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All Journal TEKNIK INFORMATIKA TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) International Journal of Advances in Intelligent Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Mantik Indonesian Journal of Electrical Engineering and Computer Science Science in Information Technology Letters Journal of Applied Computer Science and Technology (JACOST) International Journal of Engineering, Science and Information Technology Yayasan Cita Cendikiawan Al Khwarizmi Prioritas : Jurnal Pengabdian Kepada Masyarakat Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC)
Hartono Hartono
Universitas Potensi Utama, Medan, Indonesia
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Journal : International Journal of Advances in Intelligent Informatics

 1 
Hybrid approach redefinition with cluster-based instance selection in handling class imbalance problem Hartono Hartono; Erianto Ongko; Dahlan Abdullah
International Journal of Advances in Intelligent Informatics Vol 7, No 3 (2021): November 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v7i3.515

Abstract

Class Imbalance problems often occur in the classification process, the existence of these problems is characterized by the tendency of a class to have instances that are much larger than other classes. This problem certainly causes a tendency towards low accuracy in minority classes with smaller number of instances and also causes important information on minority classes not to be obtained. Various methods have been applied to overcome the problem of the imbalance class. One of them is the Hybrid Approach Redefinition method which is one of the Hybrid Ensembles methods. The tendency to pay attention to the performance classifier, has led to an understanding of the importance of selecting an instance that will be used as a classifier. In the classic Hybrid Approach Redefinition method classifier selection is done randomly using the Random Under Sampling approach, and it is interesting to study how performance is obtained if the sampling process is based on Cluster-Based by selecting existing instances. The purpose of this study is to apply the Hybrid Approach Redefinition method with Cluster-Based Instance Selection (CBIS) approach so that it can obtain a better performance classifier. The results showed that Hybrid Approach Redefinition with cluster-based instance selection gave better results on the number of classifiers, data diversity, and performance classifiers compared to classic Hybrid Approach Redefinition.
Biased support vector machine and weighted-smote in handling class imbalance problem Hartono Hartono; Opim Salim Sitompul; Tulus Tulus; Erna Budhiarti Nababan
International Journal of Advances in Intelligent Informatics Vol 4, No 1 (2018): March 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i1.146

Abstract

Class imbalance occurs when instances in a class are much higher than in other classes. This machine learning major problem can affect the predicted accuracy. Support Vector Machine (SVM) is robust and precise method in handling class imbalance problem but weak in the bias data distribution, Biased Support Vector Machine (BSVM) became popular choice to solve the problem. BSVM provide better control sensitivity yet lack accuracy compared to general SVM. This study proposes the integration of BSVM and SMOTEBoost to handle class imbalance problem. Non Support Vector (NSV) sets from negative samples and Support Vector (SV) sets from positive samples will undergo a Weighted-SMOTE process. The results indicate that implementation of Biased Support Vector Machine and Weighted-SMOTE achieve better accuracy and sensitivity.
Co-Authors Ammar Yasir Nasution Andi Rahmadsyah Asmah Indrawati B. Herawan Hayadi Dahlan Abdullah Desniarti Dian Maya Sari Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erna Budhiarti Nababan Firman Syahputra Irwan Daniel Jaka Kusuma Lili Suryati Meli Handayani Muhammad Khahfi Zuhanda Muhammad Sadikin Muhammad Zen, Muhammad Nur Anzelina Opim Salim Sitompul Rahmad Syah, Rahmad Rahman, Sayuti Retna Astuti Kuswardani Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly Rubianto Sembiring, Arnes Silvia Lestari Sugeng Riyadi Suswati Tulus Tulus Wanayumini Wulan Dari Yeni Risyani Zakarias Situmorang Zuhanda, Muhammad Khahfi