Abstract
Indonesian Credit Rating Agency (CRA) is currently on its way to becoming
the early mover of digital transformation. CRA controls macroeconomics and has a
significant impact on many industries across the world. However, there are always
those that can exploit it through asymmetric information and human interaction. A
solution to reduce human interaction and enhancement is to build Natural Language
Processing (NLP) sentiment analysis models and then display the results using an
interactive dashboard story. Objectives are created for the aim of the project to be able
to conduct a feasibility study, develop a model based on a press release dataset,
conduct model evaluation, and display the results on an interactive dashboard. The
research aims to utilise press release documents with NLP sentiment analysis to
produce prescriptive analysis with interactive visualisation as the final output. Press
release files are processed by using several Machine Learning (ML) algorithms such as
Support Vector Machine (SVM), Multinomial Naive Bayes (MultinomialNB), Logistic
Regression (LR), and Multi-Layer Perceptron Artificial Neural Network (MLP-Ann).
This research will be carried out under Dynamic Systems Development (DSDM) and
Knowledge Discovery Database (KDD). This will allow the researchers to achieve all
objectives, permit models to perform very well, and let the output get displayed on a
dashboard as a storyboard.