Analisis Bibliometrik Penelitian Pohon Keputusan untuk Prediksi Kanker Payudara

Abstract

The purpose of this paper is to conduct a bibliometric analysis of scientific publications that discuss the use of the decision tree method for breast cancer prediction. A total of 322 documents from Scopus were collected for analysis using bibliometric indicators such as productivity and citations. The bibliometric analysis produces scientific mapping based on the keywords co-occurrence, co-authorship, and co-citation analysis to reflect the conceptual, social, and intellectual structure of the research. The results of the analysis of evolution article found an exponential increase in citations and the number of authors in this study in the period 2005-2023, where China was the dominant country in conducting research. In the thematic map analysis, three research topics were produced, namely the medical field, the computer field and the bioinformatics field. Research topics in the use of the decision tree method for breast cancer prediction are included in the computer field. This study suggests that research on the use of the decision tree method for breast cancer prediction is a research topic that needs to be continuously improved.