Machine Learning Application of Oil Palm: A Bibliometric Analysis

Abstract

The advancement of machine learning-based technology spread widely, especially in oil palm. Oil palm has become a main source of domestic products because of its high production and a leading commodity where it cannot be separated from the use of machine learning. However, the potential of machine learning has not yet been identified specifically through bibliography aspects where those aspects are needed for future research. The main objective of this research is to analyze trends of machine learning utilization and potential topics in oil palm by using bibliometric analysis to obtain year distribution, author productivity, citation, and keyword co-occurrence. As a result, the highest peak number of publications is 2023 where the most cited authors are Haohuan Fu and Weijia Li. Then, the most used algorithms are deep learning, ANN, SVM, RF and CNN based on the occurrences while the tree detection and counting topic has the highest citation articles. The result indicates that scientific interest in the study of this research benefits as a starting point for future works.