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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) International Journal of Advances in Intelligent Informatics InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Data Science: Journal of Computing and Applied Informatics Jurnal Mantik Indonesian Journal of Electrical Engineering and Computer Science
Opim Salim Sitompul
Universitas Sumatera Utara
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : International Journal of Advances in Intelligent Informatics

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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 Afriandy Sharif Alexander F.K. Sibero Andrew Handoko Dedy Arisandi Dennis Dennis Elviawaty Muisa Zamzami Erna Budhiarti Nababan Goklas Tomu Simbolon Hartono Hartono Jonas Franky R Panggabean Lubis, Arif Ridho Mahyuddin K. M Nasution Mardingsih Mardingsih Muhammad Khahfi Zuhanda Rahmad Nurhadi Yusra Romi Fadillah Rahmat Saib Suwilo Sarah Purnamawati Sawaluddin Nasution Seniman Tulus Tulus Yundari, Yundari Yuni Cancer