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All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika) Indonesian Research Journal on Education
Rijal, Amir Salim Khairul
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Religion Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Energy Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Artificial Neural Network Untuk Prediksi Kelulusan Calon Peserta Didik Baru (Studi Kasus: MAN 1 Padangsidimpuan) Gaja, Rizqi Nusabbih Hidayatullah; Karseno, Doni; Rijal, Amir Salim Khairul; Juliantho, Dwana Abdi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 8, No 1 (2024): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v8i1.782

Abstract

There is fierce rivalry amongst schools as a result of competitiveness in the educational field. Therefore, the processing of an educational institution must keep up with technological advancements. Artificial intelligence (AI) and intelligent systems, sometimes called AI systems, are used to simulate human-like critical thinking and intelligent behavior. A popular technique for categorization and prediction is the artificial neural network. MAN 1 Padangsidimpuan faces the challenge of determining whether new students will graduate because each year's quota of applications is exceeded. In this study, potential new students at MAN 1 Padangsidimpuan will have their graduation dates predicted, and the degree of prediction accuracy will be assessed. Artificial Neural Networks are the research approach employed in this study. The steps that are completed include problem formulation and identification, literature review, data gathering, pre-processing, processing, and assessment. Data about potential new students for the academic year 2023–2024 was utilized in this study. The study's findings demonstrate that the neural network model produces outcomes that are 6-6-2 (6 input neurons, 6 hidden layers, and 2 output neurons). 97.31% was the greatest accuracy performance level attained, while 90.30% was the lowest. 615 people made the most accurate predictions, while 569 people made the fewest accurate ones. There were 17 forecasts that were wrong the least and 63 wrong predictions the most.
Artificial Neural Network Untuk Prediksi Kelulusan Calon Peserta Didik Baru (Studi Kasus: MAN 1 Padangsidimpuan) Gaja, Rizqi Nusabbih Hidayatullah; Karseno, Doni; Rijal, Amir Salim Khairul; Juliantho, Dwana Abdi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 8, No 1 (2024): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v8i1.782

Abstract

There is fierce rivalry amongst schools as a result of competitiveness in the educational field. Therefore, the processing of an educational institution must keep up with technological advancements. Artificial intelligence (AI) and intelligent systems, sometimes called AI systems, are used to simulate human-like critical thinking and intelligent behavior. A popular technique for categorization and prediction is the artificial neural network. MAN 1 Padangsidimpuan faces the challenge of determining whether new students will graduate because each year's quota of applications is exceeded. In this study, potential new students at MAN 1 Padangsidimpuan will have their graduation dates predicted, and the degree of prediction accuracy will be assessed. Artificial Neural Networks are the research approach employed in this study. The steps that are completed include problem formulation and identification, literature review, data gathering, pre-processing, processing, and assessment. Data about potential new students for the academic year 2023–2024 was utilized in this study. The study's findings demonstrate that the neural network model produces outcomes that are 6-6-2 (6 input neurons, 6 hidden layers, and 2 output neurons). 97.31% was the greatest accuracy performance level attained, while 90.30% was the lowest. 615 people made the most accurate predictions, while 569 people made the fewest accurate ones. There were 17 forecasts that were wrong the least and 63 wrong predictions the most.
Memanfaatkan Teknologi Informasi untuk Meningkatkan Operasional Bisnis Online Rijal, Amir Salim Khairul; Veri, Jhon
Indonesian Research Journal on Education Vol. 4 No. 2 (2024): irje 2024
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/irje.v4i2.526

Abstract

Ketika kehadiran Internet semakin tak terelakkan, penggunaannya telah merambah banyak bidang kehidupan.Saat digunakan, ia tidak memberitahukan usia atau latar belakang seseorang. Siapa pun dapat menggunakan Internet, termasuk pengusaha , dalam upaya pengembangan bisnisnya. Dampak Teknologi Informasi Terhadap Pengusaha mempengaruhi pengusaha untuk menghemat waktu dalam berbisnis, mempengaruhi pengusaha menjadi mahatahu (informasi mudah didapat), mempengaruhi komunikasi. Dampak dan peran sistem informasi terhadap bisnis mempunyai banyak implikasi bagi bidang bisnis teknologi informasi saat ini. Teknologi Informasi saat ini sangat penting bagi para pengusaha yang menggunakan Teknologi Informasi untuk mempromosikan usahanya. Ada banyak fitur yang sangat penting bagi pengusaha untuk menjalankan bisnisnya. Pengusaha dapat menggunakan untuk mengimplementasikan inovasi dan ide menggunakan teknologi informasi. Sangat penting bagi perusahaan untuk mengikuti tren bisnis dan jual beli saat ini. dilakukan hampir seluruhnya secara online dengan menggunakan teknologi informasi. Anda Harus Menjadi Pengusaha Kami menyadari tren TI dalam bisnis online maupun di dunia manual.
Co-Authors Gaja, Rizqi Nusabbih Hidayatullah Juliantho, Dwana Abdi Karseno, Doni Veri, Jhon