Analysis of Information Technology (IT) Goods Sales Patterns Using the FP-Growth Algorithm

Determination of sales patterns is very important in marketing. Sales pattern serves to conduct an effective analysis in improving marketing. Sales analysis aims to explore new knowledge that can help design effective strategies by utilizing sales transaction data. This study processes sales data for 12 transaction days containing 47 items using the Fp-Growth algorithm. The results of this study are items with a minimum value of support > 0.10 and confidence 0.60 and will be compared with testing data using RapidMiner to test whether the results are valid so that the test results can help in designing sales strategies.

Use of Branded Food Composition Databases for the Exploitation of Food Fortification Practices: A Case Study on Vitamin D in the Slovenian Food Supply

Vitamin D deficiency is a worldwide public health concern, which can be addressed with voluntary or mandatory food fortification. The aim of this study was to determine if branded food composition databases can be used to investigate voluntary fortification practices. A case study was conducted using two nationally representative cross-sectional datasets of branded foods in Slovenia, collected in 2017 and 2020, and yearly sales data. Using food labeling data we investigated prevalence of fortification and average vitamin D content, while nutrient profiling was used to investigate overall nutritional quality of the foods. In both datasets, the highest prevalence of vitamin D fortification was observed in meal replacements (78% in 2017; 100% in 2020) and in margarine, corresponding to high market share. Other food categories commonly fortified with vitamin D are breakfast cereals (5% in 2017; 6% in 2020), yogurts and their imitates (5% in 2017; 4% in 2020), and baby foods (18% in both years). The highest declared average content of vitamin D was observed in margarine and foods for specific dietary use (7–8 μg/100g), followed by breakfast cereals (4 μg/100g), while the average content in other foods was below 2 μg/100g. Only minor differences were observed between 2017 and 2020. Major food-category differences were also observed in comparison of the overall nutritional quality of the fortified foods; higher overall nutritional quality was only observed in fortified margarine. Our study showed that branded food composition databases are extremely useful resources for the investigation and monitoring of fortification practices, particularly if sales data can also be used. In the absence of mandatory or recommended fortification in Slovenia, very few manufacturers decide to add vitamin D, and even when this is the case, such products are commonly niche foods with lower market shares. We observed exceptions in imported foods, which can be subject to fortification policies introduced in other countries.

Rose-Patisserie and Coffee House

This case traces the life of a new endeavor, starting with a small patisserie and coffeehouse and the subsequent development of the business, considering three alternatives, namely optimizing the concept, expanding through a franchise network, and building a network of company-owned stores. The story of Rui and Joana raises a wide range of issues that managers need to address. After reading and working through the case, students will be able to evaluate the product portfolio, based on actual sales data, and to evaluate and propose strategic options using classical models.

Comparative Analysis of the Effects of False Low-Price Marketing Strategy on Multiple Platforms

In order to make full use of the characteristics of commodity prices, merchants on e-commerce platforms have adopted the low-price marketing strategy. Regular promotional discounts can bring new vitality to the commodity sales market, but extreme discount marketing methods would lead to serious impacts on the sales of competing products, thus affecting the stable development of the online shopping market. The sales data of four electrical products using the false low-price marketing strategy on three e-commerce platforms (Taobao, JD, and Amazon) were used in this study. The sales data from different e-commerce platforms and different time periods were analyzed, and one-way ANOVA was used on the factors affecting the effect of marketing strategy. The results showed that there is a significant difference between the direct marketing of high-priced products and low-priced products on Taobao; the difference between the marketing effects of high-priced products and mid-priced products on JD and Amazon is significant. This analysis would help businesses formulate reasonable marketing strategies and promote the stable development of the online shopping market.

Penerapan Asosiasi Algoritma Apriori Pada Data Penjualan Alat-Alat Listrik Dan Tekhnik

The incompatibility of information in reporting productsthat are sold, and data storage is very large, business people, especially in the sales business are required to find an appropriate strategy that can increase sales and marketing of products sold, one of which is by using electronic product sales data. Therefore, anapplication is needed that is able to sort and select data, so that information can be obtained that is useful for users, namely data mining. Associate patterns can be used to place products that are often purchased together into an area that is close together so as to facilitate the customer in finding the desired product and designing the appearance of products in the catalog. The method used is theApriori Algorithm method, with the help ofTanagra 1.4.50 tools and processing transaction data using Microsoft Excel 2007.

Sistem Informasi Persediaan Barang Dengan Metode Weight Moving Average Berbasis Android Di Toko Awd Mranggen

The AWD Mranggen store is a store that is engaged in the sale of bags, belts, shoes with sales developments increasing from year to year, with fairly tight business competition, the AWD Mranggen store must be able to calculate the estimated number of items to be purchased based on previous sales data, the prediction is very influential on the decision to determine the number of items to be provided by the AWD Mranggen Store for the next sales period data. Inventory of goods that are not right cause some losses in terms of time and also costs, it is necessary to have a forecasting system. Forecasting is a technique to identify a model that can be used to predict conditions in the future. By using the weight moving average method, it can be seen that the error value is more than smaller than other methods and the estimated results can be more precise so that it can help owners make decisions in carrying out inventory.

Sistem Pendukung Keputusan Pemilihan Sales Terbaik Menggunakan Metode Rank Order Centroid (ROC) dan Additive Ratio Assessment (ARAS) Berbasis Web

Setiap tahun, CV. Anugerah Wangi melakukan pemilihan sales terbaik untuk memotivasi para sales dalam memberikan pelayanan dan peningkatan penjualan sepeda motor. Proses pemilihan sales terbaik masih dilakukan secara manual dengan mengumpulkan data seluruh sales dalam 1 tahun. Pekerjaan ini tentu tidak efektif dan efisien. Selain itu, perhitungan yang dilakukan juga menjadi sulit karena mencakup banyak kriteria penilaian. Karena itulah perlu dibuat suatu sistem pendukung keputusan dalam pemilihan sales terbaik pada CV. Anugerah Wangi yang dapat memudahkan pimpinan untuk melakukan proses perhitungan. Sistem Pendukung Keputusan Pemilihan Sales Terbaik dibuat dengan menggunakan metode Rank Order Centroid (ROC) dan Additive Ratio Assessment (ARAS). Penggabungan metode ROC dan ARAS dapat mengoptimalkan terhadap pembobotan dalam setiap kriteria yang digunakan. Adapun kriteria yang digunakan dalam pemilihan sales terbaik yaitu, jumlah penjualan (C1), penilaian pelayanan (C2), jumlah penjualan (C3), masa bekerja (C4) dan kedisiplinan (C5). Dari penelitian ini, dilakukan uji coba terhadap 23 data sales yang kemudian dilakukan perhitungan sehingga mendapatkan hasil rangking teratas yang menjadi sales terbaik yaitu Faizur Rohman dengan nilai 0,916. Abstract Every year, CV. Anugerah Wangi selects the best sales to motivate sales in providing services and increasing motorcycle sales. The process of selecting the best sales is still done manually by collecting data on all sales in 1 year. This work is certainly not effective and efficient. In addition, the calculations made also become difficult because it includes many assessment criteria. That why it is necessary to make a decision support system in selecting the best sales for CV. Anugerah Wangi. So, it can make it easier for leaders to carry out the calculation process. The Best Sales Selection Decision Support System was made using the Rank Order Centroid (ROC) and Additive Ratio Assessment (ARAS) methods. The combination of ROC and ARAS methods can optimize the weighting in each of the criteria used. The criteria used in the selection of the best sales are the number of sales (C1), service assessment (C2), number of sales (C3), years of service (C4), and discipline (C5). From this study, a trial was carried out on 23 sales data which was then calculated so that the top-ranking results were the best sales, namely Faizur Rohman with a value of 0.916.

Negative Binomial Time Series Regression – Random Forest Ensemble in Intermittent Data

Intermittent dataset is a unique data that will be challenging to forecast. Because the data is containing a lot of zeros. The kind of intermittent data can be sales data and rainfall data. Because both sometimes no data recorded in a certain period. In this research, the model is created to overcome the problem. The approach that is used in this research is the ensemble method. Mostly the intermittent data comes from the Negative Binomial because the variance is over the mean. We use two datasets, which are rainfall and sales data. So, our approach is creating the base model from the time series regression with Negative Binomial based, and then we augmented the base model with a tree-based model which is random forest. Furthermore, we compare the result with the benchmark method which is The Croston method and Single Exponential Smoothing (SES). As the result, our approach can overcome the benchmark based on metric value by 1.79 and 7.18.