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All Journal Jurnal Informatika Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Kaputama (JIK) JURSIMA (Jurnal Sistem Informasi dan Manajemen) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Responsif : Riset Sains dan Informatika Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Computer Science (CO-SCIENCE) Reputasi: Jurnal Rekayasa Perangkat Lunak Jurnal Abdimas Komunikasi dan Bahasa Indonesian Journal of Networking and Security - IJNS JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Interkom : Jurnal Publikasi Ilmiah Bidang Teknologi Informasi dan Komunikasi J-Intech (Journal of Information and Technology) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY JURSIMA Sinergi: Jurnal Pengabdian Kepada Masyarakat Journal of Accounting Information System Bulletin of Informatics and Data Science Jurnal Ilmiah Manajemen Ekonomi Dan Akuntansi (JIMEA) Jurnal Sistem Informasi dan Manajemen Media Teknologi dan Informatika Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat
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Journal : KLIK: Kajian Ilmiah Informatika dan Komputer

Klasifikasi Risiko Kesehatan Ibu Hamil Menggunakan Random Oversampling Untuk Mengatasi Ketidakseimbangan Data Riska Aryanti; Titik Misriati; Rahmat Hidayat
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 5 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i5.728

Abstract

Data imbalance is a common problem in classification, including in maternal health risk classification. Data imbalance occurs when the number of samples in the positive class is much less than the negative class. Data imbalance can cause the classification model to be inaccurate and tend to predict the majority class. One way to overcome the problem of data imbalance is to use the random oversampling technique. In this study, the random oversampling method is applied to overcome the problem of data imbalance in the classification of maternal health risks. Particle swarm optimization (PSO) is used for attribute weighting, improving the results of random oversampling and model performance. The results show that random oversampling can improve accuracy and reduce errors in predicting minority classes. In addition, the PSO technique also significantly contributed to improving the model's accuracy. The results of testing the random forest algorithm using 10-fold cross-validation on the health risks of pregnant women have an accuracy of 80.77%. After going through the random oversampling technique, the accuracy rate reaches 81.86%, and after optimization using the PSO technique, there is an increase of 2.15%, so the accuracy rate reaches 82.92%.
Co-Authors Agus Junaidi Agustiani, Sarifah Aldian Mauluda Alif Rizqi Mulyawan Andi Saryoko Andreas Roy Prasetya Ari Sulistiyawati Arifin, Yosep Tajul Asriyani Sagiyanto ASRIYANI SAGIYANTO, ASRIYANI Atang Saepudin Atang Saepudin Atang Saepudin Azis, Munawar Abdul Bayu Kusuma Ilyasa Universitas Bina Sarana Informatika Cindy Sri Wahyuni Dahlia Dahlia Darma Setiawan Putra Dede Firmansyah Dede Firmansyah Saefudin Deni Gunawan Diah Puspitasari Dian Ardiansyah Dian Ardiansyah Eka Fitriani Eka Fitriani Eka Fitriani Eka Fitriyani Fachri, Muhamad Haliza Ramadhanti, Pristya Harefa, Kristine Haryani Hasan, Fuad Nur Herdian Pratama I Gede Iwan Sudipa Irfan Ridwan Jananto Watori KOMALASARI, YULI Masjuwita Aulia Munthe Masngud Megawaty, Dyah Ayu Mesran, Mesran Mochamad Wahyudi Nova Damai Yanti Bancin Oktaviyani Oktaviyani Oprasto, Raditya Rimbawan Pasaribu, A. Ferico Octaviansyah Perani Rosyani Permana, Rifky Pristya Haliza Ramadhanti Rachilsyah Ramdhani Efendi Rahmat Hidayat Rahmat Hidayat Ramadhani, Arya Richardus Eko Indrajit Rifky Permana Rifqi Rizaldi Rina Martenia Rizqi Nur Esmeralda Rosiun Universitas Bina Sarana Informatika Roy Prasetya, Andreas Royadi - Royadi Royadi Royadi, Royadi Salman Alfarizi SALMAN ALFARIZI Samudi Samudi Sari Dewi Universitas Bina Sarana Informatika PSDKU Pontianak Setiawansyah Setiawansyah Siti Khotimatul Wildah Siti Marlina, Siti siti rodiah Sopiyan Dalis Sumanto, Sumanto Titik Misriati tri wahyuni Tri Wahyuni Ulum, Faruk Walim Walim Wang, Junhai Yanto, Andika Bayu Hasta Yarimani Laia