Multi-Objective Design of Profit Volumes and Closeness Ratings Using MBHS Optimizing Based on the PrefixSpan Mining Approach (PSMA) for Product Layout in Supermarkets

Product layout significantly impacts consumer demand for purchases in supermarkets. Product shelf renovation is a crucial process that can increase supermarket efficiency. The development of a sequential pattern mining algorithm for investigating the correlation patterns of product layouts, solving the numerous problems of shelf design, and the development of an algorithm that considers in-store purchase and shelf profit data with the goal of improving supermarket efficiency, and consequently profitability, were the goals of this research. The authors of this research developed two types of algorithms to enhance efficiency and reach the goals. The first was a PrefixSpan algorithm, which was used to optimize sequential pattern mining, known as the PrefixSpan mining approach. The second was a new multi-objective design that considered the objective functions of profit volumes and closeness rating using the mutation-based harmony search (MBHS) optimization algorithm, which was used to evaluate the performance of the first algorithm based on the PrefixSpan algorithm. The experimental results demonstrated that the PrefixSpan algorithm can determine correlation rules more efficiently and accurately ascertain correlation rules better than any other algorithms used in the study. Additionally, the authors found that MBHS with a new multi-objective design can effectively find the product layout in supermarket solutions. Finally, the proposed product layout algorithm was found to lead to higher profit volumes and closeness ratings than traditional shelf layouts, as well as to be more efficient than other algorithms.

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>

Analysis of marketing strategy at setia stores using ahp, clustering, and ar-mba method

A company can survive and thrive when the strategies and processes applied in its business are correct. One of the processes in determining strategy in decision making. The owner of Setia Store has difficulty in choosing a marketing strategy. The product layout shows this in the Setia Store, which confuses customers. Setia Store also rarely offers a promotion, making it difficult to compete with competitors. This study aims to help Setia Store increase sales by determining the right marketing strategy. To determine the right marketing strategy, there are three methods developed. First of all, the analytical hierarchy process (AHP) is employed to find the customer priorities. Then, clustering is proposed to find potential marketing targets that have similar characteristics from the results of the AHP method. Third, association rule-market basket analysis (AR-MBA) is developed to find the best rules for product marketing strategy. The first method shows that the housewives (EV=0.6270) are Setia Store's priority customers from the three methods. Second, cluster 3 (which has three characteristics in common) is a very potential target market. Third, the best rule is to buy products from departments 2 and 3 (Confidence 60%, Support 12%). From these results, the right marketing strategy is to create a buy 1 get 1 promo banner or label for products that are rarely purchased, such as household appliances. Then, create a catalog by bringing together frequently purchased products such as spices and food ingredients. Finally, improve the layout by bringing the departmental shelves closer to frequently purchased products.

Prediksi Pola Tata Letak Produk untuk Strategi Penjualan Menggunakan Algoritma Apriori

Data mining is a term used to describe the discovery of knowledge in databases. Data mining is a process that uses statistical techniques, mathematics, artificial intelligence, and maching learning to extract and identify useful information and related knowledge from large databases. One of the data mining methods is the association rule by analyzing a sales transaction at the 212 mart latsitarda Kisaran store. Sales transaction analysis aims to design a sales strategy. To design an effective sales or marketing strategy. In addition, the use of this analytical technique can also find changing patterns of products that are often purchased together or products that tend to appear together in a transaction from transaction data which are generally large in size. Store 212 mart latsitarda Kisaran can then use this pattern to place frequently purchased products into a contiguous area. Designing product displays in catalogs, designing product package sales, and so on using data mining concepts (a priori algorithm approach) so that they can analyze buyer behavior. Keywords: Data Mining; Product Layout Pattern; Apriori Algorithm Abstrak: Data Mining adalah suatu istilah yang digunakan untuk memguraikan penemuan pengetahuan didalam database. Data Mining adalah proses yang menggunakan teknik statistik, matematika, kecerdasan buatan, dan maching learning untuk mengestraksi dan mengindentifikasi informasi yang bermanfaat dan pengetahuan yang terkait dari berbagai database besar. Salah satu metode data mining adalah aturan asosiasi dengan melakukan analisis suatu transaksi penjualan pada toko 212 mart latsitarda Kisaran. Analisis transaksi penjualan bertujuan untuk merancang strategi penjualan. Untuk merancang strategi penjualan atau pemasaran yang efektif. Selain itu, penggunaaan teknik analisis ini juga dapat menemukan pola berubah produk-produk yang sering dibeli bersamaan atau produk yang cenderung muncul bersaama dalam sebuah transaksi dari data transaksi yang pada umumnya berukuran besar. Toko 212 mart latsitarda Kisaran lalu dapat menggunakan pola ini untuk menempatkan produk yang sering dibeli kedalam sebuah area yang berdekatan. Merancang tampilan produk di katalok, merancang penjualan paket produk, dan sebagainya dengan menggunakan konsep data mining (pendekatan algoritma apriori) sehingga dapat menganalisis prilaku pembeli. Kata kunci: Data Mining; Pola Tata Letak Produk; Algoritma Apriori

Improving Efficiency of Apparel Manufacturing Through the Principles of Resource Management

To gain the competitive advantage, it has become essential for manufacturing industry to use its resources effectively, efficiently and economically. It is required to understand that such resources are based on 5 Ms (manpower, methods, materials, money, and machinery). In this study an apparel industry was selected to create a directorial plan by using the ideologies of resource management to improve the process efficiency. For this the data related to the product layout, operation plan, and process flow was collected. Time motion study was performed for aspect analysis. Information regarding operation, number of machines and efficiency of the production line was evaluated. The proposed plan successfully increase the efficiency up to 10%. It also shows an improvement in effective utilization of manpower and money.

SCANNING RITEL STORE USING THE BUSINESS MODEL CANVAS METHOD

The retail industry in Indonesia is currently experiencing unpredictable ups and downs. Many retail stores are closed and new ones keep popping up. Changes in the environment that keep happening make retail owners / management have to understand the changes themselves. For this reason, the business model must be determined in order to be able to compete with competitors. The purpose of this study is to determine the Wendys retail store business model using the (BMC) Business Model Canvas method. This research method uses descriptive analysis with the Business Model Canvas method using primary and secondary data. The customer segment of the Wendys retail store is local residents. Its value proposition is convenience of the shop building, product layout on the storefront, easy access, friendly service and product completeness. The main channels used are shop buildings and social media. Customer Relations is a delivery service for certain customers. Key activities are finding suppliers at low prices, purchasing products, processing products for sale (sorting, packaging), and keeping merchandise clean, well-maintained and resaleable. Main Resources owned are shop buildings, shop facilities and shop attendants. Its main partners are consumer goods suppliers and retail store communities. The cost structure includes operational costs which include product maintenance and maintenance, salaries, electricity, water. Non-operational costs depreciation of building value. The revenue stream is only from product sales.

Implementasi Data Mining Menggunakan Algoritma Apriori Untuk Analisis Keranjang Belanja Pada Transaksi Penjualan Pada PT Madu Kembang Joyo

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.

REDESAIN TATA LETAK PRODUK DI SUPERMARKET BERDASARKAN PERILAKU PEMBELIAN DENGAN METODE MARKET BASKET ANALYSIS

Lamanya pembeli swalayan mencari barang yang diperlukan mengurangi ketidaknyamanan. Jika jenis dan jumlah produk yang dicari cukup banyak dan letak produk - produk yang dibeli berjauhan, maka waktu di dalam ruang belanja akan semakin lama. Penelitian ini bertujuan untuk mensimulasikan penataan produk produk yang dijual di swalayan dengan mempertimbangkan perilaku konsumen yaitu kelompok produk yang dibeli berdasarkan data dari struk belanja. Metode yang digunakan adalah market basket analysis yang akan mengukur support factors dari kelompok produk dan menata produk yang harus didekatkan berdasarkan confident value. Hasil perhitungan Market Basket Analysis menemukan delapan pasang kelompok produk yang sebaiknya diletakkan berdekatan menurut nilai support factor. Kedekatan antar kelompok produk kemudian ditata menurut nilai confident value dan dilakukan validasi dengan mengukur nilai improvement rasio. Simulasi jarak yang harus ditempuh pengunjung setelah produk ditata sesuai dengan kelompok produk mendapatkan reduksi jarak 10 % dibanding penataan produk yang tidak mempertimbangkan kelompok produk. Abstract[Title: Redesign of Product Layout in Supermarket Based on Purchase Behavior used Market Basket Analysis Method] The length of time that self-service buyers search for the necessary item reduces inconvenience. If the types and quantities of product are large enough and the locations of the products are far apart, the shopping time will be longer. This study aims to simulate the arrangement of product sold in supermarkets by considering consumer behavior in purchased product groups based on data from shopping receipts. The method used is market basket analysis, which measures support factors from product groups and arranges that must be placed close together based on confident value. The calculation results of Market Basket Analysis found eight pairs of product groups that should be placed close together according to the high support factor value. The closeness between product groups is then arranged according to the confident value and validated by measuring the value of the improvement ratio. The simulation of the distance that visitors must travel after the product is arranged according to the product group has a 10% reduction in distance compared to the product arrangement that does not consider product groups.Keywords: product arrangement, supermarket, Market Basket Analysis