INPLEMENTASI BUSINESS INTELLIGENCE DAN MARKET BASKET ANALYSIS UNTUK ANALISA DATA PENJULAN DI PT. ABC

Ditengah merebaknya kasus pandemi Covid-19 pada tahun 2020 di Indonesia, terjadi perubahan kecenderungan perilaku pelanggan dalam melakukan proses transaksi belanja khususnya pada gerai minimarket. Dengan diberlakukannya pysical distancing, pelanggan dituntut untuk berbelanja seefektif mungkin untuk menghindari penumpukan di dalam gerai. Manajemen perusahaan harus membuat setrategi untuk menyikapi perubahan perilaku dari pelanggan. Pada penelitian ini dikembangkan Business Intelligence dan metode Market Basket Analysis yaitu Apriori untuk menganalisa perilaku pelanggan dengan cara menganalisa riwayat transaksi penjualan. Hasil penelitian menunjukkan dashboard Business Intelligence dapat menampilkan data dalam bentuk grafik dan tabel sehingga memudahkan pengguna dalam proses analisa. Selain itu Association Rule menggunakan metode Apriori menghasilkan nilai support dan confidence sebagai gambaran produk-produk yang saling terkait, sehingga pihak merchendaising dapat dengan mudah membuat keputusan. Hasil pengujian blackbox menunjukkan aplikasi yang dikembangkan dapat diterima oleh pengguna karena semua kebutuhan pengguna dapat diselesaikan oleh aplikasi.

Thoughts on Women Entrepreneurship: An Application of Market Basket Analysis with Google Trends Data

This paper focuses on the popularity and awareness of keywords in Google Trends data related to entrepreneurship of women in a global and cross-regional setting by using market basket analysis. Google Trends is one of the digital data platforms that provides a time series index of the volume of queries users enter into Google in a given geographic area. It is the most popular tool for gathering any information, and it has been used in several topics. Market basket analysis indicates items that appear/used together and the frequency of these appearances. Such technique is appropriate in finding hidden associations between items, which is also crucial in assessing individuals’ thoughts on a specific topic. This study contributes to the literature in terms of being the first study to use market basket analysis on Google trends data in the context of women’s entrepreneurship finding hidden associations between items, which is crucial in assessing individuals’ thoughts on a specific topic. The results of the analysis are interpreted through the lens of genderresponsive strategies, equality, efficiency and social justice in different country and region contexts.

MARKET BASKET ANALYSIS OF MEDICAL STORES DURING COVID19 TO DISCOVER NEW REVENUE PRODUCTS

COVID 19 pandemic has negatively affected almost all sectors of Indian economy,but few sectors like pharmaceuticals, have seen growth during this period. This has spurred sales of specific medicines and equipment in pharmacies. However,for better profit margin,pharmacies have to look beyond traditional medicines and equipment.This research helps in identifying uncommon items which can be sold along with medicines by pharmacies in Tiruvallur district for better profit margin.This is achieved through market basket analysis of transactions carried out in pharmacies.

PENERAPAN METODE MARKET BASKET ANALISIS DALAM PENENTUAN PEMASARAN IKAN KOI (STUDI KASUS: SUMBER KOI BLITAR)

Semakin berkembangnya teknologi internet, petani koi di Desa Sumber Blitar masih mempunyai suatu kendala dalam penjualan. Usaha koi “Sumber Koi” Blitar bergerak di bidang pembesaran bibit dan penjualan ikan koi. Penjualan sebelumnya dilakukan dengan cara membuka website sumber koi blitar di internet, instagram dan juga whatssap sehingga hanya customer tetap yang dapat mengakses. Petani di “Sumber Koi” membutuhkan suatu metode cepat untuk memperkirakan jumlah bibit, jenis bibit, dan rekapitulasi penjualan untuk mempermudah proses pemasaran ikan koi. Untuk mengatasi permasalahan ini digunakan metode (MBA) yang dapat menganalisis produk yang dibeli secara bersamaan, produk yang sering dibeli oleh pelanggan serta jumlah produk yang terbeli. Metode penelitian yang digunakan pada penelitian ini adalah metode prototype meliputi yang dimulai dari pengumpulan kebutuhan, membangun prototype, mengkodekan sistem, dan menguji sistem. Pada penelitian ini diperoleh hasil suatu aplikasi yang dapat digunakan untuk memperkirakan pemasaran ikan koi menggunakan metode Market Basket Analysis (MBA). Pengujian yang dilakukan meliputi, pengujian Black Box, pengujian ahli validator, serta pengujian pengguna. Dari pengujian Blacx Box diperoleh hasil keseluruhan fungsional aplikasi berfungsi dengan baik. Dari pengujian validasi yang dilakukan oleh 2 validator diperoleh porsentase kesesuaian hasil 77,5%. Hasil pengujian aplikasi oleh pengguna diperoleh porsentase kesesuaian hasil 89%

Market Basket Analysis for Determination of Consumer Behavior at XYZ Stores Using R Programming

Data mining is one of the fields of science in the world of informatics which has an important role, especially with regard to data. There are many algorithms and methods that can be used to process data. The paper this time the author tries to conduct research on consumer behavior by using one of the data mining techniques, namely market basket analysis. This research uses the R Programming tool, where it is hoped that the research can be carried out effectively and efficiently. Based on the research conducted, it is known that there has been a significant purchase of several items that have been described as a plot. The tendency of consumers to buy several items followed by other items can be a consideration for arranging the layout of goods on the sales shelf or arranging product stock in a supermarket.

A Seasonal and Multilevel Association Based Approach for Market Basket Analysis in Retail Supermarket

Market Basket Analysis is an observational data mining methodology to investigate the consumer buying behavior patterns in retail Supermarket. It analyzes customer baskets and explores the relationship among products that helps retailers to design store layouts, make various strategic plans and other merchandising decisions that have a big impact on retail marketing and sales. Frequent itemsets mining is the first step for market basket analysis. The association rules mining uncovers the relationship among products by looking what products the customers frequently purchase together. In retail marketing, the transactional database consists of many itemsets that are frequent only in a particular season however not taken into consideration as frequent in general. In some cases, association rules mining at lower data level with uniform support doesn't reflect any significant pattern however there is valuable information hiding behind it. To overcome those problems, we propose a methodology for mining seasonally frequent patterns and association rules with multilevel data environments. Our main contribution is to discover the hidden seasonal itemsets and extract the seasonal associations among products in additionally with the traditional strong regular rules in transactional database that shows the superiority for making season based merchandising decisions. The dataset has been generated from the transaction slips in large supermarket of Bangladesh that discover 442 more seasonal patterns as well as 1032 seasonal association rules in additionally with the regular rules for 0.1% minimum support and 50% minimum confidence.

Penerapan Algoritma Apriori Dengan Market Basket Analysis Untuk Pengaturan Tata Letak Barang

Penelitian ini bertujuan untuk membantu pihak toko untuk menganalisa barang apa saja yang sering dibeli dalam kurun waktu tertentu dan diletakkan saling berdekatan dan agar memperoleh proses penataan tata letak barang pada display area dengan mempertimbangkan pola pembelanjaan pelanggan untuk memudahkan dalam menemukan produk yang akan di beli secara bersamaan dengan menggunakan algoritma apriori. Data data yang yang terlibat dalam setiap transaksi penjualan pada sares Gallery sehingga terjadinya tumpukan data yang dibiarkan saja.untuk itu digunakanlah metode market basket analysis untuk menyelesaikan masalah yang dihadapi. Kemudian, sistem akan menjalankan proses penghitungan nilai dukungandari setiap kumpulan data transaksi yang ada dalam rentang waktu tersebut dan memilih sesuai dengan nilai dukungan minimum. Dalam menetapkan aturan asosiasi yang hendak ditunjuk, maka tentu harus mengurutkan terlebih dahulu berdasarkan support x confidence. Aturan tersebut akan diambil sebanyak n aturan yang mempunyai hasil terbesar. Maka, diambil kesimpulan tiga item yang sering dibeli bersamaan adalah Baju, sandal, dompet

Penerapan Association Rules - Market Basket Analysis untuk Mencari Frequent Itemset dengan Algoritma FP-Growth

<p><strong>In retail stores, product variations and prices are the main attraction. Products with many discounts are the most sought-after products. The promotion itself requires a special method for determining the discount. The layout in supermarkets is also something that retail stores need to pay attention to. One method that can be used to determine the product layout, promo for each product is Market Basket Analysis. The purpose of this research is to determine associative relation that occurs between items and to find out the solution to the problem of layout arrangement, catalog creation, and determination of shopping vouchers in Gading Mas Swalayan 1 based on the output of Rapid Miner software. Based on the output results obtained 7 associative relationships that have a lift ratio value &gt; 1 and it can be seen the determination of the layout of the item, catalog, and shopping voucher form. Layout changes are made for the comfort and convenience of consumers in taking the products they need and cataloging is determined by combining frequently purchased products with products that are rarely purchased. And the making of shopping vouchers is used to provide discounted prices where this is to reduce inventory and attract consumers.</strong></p><p><strong>Keywords – </strong><em>Market Basket Analysis, Rapid Miner, Retail, The relation of associative</em></p>