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This study applies a quantitative approach with a survey method as a data collection technique. Research data were obtained by distributing questionnaires to respondents who were the subjects of the study, namely small and medium enterprises (SMEs) engaged in shell craft in the coastal areas of Surabaya. The influence of digitalization and competitiveness on increasing income from digitalization was measured through the use of social media, e-commerce platforms, and the use of information technology in business activities. Meanwhile, the competitiveness variable was measured based on product quality, innovation, price, and marketing capabilities. Digitalization has a positive effect on increasing income for small and medium enterprises (SMEs) engaged in shell craft. The use of digital media has been proven to be able to expand the market and increase sales volume. In addition, competitiveness also affects income, where innovation is the main factor that drives increased sales value. Simultaneously, digitalization and competitiveness contribute significantly to increasing income for small and medium enterprises (SMEs). Support for related institutions and business actors in digital literacy, product innovation, and sustainable marketing strategies is needed to strengthen competitiveness and improve the welfare of coastal communities.

This study aims to analyze the implementation of digital marketing in Sharia cooperative retail business units to increase sales volume. Advances in information technology have driven changes in consumer behavior, leading to an increasing reliance on digital media for product information and transactions. This situation requires Sharia cooperatives to adapt through the implementation of effective digital marketing strategies. This study employed a qualitative method with a case study approach. Data were obtained through observation, in-depth interviews, and documentation. The research informants consisted of cooperative administrators, retail business unit managers, and consumers who interacted with the cooperative's digital marketing media. Data analysis techniques used the Miles and Huberman model, which includes data reduction, data presentation, and conclusion drawing. The results show that the implementation of digital marketing through social media, WhatsApp Business, and digital promotions can expand market reach, enhance interaction with consumers, and drive increased sales volume. However, obstacles remain, including limited human resources and consistency in digital content management. Therefore, improving the digital competency of cooperative managers is necessary to optimize digital marketing strategies.

The results of the study show that pricing strategy contributes dominantly to increasing sales, but the lack of digital promotion causes limited market reach. Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in driving national economic development and providing employment. However, in facing an increasingly competitive market, MSMEs need to implement efficient marketing strategies to ensure sustainability and sustainable growth. This community service activity aims to provide knowledge and assistance to Indonesian Es Teh MSMEs regarding the implementation of flexible marketing strategies, both through digital and traditional channels. The activity took place at the Es Teh Kampung Solo outlet in Kramatwatu Square. The methods used included counseling, training, and assessment of marketing strategy implementation, with a primary focus on optimizing social media as an interactive and competitive digital promotional tool. The results of this activity demonstrated a significant increase in MSMEs' understanding of strategic marketing planning, promotional innovation, and the use of digital platforms to expand market reach. Thus, it is hoped that digital-based marketing strategies can strengthen the competitiveness and sustainability of MSMEs. This activity is expected to contribute to increasing the competitiveness and sales volume of the Kampung Solo Es Teh MSME in a sustainable manner through the implementation of a modern marketing approach that is responsive to technological changes.

Amid intense market competition, the profitability of manufacturing companies is not solely determined by sales volume but is highly dependent on the precision of financial management, particularly in managing the working capital cycle and operating cash flow circulation. This study aims to evaluate the relationship between Working Capital Turnover (X1) and Operating Cash Flow (X2) on Profitability (Y) in consumer goods industry companies listed on the Indonesia Stock Exchange during the 2022–2024 period. Using a quantitative approach and multiple linear regression analysis, this study processes 77 observations that have passed purposive sampling and outlier testing. The partial test results reveal contrasting findings: Working Capital Turnover (X1) does not have a significant effect on profitability, while Operating Cash Flow (X2) is proven to be a strong positive determinant. However, simultaneously, both variables have a significant influence on the financial performance of companies (Fhitung 24,008 > Ftabel 3,08), with operating cash flow acting as the dominant driving factor of profit. The implications of these findings emphasize that to maintain profit stability, management should prioritize the availability of cash generated from core operations, while investors should be more attentive to cash flow trends as an indicator of fundamental financial health before making investment decisions.

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 implementation of digital marketing in increasing sales of small and medium enterprises (SMEs) in the bedding equipment sector on online platforms. The background of this research is driven by the high level of competition in marketplaces and the need for business actors to optimize digital marketing strategies to remain competitive. The research method used is Participatory Action Research (PAR), combined with SWOT analysis to identify business conditions comprehensively. Data collection techniques were carried out through direct observation of production and marketing activities. The results show that the implementation of digital marketing through marketplaces and social commerce can expand market reach, increase sales volume, and enhance the business actor’s understanding of managing online marketing strategies. In addition, product content optimization, the use of promotional features, and customer service play an important role in increasing consumer trust and purchase decisions. However, challenges such as high advertising costs and frequent changes in platform policies were also identified. Overall, this study concludes that well-planned and efficient digital marketing strategies can improve competitiveness, profitability, and business sustainability of SMEs in the digital era.

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.

The purpose of this study is to analyze and evaluate the effectiveness of digital marketing strategies implemented by Micro, Small, and Medium Enterprises (MSMEs), particularly those engaged in the culinary sector, within the Pasar Raya MMTC (Medan Metropolitan Trade Center) area in facing digital era competition. The research method employed is descriptive qualitative with a case study approach. Data collection involved in-depth interviews with MSME owners, observation of digital promotional activities (Social Media and Marketplaces), and content analysis. The results indicate that the most effective and commonly used digital strategies include: (1) Marketplace Optimization (focusing on discount and flash sale features), (2) Social Media Marketing Utilization (Instagram and TikTok for visual/video content), and (3) Collaboration with Local Micro-Influencers or food vloggers. The effectiveness of these strategies is measured by the increase in sales volume (an average of 20-30% after digital adoption) and improved brand visibility. The main obstacles encountered by MMTC MSMEs are the lack of consistency in content creation, limited funds for paid advertising, and insufficient understanding of digital data analytics. This study concludes that digital adaptation is essential, but it must be supported by improving digital literacy and providing targeted assistance focused on analyzing the return on investment (ROI) of digital marketing activities for sustainable growth.

This study aims to analyze the impact of inflation on the profitability of Micro, Small, and Medium Enterprises (MSMEs) operating in traditional markets. Inflation influences key business aspects, including rising production costs, declining consumer purchasing power, and instability in input prices, all of which can disrupt business performance. The research employed a quantitative approach using survey data collected from MSME actors to assess these effects. The findings reveal that inflation has a significant negative impact on MSME profitability, particularly through the reduction of profit margins. This occurs as businesses face higher raw material costs while simultaneously experiencing a decline in sales volume due to weakened consumer demand. As a result, many MSMEs struggle to maintain financial stability and sustain their operations under inflationary pressure. These findings highlight the need for adaptive strategies among MSMEs, such as cost efficiency and pricing adjustments. Additionally, the study offers important policy implications for the government to support MSMEs through targeted interventions, including price stabilization measures and financial assistance programs, in order to maintain business resilience and economic sustainability.

The rapid acceleration of the digital economy has positioned Micro, Small, and Medium Enterprises (SMEs) at a strategic crossroads. This study investigates the impact of digital marketing and social media marketing on the performance of SMEs in Binjai, North Sumatra, while exploring the mediating role of Electronic Word of Mouth (e-WOM). Utilizing a quantitative approach with a sample of 182 SME owners, data were analyzed using multiple linear regression and path analysis via SPSS 26. The findings demonstrate that digital marketing and social media marketing initiatives significantly and positively influence business performance, accounting for 54.2% of the variance. Notably, social media marketing emerged as the most dominant predictor, fostering high levels of customer engagement. Furthermore, path analysis reveals that e-WOM serves as a critical mediator; effective social media strategies stimulate authentic digital testimonials, which subsequently enhance consumer trust and sales volume. This research concludes that for SMEs in emerging local markets like Binjai, the orchestration of digital reputation through e-WOM is fundamental to achieving sustainable competitive advantage in an increasingly volatile digital landscape.

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.

This research aims to evaluate the effectiveness of Online Travel Agent (OTA) distribution channels in influencing room sales volume and net profit for hotels in Java. Although OTAs have become a primary distribution choice that successfully boosts sales figures, there is still a lack of research highlighting the impact on net profitability due to high commission costs.Using a quantitative associative method through panel data regression analysis, this study examines the causal relationship between the proportion of sales made via OTAs and two performance indicators over a two-year period (2021–2023). The primary findings reveal a dual effect:OTA Distribution Channels have a positive and significant influence on Room Sales Volume (supporting Hypothesis H1).Conversely, OTAs have a significant negative impact on Hotel Profit Margins (supporting Hypothesis H2), indicating a substantial financial trade-off.The contribution of this research is to provide balanced empirical evidence regarding volume gains versus margin losses resulting from OTA usage. The managerial implications suggested by these findings are that hotels need to implement distribution strategies focused on Net Revenue Management and channel mix optimization to achieve a balance between volume requirements and profitability.

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 State Logistics Agency (Bulog) plays a strategic role in maintaining national food security by stabilizing the prices and availability of staple food commodities. Amidst increasingly fierce market competition and changing consumer behavior, the Maumere branch of Bulog faces challenges in increasing commercial commodity sales without neglecting its public function. This study aims to analyze the marketing strategy implemented by Bulog Maumere to increase food commodity sales, as well as identify obstacles and improvement efforts. Using a descriptive qualitative approach through observation, interviews, and documentation, the findings indicate that Bulog Maumere's marketing strategy integrates the 4Ps of the marketing mix—product, price, place, and promotion—through expanded distribution channels (RPK, traditional markets, government agencies), market operations (SPHP, the Affordable Food Movement), and collaboration with local partners. This strategy is effective in increasing sales volume and accelerating stock turnover, although it remains hampered by reliance on government assignments, lengthy bureaucratic procedures, and distribution delays. Key recommendations include strengthening commercial sales, optimizing digital marketing, and improving operational efficiency. The results of this study provide a practical contribution to the development of marketing strategies for public food institutions in the archipelago.

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.

This community service initiative provides a comprehensive business analysis to evaluate financial feasibility, aiming to mitigate potential losses and ensure operational viability. By offering concrete data on business prospects and challenges, this analysis serves as a strategic guide for resource allocation and market targeting, while simultaneously enhancing attractiveness to potential investors. The program was conducted in the South Nunukan District, Nunukan Regency, North Kalimantan. As Indonesia's 34th province and a strategic border region, North Kalimantan faces significant challenges in food security due to limited supply chains. A central component of this study is the Break-Even Point (BEP) analysis—the threshold at which a business incurs neither profit nor loss. The BEP analysis provides critical insights into the relationship between pricing, operational costs, sales volume, and production levels. Consequently, it serves as a vital decision-making tool for business owners to optimize profitability. The results of this study demonstrate that, despite the continued use of traditional methods, the polyculture system remains highly profitable and sustainable for the local community.

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.

This study aims to analyze the preparation and role of a comprehensive budget in supporting the financial feasibility and business sustainability of the character coffee. The method used is budgetary analysis, which includes sales budgets, production budgets, raw material budgets, labor budgets, factory overhead costs, cash budgets, budgeted income statements, and Break Even Point (BEP) analysis. The results show that systematic budget planning helps business owners plan, control, and evaluate operational activities effectively. Sales projections indicate considerable market potential, with target consumers consisting of students, office workers, and the general public, enabling the business to generate sufficient revenue to cover operational costs and earn profits. Cash flow projections are also positive, reflecting the company’s ability to maintain liquidity. BEP analysis shows that the break-even point can be achieved at a realistic sales volume, indicating a relatively low risk of loss. Nevertheless, the business faces risks such as intense competition, fluctuations in raw material prices, and changes in consumer preferences. Therefore, regular budget evaluations, continuous product and service innovation, and disciplined financial management are essential. Overall, the findings indicate that character coffee is financially feasible and has promising prospects for sustainable growth if managed professionally.

This study aims to classify customer payment methods at 17 Coffee & Eatery using machine learning algorithms, namely Naïve Bayes and Support Vector Machine (SVM). The increasing use of digital and non-cash payments has generated large volumes of transaction data that are rarely analyzed optimally, even though such data contain valuable information for business decision making. This research used secondary transaction data collected from January to March 2025, consisting of 10,147 transaction records. The dataset included several attributes such as order time, payment time, transaction type, total sales, number of items, and payment method. Data preprocessing was performed through data cleaning, feature engineering, normalization, and label encoding before being divided into training and testing sets with an 80:20 ratio. The Naïve Bayes and SVM models were then trained and evaluated using accuracy, precision, recall, F1-score, and ROC–AUC metrics. The results show that both algorithms were able to classify payment methods effectively, but SVM achieved higher accuracy and more stable performance than Naïve Bayes. These findings indicate that SVM is more suitable for handling complex and heterogeneous transaction patterns. The implementation of machine learning for transaction classification can support more efficient financial management and data-driven decision making for small and medium enterprises in the culinary sector.

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.