{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T04:44:11Z","timestamp":1785818651471,"version":"3.56.0"},"reference-count":0,"publisher":"State University of Malang (UM)","issue":"2","license":[{"start":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T00:00:00Z","timestamp":1672358400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-sa\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Knowledge Engineering and Data Science"],"abstract":"<jats:p>The ensemble method is considered an advanced method in both prediction and classification. The application of this method is estimated to have a more optimal output than the previous classification method. This article aims to determine the ensemble's performance to classify journal quartiles. The subject of agriculture was chosen because Indonesia is an agricultural country, and the interest of researchers in this field shows a positive response. The data is downloaded through the Scimago Journal and Country Rank with the accumulation in 2020. Labels have four classes: Q1, Q2, Q3, and Q4. The ensemble applied is Boosting and Bagging with Decision Tree (DT) and Gaussian Na\u00efve Bayes (GNB) algorithms compiled from 2144 instances. The Boosting meta-ensembles used are Adaboost and XGBoost. From this study, the Bagging Decision Tree has the highest accuracy score at 71.36, followed by XGBoost Decision Tree with 69.51. The third is XGBoost Gaussian Na\u00efve Bayes with 68.82, Adaboost Decision Tree with 60.42, Adaboost Gaussian Na\u00efve Bayes with 58.2, and Bagging Gaussian Na\u00efve Bayes with 56.12 results. This paper shows that the Bagging Decision Tree is the ensemble method that works optimally in this subject classification. This result suggests that the ensemble method can still fail to produce an ideal outcome that approaches the SJR system.<\/jats:p>","DOI":"10.17977\/um018v5i22022p137-142","type":"journal-article","created":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T20:44:11Z","timestamp":1685393051000},"page":"137-142","source":"Crossref","is-referenced-by-count":1,"title":["Performance of Ensemble Classification for Agricultural and Biological Science Journals with Scopus Index"],"prefix":"10.17977","volume":"5","author":[{"given":"Nastiti Susetyo Fanany","family":"Putri","sequence":"first","affiliation":[{"name":"Universitas Negeri Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aji Prasetya","family":"Wibawa","sequence":"additional","affiliation":[{"name":"Universitas Negeri Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harits Ar","family":"Rosyid","sequence":"additional","affiliation":[{"name":"Universitas Negeri Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agung Bella Putra","family":"Utama","sequence":"additional","affiliation":[{"name":"Universitas Negeri Malang"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wako","family":"Uriu","sequence":"additional","affiliation":[{"name":"Chikushi Jogakuen University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7463","published-online":{"date-parts":[[2022,12,30]]},"container-title":["Knowledge Engineering and Data Science"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/journal2.um.ac.id\/index.php\/keds\/article\/viewFile\/37161\/11293","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/journal2.um.ac.id\/index.php\/keds\/article\/viewFile\/37161\/11293","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T03:49:16Z","timestamp":1785815356000},"score":1,"resource":{"primary":{"URL":"https:\/\/citeus.um.ac.id\/keds\/vol5\/iss2\/11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,30]]},"references-count":0,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,12,30]]}},"URL":"https:\/\/doi.org\/10.17977\/um018v5i22022p137-142","relation":{},"ISSN":["2597-4637"],"issn-type":[{"value":"2597-4637","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,30]]}}}