Stock Shortage Research Articles

Application of the K-Means Algorithm to determine the accuracy of goods inventory based on sales data classification at PT Batu Indah Raya

The research aims to apply the K-means algorithm to classify sales data and to test the final results of Clustering Accuracy of each type of stone using DBI (Davies-Bouldin Index) testing. In the last 9 months PT Batu Indah Raya has experienced uncertain sales ups and downs, from these problems it is difficult to know the level of inventory of goods each month. The impact is that the company experiences a buildup or shortage of stock of goods every month and incurs costs related to excessive storage of goods or additional costs that arise due to lack of stock, to be able to overcome the problems that occur, requires a method or system to find out inventory by classifying sales data of each type and testing the level of accuracy with a test method or system. One method that can be used to solve these problems is using the K-means Clustering algorithm. The K-means method is expected to help companies identify inventory more easily. So that business people can show effectiveness in product / goods procurement. Data to determine the level of accuracy of inventory is taken based on sales every month at PT Batu Indah Raya. By using 2 clusters, namely cluster 1, it means that cluster 1 is in high demand and cluster 2 is less in demand in applying the k-means algorithm method with the results of the type of yellow brongkol stone in cluster 1 getting 59 members and cluster 2 getting 31 members with the DBI accuracy test result of 2.292 which is in the very good range. The type of white cobblestone in cluster 1 gets 36 members and cluster 2 gets 54 members with a DBI accuracy test result of 3.711 which is in the good range. The type of zeolite stone in cluster 1 gets 42 members and cluster 2 gets 36 members with a DBI accuracy test result of 3.597 which is in the good range.

Application of autoregressive integrated moving average and vector autoregression prediction models for stock and price stabilization at perum bulog

This study implements the ARIMA (Autoregressive Integrated Moving Average) method to predict rice stock levels at Perum Bulog in Lhokseumawe City. The objective of this research is to forecast rice stock levels for the upcoming year, 2024, and provide Perum Bulog Lhokseumawe with a more accurate reference for future stock planning. The benefit of this research lies in its potential to enable preventive measures to minimize rice stock shortages and support Perum Bulog in formulating policies to reduce the risk of future shortages. Error testing for rice prices with the ARIMA model shows MAPE values of ARIMA (1,0,0) = 21,256,076,432,276.10%, ARIMA (0,0,2) = 3.54%, and ARIMA (1,0,2) = 21,305,440,935,436.50%. Rice stock testing with MAPE error values yielded ARIMA (2,0,0) = 13.49%, ARIMA (0,0,1) = 13.65%, and ARIMA (2,0,1) = 10.27%. The error measurement results for prediction using MAPE are 1.5% for rice prices and 58.9% for rice stock. Based on these error measurements, the VAR model appears sufficiently accurate for predicting rice prices, as the MAPE value is at a low level.

Implementasi Data Mining Menggunakan Metode Algoritma FP-Growth Dan Algoritma Apriori Pada Toko IBR Jaya Untuk Meningkatkan Penjualan

Dian trading business is one of the grocery stores engaged in buying and selling the main household needs of nine basic ingredients which have been doing a lot of grocery sales transactions. This transaction Data continues to grow every day and in the IBR Jaya store sales transaction data is only presented as an archive or report and it is not mentioned what the benefits of these data are. Nah, the problem at the IBR Jaya store is the improvement of improvements due to the shortage of basic food stocks that are often purchased by consumers are not available which results in improvements and usability improvements then the FP-Growth algorithm is used to analyze patterns of improvement and a priori algorithms for comparison through archived transaction data goods that will be purchased later as a reference to increase food stocks so as to increase sales at the IBR Jaya Food Store in the hope that this increase can help this is one of many ways to make money online. Association rules are a process in Data Mining to establish all associative policies that meet the minimum requirements for support (minsup) and trust (minconf) in a database . In association rules, there are 2 methods that can be used, namely a priori method and FP-Growth method. In this study the method used is FP-Growth algorithm and a priori algorithm, FP-Growth algorithm and a priori method is a method to find the most frequently appearing data set (frequent itemset) without using candidate generation that is suitable to analyze a data transaction.

Evolution of Nuvoton Microcontroller-based Education Board

Background:: The novel coronavirus pandemic has not only affected people's health. The pandemic has also affected their social life and work. For all the reasons mentioned, international trade has suffered and is still in the process of recovery. Objective:: Especially in the semiconductor industry, many manufacturers postponed their deliveries to future periods and this triggered the chip crisis. Many hightech industries, including the automotive industry, were deeply affected by the consequences of the crisis, with factories halting or slowing down production. Despite the shortage of chip stocks, Nuvoton has a large amount of Microcontroller Units (MCUs), but due to the shortage of resources, education and libraries, software developers have not been able to integrate their products in a limited time. Methods:: In this paper, the Nuvoton Education Board has presented 20 common examples for embedded software developers and beginners. Results:: The PCB is designed considering all modules connected to separate General Purpose Input Output (GPIO) pins to make multiple module examples without changing the peripherals and pin configuration of the MCU. Clock configuration has been simplified and unnecessary details have been meticulously removed to make the examples easily understandable. Nuvoton NuMaker M263KI V1.3 was added on the designed PCB. Conclusion: The PCB contains almost all the necessary electronics to learn embedded software and use Nuvoton MCUs in industrial projects. The board is supported with user interfaces and printed documentation. The codes are explained with command lines to teach users even small details. A patent application has been filed for the proposed education board.

Perancaangan Sistem Informasi Apotik Berbasis Web: Optimalisasi Layanan Pelanggan

This research discusses the development and implementation of a "Web-Based Pharmacy Information System" which aims to improve the efficiency of customer service and drug inventory management. By using web technology, PHP programming language, and MySQL database, this system allows pharmacies to monitor drug stocks in real-time, manage patient information, and provide integrated services. The use of PHP and MySQL in developing this application allows the automation of administrative tasks, including drug stock tracking, orders, and patient data management. This system also facilitates customer service with easy access to drug information and online drug ordering services. The research results show that the implementation of the Web-Based Pharmacy Information System has succeeded in increasing pharmacy efficiency, reducing drug stock shortages, and improving customer service. This system supports integrated drug management by integrating patient data, drug stock and customer service in one platform. Overall, this system illustrates how the use of web, PHP, and MySQL technologies can optimize customer service and medication inventory management in the pharmacy context, providing major benefits to pharmacies and patients.

Analisis Peramalan Persediaan Sparepart Menggunakan Metode Exponential Smoothing di PT. XYZ

XYZ is a manufacturing company that produces Yamaha brand motorbike parts such as electrical switches, electrical sockets, lever assembly and horns. Many of the products sent were returned by customers because they did not meet quality standards, for example in March 2024 there were 1,420 pcs out of a total of 19,900 pcs that were returned. This means that companies have to increase production time and costs to replace defective products that are returned because they do not have safety stock. Forecasting is needed to control the production system so that it does not experience over stock and safety stock shortages. This research aims to provide recommendations for forecasting methods that companies can use to minimize the occurrence of production excesses and shortages in the company. Forecasting is done based on historical company sales data for 12 months. The method used is the exponential smoothing method which is then tested whether this method can be used in the future. This calculation uses the help of POM-QM (Production Operation Management – Quantitative Method) software. Calculations are carried out by testing the MAD, MSE, and MAPE values to obtain calculation error values. The results obtained by forecasting the main sw srtg lock assembly product using the exponential smoothing method were 15,708 for demand for the next period, MAD 3.38, MSE 22.84 and MAPE value 26%. Based on these results, the exponential smoothing method can be a recommendation for companies to forecast future demand. This is because the value of forecasting accuracy or MAPE is reasonable. The smallest percentage of MAPE values has a fairly minimal possibility of error in forecasting results.

Prediction of Tempe Raw Material Needs for Home Industry Using Tsukamoto Fuzzy Logic Algorithm

The home tempeh industry is faced with the challenge of accurately predicting raw material needs. Implementing an effective prediction system can help estimate the amount of tempeh production in the future, so as to avoid stock shortages of raw materials. In addition, when tempeh producers have accurate predictions, they can manage soybean stocks better, especially when there is a stock shortage, so that production is not affected by rising soybean prices. This research aims to develop a Tsukamoto Fuzzy Logic based prediction system to overcome this problem. Research methods include collecting historical production data, designing fuzzy models, and system testing. Interim results show that the developed system is able to increase prediction accuracy by up to 95%, which in turn can reduce production costs and minimize waste of raw materials.

Pengendalian Persediaan Sparepart dengan Menggunakan Metode Fifo di Warehouse di PT.Heinz ABC Indonesia Pasuruan

Spare parts inventory is a common problem faced by many companies that use lots of machines or robots in their production processes. Where the spare parts warehouse in the company is required to always be prepared and there is no delay in the availability of spare parts to continue to support production machine activities. If the availability of spare parts is late or empty, it will hamper the production process activities within the company. Seeing this problem, researchers are trying to maintain the availability of spare parts using the FIFO (first in first out) method so as to prevent delays or stock shortages. The FIFO method is a method of inventory management that uses product stock in the warehouse based on the time of entry. By using this method, it is hoped that there will be no delays or stock vacancies in the warehouse due to irregularities in picking up spare parts in the warehouse. The aim of this research is to ascertain how the use of the FIFO method affects the warehouse's ability to manage spare parts inventory efficiently. Field research is this type of research. This research uses a qualitative data analysis methodology and inductive reasoning, which starts with precise and real facts before drawing conclusions from them. The research results provide significant benefits in increasing operational efficiency and reducing the possibility of excess or shortage of stock, which can disrupt production and delivery processes. Efficient receiving also helps in maintaining spare parts quality, ensuring that only items that meet quality standards are received and stored. Application of the FIFO method in the spare parts warehouse at PT. Heinz ABC Indonesia also has a positive impact on inventory recording and reporting. With a more regular flow of goods in and out, the recording system becomes more accurate and easier to track. This makes it easier for the accounting and management team to carry out audits and identify potential problems.

Analisis Efektifitas Distribusi Produk Guna Meminimalisir Bullwhip Effect dengan Menggunakan Metode Peramalan pada Distributor PT. Kosmetika Global Indonesia

The bullwhip effect phenomenon occurs due to differences in demand patterns between distributors and retailers, causing overstock. This happened to Distributor PT. INDONESIAN GLOBAL COSMETICS where companies experience overstock and sometimes stock shortages, due to information distortion between companies, distributors and retailers due to different demand predictions. Therefore, the author conducted research to minimize the bullwhip effect phenomenon using the forecasting method in Microsoft Excel software. The data used in this research is demand and sales data for the period July 2023 to June 2024 for facial wash beauty products. Data processing is carried out by calculating the bullwhip effect value for the product. Next, carry out forecasting calculations. Then a comparison of the bullwhip effect values ​​was carried out as an improvement with this forecasting method. Furthermore, the results obtained from this research are the magnitude of the bullwhip effect in the PT Distributor supply chain. INDONESIAN GLOBAL COSMETICS has a value of 1.012 and is greater than 1, which means there has been a bullwhip effect in the observed supply chain. From the results of the analysis, it is known that the causes of the bullwhip effect include the absence of a user system and strategy in forecasting needs, unmeasured inventory or shortages of inventory, fluctuating prices, order sizes and grace periods for order fulfillment, as well as estimated inventory results in the following month of 992 .71 pcs with a minimum of 929.40 pcs and a maximum of 1056.02 pcs. Ways that may be effective in reducing the bullwhip effect that occur include managing product availability well, namely by implementing controlled forecasting, selling product orders and also the accuracy of information from product sales so that business owners will easily calculate forecasting values ​​for the coming period.

INOVASI E-COMMERCE UNTUK OPTIMALISASI PROSES KONSUMEN, PRODUKSI, DAN PEMASARAN BAGI PELAKU UMKM

E-commerce technology enables efficient online transactions, providing customers with a convenient and efficient purchasing experience. In terms of production, e-commerce information systems can be integrated with production management, enabling monitoring of the production process, optimizing production efficiency and reducing the risk of stock shortages. E-commerce technology also opens up opportunities for more sophisticated marketing strategies, as MSMEs can utilize consumer data analysis, increasing customer appeal and ordering and sales. E-commerce technology facilitates direct interaction between consumers, fostering closer relationships and improving customer experience. The development of e-commerce technology has significantly increased the effectiveness and efficiency of MSMEs specifically in the fried chicken sector, enabling them to compete in the digital business era. The purpose of this study is to develop an E-Commerce information system in the "Maju Makmur" Kalasan fried chicken industry center that manages MSMEs fried chicken. The research method is a prototype model. This model starts from data collection, system design and testing. The stages of the prototyping development model consist of: communication, rapid planning, rapid modeling, construction, and delivery. The results of this study are a web-based system to optimize consumer, production, and marketing processes in order to increase operational efficiency and market access through an online platform.

Infant Food Flours Made from Local Products to Combat Acute Malnutrition in Children Under 5 Years Old in Côte D’ivoire

In Côte d'Ivoire, recurring stock shortages and difficulties in accessing specialized food products compromise nutritional treatment. This study proposes food formulas of flours composed of locally available products capable of meeting the protein-energy needs of children aged 6 to 59 months diagnosed with moderate acute malnutrition. The methodological approach consists of formulating and determining the physicochemical, nutrient, and functional characteristics of four new formulations (1F, 2F, 3F, 4F, and 5F). The results indicate that the formulated foods have high levels of calcium (215.60-252,29 mg/100g MS), potassium (555,70-789,29 mg/100 g MS), magnesium (261,26-200,63 mg/100g MS), iron (4,86-7,03 mg/100g MS) and phosphorus (392,36 -469,36 mg/100g MS). The fat content varies from 9.66% to 23.86%. The energy value determined for all flours corresponds well to the Codex. The food formulas developed would also be able to meet more than 100% of the daily requirement of vitamins E and B1. The phytate (180.26 - 227.05 mg/100 g) and oxalate (66.00 - 88.00 mg/100 g) contents are low. The presence of phenolic compounds, including flavonoids (7.78-15.44 mg/100 g) and antioxidant activity (31.09-32.84%) would be a significant asset. The levels of deoxynivalenol (62 μg/kg) recorded in flours are below 200 μg/kg recommended for infants and young children. The proposed formulations have high-water absorption capacity (136.15 -252.94%) and high solubility index (56.84 -59.2%). The wettability time ranges from 3.66 ± 0.16 s to 33.71 ± 0.23 s. Flours (1F, 2F, 3F, 5F) have a better absorption capacity for refined palm oil (132 %, 139 %, 121 %; 115 %). The proposed new formulations have nutritional characteristics close to standard data and could therefore be recommended for children aged 6 to 59 months for complementary feeding in the context of the fight against moderate acute malnutrition.

Sistem prediksi pengadaan stok bahan baku kayu menggunakan Metode Double Exponential Smoothing (Studi Kasus: CV. Jati Sari)

In managing the supply of wood raw materials at CV. Jati Sari is still carried out based on the personal experience of business entity owners. Because it is based on personal experience without carrying out in-depth analysis or forecasting, it will create a risk of excess or shortage of stock, making stock management inefficient. The software development method used is the Waterfall method. Double Exponential Smoothing is implemented in this research as a forecasting prediction calculation method. This research produces a prediction system that can produce output in the form of a predicted amount of wood needed as inventory or stock in the warehouse in cubic meters. For manual calculations, the DES method has a prediction calculation result for the 21st period of 4.8 m3. Based on the system testing using black box and white box testing that has been carried out, it can be concluded that the prediction system for procurement of wood raw material stock using the website-based Double Exponential Smoothing method has succeeded well in solving the problem of predicting the amount of wood raw material stock for the next period at CV. Jati Sari.

Pricing and Replenishment Decision System Based on LSTM

Fresh supermarket vegetables have a very short shelf life, and the quality of vegetables will also be affected by the storage time. If most of the goods are not sold on that day, they will not be sold on the next day. From the demand side, the sales volume of vegetables is related to the supply side of vegetables from April to October. At the same time, the sales space of the supermarket is limited, which makes a reasonable sales portfolio extremely important. The commercial overpricing replenishment decision system based on LSTM analyzes the relationship between daily sales volume and cost-plus pricing for each vegetable category and single product over three years. It predicts the sales volume and wholesale price of each category for the next week, determining replenishment volume and pricing strategy based on forecasted sales volume and average loss rate. The system considers limited sales space and uses the entropy method to calculate weights for key indicators like total profit. It employs the TOPSIS method to sort items, considering forecasted wholesale prices, to select items for pricing decisions. The system aims to maximize total profit while ensuring the supermarket meets minimum display conditions. By assisting supermarkets in formulating more reasonable pricing strategies, it aims to reduce overstock, backlog, or stock shortages, ultimately improving sales volume and operational efficiency.

Linear Regression Analysis in Predicting the Amount of Stock of HP Sparepart Goods in GMT

The rapid advancement of the digital era has made smartphones an essential part of daily life, making the availability of high-quality spare parts crucial for their seamless operation. GMT, a store specializing in smartphone spare parts, faces challenges in predicting fluctuating consumer demand, often leading to either stock shortages or excesses. To address this issue, this research develops a stock prediction system based on linear regression, which analyzes sales data to accurately forecast stock needs. The implementation of this method has resulted in improved accuracy in stock management, enabling GMT to optimize inventory, minimize potential losses, and enhance both customer satisfaction and operational efficiency.

Performance Comparison of ARIMA, LSTM, and Prophet Methods in Sales Forecasting

The development of the business world that is growing rapidly today resulted in tighter competitiveness between fellow business actors. One of the businesses that has sprung up in the market today is the bakery business. Currently, bread is one of the food needs in Indonesia that is great demand by children to the elderly, which is often used as breakfast or snack. One of the companies that produces white bread is the Bandung White Bread Factory. The number of sales at this factory continues to increase every month based on total sales data recorded since 2021. With the increasing number of sales at this factory, the factory often experiences stock shortages and cannot meet customer demand. Therefore, in this study, a model has been developed to forecast the sales of white bread using the ARIMA, LSTM, and Prophet methods. The results of the study showed that the ARIMA method (1,0,2) had the best performance compared to the LSTM and Prophet methods, because the ARIMA method (1,0,2) produced the smallest error accuracy value, namely with a MAPE value of 4.548%, an MSE value of 2248.0822, and an RMSE value of 47.4139.

Enhanced Pharmacy Service Delivery Through a Pharmacy Information System at a Medical Center: A Case Study.

A pharmacy information system (PIS) is a crucial tool for preventing errors and enhancing patient safety. This study aims to assess the influence of a PIS on workflow and medication errors (MEs) within the pharmacy department of a medical city in Saudi Arabia. The analysis encompasses an evaluation of the current workflow within pharmacy modules (in-patient, out-patient, and clinical pharmacy modules) and an exploration of associated challenges and inefficiencies. The study employed both qualitative and quantitative methodologies, incorporating structured interview techniques and the review of system records, such as logs, incident reports, and ME databases. Respondents recognized the benefits of the PIS, including the management of high-quality real-time data (26%), reduction of MEs (25%), acceleration of healthcare practices (23%), and absence of space-time constraints (14%). The study highlighted the role of PIS in addressing medication stock control and shortage issues, thereby improving overall medication availability. Furthermore, PIS significantly enhanced safety (93.3%), efficiency (80%), reliability, accuracy, ease of use (56.7%, 56.7%), and cost-effectiveness (53.7%). Following the implementation of the PIS, there was an increase in ME reporting, indicating improved error detection and management. The research revealed an increase in ME reporting rates in hospitals after PIS installation, attributed to improved medication management processes resulting in higher detection rates. As healthcare facilities increasingly embrace electronic medical records, the understanding of patient care quality will be significantly impacted. Consequently, further research is warranted to explore the role of PIS in reporting, detecting, analyzing, and mitigating MEs, as well as their influence on the work environment to promote a secure and efficient patient journey.

Study of the Procurement of Landscape Plant Nurseries in Sukamantri Village Tamansari Sub-district Bogor Regency

Abstract Nurserymen play an important role in the landscape industry by producing and providing plants according to the required specifications. Sukamantri Village is one of the centers of landscape plant production and sales in Bogor Regency. The main problem faced by the nursery is the fluctuating demand for landscape plants, which can cause a shortage or excess of plant stock. This research was conducted in Sukamantri Village, Tamansari Sub-district, Bogor Regency, from November 2022 to February 2023. This study aims to obtain information on the variety of plants in the nurseries and analyze the problems in order to obtain recommendations for the development and sustainability of the nursery. Data obtained through surveys, interviews, and secondary data. They were analyzed quantitatively and qualitatively using the SWOT approach regarding internal and external factors in the procurement of landscape plants. The results show the variety of plants includes indoor and outdoor ornamental plants, herbal plants, and fruit plant seedlings. The problem faced is the decline in domestic and foreign sales. Some of the recommended strategies include developing human resource skills, improving production technology, better planning production, promoting on social media, and expanding the market by strengthening networks.

Analysis of Supply Chain Management on Audio System Product at CV. Cipta Mekar

This study aims to analyze the supply chain management performance of audio system products at CV. Create Bloom. Another objective is to find out the material flow, information flow, and product flow run by CV. Cipta Mekar. The research method used is descriptive qualitative, using purposive sampling technique. Data collection techniques in this study were observation, interviews and documentation. In addition, performance assessment is carried out using the Scor Model. The results showed that the material flow did not run properly. The flow of information with a circular communication pattern and the simultaneous dissemination of information did not go well. In the product flow there is a shortage of stock and there is no quality control process. The results of the Scor Model show that the daily inventory performance is not good. In this case, there are still many things that need to be improved in the supply chain management of audio system products on CV. Cipta Mekar.

ANALISIS BIAYA PRODUKSI DAN PENGELOLAAN PERSEDIAAN PADA PERUSAHAAN PT NOORE SPORT INDONESIA DI KOTA BANDUNG

Effective production cost management is crucial for determining competitive selling prices, especially when facing competitors offering similar products at affordable prices. Inventory management plays a vital role in the sales process, making it essential for companies to manage and monitor their inventory effectively. This research addresses the challenges faced by companies regarding suboptimal production cost calculations and inadequate inventory management, leading to stock shortages. The study aims to analyze the practices employed by companies to optimize production costs and manage inventory efficiently, thereby maintaining product quality and responding to market changes. The focus is on understanding how companies identify, measure, and control production costs and manage inventory efficiently. The research employs descriptive and quantitative methods, including observations, interviews, and documentation related to production cost reports and inventory data. The findings indicate that current company policies are not optimal and lack efficiency. This study compares the company's production cost calculations with the full costing method and applies the Economic Order Quantity (EOQ) method for inventory management to enable efficient inventory control. The implications suggest that adopting these methods can significantly improve production cost management and inventory efficiency, providing a competitive edge in the market

Optimasi Pengendalian Pengadaan Barang Consumable Menggunakan Metode Economic Order Quantity di PT. ZZ

One of the most important things for companies, especially those operating in the manufacturing industry, is inventory. Often there is a shortage or excess of stock in companies when inventory control is still not optimal. PT. ZZ is a manufacturing company which supplies consumable goods with 1 inch paper duct tape as supporting goods in the excavator assembly process. These goods often experience stock shortages so that the production process is disrupted. To overcome this problem, it is necessary to carry out an analysis using the Economic Order Quantity (EOQ) approach to determine order size, order frequency, safety stock, and reorder point. The results obtained were a Total of 892.23 orders, with orders made twice a year and an interval of 130 days. Apart from that, a safety stock of 89 pcs was also produced and are order point of 115 pcs. Furthermore, according to company policy, all costs required to purchase consumable materials such as 1 inch paper duct tape are IDR 1,632,200. Meanwhile Rp. 290,196.61 is the amount needed if applying the EOQ approach. This means that the company can save IDR 1,342,003.39 if the company controls its procurement of goods using the EOQ approach. Keywords: Consumables, Economic order quantity, Inventory, Procurement