THE DEVELOPMENT OF PERUM BULOG’S RICE IMPORT QUANTITY DETERMINATION MODEL TO CONTROL THE INCREASING RATE OF RICE RETAIL PRICE

• Main Author: Shafwan Rasyid, Arif
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/86979
• Institution: Institut Teknologi Bandung

Rice is a staple food with a high level of consumption in Indonesia, and its consumption level is predicted to continue to increase if we look at the trend of increasing population in Indonesia. This makes rice have an important role in maintaining national food security. However, the phenomenon that is happening today is that the level of rice production continues to decline. An imbalance in the demand and supply of rice will result in a scarcity phenomenon characterized by the price of rice that continues to increase. Perusahaan Umum (Perum) Badan Usaha Logistik (BULOG) plays the role of a State-Owned Enterprise that is tasked with maintaining a balance in the demand and supply of rice through rice imports to maintain the stability of the retail price of rice in the market, in addition to its main goal of obtaining maximum profits. This study develops an optimization model to determine the amount of rice that must be imported by Perum BULOG to minimize the increase in rice price between 2 consecutive months. The retail market price of rice will be predicted each month by considering factors that affect rice prices, in addition to the harvest season factor. The determination of the amount of rice imports is carried out by first modeling the rice supply chain network managed by Perum BULOG. The modeled rice supply chain network includes Perum BULOG rice stocks, Perum BULOG rice suppliers consisting of domestic rice mills and import source countries, as well as Perum BULOG rice consumers. The supply chain network model is represented in the form of a linear programming model with decision variables in the form of the amount of rice supplied from the source country of import per month and the function of minimizing the increase in rice price between 2 consecutive months. The retail market price of rice in a month is predicted using factors that affect the retail rice market price, namely the level of rice production, the exchange rate of the rupiah against the dollar, Gross Domestic Income (GDP) per capita, the area of agricultural land, the price of Harvested Dry Rice (GKP) per kg, the price of Ground Dry Rice (GKG) per kg, the amount of rice supplied from domestic rice mills per month, the amount of rice supplied from the source country of imports per month, the amount of rice stored as Perum BULOG stock per month, and the amount of rice distributed by Perum BULOG to rice consumers per month. Retail rice market price prediction is modeled using a machine learning method of a compound linear regression model. The values of each explanatory variable are estimated using the appropriate method for the historical data pattern of each explanatory variable. The rice production rate, the rupiah exchange rate against the dollar, the area of agricultural land, the price of GKP per kg, the price of GKG per kg, and the amount of rice supplied from domestic rice mills per month are estimated using the triple exponential smoothing approach. GDP per capita is estimated using a double exponential smoothing approach. Perum BULOG's rice consumer demand is estimated using the triple exponential smoothing approach, and the amount of rice distributed by Perum BULOG to rice consumers per month is determined to be able to meet these needs. Perum BULOG's rice stock at the end of the month is the result of the addition of Perum BULOG's rice stock at the beginning of the month plus the amount of rice supplied from domestic rice mills and from import source countries minus the rice distributed by Perum BULOG to meet consumer needs. Rice imports are carried out if Perum BULOG's rice stock at the end of the month is less than the lower limit value of the strategic inventory, and the amount of rice imports is determined so that Perum BULOG's rice stock at the end of the month is at least a certain number of the lower limit of the strategic inventory. The model developed was tested to determine the quantity of rice imports for 4 periods, namely 2020, 2021, 2022 and 2023. The results of the model test show that the rate of increase in rice price between 2 consecutive months can be controlled at a maximum price increase rate ranging from 0.42% to 0.53% with a standard deviation ranging from 0.39% to 0.53%. These values are lower than the expected price increase rate, which is 2-3 %. Sensitivity analysis was carried out on the model developed by changing the lower limit value of the strategic inventory. The results of the sensitivity analysis show that the rate of increase in rice price for 2 consecutive months remains controllable and never greater than 1%.