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All Journal Al-MIKRAJ: Jurnal studi Islam dan Humaniora Arcitech: Journal of Computer Science and Artificial Intelligence
Apriana, Diwi
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Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Sistem Pendukung Keputusan Siswa SMKN 1 Kota Bengkulu dalam Menentukan Pemilihan Perguruan Tinggi Menggunakan Metode Simple Additive Weighting (SAW) Apriana, Diwi; Murlena, Murlena; Kaseri, Kaseri; Handayani, Nurfitri; Widyastuti, Rini
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 3 No. 1 (2023): June 2023
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v3i1.7862

Abstract

At this time education is very important, in addition to gaining knowledge, the level of education is usually very decisive in finding work and supporting skills, there are many third-grade high school or vocational high school students who find it very difficult to determine which college to choose, this is usually because of the lack of information about the university you want to go to, such as tuition fees, campus facilities, the distance of the campus from the city center, and most importantly, the accreditation of each campus itself. As is known at this time mainly private universities in the city of Bengkulu. Therefore, to solve this problem an appropriate decision support system method is needed to help students. The SAW method is used to determine the selection of tertiary institutions as a process model and the TAM model is used to see responses from respondents based on the influence of acceptance, usability and usefulness variables. From the results of the research conducted, the acceptance rate reached 10.2%, which means that the university selection system using the SAW method is acceptable.
Penerapan Data Mining Untuk Memprediksi Ketersediaan Stok Produk HNI HPAI Menggunakan Algoritma C4.5 Murlena, Murlena; Apriana, Diwi
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 2 No. 1 (2022): June 2022
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (406.098 KB) | DOI: 10.29240/arcitech.v2i1.5271

Abstract

In a company, the availability of this stock must be considered to avoid product losses caused by expiration and also to avoid order cancellations. The data contained in the HPAI company application, called the HSIS application, can be utilized and applied for data mining in determining which products are in demand in everyday life. This HSIS application can be used by the Business Center (BC) and all Stock Agents in the HPAI HNI business. To maintain the availability of product stock, the purpose of this study is to test the Stock Agent using the C4.5 Algorithm to predict that the availability of products that must be maintained is in accordance with customer needs. The use of the C4.5 algorithm on stock agents can overcome stockpiling and finance or stock agents capital can be used to buy stock that must be available. The results of the analysis using the C4.5 algorithm stated that although the price of the product was expensive, it was still selling well as herbal products. So of the three types of HPAI HNI products (Herbs product, Health food & beverage and Cosmetic & home care), the stock that must be increased or available is the Herbs Product.
Mengoptimalkan Penjualan Online Melalui Teknik Data Mining (Studi Kasus E-Commerce) Apriana, Diwi; Yuliansyah, Chandra
AL-MIKRAJ Jurnal Studi Islam dan Humaniora (E-ISSN 2745-4584) Vol 4 No 02 (2024): Al-Mikraj, Jurnal Studi Islam dan Humaniora
Publisher : Pascasarjana Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/almikraj.v4i02.4774

Abstract

The aim of this research is to optimize online sales through data mining techniques (e-commerce case study). This type of research is a literature review. Data collection with documentation. Data analysis with SLR. Research result. Research results The use of data mining techniques in optimizing online sales, especially in the context of e-commerce, can provide significant benefits for companies. By analyzing purchasing patterns and consumer behavior using data mining algorithms, companies can identify customer trends and preferences, improve promotional targeting, and optimize marketing strategies. This not only improves operational efficiency, but also results in a significant increase in sales. Thus, the integration of data mining techniques becomes a necessity for e-commerce companies that want to remain competitive and successful in an increasingly competitive market
Mengoptimalkan Penjualan Online Melalui Teknik Data Mining (Studi Kasus E-Commerce) Apriana, Diwi; Yuliansyah, Chandra
AL-MIKRAJ Jurnal Studi Islam dan Humaniora Vol. 4 No. 02 (2024): Al-Mikraj, Jurnal Studi Islam dan Humaniora
Publisher : Pascasarjana Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/almikraj.v4i02.4774

Abstract

The aim of this research is to optimize online sales through data mining techniques (e-commerce case study). This type of research is a literature review. Data collection with documentation. Data analysis with SLR. Research result. Research results The use of data mining techniques in optimizing online sales, especially in the context of e-commerce, can provide significant benefits for companies. By analyzing purchasing patterns and consumer behavior using data mining algorithms, companies can identify customer trends and preferences, improve promotional targeting, and optimize marketing strategies. This not only improves operational efficiency, but also results in a significant increase in sales. Thus, the integration of data mining techniques becomes a necessity for e-commerce companies that want to remain competitive and successful in an increasingly competitive market
Co-Authors Kaseri, Kaseri Murlena, Murlena Nurfitri Handayani, Nurfitri Rini Widyastuti Yuliansyah, Chandra