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Mambang
Universitas Sari Mulia
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Journal : TIERS Information Technology Journal

 1 
Predictive Modeling Classification of Post-Flood and Abrasion Effects With Deep Learning Approach Finki Dona Marleny; Mambang Mambang
TIERS Information Technology Journal Vol. 3 No. 1 (2022)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (624.488 KB) | DOI: 10.38043/tiers.v3i1.3604

Abstract

Floods and abrasion are the most common disasters in Indonesia. A lot of data is collected from post-flood and abrasion disasters. From the data released by BNPB, disaster data is directly based on the occurrence of disasters. From these data, we will test predictive modeling classification with a deep learning approach. Big data can be made through classification and predictive modeling. Our proposed model is a classification of predictive modeling of post-flood and abrasion data using the H2O deep learning approach. Deep learning H2O models can also be evaluated with specific model metrics, termination metrics, and performance charts. This approach is used to optimize the performance and accuracy of predictions during the modeling process using our dataset pool training. The big data to be processed will generate new knowledge for policies in decision making. Big data performance modeled with Deep Learning H2O is used to predict the Survival attributes of post-flood and abrasion sample datasets. The best metric performance is obtained from the maxout activation function with a 200-200 unit layer that gets an accuracy of 93.49% with AUC: 0.808 +/- 0.022 (micro average: 0.808).
Co-Authors Abdul Kadir Adini, Muhammad Hifdzi Ahmad Hidayat Ahmad Hidayat Ahmad Riki Renaldi Ahmad Riki Renaldy Akhmad Baddrudin Amelia, Mahlianor Anggrita Sari Anggrita Sari Antonia Yenitia Ari Yunus Hendrawan Aulia Fitri, Aulia Ayu Ahadi Ningrum Bambang Lareno, Bambang Bayu Nugraha Bayu Nugraha Bima Wicaksono Budiman, Haldi Cipta, Subhan Panji Dixky Dixky Dwi Salmarini, Desilestia Fatimah, Nora Ova Putri Martiani Finki Dona Marleny Fitriansyah, Muhammad Haniffah Sri Rinjani Hati Waruwu, Riang Heni Pujiastuti Hudatul Aulia Husna Karima Ika Hariati Ika Hariati Ika Hariati Ika Hariati, Ika Hariati Indah Tri Handayani Indah Wulandari Jaya Hari Santoso Johan Wahyudi Johan Wahyudi, Johan Kamarudin Kartika Kartika Kunti Nastiti Ladjar, Imelda Ingir Liliana Swastina M Samsul Hasbi M Samsul Hasmi Maria Ulfah Maulida, Ihdalhubbi Maulida, Nur Meilianti Melda Melda Melda, Melda Meyska Widyandini Miranda Miranda Mohammad Basit, Mohammad Muhammad Khairul Akbar Muhammad Riduan Syafi’i Muhammad Satrio Ayuba Muhammad Zaini Bakri Muhammad Ziki Elfirman Muhammad Zulfadhilah Mukhaimy Gazali Muliawan, dadang Mutiara R, Chatrine Indri Mutmainah Mutmainah Mutmainah Mutmainah Nahdi Saubari Nalo Valentino Naparin, Husni Nisa, Reny Ayu Nor Azizah Novita Sari Novriansyah, Irvan Nur Hafiz Ansari Nur Meilianti Maulida Nurhaeni Nurhaeni Nurhaeni Nurhaeni Nurhasanah Nurhasanah Oktavia, Samita Oktovin, Oktovin Pasaribu, Annisa Pebrianti, Eva Wulani Prasetya, M. Riko Anshori Prastya, Septyan Eka Pratama, Ramadhani Noor Putri Putri Putri Putri, Putri Rafi'i, Rafi'i Rahmini Rahmini Ramli, Muhammad Reza Risdianti, Risdianti Risma Maulida Risma Risma Rismawati Rismawati Rizkian Muhammad Fikri Rochman, Wisnu Nur Ropikah Ropikah Ropikah, Ropikah Rudy Ansari Rudy Ansari Rudy Ansari, Rudy Rusidah, Rusidah Samita, Mambang Sandro Nesta Pembriano Sari, Anggrita Sa’adah Septyan Eka Prasetya Septyan Eka Prastya Septyan Eka Prastya Siti Gadis Hardianti Subhan Panji Cipta Subhan Panji Cipta Sultan Arrasyid SUMARNI ZAINUDDIN Syapotro, Usman Tasya Salsabila Theresia Kurniati Seran Tiara, Astia Rahma Tumanggor, Agustina Hotma Uli Wahyudin, Rahmawati Winda Astria Nuansa Saputri Windarsyah Windarsyah Wulandari Febriani Wulandari Febriani Yanti Saubari Yanti Saubari Yuslena Sari, Yuslena