COMPARISON OF LEXRANK ALGORITHM AND MAXIMUM MARGINAL RELEVANCE IN SUMMARY OF INDONESIAN NEWS TEXT IN ONLINE NEWS PORTALS

  • Siti Tuhpatussania (1*) Universitas AMIKOM Yogyakarta
  • Ema Utami (2) Universitas AMIKOM Yogyakarta
  • Anggit Dwi Hartanto (3) Universitas AMIKOM Yogyakarta

  • (*) Corresponding Author
Keywords: autotext summarization, lexrank, Maximum Marginal Relevance, TF-IDF

Abstract

The presence of online media has shifted print media for news readers to get information that is fast, accurate, and easy to access. However, the problem arises because the length of the news text makes the reader bored to search for the news as a whole so the news that is obtained will be less accurate. For this reason, it is necessary to have an automatic text summary that was raised in this study as well as to compare the Maximum Marginal Relevance (MMR) algorithm and the LexRank algorithm to the summary of Indonesian news texts on the online news portal graphanews. com. the results of the comparison test of text summarization using f-measure , precision and recall show the performance of text summarization with the MMR algorithm is better where f-measure is 91.65%, precision is 91.08% and recall is 92.23%.

Downloads

Download data is not yet available.

References

Andriani, D., & Tanzil Furqon, M. (2019). Peringkasan Teks Otomatis Pada Artikel Berita Hiburan Berbahasa Indonesia Menggunakan Metode BM25. JPTIK (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer).

Arisandi, D., & Sutrisno, T. (2022). Aplikasi peringkasan dokumen menggunakan metode maximum marginal relevance (mmr). Jurnal Ilmu Komputer dan Sistem Informasi.

Ayu Syahfitri, R., Kurniawan, A., & Irsan Humaidy, M. (2022). Penerapan Algoritma Maximum Marginal Relevance Dalam Peringkasan Teks Secara Otomatis. Bulletin of Data Science.

Dimas, F., Al-Hafiidh, F., Rozi, I., & Kusumaning, P. (2022). Peringkasan teks otomatis pada portal berita olahraga menggunakan metode maximum marginal relevance. JIP (Jurnal Informatika Polinema).

Elbarougy, R., Behery, G., & el Khatib, A. (2020). Extractive Arabic Text Summarization Using Modified PageRank Algorithm. Egyptian Informatics Journal.

Fauzi, A. (2022). Penerapan Algoritma Text Mining dan Lexrank dalam Meringkas Teks Secara Otomatis. Bulletin of Data Science.

Hermawan, L., Ismiati, M. B., Bangau, J., 60, N., & Charitas, M. (2020). Pembelajaran Text Preprocessing berbasis Simulator Untuk Mata Kuliah Information Retrieval. TRANSFORMATIKA.

Lin, N., Li, J., & Jiang, S. (2022). A simple but effective method for Indonesian automatic text summarisation. Connection Science.

Rifano, E. J., Fauzan, Abd. C., Makhi, A., Nadya, E., Nasikin, Z., & Putra, F. N. (2020). Text Summarization Menggunakan Library Natural Language Toolkit (NLTK) Berbasis Pemrograman Python. ILKOMNIKA: Journal of Computer Science and Applied Informatics.

Riyani, A., Zidny Naf’an #2, M., & Burhanuddin, A. (2019). Penerapan Cosine Similarity dan Pembobotan TF-IDF untuk Mendeteksi Kemiripan Dokumen. Jurnal Linguistik Komputasional.

Rofiqi, M. A., Fauzan, Abd. C., Agustin, A. P., & Saputra, A. A. (2019). Implementasi Term-Frequency Inverse Document Frequency (TF-IDF) Untuk Mencari Relevansi Dokumen Berdasarkan Query. ILKOMNIKA: Journal of Computer Science and Applied Informatics.

Sari Yunita, & Fatonah Nenden. (2021). Peringkasan Teks Otomatis pada Modul Pembelajaran Berbahasa Indonesia Menggunakan Metode Cross Latent Semantic Analysis (CLSA). JEPIN (Jurnal Edukasi Dan Penelitian Informatika).

Shiddiqi, A. M., Ijtihadie, R. M., Ahmad, T., Wibisono, W., Anggoro, R., Bagus, D., & Santoso, J. (2020). Penggunaan Internet dan Teknologi IoT untuk Meningkatkan Kualitas Pendidikan. Jurnal Direktorat Riset dan Pengabdian Kepada Masyarakat-DRPM ITS.

Tuhpatussania, S. (2022). Perbandingan Algoritma LexRank dan Maximum Marginal Relevance pada peringkasan teks berbahas Indonesia pada portal berita online.

Yulita, W., Priyanta, S., & SN, A. (2019). Automatic Text Summarization Based on Semantic Networks and Corpus Statistics. IJCCS (Indonesian Journal of Computing and Cybernetics Systems).

Published
2022-09-13
How to Cite
Tuhpatussania, S., Utami, E., & Hartanto, A. (2022). COMPARISON OF LEXRANK ALGORITHM AND MAXIMUM MARGINAL RELEVANCE IN SUMMARY OF INDONESIAN NEWS TEXT IN ONLINE NEWS PORTALS. Jurnal Pilar Nusa Mandiri, 18(2), 187-192. https://doi.org/10.33480/pilar.v18i2.3190
Article Metrics

Abstract viewed = 17 times
PDF downloaded = 19 times