Topic Classification of Islamic Consultation Question and Answer Using Supervised Learning
FARHAN ARRAHMAN
Informasi Umum
Kode
21.04.3279
Klasifikasi
658.302 - Supervision
Jenis
Karya Ilmiah - Skripsi (S1) - Reference
Subjek
Classification
Dilihat
302 kali
Informasi Lainnya
Abstraksi
Islamic question-and-answer (Q&A) websites are available as platforms for sharing and learning about Islam. Different Islamic Q&A websites usually shares similar Q&A topics that have been frequently asked by Islamic learners. However, due to a large number of Q&A entries in such websites, manual topic classification would be costly and time consuming. The objectives of this research are to develop a classification system for Islamic Q&A topics and analyze the vocabulary words that affect the classification results. To achieve these objectives, well-known supervised learning methods that have been previously implemented to classify Islamic texts are utilized, namely K-Nearest Neighbor (K-NN), Support Vector Machine (SVM), Multinomial Naive Bayes (MNB), and Multinomial Logistic Regression (MLR). In this research, these classifiers are evaluated in classifying Islamic Q&A entries. The evaluation finds that the SVM achieves the best accuracy and Hamming loss at 79.8 percent and 0.202, respectively. This research also finds that the relevant or specific vocabulary from a class can improve the classification system’s ability to predict correctly and vice versa.
Koleksi & Sirkulasi
Seluruh (1) koleksi tidak tersedia
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Pengarang
| Nama | FARHAN ARRAHMAN |
| Jenis | Perorangan |
| Penyunting | Kemas Muslim Lhaksmana, Danang Triantoro Murdiansyah |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S1 Informatika |
| Kota | Bandung |
| Tahun | 2021 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
