Identification of customer needs in the future, can be known by measuring the company's current performance. The purpose of the study was to measure the supply chain performance index of the coffee agroindustry in Ciporeat Village, Cilengkrang, Bandung Regency by using the Supply Chain Operations Reference (SCOR). Performance measurement is carried out by following 6 stages of research, namely, identifying level 1 supply chain networks, determining supply chain objectives, determining the coffee agroindustry supply chain hierarchy based on reliability and responsiveness, calculating weights using AHP, normalizing data and measuring coffee agroindustry supply chain performance. The results of the normalization calculation are used for the calculation of the performance index. The results of the performance calculation show that the supply chain performance of the coffee agroindustry in Ciporeat Village is very good, which is 96.5% (above 90%).
Blood supply chain manages the flow of blood product from donors to patients. One of the service provider is PMI which contributes 92% of blood national donation. In fact, demands and supplies of in a blood supply chain are often unpredictable. They contribute to the occurrence of risks which have direct impacts on human life. Thus need a risk management to mitigate such impacts. One way to do so is by using Supply Chain Operational Reference (SCOR) model for mapping the activities of blood chain. Thus, it can facilitate the identification of risk events and risk agents. Further risk events and risk agents are processed using House of Risk (HOR). While the aim of HOR1 is to identify priority of the risk events, the HOR2 arranges necessary mitigation strategies. Moreover, in this work, there are 9 risk agents chosen from HOR1 and 8 preventive actions for the mitigation. Additionally, this research develop a monitoring system that may assist to monitor the occurring risks.
One of the key performance indicators for the logistics industry, especially freight forwarder company (cargo), is the delivery time. This is still a challenge in this industry in terms of ensuring the customer service level and reducing transportation costs. On the other hand, the development of information technology now allows an organization or company to collect large amounts of data automatically. A decent method that can be used to analyze the data for prediction purposes is machine learning, which is a method of extracting data into a certain pattern of information. This research aims to apply three machine learning methods to estimate the status of shipping goods. The method used in this study follows the machine learning process published by the Cross Industry Standard Process for Data Mining (CRISP-DM), namely; business processes understanding, data understanding, data preparation, model development, evaluation, and implementation. Based on the results of the study, the random forest method produces better accuracy than the logistic regression and artificial neural network (ANN) methods, which is 76.6%, while the results of ANN and logistic regression methods are 73.81% and 72.84% respectively.
Distribution activities are an important part and very considered in the world of logistics because distribution is one of the key drivers of profits earned by companies. One that is related to distribution is transportation. Transportation refers to moving products from one location to another where the product moves from the beginning of the supply chain to consumers where this transportation will incur costs and is one of the costs that affect the price of a product. This research aims to schedule ship transportation from 3 production ports to 6 consumption ports with a heterogeneous fleet of ships to minimize the total transportation costs in the cement industry companies. Maritime Inventory Routing Problem (MIRP) is a problem of ship scheduling which is not only related to the distribution of products from production ports to consumption ports, it also manages the inventory at these ports and is usually used for bulk industrial products. The method used in this research is MIRP with Mixed-Integer Linear Programming (MILP) approach where this method can minimize the total transportation costs. The results show that the method used can reduce the total waiting time so that the total transportation costs are also reduced.
This research was carried out at one of the companies engaged in the cement industry, which distributed its products throughout Indonesia. However, based on audit results for the Central Java region, there are still a number of minor and major statuses in warehouse management perspectives and the percentage of warehousing cost components to the total distribution costs that exceed the maximum limit set at the warehouses rented from the distributor. Therefore, it’s necessary to determine a new distribution warehouse location owned by the company by considering qualitative and quantitative aspects, then stop the operation of a rented warehouse from a distributor because of the high subsidy costs. The method used in this research is investment feasibility analysis using Net Present Value and Benefit Cost Ratio calculations, determining optimal locations using the P-Median method, and determining location based on multi-criteria using the Analytical Network Process method. The results showed that the location with the highest weight based on multi-criteria decision making and declared feasible based on investment feasibility analysis was located in Cilacap Regency with the optimal location in North Cilacap District. If this decision is carried out, the company can reduce the total distribution costs that must be incurred by the company.
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