Analisis Keranjang Belanja Pada Transaksi Penjualan Menggunakan Algoritma Apriori

Sari, Retno; Hayuningtyas, Ratih Yulia

doi:10.31294/evolusi.v9i1.9999

Cited by 9 publications

(10 citation statements)

References 1 publication

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“…Dalam penelitian ini penulis melakukan studi pada 6 penelitian yang pernah dilakukan sebagai referensi, diantaranya adalah data mining yang digunakan untuk (1) Menyesuaikan produk yang akan dipaketkan berdasarkan informasi strategi penjualan bisnis ritel [4]. (2) Menyusun strategi dalam proses stok barang, analisis, retensi customer dan deteksi penipuan [5]. (3) Mengatur strategi pemasaran tiket oleh pihak pemilik travel dengan mengetahui jenis tiket yang sering di pesan oleh pembeli [6].…”

Section: Pendahuluanunclassified

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Implementasi Association Rule Dalam Menganalisis Data Penjualan Sheshop dengan Menggunakan Algoritma Apriori

2022

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Sheshop is a business activity engaged in the field of hamper making services. Since the last 2 (two) years, sales transactions in Sheshop have been increasing, the transaction data is only used as a report and is not used to regulate business strategies. The transaction data should be used to see the attachment of each type of product purchased by the customer simultaneously. The amount of sales transaction data on Sheshop can be used as an analysis of customer behavior in making purchases of hampers at Sheshop. This study performs data analysis by implementing the Apriori algorithm method because this algorithm handles data mining processes quickly on large amounts of data, from the results of this study Sheshop can make decisions on what items need more inventory compared to other items by looking at the value confidence and support by using the RapidMiner application. The results of this study indicate that the association rule formed from 568 Sheshop sales data uses a minimum support value of 10% and a minimum confidence of 50% produces 6 (six) association rules with a confidence value of 58% to 75% with all rules having a positive correlation level. Based on the 6 (six) association rules obtained, 2 products are often purchased at the same time, namely the Koran and tasbih with a confidence value of 75%.

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Section: Pendahuluanunclassified

“…(4) Pedoman dalam mengatur letak barang [7]. (5) Menemukan pola pembelian konsumen yang dapat membantu perusahaan untuk mendirikan cabang baru [8]. (6) Memantau stok barang serta menentukan persedian barang yang sering dibeli oleh customer [9].…”

Section: Pendahuluanunclassified

Implementasi Association Rule Dalam Menganalisis Data Penjualan Sheshop dengan Menggunakan Algoritma Apriori

2022

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“…Peran teknologi pada sektor bisnis adalah melakukan transasksi secara online yang dapat dilakukan kapanpun serta dimanapun atau biasa disebut dengan Ecommerce. Ecommerce merupakan sebuah wadah atau tempat yang digunakan oleh pembeli atau penjual untuk melakukan transasksi berbagai macam produk dengan menggunakan bantuan teknologi baik komputer, laptop ataupun handphone yang tidak perlu mempertemukan antara pembeli dan juga penjual [1], [2].…”

Section: Pendahuluanunclassified

Penerapan Algoritma Apriori Pada Analisa Data Penjualan Ecommerce

Badaruddin

Rayendra²

2022

mib

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Already all sectors are now using the role of this technology. The role of technology in the business sector is to carry out online transactions that can be done anytime and anywhere or commonly referred to as E-commerce. Now E-commerce has grown very rapidly, this is because there are many benefits that can be obtained from the use of E-commerce. But that does not mean that the use of e-commerce is not experiencing losses, the use of e-commerce that is not on target will also create losses for business people. Of course this is a problem that must be solved wisely by being able to read the pattern of goods requested by consumers or products that are not in demand by consumers. Where to find out the pattern can be seen from the e-commerce sales data that is already available. Data mining is a technique used to perform data processing. Data processing is carried out in data mining to obtain new information that can be implemented. A priori algorithm is a method used to find a pattern of relationships between one or more dataset items. In the results of the study, it was found that there are 3 items of E-commerce sales data that can be prioritized for sales. Where of the three items there are 3 combinations of items A1èA2 with a support value of 40% and a confidence value of 67%. A combination of items A1èA5 with a support value of 50% and a confidence value of 83%. Combination of items A2èA5 with a minimum support value of 40% and a confidence value of 50%

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“…Algoritma Apriori adalah algoritma yang paling terkenal untuk menentukan pola frekuensi tinggi. Pola frekuensi tinggi merupakan pola item-item didalam suatu database yang memiliki frekuensi atau support diatas ambang batas tertentu yang disebut istilah minimun support [1]- [5]. Pola frekuensi ini digunakan untuk menyusun aturan assosiatif dan juga beberapa teknik data mining lainnya.…”

Section: Pendahuluanunclassified

“…Algoritma ini banyak digunakan untuk jenis transaksi atau biasa disebut dengan istilah analisis keranjang belanja untuk mengetahui hubungan antara barang 1 dengan barang lainya. Algoritma Apriori dibagi menjadi beberapa tahap yang disebut iterasi atau pass [1], [5], [13]. Tiap iterasi menghasilkan pola frekuensi tinggi dengan panjang yang sama dimulai dari pass pertama yang menghasilkan pola frekuensi tinggi dengan panjang satu.…”

Section: Pendahuluanunclassified

Implementasi Algoritma Apriori Dalam Keterkaitan Data Pada Kelangkaan Minyak Goreng

Ulvah

Laswi²

2022

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The shortage of edible oil has caused the price of oil to be significantly higher than normal, which has led to higher oil prices even in certain regions where there are no edible oil inventories at all (empty warehouses). Due to the phenomenon of cooking oil shortages, many traders sell at high prices using correlation techniques, but they are not suitable. Given so many incidents where traders were selling cooking oil with related technology but not suited to consumers' needs, the authors became interested in analyzing the data connections by applying the a priori algorithm so that the goods paired with the cooking oil were not more useless and can be beneficial to buyers. Transaction data as a reference by a correlation by setting a cut-off value of 15% resulting from scanned transaction data, when buying cooking oil, often from 210 samples at the same time, and the samples taken have too good a number to be used as a correlation to become as they have a leverage value > 1.00 so that they can be used as a reference to arrange the cooking oil supply packaging along with other items.

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Analisis Keranjang Belanja Pada Transaksi Penjualan Menggunakan Algoritma Apriori

Cited by 9 publications

References 1 publication

Implementasi Association Rule Dalam Menganalisis Data Penjualan Sheshop dengan Menggunakan Algoritma Apriori

Implementasi Association Rule Dalam Menganalisis Data Penjualan Sheshop dengan Menggunakan Algoritma Apriori

Penerapan Algoritma Apriori Pada Analisa Data Penjualan Ecommerce

Implementasi Algoritma Apriori Dalam Keterkaitan Data Pada Kelangkaan Minyak Goreng

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