Pembuatan Kata Kunci Otomatis Dalam Artikel Dengan Pemodelan Topik

Lucky Adhikrisna Wirasakti (Universitas Amikom Yogyakarta,Yogyakarta)
Rony Permadi (Universitas Amikom Yogyakarta,Yogyakarta)
Anggit Dwi Hartanto (Universitas Amikom Yogyakarta,Yogyakarta)
Hartatik Hartatik (Universitas Amikom Yogyakarta,Yogyakarta)

JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 4, No 1 (2020): Januari 2020

This study aims to determine the appropriate keywords to be used in the publication of articles on the blog, the Latent Dirichlet Allocation (LDA) Model, an opportunity model which will produce a variety of different topics. Beginning with taking data from articles / blogs, then cutting articles per section and doing data preprocessing, and changing vector data into corpus to be modeled with LDA, then grouping with K-means to search for topics with higher assistance. The results of quoting from the LDA Model obtained 4 topics with 8 words with the highest probability value, mesin (0.09375857), maksimal (0.064600445), mazda (0.10009629), varian (0.07572112), cx-8 (0.10170187), mazda (0.101048954), mobil (0.09820121), dan mazda (0.05679208)