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All Journal Jurnal Informatika Universitas Pamulang
Ari Setiawan
Universitas Buana Perjuangan Karawang
Computer Science & IT

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Journal : Jurnal Informatika Universitas Pamulang

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Implementasi Teks Mining Pada Website Kemenkes Dengan Metode LDA Menggunakan Algoritma K-Means Ari Setiawan; Deden Wahiddin; Cici Emilia Sukmawati
Jurnal Informatika Universitas Pamulang Vol 9 No 2 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v9i2.38971

Abstract

This research aims to improving the accessibility and management of health information on the Ministry of Health (Kemenkes) website. Before this research was conducted, content on the Ministry of Health's website was scattered without a clear structure, making it difficult for users to find the health information they needed quickly and efficiently. This results in a decrease in the quality of the user experience and a potential decrease in trust in official health information sources. With the aim of making it easier for users to find relevant information, this research uses the K-Means algorithm to group website content based on themes. Through the text mining method, five main clusters were identified, covering topics such as emergency health, certain diseases, and innovations in handling COVID-19. The results show an increase in navigation efficiency with clustering accuracy reaching 72%. The conclusion of this research is that this grouping succeeded in improving the structure and quality of information on the Ministry of Health's website, supporting data-based decision making, and improving public health services.
Co-Authors Deden Wahiddin Sukmawati, Cici Emilia