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This study aims to determine the effect of product availability, communication effectiveness, and promotional strategy on sales volume at PT.Distribusindo Cemerlang Jaya, a cosmetic and skincare distribution company in Batam city. The background of this research is based on pre-survey result indicating suboptimal sales volume along with operational challenges including stock shortages, communicatiob gaps, and limited promotional activities.ths research employs a quantitative method. The population consist of all comsumers, with a sample of 43 respondent selected using a saturated sampling technique. Data were collected through questionnaires using a likert scale and analyzed using validity and reliability test, classical assumption tests, multiple linear regression, t-test, F-test, and coefficient of determination (R²) with SPSS. Result show that partially, product availability does not significantly affect sales volume (sig. 0,313 > 0,05), and communication effectiveness also does not significantly affect sales volume (sig. 0,898 > 0,05). However, promotional strategy has a positive and significant effect  on sales volume (sig, 0,000 < 0,05). Simultaneously, all three variables significantly affect sales volume (F = 212.642, sig. 0,000 < 0,05). The coefficient of determination (R²) is 0,942 indicating that 94,2% of the variation in sales volume is explained by the three independent variables. Promotional strategy is the most dominant factor influencing sales volume is explained by the three independent variables. Promotional strategy is the most dominant factor influencing sales volume at PT.Distribusindo Cemerlang Jaya.  

This study aims to analyze the effect of production costs and sales volume on profit with firm size as a moderating variable in food and beverage sector companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2024 period. This study used a quantitative approach with an associative research design. The data used were secondary data obtained from annual financial statements of food and beverage companies listed on the IDX. The sampling technique used purposive sampling and obtained 110 observations. The analysis method employed was Moderated Regression Analysis (MRA) using IBM SPSS Statistics. The results of the study indicate that production costs do not have a significant effect on company profit. Meanwhile, sales volume has a positive and significant effect on profit. Firm size has a negative and significant effect on profit. Furthermore, firm size is unable to moderate the relationship between production costs and profit as well as the relationship between sales volume and profit. The coefficient of determination test shows that the independent and moderating variables are able to explain 56.8% of the variation in company profit, while the remaining 43.2% is explained by other variables outside the research model. This study implies that companies need to focus more on increasing sales volume and improving operational efficiency to enhance profitability.

SMEs play an important role in Indonesia's economy, one of which is the woodcraft industry that has great potential for export. Putra Mandiri Woodcraft (PMW) faces sales instability, ranging from 30% to 145.48% of the set target, which affects production efficiency. This study aims to formulate an effective marketing strategy to increase sales volume and business competitiveness. The methods used in this study include the IFE and EFE Matrix analysis to identify internal and external factors affecting the company, SWOT analysis to formulate various strategies, and QSPM to determine strategy priorities based on the Total Attractiveness Score (TAS) value. The analysis results show that Putra Mandiri Woodcraft has an IFE score of 2.70 and an EFE score of 2.80, indicating that the company's internal condition is quite strong, although the response to external factors is still moderate. The company's main strengths lie in product quality and consumer trust, while its weaknesses are the lack of innovation in product design. Based on the SWOT analysis results, eight potential strategies were found, and the QSPM shows that expansion through a marketplace based on product quality and more varied designs is the main priority with a TAS value of 6.16.

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the economy and community independence. However, the great potential of home-based businesses is often hindered by administrative issues related to business legality. This research focuses on UMKM Krecek Kulit Sapi Ashif in Jatirejo Village, which has been operating since 2018 but lacks a Business Identification Number (NIB), Household Industry Food (PIRT) permit, and halal certification due to perceived complex procedures. The main objective of this activity is to strengthen business management through product standardization and obtaining legal certifications to enhance the competitiveness of this MSME. The research method used a descriptive qualitative approach with a community service method based on mentoring, including observation, in-depth interviews, and hands-on practice in managing documents through the Online Single Submission system. The results show that through phased mentoring, UMKM Krecek Kulit Sapi Ashif successfully obtained an NIB and increased the owner’s awareness of PIRT food safety standards and halal certification procedures. The impact of this activity includes meeting administrative legality and improving knowledge, confidence, and professionalism in business management. Intensive mentoring proved crucial in transforming informal businesses into formal, legally protected entities.

This study aims to analyze the impact of the increase in Value Added Tax (VAT) and inflation on the sales revenue of PT Astra International Tbk during the 2022–2024 period. The research employs a quantitative approach using multiple regression analysis to examine the relationship between VAT, inflation, and sales revenue. Secondary data were obtained from the company’s financial statements, inflation data from Statistics Indonesia (BPS), and VAT rate information from the Directorate General of Taxes (DJP). The data were analyzed to identify how VAT and inflation influence the company’s revenue. The results indicate that both VAT and inflation have a significant effect on sales revenue, both simultaneously and partially. The coefficient of determination (R²) of 0.899 shows that 89.9% of the variation in sales revenue is explained by the changes in VAT and inflation rates. These findings suggest that VAT and inflation are important economic factors that should be considered by businesses, especially in the automotive industry, when planning strategies for revenue generation. Furthermore, the study emphasizes the critical need for companies to adapt to changing fiscal policies and macroeconomic conditions to maintain profitability and competitive advantage in a fluctuating economic environment.

The retail industry generates an extremely large and continuously growing volume of transactional data along with the advancement of digital technology, thereby requiring sophisticated and systematic data analysis approaches to support effective and evidence-based business decision-making. This study aims to analyze retail sales data by utilizing the Retail Sales Dataset obtained from the Kaggle platform, which consists of 100,000 transaction records and broadly represents the characteristics of retail transactions. The main focus of this study is to classify product categories and predict customer segments, including the identification of high-spending customers (high spenders), based on demographic attributes such as age and gender, as well as various transaction-related features. The research methodology includes data preprocessing, label encoding, and feature engineering to generate additional variables, including Age_Group, Is_Holiday, and Spender_Group, which are expected to enhance the predictive capability of the models. Several machine learning algorithms, namely Decision Tree, Random Forest, and XGBoost, were implemented and evaluated to compare their respective performance. The experimental results indicate that multiclass product category classification achieves relatively low accuracy, ranging from 27% to 34%. These findings suggest the high complexity of retail data and highlight the need for further model optimization, class balancing techniques, and feature refinement to improve predictive performance in future studies.

The rapid development of the sea transportation industry produces a massive and complex volume of transaction data, requiring strategic management to support managerial decision-making. This research aims to implement the Executive Information System on SeaPass in order to evaluate the performance of ship ticket sales. The research method uses data visualization with a two-level drill-down mechanism, which allows the presentation of information hierarchically from general summaries to specific details. The methodological stages include needs analysis, user interface (UI) design using Figma, front-end implementation with HTML, CSS, and JavaScript, database integration, and system testing through Black Box Testing. The results showed that the SIE implementation successfully integrated operational data, including schedules, ships, and manifests, into an interactive dashboard. The two-level drill-down feature provides the ability for executives to identify operational anomalies and market fluctuations in real-time. In conclusion, the system significantly enhances executive data analysis capabilities, transforming complex transaction data into accurate strategic information, thereby supporting more precise business decision-making and adaptive to the dynamics of the marine transportation market.