APLIKASI PREDIKSI RATING PENJUALAN MINUMAN BERBASIS WEBSITE MENGGUNAKAN METODE ASOSIASI FP-GROWTH

PURBA, TIGOR NOVANDA (2020) APLIKASI PREDIKSI RATING PENJUALAN MINUMAN BERBASIS WEBSITE MENGGUNAKAN METODE ASOSIASI FP-GROWTH. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

The culinary business is now increasingly developing and competition is increasing, so it requires a strategy to market the products to be sold. In the business sector, the results of the implementation of FP-Growth algorithm data mining can help business people find opportunities from consumption trends so that culinary business people can find out what types of products currently have the highest rating in the community so that managers can provide menu recommendations so they can increase sales turnover. The data required is a certain period of transaction data which is analyzed to produce product recommendations by the association rules. The design of this application uses HTML as the base system used in making websites, PHP as a means to develop websites, and SQL as a medium for data storage and processing. The testing process begins with the login process, then determines the support and confidence parameters, and determines the transaction time period. From the conclusion, managers can determine marketing strategies by increasing the stock of raw materials in beverage products that have the highest itemset value. Then the product with the lowest itemset value can provide promos or discounts on the purchase of goods to attract consumer buying interest. Key words: FP-Growth, Sales Prediction, Website Bisnis kuliner kini semakin berkembang dan persaingan semakin ketat, sehingga diperlukan strategi untuk memasarkan produk yang akan dijual. Di bidang bisnis, hasil penerapan algoritma data mining FP-Growth dapat membantu para pelaku bisnis menemukan peluang dari tren konsumsi sehingga para pelaku bisnis kuliner dapat mengetahui jenis produk apa saja yang saat ini memiliki rating tertinggi di masyarakat sehingga pengelola dapat memberikan rekomendasi menu sehingga dapat meningkatkan omset penjualan. Data yang dibutuhkan adalah data transaksi periode tertentu yang dianalisis untuk menghasilkan rekomendasi produk sesuai aturan asosiasi. Perancangan aplikasi ini menggunakan HTML sebagai sistem dasar yang digunakan dalam pembuatan website, PHP sebagai sarana pengembangan website, dan SQL sebagai media penyimpanan dan pengolahan data. Proses pengujian dimulai dengan proses login, kemudian menentukan parameter support dan confidence, serta menentukan jangka waktu transaksi. Dari kesimpulan tersebut, manajer dapat menentukan strategi pemasaran dengan meningkatkan stok bahan baku pada produk minuman yang memiliki nilai itemset tertinggi. Kemudian produk dengan nilai itemset paling rendah dapat memberikan promo atau diskon pembelian barang untuk menarik minat beli konsumen. Kata kunci: FP-Growth, Prediksi Penjualan, Website

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 22 188
NIM/NIDN Creators: 41516110157
Uncontrolled Keywords: FP-Growth, Prediksi Penjualan, Website
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 658 General Management/Manajemen Umum > 658.01-658.09 [Management of Enterprises of Specific Sizes, Scopes, Forms; Data Processing]/[Pengelolaan Usaha dengan Ukuran, Lingkup, Bentuk Tertentu; Pengolahan Data]
600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 658 General Management/Manajemen Umum > 658.01-658.09 [Management of Enterprises of Specific Sizes, Scopes, Forms; Data Processing]/[Pengelolaan Usaha dengan Ukuran, Lingkup, Bentuk Tertentu; Pengolahan Data] > 658.05 Data Processing Computer Applications/Pengolahan Data Aplikasi Komputer
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: ADELINA HASNA SETIAWATI
Date Deposited: 03 Mar 2023 08:32
Last Modified: 03 Mar 2023 08:32
URI: http://repository.mercubuana.ac.id/id/eprint/74657

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