Rama Jayapermana's scientific contributions

What is this page?
This page lists the scientific contributions of an author, who either does not have a ResearchGate profile, or has not yet added these contributions to their profile.

It was automatically created by ResearchGate to create a record of this author's body of work. We create such pages to advance our goal of creating and maintaining the most comprehensive scientific repository possible. In doing so, we process publicly available (personal) data relating to the author as a member of the scientific community.

If you're a ResearchGate member, you can follow this page to keep up with this author's work.

If you are this author, and you don't want us to display this page anymore, please let us know.

Publication (1)

Figure 1. Purposed system
Figure 2. Preprocessing steps
Confusion matrix for multi-class classification [21]
Result of the confusion matrix on the proposed model
Model performance comparison
Implementation of Stacking Ensemble Classifier for Multi-class Classification of COVID-19 Vaccines Topics on Twitter
Article
Full-text available
  • May 2022
Purpose: However, from the variety of uses of these algorithms, in general, accuracy problems are still a concern today, even accuracy problems related to multi-class classification still require further research.Methods: This study proposes a stacking ensemble classifier method to produce better accuracy by combining Logistic Regression, Random Fo...
Cite
Download full-text

Citations

... Another method are Support Vector Machine (SVM) [14][15] [16], and Backpropagation Neural Network [17]. Naive Bayes has the advantage of being simple but has high accuracy even though it uses not a lot of data, while SVM has the advantage of solving linear and non-linear classification and regression problems which can become a learning algorithm capability for regression and classification, but the Support Vector Machine (SVM) are not efficient in training large-capacity data [18]. Backpropagation has advantages over other Neural Networks, namely Backpropagation using supervised training [19]. ...
Reference: Optimization of breast cancer classification using feature selection on neural network
View full-text