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.
Highlights
News coverage in the mass media is the result of a professional and organized work process based on certain parameters and ethics
The results of modeling Latent Dirichlet Allocation (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%)
With the background described above, the following research will discuss the topic of online news headline modeling at https://news.detik.com for the first 8 months since the COVID-19 case was discovered in Indonesia
Summary
News coverage in the mass media is the result of a professional and organized work process based on certain parameters and ethics. With the background described above, the following research will discuss the topic of online news headline modeling at https://news.detik.com for the first 8 months since the COVID-19 case was discovered in Indonesia. Preliminary research related to text mining analytic media and modeling topics with Latent Dirichlet Allocation (LDA), including research on the classification of messages that enter through social media at the Surabaya social service. Research conducted by Aulia Rizki Destarani in 2019 on the topic of modeling complaints from Denpasar residents on an online public complaint site to find out the problems that occur in the community shows that data processing from this study resulted in 4 trending topics, with the biggest problems being damaged roads and requests for road repairs (Destarani et al, 2019). The research stages to be carried out in this study are as shown in Figure 1 below: Data Retrieval www.detik.com
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