Indonesian Sentiment Analysis towards MyPertamina Application Reviews by Utilizing Machine Learning Algorithms

Machine Learning-based Sentiment Analysis of Automatic Indonesian Translations of English Movie Reviews

Sentiment analysis is the automatic classification of the overall opinion conveyed by a text towards its subject matter. This paper discusses an experiment in the sentiment analysis of of a collection of movie reviews that have been automatically translated to Indonesian. Following [1], we employ three well known classification techniques: naive bayes, maximum entropy, and support vector machin...

Comparative Analysis of Machine Learning Algorithms with Optimization Purposes

The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches‎. ‎Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data‎. ‎In this paper‎, ‎a methodology has been employed to opt...

Body Mass Index Classification based on Facial Features using Machine Learning Algorithms for utilizing in Telemedicine

Background and Objectives: Due to the impact of controlling BMI on life, BMI classification based on facial features can be used for developing Telemedicine systems and eliminating the limitations of measuring tools, especially for paralyzed people. So that physicians can help people online during the Covid-19 pandemic. Method: In this study, new features and some previous work features were e...

Towards Intelligent Machine Learning Algorithms

Resources for Indonesian Sentiment Analysis

In this work, we present subjectivity lexicons of positive and negative expressions for Indonesian language created by automatically translating English lexicons. Other variations are created by intersecting or unioning them. We compare the lexicons in the task of predicting sentence polarity on a set of 446manually annotated sentences andwe also contrast the generic lexicons with a small lexic...