Analisis Backpropagation Dalam Menentukan Jumlah Perusahaan Industri Besar Dan Sedang (IBS) Di Indonesia
DOI:
https://doi.org/10.47065/jimat.v4i4.414Keywords:
Analytics; ANN; Corporation; Industry; BackpropagationAbstract
Companies are economic actors whose main function is to produce goods and services needed by the community. However, in 2020, the COVID-19 pandemic had an impact on various economic activities, causing many workers to lose their jobs and the unavailability of new jobs, which led to an increase in unemployment in Indonesia. Therefore, strategic steps are needed to prevent an increase in the number of unemployed. One of them is to forecast the number of IBS companies for the next few years. Implementing early prevention as a step to identify new job opportunities in the industry. The forecast data is the number of IBS companies (large and medium industrial companies) collected by BPS for the period 2015-2022. The algorithm used for prediction is a backpropagation artificial neural network. This algorithm is able to remember what existed before and make generalizations from it. This backpropagation algorithm uses five architectural models including 6-10-1, 6-20-1, 6-35-1, 6-45-1, and 6-60-1. Of the five architectural models used, the best architecture was chosen, namely 6-35-1 which has an accuracy of 88%, MSE of 0.003821515 and the error rate used is 0.001-0.07. So this architectural model is good enough to predict the number of IBS companies.
Downloads
References
E. W. Sofiati, “Neural Network Backpropagation Untuk Prediksi Kunjungan Pada Ruang Belajar (Studi Kasus Di Bagindo Aziz Chan Youth Center Kota Padang),” JIKO (Jurnal Informatika dan Komputer), vol. 8, no. 1, p. 62, 2024, doi: 10.26798/jiko.v8i1.1100.
A. R. Wiranto, E. Setiawan, A. Nuryaman, and M. Usman, “Implementasi Metode Backpropagation Neural Network Dalam Meramalkan Tingkat Inflasi Di Indonesia,” MATHunesa: Jurnal Ilmiah Matematika, vol. 11, no. 1, pp. 8–16, 2023, doi: 10.26740/mathunesa.v11n1.p8-16.
International Labour Organization, “The COVID-19 response: Getting gender equality right for a better future for women at work,” Pancanaka, vol. 1, no. May, p. 14, 2020.
P. K. Ozili and T. G. Arun, “Spillover of COVID-19: Impact on the Global Economy,” SSRN Electronic Journal, 2020, doi: 10.2139/ssrn.3562570.
O. Coibion, Y. Gorodnichenko, and M. Weber, “Labor Markets During the COVID-19 Crisis: A Preliminary View,” vol. 8, no. 1, 2020.
S. Lee, D. Schmidt-Klau, and S. Verick, “The Labour Market Impacts of the COVID-19: A Global Perspective,” Indian Journal of Labour Economics, vol. 63, no. s1, pp. 11–15, 2020, doi: 10.1007/s41027-020-00249-y.
S. I. Statistik, “Analisis Hasil Survei Dampak COVID-19 terhadap Pelaku usaha,” Analisis Hasil Survei Dampak COVID-19 terhadap Pelaku usaha, p. vi+ 22 halaman, 2020.
Badan Pusat Statistik, “Jumlah Perusahaan IBS (KBLI 2020) (Unit), 2015-2020.”
Badan Pusat Statistik, “STATISTIK INDONESIA 2023,” Statistik Indonesia 2023.
Badan Pusat Statistik, “Jumlah Perusahaan IBS (KBLI 2020) (Unit), 2015-2020.”
Badan Pusat Statistik, “STATISTIK INDONESIA 2023,” Statistik Indonesia 2023.
Putrama Alkhairi and A. P. Windarto, “Classification Analysis of Back propagation-Optimized CNN Performance in Image Processing,” Journal of Systems Engineering and Information Technology (JOSEIT), vol. 2, no. 1, pp. 8–15, 2023, doi: 10.29207/joseit.v2i1.5015.
M. Thoriq, “Peramalan Jumlah Permintaan Produksi Menggunakan Jaringan Saraf Tiruan Algoritma Backpropagation,” Jurnal Informasi dan Teknologi, vol. 4, pp. 27–32, 2022, doi: 10.37034/jidt.v4i1.178.
N. A. Santoso and M. N. Hasan, “Penerapan Algoritma Jst Menggunakan Metode Backpropagation Untuk Mengidentifikasi Potensi Mahasiswa Baru Stmik Tegal Application of Jst Algorithm Using Backpropagation Method for Identify Potential New Students Stmik Tegal,” Teknomatika, vol. 13, no. 02, pp. 28–33, 2023.
W. Aryanti, “dengan Algoritma Backpropagation untuk Memprediksi Harga Saham,” Jurnal Riset Statistika (JRS), vol. 3, pp. 107–118, 2023.
R. Maiyuriska, “Penerapan Jaringan Syaraf Tiruan dengan Algoritma Backpropagation dalam Memprediksi Hasil Panen Gabah Padi,” Jurnal Informatika Ekonomi Bisnis, vol. 4, pp. 28–33, 2022, doi: 10.37034/infeb.v4i1.115.
W. T. Rosaamalia, R. Santoso, and S. Suparti, “Penerapan Algoritma Backpropagation Dan Optimasi Conjugate Gradient Untuk Klasifikasi Hasil Tes Laboratorium,” Jurnal Gaussian, vol. 11, no. 4, pp. 506–511, 2023, doi: 10.14710/j.gauss.11.4.506-511.
W. Saputra, A. P. Windarto, and A. Wanto, “Analysis of the Resilient Method in Training and Accuracy in the Backpropagation Method,” The IJICS (International Journal of Informatics and Computer Science), vol. 5, no. 1, p. 52, 2021, doi: 10.30865/ijics.v5i1.2922.
K. F. Irnanda, A. P. Windarto, and I. S. Damanik, “Optimasi Particle Swarm Optimization Pada Peningkatan Prediksi dengan Metode Backpropagation Menggunakan Software RapidMiner,” JURIKOM (Jurnal Riset Komputer), vol. 9, no. 1, p. 122, 2022, doi: 10.30865/jurikom.v9i1.3836.
S. Samsudin, A. Ikhwan, R. A. Putri, and M. Badri, “Implementasi Algoritma Backpropagation Neural Networks Untuk Memprediksi Hasil Kinerja Dosen,” Journal of Information System Research (JOSH), vol. 4, no. 2, pp. 410–417, 2023, doi: 10.47065/josh.v4i2.2685.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Analisis Backpropagation Dalam Menentukan Jumlah Perusahaan Industri Besar Dan Sedang (IBS) Di Indonesia
ARTICLE HISTORY
Issue
Section
Copyright (c) 2024 Adinda Frizy Pramesti, Rica Ramadana, Intan Beauti, Adinda Febiola, Agus Perdana Windarto
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
