Inventory Production Research Articles

Don't waste that free lettuce! Impact of BOGOF promotions on retail profit and food waste

Buy‐one‐get‐one‐free (BOGOF), a ubiquitous sales promotion scheme by which consumers get two items for the price of one, encourages consumers to buy and waste food. An alternative promotional scheme is one where consumers receive a coupon for a second item available for free at a later time. Our work is motivated by British supermarkets which, facing criticism from lawmakers for running BOGOF promotions on perishables, started a “BOGOF Later” campaign with the claim that it would reduce the amount of waste. Food waste is indeed a very pressing issue, which has not yet been explored in connection to sales promotions. We compare the impact of these promotion schemes on a retailer's profit as well as on the amount of product wasted at the retail and household levels. We consider two possible applications: unexpected high inventory of a fresh product with a short shelflife and excess leftover inventory for an item at the end of its season or product life. We propose a two‐period newsvendor model which captures the sales‐boosting effect of promotions, the postpromotion sales drop due to satiation, the coupon‐redemption behavior, and the increased consumer wastage rate from BOGOF promotions. We obtain analytical comparisons of order quantity, profit, and waste across the different promotion schemes and use numerical experiments to generate further insights. We find that, in general, BOGOF promotions are profitable ways to liquidate inventory. In many instances, the increase in waste at the consumers' homes is offset by the decrease in waste at the retail store. As a result, BOGOF promotions often constitute “win‐win propositions” by simultaneously increasing the retailer's profit and decreasing total waste. Overall, our results paint a more favorable picture of the BOGOF promotion scheme than commonly perceived and suggest that its environmental criticism emanates from a too narrow and too consumer‐centric view of the waste problem.

Insight into quantities, flows, and recycling technology of E-waste in China for resource sustainable society

The difficulty of tracking the metabolism of e-waste throughout its life cycle caused by scattered distribution has long constrained the development of the recycling industry and further policy making. In this study, the monitoring of Chinese e-waste, including sources, flows, scrap, and recycling potentials of electronic products, was measured and predicted based on data from both the government and 109 formal e-waste recycling enterprises. From 2009 to 2030, the inventory of electronic products is expected to increase due to overcapacity and near saturation of household possession. Meanwhile, the total amount of e-waste scrapping is predicted to increase from 1.77 million tons to 18.86 million tons, and the amount of generated e-waste will also increase, reaching 240 million tons by 2030. Currently, e-waste recycling is gradually becoming the official waste disposal approach. However, this newly emerged industry has numerous problems, such as lower recycling efficiency and scale, lack of advanced technologies, and corresponding laws and regulations. Hence, the data collected and analyzed in this study shed light on the e-waste market size in China. Meanwhile, to establish an ideal resource-sustainable society, suggestions regarding the optimization of the e-waste recycling industry through legal, reasonable, and efficient methods are put forward from our point of view.

Estimation of biases and uncertainties on PWR nuclide inventories for severe accidents analyses

The work presented in this paper deals with bias and uncertainty quantification on nuclear fuel inventory in a pressurized water reactors core during normal operation. This actinides and fission products inventory is used as input data for radiological releases evaluation in case of a severe accident. The different sources of bias and uncertainty, as well as their impacts for UO2 and MOX fuel at the assembly and core levels, are discussed. Uncertainty sources include technological uncertainties (e.g. dimensions, irradiation history, temperatures), modeling assumptions, uncertainties related to the resolution methods used in the calculation tools and nuclear data uncertainties. For each source of uncertainty investigated in this paper, an evaluation of the associated biases and uncertainties on nuclide inventory is performed. It is shown that, among the sources of bias and uncertainties studied, spread due to nuclear data as well as the bias and uncertainties due to “infinite lattice approximation” are the most significant ones, for the isotopes of interest.

ANALISIS PERENCANAAN DAN PENGENDALIAN PRODUKSI INJECTION PART NEW MODEL PAJERO SPORT 20 MY DI PT. SHIN SAM PLUS INDUSTRY KARAWANG

The purpose of this study is to analyze how planning, controlling and project recommendations for making injection components for the New Model Pajero Sport 20 MY car at PT. Shin Sam Plus Industry in fulfilling customer demand Using a qualitative approach, data collection techniques through interviews and observations, compiling research instruments and conducting analysis and checking the validity of the data, the object of research is in the Division of Production Planning and Inventory Control (PPIC) Sukaluyu, Telukjambe Timur, Kabupaten Karawang. The results of the research on project planning for the manufacture of injection components for the New Model Pajero Sport 20 MY car at PT. Shin Sam Plus Industry, in fulfilling customer requests, performs machine check sheets, for example 5 (five) minutes before starting the process is checked so that when production hours are running well there are no obstacles whatsoever that impact Stop production. Checking the raw materials, the plan has been distributed H-1 or according to company policy, all according to the plan that has been set, if there is a revision, it is not immediately revised. Control is carried out indirectly, meaning that the capacity is insufficient and a back up plan is needed, namely by subcontracting the product to the vendor and the need for a feasibility study with an audit so that it can meet the requirements requested by the customer. Control based on certain conditions is by means of the need for a contingency plan in all aspects so as to meet customer demand when there are internal or external abnormal conditions. PPC also monitors the materials required for production. Convey as detailed information as possible from internal and customers. Analyze the data obtained. Display data and discuss and then monitor production forecasts that have been made. Taken from the forest data sent by the customer and calculated for the Reject Ratio, Monitor consumption consumption, production and standard consumption data from engineering. Proposals related to solutions for fulfilling customer requests that can be provided to Management, so as to increase company profits, Request to the Dept. Engineering to be able to review consumption standards at least once a month to avoid differences in consumption usage. Then the addition of equipment/tools used by the process (such as packaging, jigs, trolly, etc.), agenda for routine review between departments. POs received from customers must enter the maximum AKR at the end of the month or on the 20-25th to carry out cost calculations and update production capacity, recommendations for employees of PT. Shin Sam Plus Industries. In order to be more intentional about checking raw materials, this is done to ensure that production does not stop due to waiting for material or not available so that productivity is constrained.

Implementation Of Data Mining Sales Of Household Furniture At Smart Kitchen Shop Using The Method K-Means

Household furniture is an item that is very much in demand by many people, especially mothers, the higher the number, the more demand. To get the desired information so that a store can sort out the inventory that must be met. So it takes a prediction for the sale of furniture products that are most requested by consumers which aims to facilitate the provision of stock goods. The purpose of this research is to apply data mining to determine what products or goods are most in demand, moderately desirable, less desirable. From the various data that the authors observe at the Smart Kitchen Store, namely the Smart Kitchen Store, it is still difficult to predict product inventory in the future. With this problem, we need to group the data based on the characteristics of product sales. In the grouping process, a grouping method will be used using the K-Means Algorithm as a manual calculation method and in its implementation a data mining software using RapidMiner Studio version 7.1 will be used.The results of the study consisted of 3 clusters, namely, 42 Most Interested Products (Double Stan Hangers, Napkins, and Stainless Dish Racks), 46 Moderately Interested Products (Super Mop Floor Mops, Surpets, and Electric Grater) and 32 Less Interested Products (Shower Hood 4 stacking, Ring Light, and stainless hood). at the Smart Kitchen Store, so that the data is used as a reference for the Smart Kitchen Store to manage the stock of goods so that the store does not disappoint customers because the goods or products you want to buy are not available.

Pengurangan Bullwhip Effect pada Rantai Pasok Air Minum Dalam Kemasan Menggunakan Metode Collaborative Planning, Forecasting, and Replenishment (CPFR): Studi Kasus

CV Tirta Alam Dodu is a privately owned company engaged in the beverage industry in the form of AMDK. The problem faced by the company is that there is a difference between demand and sales, or better known as the bullwhip effect problem. The purpose of this study is to reduce the bullwhip effect on the supply chain and optimize the amount of product inventory according to the amount of demand. The method used is the Collaborative Planning, Forecasting, and Replenishment (CPFR) method. Based on the results of the research conducted, it can be concluded that the analysis of demand forecasting calculations on AMDK products at CV Tirta Alam Dodu was carried out using historical data on product demand through five analytical methods, including Linear Trend, Moving Average, Exponential Smoothing, Decomposition, and Winter's Model. The best forecasting resulted in Winter's Model which showed the smallest error value compared to the other four models. The way to minimize so that it does not become a bullwhip effect is to use the CPFR method, where the bullwhip effect value is obtained on glass mineral water products and gallons of mineral water of 0,985 and 0,898, respectively. This result shows that there is no amplification of demand and has reached the company's target, which is to fall below number one. The way to optimize inventory so that there is no excess stock or shortage of stock in the product is to make the amount of inventory based on the amount of demand from the forecasting results plus the safety stock.

ВИРОБНИЧІ ЗАПАСИ: ЇХ ЕКОНОМІЧНА ПРИРОДА ТА РОЛЬ В ГОСПОДАРСЬКІЙ ДІЯЛЬНОСТІ ПІДПРИЄМСТВА

Production stocks are an integral part of the production process, and their sufficient quantity and effective use have a significant impact on the economic security of the enterprise. The inventory management system is inextricably linked with the accounting system. Accounting information is the basis for making strategic management decisions. And the possibility of using credentials is ensured by the qualitative properties of the information itself. The article analyzes dissertation works in which “inventories” were studied as an economic and accounting category. The research of the category “inventories” was carried out according to the directions: inventories (in general), production inventories, merchandise inventories, material inventories. It was established that the most popular area of research was production stocks, which were considered taking into account the sectoral characteristics of enterprises. In order to highlight the features that reveal the economic nature of production stocks, the interpretation and approaches to understanding their essence have been studied. Signs that identify stocks as production are: 1) used in production business processes; 2) transfer their cost to the manufactured product; 3) lose (or change) their shape during the production process; 4) are consumed completely during one operating cycle. An important role in scientific knowledge belongs to classification, which makes it possible to detail objects, to highlight connections between them. The article summarizes the views of Ukrainian scientists on the construction of the classification of production stocks. The expediency of their use in the accounting practice of enterprises has been determined. An alternative approach to the grouping of production stocks in the accounting system is proposed, with the allocation of classification features: by sources of income; for the purpose of use in economic activity; according to the evaluation method; according to ways of disposal. The classification is accounting, built through the prism of operations that take place with production stocks in the economic activity of the enterprise. The purpose of the classification is the reliable assessment of production stocks at the stages of their movement, the completeness of the display of operations in the enterprise’s accounting system.

Impact of Carbon Emission Policies on a Production Inventory Model with Stock and Demand Dependent Production Rate and Preservation Technology Related Deterioration

Impact of Carbon Emission Policies on a Production Inventory Model with Stock and Demand Dependent Production Rate and Preservation Technology Related Deterioration

A Marketing-Oriented Production Inventory Model under Hybrid Carbon Policy with Carbon Emission Origin-Based Green Investments

A Marketing-Oriented Production Inventory Model under Hybrid Carbon Policy with Carbon Emission Origin-Based Green Investments

Sales Forecasting System for Van-Sales Channel for FMCG Industry

In the Fast Moving Consumer Goods (FMCG) sector, the availability of sufficient product inventory on the delivery vehicle is directly related to the accuracy of the sales forecasts. Insufficient accuracy of the estimations leads to loss of income and increases secondary costs such as transportation and labor costs. In the current situation, sales forecasts are based on the sales personnel's delivery route, knowledge, experience, and relationships. Since the knowledge and experience of the personnel are not brought into the institutional memory, this information is lost with the personnel change, and the new person needs to develop their own experiences about the route. Currently, the sales forecasting accuracy rate is calculated as 70%. It has been determined that a daily loss of 15% on a product basis and a total of 5% daily occurs. In the study carried out within the scope of this research, advanced analytical and machine learning methods that can capture the dynamics of the FMCG industry and analyze the extensive data formed effectively are studied to increase the accuracy and consistency of sales forecasts. Within the scope of the research, machine learning models to be used for sales forecasts were developed using artificial neural networks methods. We evaluated the models' performance according to the recall, precision, and accuracy metrics based on the route, point of sale, and product. It was determined that the artificial neural networks performs well for sales forecasting. Using the artificial neural networks in the experimental study, we achieved an average of 5% revenue increase for the three route groups selected as pilots. The sales forecast accuracy rate increased from 78% to 82%.

Fuzzy Production Inventory Model considering Imperfect Quality and Shortage: A Case Study in a Goat Milk SMEs

Goat milk powder is one of the perishable processed products. The decreasing quality of goat milk powder can cause financial losses to the company if not regulated properly. So far, the company is also faced with the problem of consumer demand uncertainty. When demand for powdered goat's milk is high, the company experiences stockout but can be overcome by backorder. When demand is low, there will be overstock. Overstock conditions, in addition to causing high holding costs, are also at risk of product quality degradation or expiration. In this study, an inventory model of goat milk powder was developed that considers the uncertainty of demand, product quality, and backorder to determine the optimal production quantity so that the total inventory cost incurred is minimum. The basic model used is economic production quantity. Uncertainty in demand and the percentage of products declining in quality is approached using a triangular fuzzy. While the defuzzification technique used is signed distance.

ORGANIZATIONAL ASPECTS OF THE ANALYSIS OF PRODUCTION INVENTORIES OF THE ENTERPRISE

The purpose of the article is to study the organization of the process of analysis of production inventories at the enterprise in the conditions of globalization. The methodology consists in the use of the following methods: observation method, methods of analysis and synthesis, classification, monographic method, induction and deduction, grouping, comparison, generalization method. The scientific novelty of the work consists in improving the process of analysis of production inventories, which will allow to increase the effectiveness of the application of analytical procedures in relation to production inventories and, as a result, to increase the effectiveness of the internal control system at the enterprise. Conclusions. An important issue in the analysis of production inventories is ensuring the optimal number and structure of the company’s inventories and increasing the efficiency of the use of production inventories. This can be achieved by saving production inventories, improving the technological process, optimizing processes regarding the movement and storage of production inventories at the enterprise. Key words: analysis, inventories, production inventories, assets, accounting.

Implementation Of Economic Production Quantity (EPQ) Method in Controlling Brick Production at UD SM Edi- Mardiana Serdang Bedagai

achieving its goals, the company will face certain obstacles so that the companymust have good management. Because without good management the company will experiencea shortage of production (shortage) or excess production (over stock) which results inlosses for the company. UD. SM Edi Mardiana Serdang Bedagai is a business that producesbricks which is experiencing problems in the form of excess production inventory. Therefore,a policy is needed to control the amount of production by adjusting consumer needs so as notto cause losses for the company. One method that can be used is the Economic ProductionQuantity (EPQ) method which can determine the optimal production level, the optimal timeinterval to minimize inventory costs. From the results of calculations using the EPQ method,the optimal level of brick production for each production period is 4.326.589.75 seeds withan interval of 6,79 months and the total cost of procuring production with the EPQ method isRp313.532.065,9

Clustering Sales Patterns of Best Selling and Less Selling Products at El Jhon Bengkulu Stores Using the K-Medoid Method

The clustering application of the best-selling and less-selling product sales patterns at the El Jhon Bengkulu Store can provide information on the best-selling and less-selling product sales patterns as a basis for consideration in product inventory management at the El John Store. Based on 40 total product sales and inventory data in April 2022, the results obtained that 9 data entered cluster C1 (22.5% best selling products) and 31 data entered C2 cluster (77.25% less selling products). Based on the results of the tests that have been carried out, the functionality of the product inventory is running well as expected, and can provide information on the results of product data clustering into 2 groups, namely Best Selling and Less Selling

FishSounds Version 1.0: A website for the compilation of fish sound production information and recordings

Many fish species use active sound production for communication in numerous behaviors. Additionally, likely all fish can make passive or incidental sounds that may also serve some signal functions. Despite the ecological importance of fish sounds, their evident passive acoustic monitoring applications, and extensive endeavors to document soniferous fish diversity, the fields of bioacoustics and ichthyology have historically lacked an easily accessible, global inventory of known fish sound production. To alleviate this limitation, we developed http://FishSounds.net, a website that compiles and disseminates fish sound production information and recordings. FishSounds Version 1.0 launched in 2021, cataloging documented examinations for active and passive sound production for 1185 fish species from 837 references as well as 239 exemplary audio recordings. FishSounds allows users to search by taxa (e.g., family or common name), geographical distribution (e.g., region or water body), sound type, or reference. We have also made available the code used to create the website, so that it may be used in other data-sharing efforts—acoustic or otherwise. Subsequent versions of the website will update the data and improve the website functionality. FishSounds will advance research into fish behavior, passive acoustic monitoring, and human impacts on underwater soundscapes; serve as a resource for public outreach; and provide the foundation needed to investigate more of the 96% of fish species that lack published examinations of sound production. We further hope the FishSounds design, implementation, and engagement strategies will serve as a model for future data management and sharing efforts.

Establishing, Piloting, and Evaluating Community-Managed Tour Trek in Sagnay, Camarines Sur

Tourism has always been regarded as one of the Philippines’ most important industries and a major source of revenue. Different destinations in the country are known for their cultural diversity and natural beauty. In fact, many sites are still left to be explored and developed. This study assessed the local community’s perception of tourism development in Sagñay, Camarines Sur and aimed to propose a community-managed tour trek. Interviews, surveys, ocular visits, and mock tours were conducted to achieve the objectives of the study. Results show that the local community perceives that tourism development in the area can be a tool to help the community through improved livelihood, environmental protection, and cultural appreciation. The local community recognizes the importance of tourism development and the need for participation of all the stakeholders. Meanwhile, the proposed community-managed tour trek based on the inventory of tourism products highlights the natural and cultural resources of Sagñay, Camarines Sur. The local community was tapped as the primary stakeholders together with the local government unit. A pilot test was conducted to evaluate the proposed trek and provide a suitable offering to prospective tourists. Furthermore, the study shows the need for strong commitment among the local community and the local government to assure the successful management of the proposed community-managed tour trek. It has the potential to have a significant impact, particularly in terms of improving the community’s welfare in the future.

Penerapan Metode Single Exponential Smoothing dan Moving Average Pada Prediksi Stock Produk Retail Berbasis Web

Product inventory in retail companies is crucial because a product is a major component in the business and is a thing that is traded to meet the needs of consumers. In business, entrepreneurs certainly expect optimal profits that can be achieved by increasing the value of product sales. As a supporting factor in the success of a business, stock of products must always be available to meet the needs of consumers. The problems that often occur in retail companies are a product stock shortage and product stock buildup that can result in the damage of products because of being kept in the warehouse for a long time and can hinder the capital mobility. A product stock prediction system is needed to reduce the problems and can predict the amount of product stock in the future so that product availability can be controlled and the company can achieve the expected goals. This paper aims to provide a web-based product stock prediction system with a Single Exponential Smoothing and Moving Average method to determine the amount of product stock that must be available in the future. The comparison results of the two methods implemented in the prediction system show the Single Exponential Smoothing method with an alpha value of 0.5, superior to the Moving Average method with the results of the prediction error accuracy value in the Aqua 19 L product, namely MAD = -0.50, MSE = 3.02 and MAPE =11.38.

A Study on Optimal Location Selection and Semi-Finished Product Inventory Allocation in the Steel Industry

With the development of industrial production technologies and market economy, Postponement is increasingly being adopted by continuous production enterprise as a method that enables multi-product, mass customization production. In order to make use of the Postponement in manufacturing production enterprises need to achieve customized production and reduce enterprise costs. A modeling is conducted in the production process of Postponement in iron and steel enterprises in this paper. With the goal of minimizing total costs on a specific customer service level, mixed integer nonlinear programming and particle swarm algorithms are adopted for modeling and solving, to determine the optimal location and optimal semi-finished product inventory of PDP and CODP. Finally, taking an iron and steel enterprise as an example, the feasibility and effectiveness of the model and algorithm are verified. The study shows that the change of the optimal locations of PDP and CODP is affected by the change of customer service level and delay penalty coefficient, but the speed of change of the optimal location of PDP shows longer delays. In addition, the size of the capacity of semi-finished product inventory corresponding to CODP has a direct influence on whether the semi-finished product inventory corresponding to PDP participates in production, which in turn affects the optimal semi-finished product inventory on all levels. Through the analysis, it is found that the model constructed in this paper can better describe the overall situation and the influence relationship of the Postponement, and the study supplements the deficiency of the research on Postponement in the continuous manufacturing enterprises and enriches the content of the quantitative research on the Postponement.

A Successful Patient Blood Management System Implemented during the COVID Pandemic Based on Daily Blood Inventory Levels in a Single Large Oncology Institution

Introduction: The recent pandemic brought to light the fragility of the US Blood Collection system and supply chain disruption. As blood donations declined, blood donor centers (BDC) and blood banks (BB) worldwide reported a significant blood shortage. Our blood donor center had challenges from imposed COVID precautions (social distancing, contact restrictions, donations by appointments only, wearing of PPEs, etc.) to increase blood collections to replace the units transfused daily. The study was to review our Institutional process for development of Covid-19 risk levels-based dashboards which tracked the pandemic and provided risk levels in real time to faulty/staff employees. Methods: As the Blood Inventory decreased daily during the start of the pandemic and ultimately became critical, the Transfusion Service/Blood Bank (TS/BB) would reset and lower the triage Hgb level from 7.0 gm/dl to 8.0 gm/dL based on O pRBC units in inventory. The challenge was to disseminate the blood inventory to all stakeholders, decrease the number of calls/pages to TS/BB/Transfusion Medicine Physician (TMP) on call and be consistent in setting Hgb triage levels. Surgery/Anesthesia required daily inventory to predict cases that would have to be cancelled and rescheduled for possible increased estimated blood loss. As the national/local blood supply shortage became critical especially for O RBC Units, a Blood Shortage Decision Matrix was created in collaboration with our Chief Patient Safety Officer, Chief Administrative Quality Officer and Chief Information Technology Officer teams with a color-coded legend (RED - Hgb <=7.0 gm/dL [Emergencies only], ORANGE- Hgb <=7.0 gm/dL, YELLOW -Hgb <=7.5 gm/dL and GREEN <=Hgb 8.0 gm/dL) illustrating how blood would be triaged based on the O red cells units available in Inventory for transfusion each day (See Table ). Minimal/critical numbers for each blood product/blood group were derived based on logistic regression/machine learning/manual counts from historic usage within the past 2 years. A similar color-coded diagram was used for Platelet Inventory. The blood inventory continues to be reported at the daily morning Department/Divisional (Operations) Tier Readiness Briefings (Institution's Pathway leading to a High reliability Organization) for institution wide dissemination. The TS/BB Information System is linked to real time blood inventory of all blood products entered into the system and provided us with real time inventory except for units that required a second ABO Rh and irradiation. Computer queries were performed for the latest inventory by blood product available and received, total number of Inpatient and Emergency Medicine patients by blood types and their latest hemoglobin values with transfusion orders and transfused currently, patients who were not transfused currently with no active orders and patients who were transfused since last day of transfusion by blood types. Supply Estimates were made for blood products from donors collected at our BDC and blood products that would have to be purchased from outside suppliers. This was to guide decision making for both the BDC to provide blood products to the TS/BB and for the TS/BB to assess how many products needed to be ordered from outside suppliers. Demand estimates were made from historical data, current inpatient census from the EMR inpatient dashboard, number of current inpatients (ICU, Hematologic Oncology, Acute Cancer Care Center etc.) who were O pos (Per Webi query with a real time report run each morning), by location, blood type, hemoglobin level and days since latest hemoglobin level. Data was used to assess how many of the patient groups already met hemoglobin levels designed by the color code chart described above between 7.0 and 8.0 gm/dL which assisted the TS/BB to triage pRBC orders based on Hgb levels set for the colors. Results: The Blood Shortage Decision Matrix since its implementation in October 2021 has allowed clear organizational-wide ownership across all levels of the organization, use of a standardized Blood Inventory management by the TS/BB, improved communications with primary care teams, better understanding of the challenges maintaining an adequate blood supply by the Executive/Administrative Leadership leading to allocation of additional needed resources to the Blood Donor Center/TS/BB and also helps the Institution on its path toward a High reliability Organization. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Implementasi Metode K-Means Clustering Untuk Pengelompokan Data Penjualan Pada Minimarket Remaja Kampus Bengkulu

Campus Youth Minimarket is one type of business in the field of selling daily necessities. For decision making in determining the amount of product inventory that can be adjusted to market demand, the Campus Youth Minimarket has not used the system and is still calculated manually. Therefore, this research was conducted with the aim of implementing the K-means Clustering method in grouping sales data at the Bengkulu Campus Youth minimarket. So that it can easily determine and classify high, medium and low product sales. The implementation of the system uses the PHP programming language and MySQL database and the method used in this research is the waterfall method. After the K-means process was carried out at the Campus Youth Minimarket with 15 data data tests, 3 clusters of goods were obtained, namely cluster 1 as a high sales cluster with 7 items, cluster 2 with moderate sales of 4 items and 4 items in a low sales cluster. Based on the results of processing 278 data on sales of goods in December 2021 at the Campus Youth Minimarket using the K-Means Clustering Method, the results of the grouping of product sales levels at the Bengkulu Campus Youth Minimarket were 3 clusters. Namely cluster 1 group with a high level of product sales with a total of 54 product data, cluster 2 with a moderate level of product sales with 165 types of products and cluster 3 with a low level of product sales with 51 total products. Based on the data cluster, it can be used as a reference by the Campus Youth Minimarket for the following month's product inventory. Which product clusters that have a high level of sales have a high or stable number of orders as before. Then product clusters with low sales levels, then the amount of product inventory for the next is reduced so that there is no accumulation of products in the warehouse and experiencing expiration.