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Business is an economic activity carried out by individuals or organizations to produce and sell goods or services with the aim of making a profit. The NSH Group Store is a business that sells carpets, pillows, bolsters, and dolls located in the Sei Dadap I/II Plantation, Sei Dadap District, Asahan Regency, North Sumatra 21225. The NSH Group Store was established in 2016 and is owned by Mrs. Siti Komariah Siregar. Among the challenges faced by the NSH Group Store owner are irregular stock procurement. Sales transaction processes still use conventional methods, reducing efficiency and time effectiveness, and potentially leading to data errors. Supply Chain Management is a series of approaches used to efficiently integrate suppliers so that goods can be distributed in the right quantities, locations, and at the right time, with the aim of minimizing overall system costs. A bolster pillow is a pillow that can function as both a pillow and a bolster. Bolster pillows are oval and long, so they can be hugged while sleeping. The benefits of a bolster pillow include maintaining a proper sleeping position, reducing pressure on joints, helping reduce aches, improving sleep quality, and improving overall health. Therefore, by implementing Supply Chain Management (SCM), data processing will be faster and more accurate.

Credit card fraud is a critical issue in digital financial transactions. This study aims to develop and evaluate fraud detection models using Logistic Regression and Gradient Boosting on an imbalanced dataset, where fraudulent transactions constitute only a small portion of the data. To address this imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied during preprocessing. Logistic Regression, used as a baseline model, achieved 95% accuracy, 78.6% precision, 55.9% recall, and a 65.3% F1-score. After applying class weighting and SMOTE, recall improved to 88.7%, but precision dropped to 52%, indicating that the model became overly sensitive and prone to false positives. Gradient Boosting initially produced better results, with 98% accuracy, 95.5% precision, 84.3% recall, and an 89.5% F1-score. After hyperparameter tuning and resampling, its performance improved further to 96.7% precision, 86.1% recall, and a 91.1% F1-score. These results indicate that Gradient Boosting is more effective in handling imbalanced data and offers greater reliability in detecting fraudulent transactions. The findings support the growing evidence in favor of ensemble learning techniques in fraud detection applications. This research contributes practical insights into improving the accuracy and security of machine learning-based fraud detection systems in financial services.

This research examines the application of the Elliptic Curve Digital Signature Algorithm (ECDSA) in a blockchain system as a security solution for digital payment systems in Indonesia. Using a descriptive-qualitative approach based on literature review and conceptual simulations using Python, this study discusses the working principles of ECDSA, its advantages over other digital signature algorithms, and the challenges of its adoption in Indonesia. The results show that ECDSA provides high cryptographic efficiency, maintains transaction authenticity and integrity, and supports a transparent decentralized system. The academic simulations include not only KYC processes, top-ups, transactions, validation by validators, and block recording, but also demonstrates the formation of an interconnected multi-level blockchain and tests scenarios for rejecting manipulated or invalid transactions. The contribution of this research lies not only in the theoretical review but also in the implementation illustrations that can be used as a basis for education and the initial development of blockchain-based digital payment systems. The research results show that ECDSA is capable of providing a high level of efficiency in the encryption and transaction verification process, maintaining data integrity and authenticity, and supporting a decentralized and transparent system. The academic simulations included the KYC process, wallet creation using ECDSA keys, balance top-ups through bank integration, transaction creation and validation, and block recording in the blockchain. Specifically, the simulations successfully demonstrated how new blocks are added to the chain by referencing the previous block's hash, as well as how transactions with corrupted signatures, manipulated amounts, or insufficient balances are automatically rejected by the validator consensus mechanism, maintaining system integrity. This research contributes not only theoretically, but also through conceptual representations that can be used as an educational foundation and for the initial development of blockchain-based digital payment systems in Indonesia.

CV KIA is a shop engaged in the field of computer sales and services, coming directly to make transactions and provide computer service information services. So there are obstacles that are quite time consuming and transportation costs for customers to find out information on goods, stock of goods, and the process of purchasing goods because customers have to come directly to the store. Product information on CV Kia cannot be updated in real time so that there is a delay in calculating stock of goods. The method used in this study is the prototype development method and is designed using UML. This system uses two programming languages, namely PHP. Implementation using the Xampp application, and MySQL. The results of this study are the design and creation of a web-based sales information system. The system that is built will also later facilitate the sales transaction process which can later reduce the level of competition with the outside market. This system displays information about product sales, and can carry out the sales transaction process so that customers do not need to come to the store to get information and make product purchases. The results of testing that has been carried out involving 10 Respondents that the conclusion of the quality of the feasibility of the software produced has a percentage of success with an average total of 100%.  Keywords: Sales, Prototype, PHP, Information Systems, Sublime Text

Selecting the right supplier is a critical aspect of supply chain management, especially in a retail business like Parfume Corner, which relies on product quality, availability, and on-time delivery. This study aims to implement the VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method as a multi-criteria decision-making approach to determine the best perfume supplier. The VIKOR method was chosen because of its ability to handle conflicts between criteria and produce optimal compromise solutions. The evaluation criteria used include product quality, price, on-time delivery, after-sales service, and flexibility in negotiations. Data were collected from five potential suppliers through observation, interviews, and historical transaction documents. The analysis results showed that one supplier obtained the lowest VIKOR index score, thus being determined as the best compromise solution. The implementation of the VIKOR method proved effective in providing objective and transparent recommendations, which can support Parfume Corner's strategic decisions in building long-term partnerships with reliable suppliers. This approach can also be adapted by similar businesses to improve procurement efficiency and quality. The test results obtained were that in the expert test a Good value was obtained, namely 80%, while in the system test a Very Good conclusion was obtained, namely 100%.

The bodywork industry in Indonesia is under high competitive pressure, requiring companies to be more adaptive in understanding customer behavior in order to maintain business continuity. PT. Bengawan Karya Sakti as one of the national bodywork companies, has not optimally utilized historical transaction data to assess customer loyalty. This study aims to identify customer loyalty segmentation through the application of the RFM (Recency, Frequency, Monetary) method, which is used to analyze sales transaction data in 2022 and 2023. The study uses the CRISP-DM approach which includes the stages of business understanding, data exploration, data cleaning and processing, modeling, evaluation, and implementation of results. The transaction data analyzed includes attributes of transaction date, customer, number of transactions, and transaction value, which are then processed into RFM scores based on the transaction year and classified into categories such as Very Loyal, Loyal, At Risk, and others. The segmentation results show an increase in the number of very loyal customers from 2022 to 2023, as well as a significant decrease in inactive and at-risk customers. The chi-square statistical test shows that the difference in customer distribution between years is statistically significant (p-value <0.05), indicating a real influence from the company's strategy or external factors. The main conclusion of this study is that the RFM method is effective in the bodywork industry to support data-based marketing decision making and more targeted customer retention strategies.

In today's fast growing demand of electronic transactions, with more people accessing the internet worldwide, online shopping becomes an increasingly profitable but risk, business. Selling online becomes a very competitive business and time is a critical factor in launching a web site for business. This paper studies the strategic planning process of an electronic business project and identifies how risks can be minimized by proper planning and how planning is implemented. It also describes how to detect any changes in the marketplace so that effective measures, can be made to avoid dropping out from competitor. The emphasis is on the planning tactics, particularly in ensuring accurate tracking that is specific to the e-business start up process.

Study for the effect of share trading days to the daily share returns in Stock Exchange has been carried out most invarious countries. Overseas studies produce consistent findings that the daily share returns results in negative impact on Monday (Monday Effect) and resulting inpositive impact on Friday (Week End Effect). Those effects are called as day of the week effect. The similar studies carried out Indonesia have not obtained consistent findings as similar as overseas including overseas studies make use of Ordinary Least Squares (OLS). Whereas this study does not utilize this approach, as most of the assumptions could not be fulfilled. Technical Approaches dealt with the share returns calculation dominantly affect to the amount of daily share return. These are due to the facts that the irrational factors also used by the investors to do the transactions. Consequently, the demand and supply of the share are also influenced by the behaviour of the investors them elves. Statistical approach used for examining the day effects is Autoregressive Moving Average (ARIMA) Approach. This approach is chosen as there is no hetero scedasticity or there is an existence of stationary data. To examine the difference of share trading day effects to the share returns this study utilizes Analysis of Variance (ANOVA), 244 daily aggregate share price indexes (IHSG) and LQ45 Indexes are used for this study. The findings of this study suggest that (1) all of the share trading days give a positive impact on the share returns, (2) daily aggregate share price indexes (IHSG) do significantly affect the share returns on Thursday and (3) LQ45 Indexes do significantly affect the share returns on Thursday and Friday. These findings imply that the investors should consider the day effects in deciding to be involved in share trading so that they could maximize their future returns.