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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL MEDIA INFORMATIKA BUDIDARMA ILKOM Jurnal Ilmiah JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) AL-ULUM: JURNAL SAINS DAN TEKNOLOGI Jurnal Teknologi Terpadu Journal of System and Computer Engineering Jurnal Informatika Terpadu Global Abdimas: Jurnal Pengabdian Masyarakat Sentra Dedikasi: Jurnal Pengabdian Masyarakat Journal Pharmacy and Application of Computer Sciences Jurnal Informatika: Jurnal Pengembangan IT Advances in Computer System Innovation Journal (ACSI Journal)
Firman Aziz
Universitas Pancasakti Makassar, Indonesia
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Journal : International Journal of Electrical and Computer Engineering

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Increasing electrical grid stability classification performance using ensemble bagging of C4.5 and classification and regression trees Firman Aziz; Armin Lawi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2955-2962

Abstract

The increasing demand for electricity every year makes the electricity infrastructure approach the maximum threshold value, thus affecting the stability of the electricity network. The decentralized smart grid control (DSGC) system has succeeded in maintaining the stability of the electricity network with various assumptions. The data mining approach on the DSGC system shows that the decision tree algorithm provides new knowledge, however, its performance is not yet optimal. This paper poses an ensemble bagging algorithm to reinforce the performance of decision trees C4.5 and classification and regression trees (CART). To evaluate the classification performance, 10-fold cross-validation was used on the grid data. The results showed that the ensemble bagging algorithm succeeded in increasing the performance of both methods in terms of accuracy by 5.6% for C4.5 and 5.3% for CART.
Co-Authors Ahmad Sukarna Syahrir Akbar Taufik Ali Akbar Velayaty Amri, Nur Fadhila Andi Merdewiningsi Andi Nurilmi Adriana Andyka Wahab Anggun Kusumawardhani Anirwan Anirwan Armin Lawi Benny L.E.P Benny Leonard Enrico Panggabean Dhilan Sasmita Faisal Rahman Farid Fani Temarwut Firmansyah Firmansyah Firmansyah Hasriani Hasriani Hechmi SHILI Hendra Umar Imran Iskandar Ishak, Pertiwi Jeffry jeffry jeffry - Jeffry Jeffry Jeffry Jeffry Kiki Resqy Amelia Kurnia Yahya Lutfi Budi Ilmawan M Rezky Armansyah M Rezky Armansyah Mardewi Mardewi Mardewi Mardewi Muhammad Arfah Asis Muhammad Lutfi Muhammad Rijal Muhammad Rijal Nur Ayu Asrhi Nur Ayu Asrhi Nur Hamadani Nur Nur Hamdani Nur Nurafni Shahnyb Nuru Yarkuran Nurul Fathanah Mustamin Rahmat Fuadi Syam Rohmah Nur Hidayah Satar Satar Sitti Arni Sofyan Sofyan Sofyan Sofyan Sustrin Abasa Syahrul Usman Syahrul Usman Syahrul Usman Syahrul Usman Usman, Syahrul Wungo, Supriyadi La Zulkarnain Zulkarnain