologi Informasi)
Alfianita, Rizha
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Evaluasi Teknik Preprocessing terhadap Kinerja Multinomial Naïve Bayes dalam Klasifikasi Pertanyaan Insincere Holle, Khadijah Fahmi Hayati; Alfianita, Rizha; Putri, Hikmatul Maulidia
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 12, No 4 (2024)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v12i4.82758

Abstract

Platform komunitas tanya-jawab atau Community Question Answering (CQA) telah menjadi sumber informasi yang penting namun menghadapi tantangan, salah satunya adalah adanya pertanyaan insincere. Pertanyaan insincere ini mengacu pada pertanyaan yang tidak tulus dan sering didasarkan pada asumsi keliru, yang dapat mengganggu kenyamanan pengguna dan menyebabkan penyebaran informasi yang menyesatkan. Oleh karena itu, diperlukan deteksi pertanyaan insincere. Penelitian ini bertujuan untuk mengevaluasi pengaruh teknik preprocessing teks terhadap kinerja algoritma Multinomial Naïve Bayes (MNB) dalam mengklasifikasikan pertanyaan insincere. Data yang digunakan terdiri dari 4000 pertanyaan dari Quora, dengan masing-masing 2000 pertanyaan berlabel insincere dan 2000 berlabel sincere. Pembobotan kata dilakukan menggunakan TF-IDF. Terdapat 4 skenario pengujian yang berfokus pada variasi tahap preprocessing untuk mengetahui pengaruh preprocessing terhadap akurasi sistem. Skenario tersebut adalah MNB dengan stemming, MNB dengan lemmatization, MNB tanpa stemming, dan MNB dengan stemming tanpa stopword removal. Pengujian dilakukan menggunakan teknik k-Fold Cross Validation. Hasil uji coba menunjukkan bahwa skenario MNB dengan stemming tanpa stopword removal memberikan hasil terbaik dengan akurasi 83%, presisi 78%, recall 94%, dan F1-score 85%. Sehingga dapat disimpulkan bahwa pemilihan teknik pemrosesan teks yang tepat sangat penting untuk meningkatkan kinerja teks, khususnya dalam mendeteksi pertanyaan insincere pada platform CQA.
Aspect-based Multilabel Classification of E-commerce Reviews using Fine-tuned IndoBERT Ihtada, Fahrendra Khoirul; Alfianita, Rizha; Aziz, Okta Qomaruddin
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 1, February 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i1.2088

Abstract

In recent years, e-commerce has experienced rapid growth. A significant change in consumer behavior is marked by the ease of access and time flexibility offered by e-commerce platforms, as well as the existence of the review feature to assess products and services. However, with the ever-increasing number of reviews, consumers and store owners face challenges in sorting out relevant information. This research focuses on the multilabel classification of Indonesian e-commerce reviews. This research was undertaken because the application of multilabel classification, especially for e-commerce reviews in Indonesia, has received little attention. This research compares three classification models: end-to-end IndoBERT, IndoBERT-CNN, and IndoBERT-LSTM, to determine the most effective model for multilabel aspect classification of customer reviews. The multilabel classification method was applied to determine the aspect categories of the reviews, such as product, customer service, and delivery, using different thresholds for evaluation. Results show that 0.6 threshold is optimal, with the IndoBERT-LSTM model as the best-performing model for the multilabel aspect classification of these e-commerce reviews. Optimal classification of the model enables more precise information extraction from customer reviews. This can be useful for e-commerce businesses to gain insight from the reviews they get from customers. This insight can be used to find out which aspects need to be improved from the e-commerce business which leads to increased customer satisfaction and trust.
Co-Authors Ihtada, Fahrendra Khoirul Khadijah Fahmi Hayati Holle Okta Qomaruddin Aziz Putri, Hikmatul Maulidia