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Ariani, Dhini
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Penggunaan Jaringan Saraf Tiruan untuk Memperkirakan Tenaga Kerja Berdasarkan Kategori Industri Ariani, Dhini; Saragih, Farah Yusni; Asyifah, Hazha Hikmah; Nasution, Alisa Putri Amanda; Alkhairi, Putrama
Bulletin of Data Science Vol 4 No 1 (2024): October 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v4i1.6433

Abstract

Industrial growth can affect labor mobility both geographically and in terms of professional qualifications, large industries have a strategic role as creators of added value and important job providers in the Region. As an important part of industrial production, it cannot be separated from the demand for labor, but if viewed macro, it can be concluded that the quality of work determines or greatly influences the results of labor productivity itself. The industrial sector plays a significant role in economic growth, because it absorbs labor. Labor growth is much greater than the availability of jobs, thus causing other new problems, namely high unemployment. This study uses the Backpropagation Method to classify special patterns, which reduces the error rate by adjusting the weight based on the difference between output and the desired target. The results of this study are predictions of the level of truth of the Number of Large and Medium Industrial Workers according to Industry Group. Using 5 models, namely 10-10-1, 10-45-1, 10-45-10-1, 10-75-10-1, and 10-100-75-1. From 5 architecture models, 1 best model is produced, namely the 10-75-10-1 model with an accuracy rate of 70% and the smallest epoch with a total of 383.
Co-Authors Alkhairi, Putrama Asyifah, Hazha Hikmah Nasution, Alisa Putri Amanda Saragih, Farah Yusni