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All Journal Journal of Informatics Management and Information Technology Jurnal Inovasi Artificial Intelligence & Komputasional Nusantara
Febiola, Adinda
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Computer Science & IT Education Mathematics

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Analisis Backpropagation Dalam Menentukan Jumlah Perusahaan Industri Besar Dan Sedang (IBS) Di Indonesia Pramesti, Adinda Frizy; Ramadana, Rica; Beauti, Intan; Febiola, Adinda; Windarto, Agus Perdana
Journal of Informatics Management and Information Technology Vol. 4 No. 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v4i4.414

Abstract

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.
Analisis Sistem Keamanan Pada Sistem Operasi Windows Dengan Metode Clean Instal Febiola, Adinda; Ratih Manalu; Retno Ajeng Kartika Said; Indra Gunawan; Sumarno, Sumarno; Heru Satria Tambunan
Jurnal Inovasi Artificial Intelligence & Komputasional Nusantara Vol. 1 No. 1 (2024): Volume 1 No 1 Tahun 2024
Publisher : PT Siantar Codes Academy Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.260396/0n1zyh66

Abstract

Saat ini informasi berkembang sangat pesat dan semakin canggih. Semakin canggihnya perangkat teknologi informasi berarti semakin banyak pula masyarakat yang menggunakannya. Salah satunya adalah perkembangan computer. Sistem operasi windows adalah salah satu sistem operasi yang paling banyak digunakan di seluruh dunia dan merupakan target utama serangan cyber.  Metode penelitian yang dilakukan terdiri dari dua tahap yaitu pengamatan langsung (observasi) dan studi Pustaka. Kerentanan pada system keamanan windows yang dapat dieksploitasi menggunakan metode dan Solusi clean install direkomendasikan dalam beberapa cara. Kerentanan desain fitur keamanan yaitu windows smart app control dan smart screen mengandung cacat desain yang memungkinkan akses awal tanpa peringatan keamanan untuk mengatasi permasalahan tersebut, setiap system keamanan harus mempunyai metode algoritmik tersendiri untuk mengatasi permasalahan yang ada. Setiap system operasi mempunyai permasalahannya masing masing. Setiap system operasi menggunakan algoritma yang berbeda tergantung pada fitur fiturnya, yang membuat fitur fitur tersebut sulit diretas, disusupi, atau dirusak oleh berbagai ancaman.
Co-Authors Agus Perdana Windarto Beauti, Intan Heru Satria Tambunan Indra Gunawan Pramesti, Adinda Frizy Ramadana, Rica Ratih Manalu Retno Ajeng Kartika Said Sumarno .