Topic Modeling in the News Document on Sustainable Development Goals

https://doi.org/10.22146/ijitee.67467

Hidayatul Fitri(1*), Widyawan Widyawan(2), Indah Soesanti(3)

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Indonesia is a developing country and supports the program of the Sustainable Development Goals (SDGs) which consist of 17 goals. SDGs is not only the government’s duty, but a shared duty from any elements. Online media has a crucial role in implementing goals of Indonesia’s SDG. Information published in online news related to the SDGs is an important consideration for the government, society, and all elements. Categorizing news manually to find out news topics is very time-consuming and done by the ability of news editors. News presented by online media on the news site can be used as topic modeling, where hidden topics can be found in the news on online media. Topic modeling will classify data based on a particular topic and determine the relationship between text. Latent Dirichlet allocation (LDA) is one of the methods on topic modeling to find out the trend of topics of SDGs news. Based on the result of this research, the implementation of LDA is the right choice for finding topics in a document. The result of topic modeling with k = 17 obtained the highest coherence score of 0.5405 on topic 8. Topic 8 discussed news related to the eighth SDGs goals, namely decent work and economic growth. This categorization was based on words formed after the LDA process. Then, topic 5 discussed the news on the 17th SDGs goals, namely partnerships for the goals. Topic 6 discussed the news of the first SDGs, namely no poverty.


Keywords


Topic Modeling;LDA;SDGs;News;Media Online

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DOI: https://doi.org/10.22146/ijitee.67467

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