Performance of Ensemble Classification for Agricultural and Biological Science Journals with Scopus Index

The ensemble method is considered an advanced in both prediction and classification. application of this estimated to have a more optimal output than the previous classification method. This article aims determine ensemble's performance classify journal quartiles. subject agriculture was chosen because Indonesia agricultural country, interest researchers field shows positive response. data downloaded through Scimago Journal Country Rank with accumulation 2020. Labels four classes: Q1, Q2, Q3, Q4. applied Boosting Bagging Decision Tree (DT) Gaussian Naïve Bayes (GNB) algorithms compiled from 2144 instances. meta-ensembles used are Adaboost XGBoost. From study, has highest accuracy score at 71.36, followed by XGBoost 69.51. third 68.82, 60.42, 58.2, 56.12 results. paper that works optimally result suggests can still fail produce ideal outcome approaches SJR system.