The increase in rice consumption should be balanced with an increase in rice production. However, although the national rice production was declared a surplus, the volume of national rice imports also increased. The imports in 2018 were 2.2 million tons and showed that surplus rice production is not effectively taken as an advantage in overcoming the deficit in some provinces in Indonesia. Some provinces that experiencing surplus should be able to fill the shortage in the other provinces. This paper contributes to determine distribution routes and help the government to fulfill the shortage demand. This study uses the two-steps linear programming method. The first step is performed by the transportation model and followed by the Capacitated Vehicle Routing Problem (CVRP) model in sequence. This two-step linear programming reaches an optimal global solution in distributing goods from oversupply provinces to the over-demand one. The results show cost savings are gained if this strategy is performed to meet the demand, rather than importing the rice.
The consumption pattern of the people in Indonesia is experiencing a shift. Consumption patterns that are influenced by socio-cultural factors today make people tend to consume food and drinks that are practical and easy to obtain. This pattern began in 2014 until now, making the percentage of food consumption increase by 2.5% per year. Bread is a finished food whose demand pattern has also increased. Due to the development of the middle-class population, an increase in the income of young people, and society's consumption pattern, which is increasingly shifting to a practical urban consumption pattern. The bread industry in Indonesia is still classified as the small and medium enterprises (SME) sector. Small and medium enterprises (SME) is a business sector with a significant impact on improving the economy in developing countries. The products are distributed to offices that work with bakeries and are sold in stores. This shows that the shop production must work quickly to meet consumer demand in the surrounding area. In fulfilling consumer demand, a production quality control process is required in the workstation to reduce defective products. This study aims to carry out a quality control process to reduce faulty products by using a control chart and the concept of kaizen to control and maintain the production process in bread SMEs so that quality and work effectiveness can be realized.
The blood service is a health service that utilizes human blood as basic material with humanitarian purposes, not for commercial one. Indonesian hospital ability in blood transfusions is generally still low, especially in terms of blood supply adequacy. In fact, there are still some provinces that experience excess blood supply while many other provinces experience a shortage of blood supply. The Blood Bank in Jakarta has the highest excess blood supply. Therefore, the blood can be transferred evenly from one province to another nearby province. The aim of this paper is to determine the allocation and the route of blood distribution to achieve the minimum travel times. Some variations in travel time are difficult to predict, so we take into account the stochastic properties of them. The effectiveness of blood distribution is very dependent on the accuracy of the target number of beneficiaries and the accuracy of the number of blood bags received in distribution activities. Meanwhile, the efficiency of blood bag distribution is measured by distribution routes that are directly related to transportation costs. This study uses a two-step optimization model to reach optimality. The first step is utilizing the transportation model to make sure the destination points are only the fastest to arrive. The second step is making use of the capacitated vehicle routing problem to ensure the routing is global optimal. This model successfully creates better blood demand fulfillment while minimizing transportation cost.
<p>The company discussed in this paper is a national distributor firm that distributes FMCG products. The PPIC division in the company is responsible for forecasting the demand using the combination of the moving average method and intuition according to the interest of the company. However, the PPIC staff never measures the accuracy of their forecasting method. This research paper aims to evaluate the forecasting methods used to predict the demands of 12 classes of A SKU. Four-time series forecasting methods are particularly implemented, i.e., ARIMA, moving average (MA), double exponential smoothing (DES), and linear regression (RL). Forecasting using the ARIMA method is carried out by considering the stationarity of the average and variance of the historical data points. Forecasting using DES is carried out by using the optimal alpha and gamma values of the ARIMA method. The results show that the performance of each forecasting method varies, depending on which demands of class A SKU are predicted. Based on these results, the current forecasting method utilized by the company should be improved using the time series forecasting methods leading to the smallest error values for each class of A SKU.</p>
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