Topic Modeling of Online Media News Titles during COVID-19 Emergency Response in Indonesia Using the Latent Dirichlet Allocation (LDA) Algorithm

Telematika
Universitas Amikom Purwokerto

📄 Abstract

Online media news portals have the advantage of speed in conveying information on any events that occur in society. One way to know what a story is about is from the title. The headline is a headline that introduces the reader's knowledge about the news content to be described. From these headlines, you can search for the main topics or trends that are being discussed. It takes a fast and efficient method to find out what topics are trending in the news. One method that can be used to overcome this problem is topic modeling. Topic modeling is necessary to help users quickly understand recent issues. One of the algorithms in topic modeling is Latent Dirichlet Allocation (LDA). The stages of this research began with data collection, preprocessing, forming n-grams, dictionary representation, weighting, validating the topic model, forming the topic model, and the results of topic modeling. The results of modeling LDA topics in news headlines taken from www.detik.com for 8 months (March-October 2020) during the COVID-19 pandemic showed that the best number of topics produced each month were 3 topics dominated by news topics about corona cases, positive corona, positive COVID, COVID-19 with an accuracy of 0.824 (82.4%). The resulting precision and recall values indicate that the two values are identical, so this is ideal for an information retrieval system.

🔖 Keywords

#Text Mining; Media Analytics; Topic Modeling; LDA; COVID-19 news

ℹ️ Informasi Publikasi

Tanggal Publikasi
26 August 2021
Volume / Nomor / Tahun
Volume 14, Nomor 2, Tahun 2021

📝 HOW TO CITE

R Wahyudi, M Didik; Fatwanto, Agung; UIN Sunan Kalijaga; Kiftiyani, Usfita; UIN Sunan Kalijaga; Wonoseto, M. Galih; UIN Sunan Kalijaga; , "Topic Modeling of Online Media News Titles during COVID-19 Emergency Response in Indonesia Using the Latent Dirichlet Allocation (LDA) Algorithm," Telematika, vol. 14, no. 2, Aug. 2021.

ACM
ACS
APA
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver

🔗 Artikel Terkait dari Jurnal yang Sama

A Systematic Analysis of the Impact of Non-Academic Factors on Student Academic Performance Prediction Using Data Mining

Ningsih, Gabriella Caroline Prihayu; Universitas Sebelas Maret; Liantoni, Febri; Sebelas Maret University; Sujana, Yudianto; Sebelas Maret University;

02 Apr 2026

Architecture and Field Evaluation of an IoT-Integrated Village Information System for Public Service

Hartono, Susilo; Universitas Muhammadiyah Pringsewu; Sutikno, Tole; Ahmad Dahlan University; Yudhana, Anton; Ahmad Dahlan University;

09 Mar 2026

Development of a Lightweight CNN Architecture for Multiclass Brain Tumor Detection Based on RGB Images

Fauzi, Ahmad; Pamulang University; Yunial, Agus heri; Pamulang University;

09 Mar 2026

Portfolio Risk Assessment Using VaR and CVaR: A Comparative Study of Variance–Covariance Method and Monte Carlo Simulation

Supandi, Epha Diana; Oktavia, Atika; Sunan Kalijaga State Islamic University Yogyakarta;

05 Mar 2026

Fairness Auditing and Bias Mitigation in Aspect-Based Sentiment Models for Indonesian Public Services

Jondien, Muhammad Shihab Fathurrahman; Magister of Computer Science, Amikom Purwokerto University, Indonesia; Hariguna, Taqwa; Magister of Computer Science, Amikom Purwokerto University, Indonesia; Saputra, Dhanar Intan Surya; Magister of Computer Science, Amikom Purwokerto University, Indonesia;

05 Mar 2026

Performance Analysis of the Fuzzing Method in Detecting API Vulnerabilities in Mobile Healthcare Application X Based on OWASP API Security Top 10

Hakim, Muhammad Ikhwanul; Nugroho, Radityo Adi; Nugrahadi, Dodon Turianto; Herteno, Rudy; Saputro, Setyo Wahyu;

19 Feb 2026

📊 Statistik Sitasi Jurnal