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All Journal FORUM STATISTIKA DAN KOMPUTASI Media Statistika Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI IPTEK The Journal for Technology and Science CAUCHY: Jurnal Matematika Murni dan Aplikasi Sosioinforma International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Penelitian Pertanian Tanaman Pangan BAREKENG: Jurnal Ilmu Matematika dan Terapan SINTECH (Science and Information Technology) Journal MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal Aplikasi Statistika & Komputasi Statistik FIBONACCI: Jurnal Pendidikan Matematika dan Matematika Inferensi International Journal of Advances in Data and Information Systems InPrime: Indonesian Journal Of Pure And Applied Mathematics Majalah Ilmiah Matematika dan Statistika (MIMS) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Enthusiastic : International Journal of Applied Statistics and Data Science Prosiding Seminar Nasional Official Statistics Jurnal Natural Eduvest - Journal of Universal Studies Xplore: Journal of Statistics PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Parameter: Jurnal Matematika, Statistika dan Terapannya Scientific Journal of Informatics Journal of Mathematics, Computation and Statistics (JMATHCOS) Advance Sustainable Science, Engineering and Technology (ASSET) Indonesian Journal of Statistics and Its Applications Journal on Mathematics Education
Kusman Sadik
Departemen Statistika, IPB University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Transportation Other

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Journal : Scientific Journal of Informatics

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Classification Performance of Stacking Ensemble with Meta-Model of Categorical Principal Component Logistic Regression on Food Insecurity Data Pangestika, Dhita Elsha; Fitrianto, Anwar; Sadik, Kusman
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.15315

Abstract

Purpose: Stacking is one type of ensemble whose base-models use different algorithms. The classification results from its base-models are categorical and tend to be associated with each other. They then become input for the stacking meta-model. However, there are no currently definite rules for determining the classifier that becomes the meta-model in stacking. On the other hand, recent research has found that CATPCA-LR can work well on categorical predictor variables associated with each other. Therefore, this study focuses on the classification performance of the stacking algorithm with the CATPCA-LR meta-model. Methods: The study compared the classification performance stacking with CATPCA-LR meta-model to stacking with other meta-models (random forest, gradient boost, and logistic regression) and its base-models (random forest, gradient boost, extreme gradient boost, extra trees, light gradient boost). This research used food insecurity data from March 2022. Result: The stacking algorithm with the CATPCA-LR meta-model performs better insecurity data regarding sensitivity, balanced accuracy, F1-Score, and G-Means values. This model offers a sensitivity of 46.28%, a balanced accuracy of 59.82%, an F1-Score of 37.82%, and a G-Means of 58.26%. Meanwhile, regarding specificity values, the light gradient boost (LGB) algorithm gives the highest value compared to other algorithms. This model provides a specificity value of 88.40%. Generally, the stacking with the CATPCA-LR meta-model algorithm provides the best performance compared with other algorithms on food insecurity data. Novelty: This research has explored a stacking classification performance with CATPCA-LR as meta-model.
Co-Authors . Erfiani . Indahwati A.Tuti Rumiati Aam Alamudi Abdullah, Adib Roisilmi Achmad Fauzan Agus Mohamad Soleh Ahmad Rifai Nasution Aji Hamim Wigena Akbar Rizki Akbar Rizki Akbar Rizki Akmala Firdausi Amalia, Rahmatin Nur Anadra, Rahmi Ananda Shafira Anang Kurnia Andespa, Reyuli Andi Okta Fengki ASEP SAEFUDDIN Astari, Reka Agustia Astari, Reka Agustia Aulya Permatasari Azka Ubaidillah Bagus Sartono Budi Susetyo Budi Susetyo Cici Suhaeni Cici Suhaeni Dito, Gerry Alfa Dwi Agustin Nuriani Sirodj Efriwati Efriwati Embay Rohaeti Eminita, Viarti EVITA PURNANINGRUM FARDILLA RAHMAWATI Farit Mochamad Afendi Fitrianto, Anwar Haikal, Husnul Aris Hari Wijayanto Hasnataeni, Yunia Hazan Azhari Zainuddin Hermawati, Neni I Gusti Ngurah, Sentana Putra I Made Sumertajaya I Wayan Mangku Indahwati Indahwati Indahwati Intan Arassah, Fradha Iqbal, Teuku Achmad Isnanda, Eriski Khairi A N Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Khusnul Khotimah Kusni Rohani Rumahorbo Latifah, Leli Lili Puspita Rahayu Logananta Puja Kusuma M Soleh, Agus Mochamad Ridwan Mochamad Ridwan, Mochamad Mohammad Masjkur Muh Nur Fiqri Adham Muhammad Yusran Mulianto Raharjo Naima Rakhsyanda Nisrina Az-Zahra, Putri Nur Khamidah NURADILLA, SITI Nusar Hajarisman Pangestika, Dhita Elsha Parwati Sofan, Parwati Purnama Sari Rifqi Aulya Rahman Rizki, Akbar Rizqi, Tasya Anisah ROCHYATI ROCHYATI Sahamony, Nur Fitriyani Saleh, Agus Muhammad Satriyo Wibowo Siregar, Jodi jhouranda Siti Raudlah Sitti Nurhaliza Soleh, Agus M Suhaeni, Cici Supriatin, Febriyani Eka Tendi Ferdian Diputra Titin Suhartini Titin Suhartini, Titin Tri Wahyuni Uswatun Hasanah Utami Dyah Syafitri Viarti Eminita Widhiyanti Nugraheni Yenni Angraini Yenni Kurniawati Yuli Eka Putri