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Suwanto Sanjaya
Universitas Islam Negeri Sultan Syarif Kasim Riau
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Social Sciences Transportation Other

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Prediksi Remaining Useful Life Mesin Turbofan Menggunakan Metode Deep Layer Recurrent Neural Networks Kevin Maulana Risky; Fitri Insani; Jasril Jasril; Suwanto Sanjaya; Lestari Handayani
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 1 (2025): Maret
Publisher : Universitas Wahid Hasyim

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Abstract

In recent years, the development of prognostic and health management in engines and systems has grown rapidly, with one form of interaction being predicting the remaining useful life of aircraft turbofan engines. In this study, chose to use the Deep Learning RNN method with LSTM architecture.  And in its limitation, the C-MAPSS FD001 dataset is used as a modeling dataset in which there is complex multivariate data. The main objective in this analysis and modeling process is to obtain the remaining useful life prediction results that can be a benchmark in analyzing the Remaining Useful Life (RUL) of the turbofan engine. The test results involved many criteria and parameters that were tested. Analysis of the results shows that the model with learning rate criteria of 0.001, number of epochs of 50, hidden unit of 12, Min-max normalization method, and Adam optimizer tested can understand quite accurately the RUL data pattern and follow the movement of the predetermined RUL target. Although there is a decrease and a slight spike in the unit level of machines 81 to 84, with an error value in RMSE of 26.48, but overall the model can be considered optimal in learning the prediction pattern of the RUL target. This research shows that the RNN-LSTM model has great potential in aircraft turbofan engine prognostic applications.
Co-Authors Abdussalam Al Masykur Achmad Yamin Harahap Adrian Maulana Afiana Nabilla Zulfa Ahmad Fauzan Ahmad Paisal Ahmad, Rizmah Zakiah Nur Al Fiqri, M. Faiz Alwis Nazir Alwis Nazir Alwis Nazir Alwiz Nazir Amalia Hanifah Artya Annisa Putri Arif Mudi Priyatno Ariq At-Thariq Putra Aulia Ramadhani Azizah Tasykira Paramitha El Razi Baehaqi Cut Lira Kabaatun Nisa Darmila Deny Ardianto Dodi Efendi efni humairah Eka Pandu Cynthia Elin Haerani Elvia Budianita Erni Rouza, Erni Ersad Alfarsy Absar, Ersad Alfarsy Fadhilah Syafria Fadhilla Syafria Fakhrezi, Muhammad Dzaki Febi Yanto Felian Nabila Fikri Kurnia Rahman Fioni Nikmatul Fajar Fitra Kurnia Fitri Insani Fitri Insani Fitri Insani Fitri Insani Fitri Insani (Scopus ID: 57190404820) Fitri, Dina Deswara Gusrifaris Yuda Alhafis Gusti, Siska Kurnia Hafez Almirza Harni, Yulia Hartini Hartini Iis Afrianty Iis Afrianty Ikhwanul Akhmad DLY Irman Hermadi Isnan Mellian Ramadhan Israldi, Tino Iwan Iskandar Iwan Iskandar Jasril Jasril Jasril Jasril Jasril Jasril Karina Julita Kevin Maulana Risky Kurniawan, Saifur Yusuf Lestari Handayani Lestari Handayani Lestari Handayani Lia Anggraini Lola Oktavia M Alfandri Aqilah M. Fadil Martias Masaugi, Fathan Fanrita Maulana Junihardi Mazdavilaya, T Kaisyarendika Megawati Megawati Morina Lisa Pura Muhammad Affandes Muhammad Affandes Muhammad Elfarizi Muhammad Fikry Muhammad Irfan Syah Muhammad Irsyad Muhammad Irsyad Muhammad Irsyad Muhammad Vio Hardiansyah Nabyl Alfahrez Ramadhan Amril Nazir, Alwis Nazruddin Safaat Nazruddin Safaat H Nazruddin Safaat H Negara, Benny Sukma Novi Yanti Novriyanto Novriyanto Novriyanto Pangestu, Yoga Pizaini Pizaini Puspa Melani Almahmuda Putri Ayuni, Desy Radili, Adi Rahma Shinta Rahmad Abdillah Ramadhan, Muhammad Ilham Ramu Will Sandra Reski Mai Candra Reski Mai Candra Reski Mei Candra Riska Yuliana Saputra, Nugroho Wahyu Sarah Lasniari Sarah Lasniari Shahira, Fayza Siti Ramadhani Sugandi, Hatami Karsa SURYA ADITYA GD Surya Agustian Syaputra, Muhammad Dwiky Teddie D Ulfah Adzkia Vitriani, Yelfi Yani, Susmi Syahfrida Yelfi Vitriani Yeni Fariati Yusra Yusra, Yusra Yusril Hidayat Zalwana, Hilya