Classification of marine mammals based on nucleotide using machine earning - Lukman; Tiara Dinda Hapsari; Abdul Malik; Ester Frescilla Simbolon; Ishak Ariawan; Nadia Yusuf Istiqomah (Institute of Computer Science (IOCS), 2022)
This study analyzing the nucleotide of marine mammals using machine learning techniques. Analysis on a nucleotide scale in marine mammals can help facilitate the identification process if done properly. Three types of marine mammals used for nucleotide analysis were Delphinus capensis, Dugong dugon, and Orcaella brevirostris. The solutions offered by machine learning provide a more elegant and effective solution for species identification at the nucleotide scale. This study analyzed the nucleotide s of marine mammals using various classification techniques. Based on this research, it can be concluded that the identification of marine mammals can be done easily based on nucleotide. Different classifiers have been used for analytical purposes such as Random Forest, Decision Tree, Naïve Bayes, K-Nearest Neighbor, and Multilayer Perceptron. Based on the analysis of the results, it was found that the classification method that had been applied had sufficient performance by being tested on several model performance metrics such as accuracy, precision, recall and f1 score. The study also highlights the best classifiers in the various scenarios and recommendations are given.