Garuda - Garba Rujukan Digital

Simple Multi Attribute Rating Technique untuk Pendukung Keputusan Pemberian Sanksi Siswa Gaja, Rizqi Nusabbih Hidayatullah; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurnal KomtekInfo Vol. 11 No. 4 (2024): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v11i4.553

As one of the schools that advances the courtesy of MAN 1 Padangsidimpuan concludes facing the challenge of monitoring and dealing with student violations effectively and efficiently. In this case, MAN 1 Padangsidimpuan has a student order as a reference to discipline his students. The madrasah seriousness of the need to monitor students in committing violations is very low and is still undigitalized. The research aims to design an application that can monitor student violations and support decisions to sanction students who violate order. The method used in this research is the Simple Multi Attribute Rating Technique (SMART). This method has five stages, namely, determining the number of criteria, giving weight to each criterion, normalizing the value of the criterions, giving value to each alternative, and calculating the final value. The data set processed in this study comes from the student problem book in MAN 1 Summary of the 2023/2024 school year. The dataset consists of 147 student violations records. The data sets will be tested calculations manually with calculations using the application. The results of this study show that the application can record student violations well. The result of manual calculations with the calculations on the application has similar results. From the calculation results, the highest final score a student gets is 24 points. The sanctions are given according to the points earned, namely, collecting garbage. Therefore, this research can help Teacher Counseling in monitoring student violations and make the reporting process to the Chief Madrasah faster and more accurate. Applications only help make decisions by providing information or alternative solutions to existing problems. The final decision remains with the decision maker.

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

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

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.

Systemic Literature Review Peran Program Affiliate Marketing Terhadap Minat Beli Pada Platform E-Commerce Gaja, Rizqi Nusabbih Hidayatullah; Veri, Jhon
Jurnal Ilmiah Muqoddimah: Jurnal Ilmu Sosial, Politik dan Hummaniora Vol 8, No 2 (2024): Mei 2024
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jim.v8i2.2024.%p

Perkembangan teknologi dan internet telah mendorong transformasi besar dalam industri perdagangan, termasuk di Indonesia. Sejak beberapa tahun terakhir, e-commerce telah menjadi salah satu sektor paling dinamis dan berkembang pesat, memberikan peluang baru bagi para pelaku usaha untuk menjangkau pasar yang lebih luas dan meningkatkan penjualan. Affiliate marketing telah menjadi salah satu strategi pemasaran yang signifikan dalam industri e-commerce. Penelitian ini bertujuan untuk mengeksplorasi peran program affiliate marketing terhadap minat beli konsumen pada platform e-commerce melalui metode tinjauan literatur sistemik. Affiliate marketing, sebagai salah satu strategi pemasaran digital yang semakin populer, melibatkan pihak ketiga yang mempromosikan produk untuk mendapatkan komisi dari setiap transaksi yang dihasilkan. Tinjauan literatur ini mengumpulkan dan menganalisis 15 artikel yang telah dipublikasikan dan yang mengandung kata kunci program affiliate, minat beli di e-commerce, dan platform e-commerce yang terbit pada rentang tahun 2019 sampai 2024. Penelitian ini memberikan kontribusi signifikan terhadap literatur pemasaran digital dan menawarkan wawasan praktis bagi penjual dalam meningkatkan minat beli di e-commerce. Penelitian ini menemukan bahwa metode penelitian yang banyak digunakan untuk menganalisis data peran program affiliate terhadap minat beli pada platform e-commerce ialah metode kuantitafif dan para affiliasi harus memprioritaskan kualitas foto produk saat melakukan promosi.

Systemic Literature Review Peran Program Affiliate Marketing Terhadap Minat Beli Pada Platform E-Commerce Gaja, Rizqi Nusabbih Hidayatullah; Veri, Jhon
Jurnal Ilmiah Muqoddimah: Jurnal Ilmu Sosial, Politik dan Hummaniora Vol 8, No 2 (2024): Mei 2024
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jim.v8i2.2024.%p

Perkembangan teknologi dan internet telah mendorong transformasi besar dalam industri perdagangan, termasuk di Indonesia. Sejak beberapa tahun terakhir, e-commerce telah menjadi salah satu sektor paling dinamis dan berkembang pesat, memberikan peluang baru bagi para pelaku usaha untuk menjangkau pasar yang lebih luas dan meningkatkan penjualan. Affiliate marketing telah menjadi salah satu strategi pemasaran yang signifikan dalam industri e-commerce. Penelitian ini bertujuan untuk mengeksplorasi peran program affiliate marketing terhadap minat beli konsumen pada platform e-commerce melalui metode tinjauan literatur sistemik. Affiliate marketing, sebagai salah satu strategi pemasaran digital yang semakin populer, melibatkan pihak ketiga yang mempromosikan produk untuk mendapatkan komisi dari setiap transaksi yang dihasilkan. Tinjauan literatur ini mengumpulkan dan menganalisis 15 artikel yang telah dipublikasikan dan yang mengandung kata kunci program affiliate, minat beli di e-commerce, dan platform e-commerce yang terbit pada rentang tahun 2019 sampai 2024. Penelitian ini memberikan kontribusi signifikan terhadap literatur pemasaran digital dan menawarkan wawasan praktis bagi penjual dalam meningkatkan minat beli di e-commerce. Penelitian ini menemukan bahwa metode penelitian yang banyak digunakan untuk menganalisis data peran program affiliate terhadap minat beli pada platform e-commerce ialah metode kuantitafif dan para affiliasi harus memprioritaskan kualitas foto produk saat melakukan promosi.

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