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All Journal Journal of Intelligent Decision Support System (IDSS) International Journal of Basic and Applied Science
Lukman
Universitas Pendidikan Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Physics

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A Decision Support System To Determine The Best Natural Feed For Fish Cultivation Using Topsis Method Abdul Malik; Ester Frescila Simbolon; Lukman; Tiara Adinda
Journal of Intelligent Decision Support System (IDSS) Vol 5 No 2 (2022): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v5i2.87

Abstract

Natural feed in the cultivation of carp (Cyprinus carpio) is a very important effort to do so that the cultured fish can breed quickly and of course in good health. Sometimes carp cultivators are confused about deciding which natural feed is good. This study aims to select the best natural carp feed using a Decision Support System (DSS) with the TOPSIS method. This method uses an alternative approach to the ideal solution called preference value. In this study using several criteria, namely C1: Protein; C2 : Fat; C3 : Carbohydrates; C4 : Feed Prices; C5: Yes. From the calculations performed using the TOPSIS method, the highest preference level with a value of 1 is A1. The results of the Decision Making System with the TOPSIS method from natural selection of carp that can be used by farmers, namely earthworms.  
Classification of marine mammals based on nucleotide using machine earning Lukman; Tiara Dinda Hapsari; Abdul Malik; Ester Frescilla Simbolon; Ishak Ariawan; Nadia Yusuf Istiqomah
International Journal of Basic and Applied Science Vol. 11 No. 2 (2022): Sep: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v11i1.90

Abstract

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.
Co-Authors Abdul Malik Ester Frescila Simbolon Ester Frescilla Simbolon Ishak Ariawan Nadia Yusuf Istiqomah Tiara Adinda Tiara Dinda Hapsari