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All Journal Jurnal Nasional Komputasi dan Teknologi Informasi
Nasib Ratna Sari Purba
STMIK Pelita Nusantara, Medan Indonesia
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Neuroscience Transportation

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Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Analisis Keranjang Belanja Pada Transaksi Penjualan Pada PT Madu Kembang Joyo Nasib Ratna Sari Purba; Fristi Riandari
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 4, No 1 (2021): Februari 2021
Publisher : Program Studi Teknik Informatika, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (419.205 KB) | DOI: 10.32672/jnkti.v4i1.2745

Abstract

In the sale of goods (products), companies often experience problems because of the irregular level of consumer spending. Determination of product layout is done to make it easier for consumers to find honey products so as not to disappoint consumers in finding the location of which products are suitable to be combined with other products that are often in demand by consumers, so that consumers can save time. Based on the problems faced by the company, data mining analysis tools are needed. Currently, the utilization of data that is owned is not fully maximized, it is limited to making reports. The problem of research is the accumulation of unused transaction data, the difficulty of placing products according to consumer needs. The absence of an effective product sales strategy. The application is built using the PHP programming language with the MySQL database. The data used for shopping cart analysis on the sales transaction of Joyo Flower Honey is 1 month transaction data. The combination of items with the highest support x confidence value will be used as a combination to determine the placement of the suitable item to be connected between the two products that consumers are most interested in. In addition, the combination of these items can be used by management to position the product on the shelf which will make it easier for consumers to find the product they need.
Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Analisis Keranjang Belanja Pada Transaksi Penjualan Pada PT Madu Kembang Joyo Nasib Ratna Sari Purba; Fristi Riandari
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 4, No 1 (2021): Februari 2021
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v4i1.2745

Abstract

In the sale of goods (products), companies often experience problems because of the irregular level of consumer spending. Determination of product layout is done to make it easier for consumers to find honey products so as not to disappoint consumers in finding the location of which products are suitable to be combined with other products that are often in demand by consumers, so that consumers can save time. Based on the problems faced by the company, data mining analysis tools are needed. Currently, the utilization of data that is owned is not fully maximized, it is limited to making reports. The problem of research is the accumulation of unused transaction data, the difficulty of placing products according to consumer needs. The absence of an effective product sales strategy. The application is built using the PHP programming language with the MySQL database. The data used for shopping cart analysis on the sales transaction of Joyo Flower Honey is 1 month transaction data. The combination of items with the highest support x confidence value will be used as a combination to determine the placement of the suitable item to be connected between the two products that consumers are most interested in. In addition, the combination of these items can be used by management to position the product on the shelf which will make it easier for consumers to find the product they need.
Co-Authors Fristi Riandari