Open AccessAnalysis of Health Research Topics in Indonesia Using the LDA (Latent Dirichlet Allocation) Topic Modeling Method
Author(s) -
Yoga Sahria,
Dhomas Hatta Fudholi
Publication year - 2020
Publication title -
jurnal resti (rekayasa sistem dan teknologi informasi)
Language(s) - English
Resource type - Journals
ISSN - 2580-0760
DOI - 10.29207/resti.v4i2.1821
Subject(s) - latent dirichlet allocation , topic model , respondent , computer science , python (programming language) , data science , government (linguistics) , public health , management science , information retrieval , medicine , political science , engineering , linguistics , philosophy , law , operating system , nursing
In this time, the need of research, the development and the implementation of the result of research in health is increasing both from the researchers, the government, the academic even of from the public general. One of the ways to find out the health research trend is by topic modeling. The method that used in this research is topic modeling LDA (Latent Dirichlet Allocation) method. The purpose of this research is to identify how modeling topic method LDA analyze modeling topic to some health research in Indonesia by Sinta Journal and to know how the coherence value in each topic of the model that has been made. Besides, hopefully it can be used as a reference to do heath research in Indonesia based the topic that has been modeled. The development of this research uses Anaconda3 Python Programming Language Tools and utilizes the LDA library that provided to get the topic model. To examine the result of this research the respondent are medical worker, health researcher and academics. The result of this research the topic modeling that used 94,1% respondent say very good and 5,9% say good.