SISTEM REKOMENDASI BERBASIS WEBSITE UNTUK PENJUALAN BARANG PADA TOKO AQILA FLOWRES DENGAN MENGGUNAKAN METODE CONTENT BASED FILTERING DAN ALGORITMA APRIORI

SUDARWANTO, ARI (2022) SISTEM REKOMENDASI BERBASIS WEBSITE UNTUK PENJUALAN BARANG PADA TOKO AQILA FLOWRES DENGAN MENGGUNAKAN METODE CONTENT BASED FILTERING DAN ALGORITMA APRIORI. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

The increasing growth in information technology has boosted acceleration in various areas, and it has also led to advances in the sophistication of today's technology. The system for selling goods at the aqila flowres plant plant has continued to apply by hand, that is, to software like Microsoft excel, which often leads to a problem of data irregularities. Based on the above problem, it would take a process to build a system that would recommend and determine an appropriate product. Recommendations systems that utilize the methods of content based filtering and apricot algorithms. The content based filtering and aprimentary algorithms that aim for this recommendation system may conclude that the results will provide a recommendation item of products based on the sale of the products that the buyer is most interested in and make it easier for the seller to replenish the best seller's stock, found in the output data report. Key words : Recommendation System, Content Based Filtering (CBF), Apriori Algorithm, Plants. Semakin berkembangnya teknologi informasi yang pesat telah mendorong percepatan dari segi berbagai bidang, hal ini juga mengarah munculnya kemajuan pada kecanggihan teknologi diera saat ini. Sistem pendataan penjualan barang di toko tanaman Aqila Flowres masih menggunakan dengan metode manual, yakni mencatatnya ke dalam perangkat lunak seperti Microsoft Excel, dengan metode tersebut sering terjadi permasalahan berupa ketidakcocokan data. Berdasarkan dengan permasalahan yang tertera diatas, bahwa perlu proses untuk membangun sebuah sistem yang mampu merekomendasikan dan menentukan sebuah produk barang yang tepat. sistem rekomendasi dengan memanfaatkan pada metode Content Based Filtering dan Algoritma Apriori. Dengan adanya metode Content Based Filtering dan Algoritma Apriori yang bertujuan untuk sistem rekomendasi ini dapat disimpulkan bahwa hasil sistem tersebut dapat memberikan sebuah rekomendasi item produk barang berdasarkan hasil pencatatan data penjualan produk yang paling banyak diminati oleh pembeli dan mempermudah penjual menambah stok barang yang paling (best seller) kembali, terdapat pada hasil laporan data keluar Kata kunci : Sistem Rekomendasi, Content Based Filtering (CBF), Algoritma Apriori, Tanaman.

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 22 162
NIM/NIDN Creators: 41517120078
Uncontrolled Keywords: Sistem Rekomendasi, Content Based Filtering (CBF), Algoritma Apriori, Tanaman.
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 > 003 Systems/Sistem-sistem
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
500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: ADELINA HASNA SETIAWATI
Date Deposited: 07 Nov 2022 02:34
Last Modified: 07 Nov 2022 02:34
URI: http://repository.mercubuana.ac.id/id/eprint/71359

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