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All Journal JURNAL SISTEM INFORMASI Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputer Terapan Seminar Nasional Teknologi Informasi Komunikasi dan Industri INOVTEK Polbeng - Seri Informatika Dinamisia: Jurnal Pengabdian Kepada Masyarakat ILKOM Jurnal Ilmiah Jurnal Pengabdian Masyarakat Multidisiplin Literasi: Jurnal Pengabdian Masyarakat dan Inovasi Proceeding Applied Business and Engineering Conference JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat) SATIN - Sains dan Teknologi Informasi Jurnal Informatika: Jurnal Pengembangan IT
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Journal : ILKOM Jurnal Ilmiah

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Comparative Analysis to Determine the Best Accuracy of Classification Methods Warnia Nengsih; Yuli Fitrisia; Mardhiah Fadhli
ILKOM Jurnal Ilmiah Vol 14, No 2 (2022)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v14i2.1128.134-141

Abstract

The classification method is one of the methods of supervised learning and predictive learning. This method can be used to detect an object in the image presented, whether it is in accordance with the existing object in the training phase. There are several classification methods used, including Support Vector Machine (SVM), K-Nearest Neighbors (K-NN) and Decision Tree. To determine the accuracy in detecting these objects, it is necessary to measure the accuracy of each classification method used. The object that becomes simulation in this research is the object image of Guava and Pear fruit. Testing using confusion matrix. The results showed that the Support Vector Machine (SVM) method was able to detect with an accuracy of 98.09%. Then the K-Nearest Neighbors (K-NN) method with an accuracy of 98.06%, then the Decision Tree method with an accuracy of 97.57%. From the results of the accuracy test, it can be concluded that basically these three classification methods have good accuracy with a difference of 0.49% and the overall average accuracy of the classification of the three methods is 97.89%
Co-Authors Akbar, Memen Anggy Trisnadoli Ayu Putri Hanifah Debi Gustian Dewi Hajar Erwin Setyo Nugroho Indah Lestari Jordan Abeth Teofilus Pasaribu Kartina Diah K. W. Mardhiah Fadhli, Mardhiah Muhammad Akbar Agung Triputra mutia sari zulvi Nurmalasari, Dini Rade Oktari Sakti Rika Perdana Sari, Rika Perdana Sinria Kasna Sugeng Purwantoro E.S.G.S Trisnadoli, Anggy Valdo Franata Warnia Nengsih Wenda Novayani Yoanda Alim Syahbana Yohana Dewi Lulu Widyasari