Out Of Stock Research Articles

Disruption Risk Analysis of Substitutable Dual Product Supply Chain: A System Dynamics Framework

Uncertain events such as earthquakes, epidemics, and wars have increased the risk of supply chain disruption. Due to the needs of carbon reduction policies and environmental protection, a large number of enterprises have started to produce both traditional and green products. Studying the issue of supply chain disruption for such enterprises has significant practical significance. We have developed a system dynamics model for a substitutable dual product supply chain with two levels of supply sources. Through simulation analysis, we found that (1) supply chain disruption can cause fluctuations in the manufacturer’s inventory, and disruptions from second tier suppliers have a higher impact on the manufacturer’s inventory than that from primary suppliers. In addition, the disruption of traditional products will cause consumers to flow to the green product market, resulting in a sudden increase in order for green products and components in a short period of time, causing a delayed impact on the inventory of suppliers and manufacturers of green products. (2) The disruption of upstream suppliers in traditional products causes the highest profit losses for all traditional product suppliers, while the disruption of downstream suppliers in green products causes the highest profit losses for the manufacturer and all green product suppliers. (3) From the perspective of the service level, compared to other components, the disruption of critical components in traditional products poses the highest risk of out of stock in the supply chain, while the risk of out-of-stock in the intermediate component of green product is the smallest. (4) Common sense may suggest that the more the suppliers disrupt, the higher the damage of the supply chain. However, due to the ripple effect, this article finds that from the perspectives of profit, inventory, and service level, multisupplier disruption is not necessarily inferior to single supplier disruption.

Inventory Control for Omnichannel Retailing Between One Warehouse and Multiple Stores

In this article, we research a multiperiod two-echelon inventory control problem for omnichannel retailing [i.e., online channel, offline channel, and buy-online-and-pick-up-in-store (BOPS) channel]. Especially, we jointly consider the limited storage capacity of the stores and the delivery lead time of the warehouse. For the out of stock, the unsatisfied demands for multiple purchasing channels have different processes (i.e., lost sales or backlog), based on the different characteristics of multiple channels. First, we divide the multiperiod inventory control problem for omnichannel retailing into two subproblems (the inventory control problem for the stores and the inventory control problem for the warehouse). Then, to reduce the scale of the first subproblem and the computation effort, we propose a method based on Lagrangian relaxation and value iteration to solve the inventory control problem of stores. Further, based on the results of the inventory control problem of stores, we construct a delay-aware Markov decision process (DAMDP) for the inventory control problem of the warehouse and employ the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> -learning technique based on the constructed DAMDP to solve the second subproblem. Besides, we also extend our analysis to the case of the low-level backlog in buying-online channels (i.e., online and BOPS channels). Finally, some numerical experiments are conducted to illustrate the performance of the inventory control policy for omnichannel retailing and reveal some managerial insights.

Inventory Backorder Prediction

Abstract: Product going to out of stock is a common problem in supply and chain scenario that comes under unpredictable risk in demand and supply. We aim to use Machine Learning predictive models in area of the business processes in decision making. By predicting products, backorder predictive models provides flexibility to decision authority, better clarity in the process, and helps in maintaining greater accuracy. The machine learning models that are tree based are chosen to predict material backordering. The backorders of products are predicted in this project by considering various models.

ANALISIS RESEP TIDAK TERLAYANI PASIEN RAWAT JALAN DI INSTALASI FARMASI RSU X JAKARTA

Pharmacy service is inseparable from health service system of a hospital. The service of pharmacy unit shall be a priority because an effective and efficient service will affect in the fulfillment of prescriptions. Furthermore, the management on the pharmaceutical stock will influence the revenue of the hospital (part of revenue center). The purpose of this research is to find out the percentage of unfilled prescriptions of outpatients from many different units, its reasons, and Therapeutic Class of unserved drug items. The research applies descriptive method using prospective data i.e. 25,259 R/ sheets of prescriptions obtained by total sampling technique. The research was conducted in three months from February to April 2021. The result of the research shows that there are unfilled 467 R/ prescriptions due to several factors, such as the drugs are not listed in the formularies, the drugs are out of stock, and the prescribed or patient-requested drugs are not covered by the insurance. Internal medicine unit has the most unfilled prescriptions (160 out of 467). The main reason is the drugs are out of stock (133 out of 467). Medicines for Gastritic, Respiratory, Heart Diseases and Allergicare the top lists in the Therapeutic Class, which is in accordance with data showing that Intenal Medicine, Emergency Department dan General Practisioners, Pulmonary, Dermatology and Venereology, and Obstetrics and Gynecology are the top 5 polyclinics with the number of unserved prescriptions due to out of stock.

Sales and Inventory Prediction with the EOQ Method based on Single Exponential Smoothing Forecasting

Along with the development of the era where technology is increasingly sophisticated as it is today, the needs are also increasing. Science and Technology also experienced drastic progress. Forecasting forecasting is a method for making estimates of future data by involving the use of past data in a systematic model form, and the forecasting method used is Single Exponential Smoothing. Planning for this EOQ method can minimize the occurrence of out of stock so that processes in a business are not disrupted and are able to save costs incurred due to the efficiency of inventory at the place of business concerned. Application of Supply Chain Management with data mining systems on CV. Amifa Keluarga Lestari can simplify the management of raw materials by implementing an SCM system which can reduce excess stock purchases. With the Single Exponential Smoothing method, you can predict the number of best sales for the following month in one period by looking at the smallest error. The calculation results show that the most economical order in one order is 1291 kilograms, and the total storage cost is Rp. 154,919 per Kilogram

Perceptions of Medieval Manuscripts: The Phenomenal Book by Elaine Treharne

Reviewed by: Perceptions of Medieval Manuscripts: The Phenomenal Book by Elaine Treharne Sonja Drimmer Elaine Treharne. Perceptions of Medieval Manuscripts: The Phenomenal Book. Oxford: Oxford University Press, 2021. 272 pp., 29 illustrations. $40. ISBN: 9780192843814. It wasn't easy getting a copy of this book. When I accepted the invitation to review Elaine Treharne's Perceptions of Medieval Manuscripts: The Phenomenal Book, I was told that, because Oxford University Press's website listed the book as out of stock, it might be challenging to get a hard copy; perhaps interruptions to the supply chain caused by the pandemic were partly to blame. Eventually, and happily, a hard copy arrived at my door. This is a book I could place on a shelf, reach for, hold, and use my hands to annotate. The logistics of a book's procurement are not usually fodder for a review, but in the case of Perceptions of Medieval Manuscripts, they could be considered one of the intangibles cleaving to tangibility that Treharne asks us to consider in our engagement with books produced in the Middle Ages. The book's premise is that we attend to the whole manuscript as a thing in the world—inclusive not only of its material properties and content and accretions over time, but also of the many aspects of its immanence that are perceived through the senses but often elude the scholar's empirical capture. The theoretical armature for Treharne's proposal is Maurice Merleau-Ponty's phenomenology, which takes the embodied perception of the world as offering each individual their perspective on it; manuscripts are "are archetypally phenomenal objects, dependent on sensory engagement for their fullest interpretation" as whole objects irreducible to their constituent parts (6). A key term for Treharne's intervention is the architextuality of the book (a notion inspired by, but ultimately distinct from, the architext as conceived by Gérard Genette): its essence as a concrete object through which humans have passed and experienced its transcendent properties over time. Informing the study's concept of the manuscript as an actual and ideated form, and structuring its itinerary, is Riddle 26 from the tenth-century [End Page 147] (Exeter Cathedral Library, MS 3501). The poem is spoken in the voice of a book narrating its own production and reception—not the book in which this riddle appears but a notional and abstract book inspirited with a voice that meditates on its own flesh. Excerpts from this riddle provide the heading for each of the book's chapters, which focus chiefly on British manuscripts from the seventh through the thirteenth centuries, and move us both logically and trilogically from the first three chapters on manuscripts' making and inscription to the central three chapters on the visible and invisible presences of successive users, to the final three chapters on manuscripts' representations from within medieval books themselves to their modern digital surrogates. Treharne's exegesis of this poem in chapter 2 shimmers, as she conjures its sensuality and the sonic allure of its unvoiced consonants, evocative of the parchmenter's scrape of a lunellum and swipe of a bone folder over thick membrane. As concerned as it is with its material facture, so too is this personified book aware of its transcendent value: its origins in violence and culmination as a glorious form echo the narrative of humanity's redemption through the Passion of Christ, the Word made flesh (26). The aperçu that cracks open manuscripts' affective power is that "books save lives"—whether lives here are read as Christian souls or the physical bodies that have been protected apotropaically and shielded literally by their form (35). The magnetism of the book as an enfleshment of affect resides particularly legibly in the traces of the scribes who left inky tracks of their handiwork across the pages. In this, what I found to be the most evocative chapter, Treharne reflects on the writing on the page as a manifestation of the union of scribe, tool, and effort. Here, Treharne merges the paleographer's resolute precision with a lyrical sympathy to the letterforms as they rest on the surface of skin, hover over a blind-ruled base line, and...

Inventory Control Analysis of Manual Hospital Bed Assembly Units PI-108MS, PI-208MS, PI-308MS with the EOQ (Economic Order Quantity) Method at PT. XYZ

The purpose of this study is to determine the warehouse capacity of PT. XYZ in storing hospital bed supplies can use the EOQ( Economic Order Quantity) method to determine the warehouse capacity in hospital bed supplies. The EOQ method seeks to achieve minimum inventory levels, lower costs and better quality. The EOQ method in the company will be able to minimize the occurrence of out of stock so that it does not interfere with the process and is able to save inventory costs incurred by the company. February showed that the company assembled 230 units, selling 151 units. Meanwhile, to avoid excess units, the number of assembly that must be done is 4,425 with the purchase of 2 units, Safety Stock 74.34 units and ROP 151 units. The calculation uses the EOQ method which shows that the safety stock that must always be available at PT. XYZ for unit inventory is as much as 230 units, meaning the company must have an inventory of 74.34 units in order to anticipate a shortage of units during the grace period without hampering the assembly process

Analisis Penerapan Metode Association Rule Mining Untuk Transaksi Penjualan di Toko Bangunan Dengan Algoritma Apriori

In improving the quality of service to customers, UD. Lasmi Jaya store is asked to be able to handle problems that often arise, among others, lack or absence of (out of stock) stock of building goods that are very popular, less strategic layouts, assist in decision making to develop marketing strategies and promote better products and more. Therefore, in this problem, there must be utilization of sales transaction data for processing using a priori algorithms so that it can provide new knowledge that can be utilized by shop owners. From the results of research that has been carried out from 300 sales transaction data from January 1, 2022 - June 30, 2022 with a comparison of a minimum transaction of 15 or a minimum of 5% support and a minimum of 40% confidence with a minimum of 12 transactions or a minimum of 4% support and a minimum of 30% confidence, associations the final results found were more at least 12 transactions or minimum support 4% and minimum confidence 30% because if the minimum support value and minimum confidence value were lower then the association value found would be more, so for determining stock of goods or layout of goods or as promotion and others so that it will make it easier for the owner to manage their sales so that they can grow and provide satisfaction

Analisis Peramalan Permintaan Golang-Galing dalam Memaksimalkan Manajemen Rantai Pasok Menggunakan Metode Weighted Moving Average

Forecasting the demand for golang-galing products in the Small and Medium Enterprises (SMEs) industry “Pak Liman” in Kaliori Village, Banyumas District, Banyumas Regency is planning support in production control so as to maximize supply chain management of golang-galing products. Forecasting market demand is very necessary in order to predict market opportunities for future demand for a product. Demand forecasting aims to prevent the risk of sales prediction errors that cause waste such as sales predictions that are too large which can lead to swelling in production costs and vice versa if sales predictions are too small it will result in out of stock out, so consumers need to wait a long time for sales. get the desired product. Based on these problems, an analysis of demand forecasting for golang-galing products is carried out which aims to reduce waste and maximize value for all components in the supply chain. This study uses time series analysis with the moving average method to forecast the demand for golang-galing products for the next five months. The results of the study obtained forecasting in April, May, June, July, August, September, October, November, December 2022 in sequence, namely 3,254.6; 3,254; 3,256.6; 3,254, 6; 3,254.2; 3,253.9; 2,987.3; 3,162,9; 3,156.4. From the calculation of the Mean Absolute Error (MAE) and Mean Square Error (MSE) that has been carried out, it is obtained that the calculation for MAE is 3.44 and MSE is 20.144.

Optimasi Inventori Material Bubuk Nylon pada Proses Coating dengan Pendekatan Probabilistik

&lt;p&gt;&lt;em&gt;This research aims to optimize the supply of raw material for nylon powder for the manufacturing industry. The problem was found in the nylon powder warehouse which was out of stock so that it had to be replaced with plastic raw materials to keep the production process running. The change of raw material from nylon powder to plasco was done because the company did not make an emergency order for nylon powder. This is due to the high cost of emergency orders. The use of plasco powder makes the company accept a sizeable return of goods. Therefore it is necessary to do a good inventory management to overcome the out of stock. The method used to solve this problem is the probabilistic P back order model. Demand in the previous period was normally distributed. The results of processing with the P back order model produce a service level of 99.95%. It is hoped that the company will not experience out of stock again. In addition, a savings of 4.50% were obtained from the total costs incurred by the company. Inventory policy obtained using the P back order model with an order time of (T) 0.358 or for 130 days a new order will be made, and the total inventory cost is Rp.418,363,268 / year with a service level of 99.995%.&lt;/em&gt;&lt;/p&gt;

An Uncertain APP Model with Allowed Stockout and Service Level Constraint for Vegetables

Volatile markets and uncertain deterioration rate make it extremely difficult for manufacturers to make the quantity of saleable vegetables just meet the fluctuating demands, which will lead to inevitable out of stock or over production. Aggregate production planning (APP) is to find the optimal yield of vegetables, shortage and overstock symmetry, are not conducive to the final benefit.The essence of aggregate production planning is to deal with the symmetrical relation between shortage and overproduction. In order to reduce the adverse effects caused by shortage, we regard the service level as an important constraint to meet the customer demand and ensure the market share. So an uncertain aggregate production planning model for vegetables under condition of allowed stockout and considering service level constraint is constructed, whose objective is to find the optimal output while minimizing the expected total cost. Moreover, two methods are proposed in different cases to solve the model. A crisp equivalent form can be transformed when uncertain variables obey linear uncertain distributions and for general case, a hybrid intelligent algorithm integrating the 99-method and genetic algorithm is employed. Finally, two numerical examples are carried out to illustrate the effectiveness of the proposed model.

M-GAN-XGBOOST model for sales prediction and precision marketing strategy making of each product in online stores

PurposeThe rapid development of e-commerce has brought not only great convenience to people but a great challenge to online stores. Phenomenon such as out of stock and slow sales has been common in recent years. These issues can be managed only when the occurrence of the sales volume is predicted in advance, and sufficient warnings can be executed in time. Thus, keeping in mind the importance of the sales prediction system, the purpose of this paper is to propose an effective sales prediction model and make digital marketing strategies with the machine learning model.Design/methodology/approachBased on the consumer purchasing behavior decision theory, we discuss the factors affecting product sales, including external factors, consumer perception, consumer potential purchase behavior and consumer traffic. Then we propose a sales prediction model, M-GNA-XGBOOST, using the time-series prediction that ensures the effective prediction of sales about each product in a short time on online stores based on the sales data in the previous term or month or year. The proposed M-GNA-XGBOOST model serves as an adaptive prediction model, for which the instant factors and the sales data of the previous period are the input, and the optimal computation is based on the proposed methodology. The adaptive prediction using the proposed model is developed based on the LSTM (Long Short-Term Memory), GAN (Generative Adversarial Networks) and XGBOOST (eXtreme Gradient Boosting). The model inherits the advantages among the algorithms with better accuracy and forecasts the sales of each product in the store with instant data characteristics for the first time.FindingsThe analysis using Jingdong dataset proves the effectiveness of the proposed prediction method. The effectiveness of the proposed method is enhanced and the accuracy that instant data as input is found to be better compared with the model that lagged data as input. The root means squared error and mean absolute error of the proposed model are found to be around 11.9 and 8.23. According to the sales prediction of each product, the resource can be arranged in advance, and the marketing strategy of product positioning, product display optimization, inventory management and product promotion is designed for online stores.Originality/valueThe paper proposes and implements a new model, M-GNA-XGBOOST, to predict sales of each product for online stores. Our work provides reference and enlightenment for the establishment of accurate sales-based digital marketing strategies for online stores.

SISTEM INFORMASI MANAJEMEN MONITORING STOK PADA OUTLET PT. GLAXOSMITHKLINE SEMARANG BERBASIS WEB

GlaxoSmithKline is an intermediary that transports products from manufacturers to retailers. After a product is produced by the factory, the product is sold to the distributor PT. GlaxoSmithKline namely PT. Anugerah Pharmindo Lestari (APL), PT. This APL will distribute to Minimarket Distributors, and distribute to Supermarkets, Hypermarkets. PT.GlaxoSmithKline assigned Sales Promotion Girl (SPG) and Merchandiser (MD) in supervising or monitoring stock at outlets.This study discusses the problems of the stock monitoring management information system owned by PT. GlaxoSmithKline Semarang. Stock monitoring management is an important problem faced by companies, especially supervision of developing outlets such as Indomaret and Alfamart. In meeting the smoothness of trade as well as the fulfillment of consumer demand, PT. GlaxoSmithKline should make every effort to establish stock availability at these outlets. In carrying out stock availability information, the technique used is still manual so that the company's performance is slow. Each outlet experiences stock changes from time to time, therefore a stock monitoring management information system is needed. The stock monitoring process is carried out by merchandisers who can move within the web network. This can make it easier for companies to monitor existing stock at outlets. This study tries to develop an information system for stock control and web-based prototype development. The development of a web-based prototype is expected to be able to carry out the stock control function including available goods, and out of stock (OOS) items at each outlet.Keywords: Information system, Stock monitoring, Web.&#x0D;

Decision support system for truck scheduling in logistic network through cross-docking strategy

In recent years, companies around the world need to find new ways to reduce costs, increase productivity, improve product quality, and meet various customer demands. Each Distribution Center (DC) or warehouse is specifically designed to minimize costs in the company’s supply chain. Cross-docking is a logistics technique that eliminates storing and picking up items at warehouses. Cross-docking has several advantages compared to other product distribution strategies from both an economic and an environmental point of view. Cross-docking decisions are influenced by many factors such as the level of product demand, the cost of stock-outs, and the distance from suppliers to customers. This research builds a Decision Support System (DSS) that can help companies to ensure sustainability in the supply chain. This study assumes the demand is deterministic which is indicated by Economic Order Quantity (EOQ). This system can detect the time and quantity of certain items that experience cross-docks accurately. If the customers’demand cannot be fulfilled by the warehouse, then the goods are categorized as out of stock. By knowing the time and quantity of goods at the time of the cross-dock, the warehouse manager can make operational decisions quickly and accurately related to the resources such asoperators and forklifts.

Bow tie analysis for prioritizing actions to manage the risks of out of stock on shelves in the retail

PurposeThe purpose of this paper is to present a methodology to structure the problem of retail out of stock (OOS). This methodology allows investigating risk factors and barriers related to the main causes and consequences that lead to OOS occurring.Design/methodology/approachThe proposed methodology to structure the OOS problem is based on the bow- ie tool, which allows better visualisation, understanding and analysis of a complete OOS scenario. This proposal comprises exploring the main causes and consequences of OOS, the barriers to prevention and mitigation, the escalation factors to control undesirable events and to define actions to eliminate or mitigate the OSS risk.FindingsSeveral potential causal risk factors, related to technical, behavioural, cultural and organisational aspects, were identified with this methodology. With the analysis of the OOS scenario, it was observed that the factors that lead to the OOS risk are preventable. In order to improve existing barriers or implement new barriers, a set of actions can be recommended to reduce or eliminate OOS risk factors.Originality/valueFrom a better understanding of hazard, the bow-tie methodology allows identifying crucial factors that could be acted upon to reduce the incidence of OSS. Thus, the value is to propose a methodology that allows establishing the preventive and protective barriers necessaries and the escalation factors related to each of these to help structure the problem and consequently reduce the OOS in retail organisations.

Risk analysis of milkfish supply chains in Semarang using house of risk approach to increase the supply chain resilience

This research aims to identify, measure and analyse the operational risk in supply chain of milkfish at Semarang. The supply chain activities emphasize on cooperation between parties to reduce risks in all stage of supply chain. Risk event occur are the return of fish to suppliers due to the poor quality, damaged product during the production process, and customer complaints due to improper order services. These problems result on out of stock of fresh fish, low customer satisfaction, and financial loss for the fish processing industries and distributors. Therefore, it is important to identify, measure and analyse the risks that probably occur in the supply chain from harvest area to end customer. The house of risk method used to analyse the supply chain risk and Supply Chain Operation Reference (SCOR) approach used to divided the business process into 5 main processes i.e., plan, source, make, deliver and return. The data collection was done by deep interview and spread questionnaires to industries manager and staff. The risk identification result shows that 7 risk events occur in the production process and 8 risk events in delivery process. These two processes have highest risk event number. The highest risk severity is found on Chlorine contaminated products. Based on severity value, some recommendation was formulated to reduce the impact of occurred risks to increase the supply chain resilience.

An examination of the effects of cross-docking on retail out of stock

PurposeThe objective of this paper is to examine the impact of cross-docking on the retail out of stock (OOS).Design/methodology/approachThe research is based on a three-phase Delphi study consisting of a seeding/literature review phase, a pre-testing phase and a three-round Delphi study. The Delphi study used in this paper brings together leading supply chain management experts with leading academics.FindingsThe findings of the paper show that cross-docking may impact the retailers OOS drivers positively or negatively. The study demonstrates that cross-docking has a negative impact on ordering, placement, delivery, handling, DC handling and receipt. On the other hand, cross-docking has a positive effect on supplier ordering. Finally, academics and supply chain managers disagreed on the effect of cross-docking on the promotions driver. Academics consider that cross-docking has a positive impact on promotions OOS driver, while supply chain managers believe the opposite.Research limitations/implicationsThe Delphi study was administrated to supply chain managers from a single major FMCG company, which is a supplier of grocery retailers. By including supply chain managers from the retailers' side, more perspectives on the impact of cross-docking on the OOS drivers can be investigated.Originality/valueThe study develops an original instrument to investigate the impact of cross-docking on OOS drivers. This is the first scholarly work to investigate the relationship between a distribution strategy and the OOS drivers.

SISTEM INFORMASI PEMBELIAN DAN PENGELUARAN KAS PADA CV.ANGKASA BARU

The information system for purchases and cash disbursements is one of the entire information systems. In retail sales companies need control of purchases and cash disbursements that are precise and fast. In an effort to minimize sudden out-of-stock inventory, it is necessary to secure an inventory to cope with a sudden out of stock due to delays in purchasing goods that occur at CV. New Space. This is what encourages the author to conduct research on CV. Angkasa Baru and choose the title "Purchasing Information System and Cash Distribution at CV. New Space.&#x0D; In writing this research systemin formation, the author uses the Microsoft Visual Basic 6.0 application, the research writing method uses the Research and Development (R&amp;D) model, while the stages of this research model go through the stages of observation or interviews with parties related to the data required in writing this thesis, stages of designing the application system, designing specifications, validation test stages, revision of validation until the system passes. The development method used by the author is the prototype method, where the system created will be tailored to the needs of the user, if there is a change in the system it will be repaired until the user is satisfied with the system.

Using System Dynamic Model for Predicting Inventory of Rice Necessity

Indonesian government has an organization that aims to manage basic necessity nationally, especially for rice commodity. The organization runs in the form of a business entity and has a program making welfare of the poor people by providing rice assistance. There is still over stock and out of stock in inventory while organization distributes this relief. That matter creates unbalance between commodity in inventory and commodity in distribution incurring a large cost. Prediction model using system dynamic in this study was needed to control the inventory and reduce over stock or out of stock. Causal loop diagram was used to describe the relationship between variables in the system and simulation was run with stock and flow diagram. Simulation was done by benchmarking the actual and the simulation results. The model that was built, tested using the Mean Absolute Percentage Error (MAPE). Based on the simulation results, the values of MAPE are below 5%. This indicates that the model can represent the real system and can use to predict variable for the future.

Penerapan Data Mining Untuk Estimasi Penjualan Obat Berdasarkan Pengaruh Brand Image Dengan Algoritma Expectation Maximization (Studi Kasus: PT. Pyridam Farma Tbk)

Data mining, often also called knowledge discovery in database (KDD), is an activity that includes the collection, use of historical data to find regularities, patterns or relationships in large data sets. The output of data mining can be used to improve decision making in the future. PT. Pyridam Frama Tbk is a multi-national company that produces pharmaceuticals. The problems that often occur at PT Pyrida Farma are estimation problems such as out of stock of goods at distributors, lack of labor, running out of raw materials at the factory. Another problem contained in the agency is that it does not yet have a system to predict the estimated drug sales each year, so we need an algorithm, the Expectation Maximization Algorithm. then with this made the Application of Data Mining for Estimating Drug Sales Based on the Effect of Brand Image. Expectation Maximization algorithm which is a method that supports in estimating or predicting sales target estimates for the coming period. Algorithm testing is done using SPSS and MYSQL software. From the results of research that has been done it can help the PT. Pyridam Farma to make it easier to predict drug sales estimates by using SPSS Software