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Inventory Model for Deteriorating Pharmaceutical Items with Linear Demand Rate Indrawati; Puspita, Fitri Maya; Supadi, Siti Suzlin; Yuliza, Evi; Rizki, Krisda
Science and Technology Indonesia Vol. 9 No. 1 (2024): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.1.148-155

Abstract

Good management of goods is needed so that the inventory activities of a business can run smoothly as the part of supply chain management which aims to monitor the flow of stock of goods from the purchasing process, and storage to the point of sale. In terms of inventory or supplies of pharmaceutical goods, conditions such as shortages or stockouts must also be considered which are a matter of control, management, and security. In this study, an inventory model is formulated with deterioration or damage to pharmaceutical goods that occurs due to the length of time when the goods are stored with a linear demand level. In the optimal solution, the inventory time occurs when it reaches the zero point (t1) of 0.34 and the cycle length (T1) of 0.83 with an average minimum total cost (TC) of $445.25 per cycle which is completed by WolframAlpha software. Sensitivity analysis changes the value results in the value of (TC) which that increases for all parameters. In increasing the linear function variables (a and b), it produces t1 and T1 stable values. An increase in the cost of each item damage (DC) and constant damage rate (theta) produces a t1 stable value, but the value of T1 increases. The increase in storage costs (h) results in a decrease in the value of t1 and T1. An increase in the cost of shortages (s) results in an increase in the value of t1 and a decrease in the value of T1.
Probabilistic Multi-Item Inventory Model for Chemicals in Regional Drinking Water Company Dwipurwani, Oki; Puspita, Fitri Maya; Supadi, Siti Suzlin; Yuliza, Evi
Science and Technology Indonesia Vol. 9 No. 4 (2024): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.4.1024-1032

Abstract

Inventory management of chemicals in The Regional Drinking Water Company (Perusahaan Daerah Air Minum, PDAM) is known to play an essential role in ensuring the smooth production of clean water and preventing shortages of chemicals that can affect production. At present, 2 primary models for multi-item inventory replenishment are under consideration by PDAM, namely individual and joint replenishment of items. Therefore, this study aims to evaluate the efficiency and effectiveness of individual and joint replenishment models based on uncertain demand with specific probability distribution. The results showed that a probabilistic inventory model (Q, r) with individual replenishment for chemicals in PDAM was recommended.
Minitab 20 and Python based-the forecasting of demand and optimal inventory of liquid aluminum sulfate supplies Dwipurwani, Oki; Puspita, Fitri Maya; Supadi, Siti Suzlin; Yuliza, Evi
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i3.pp1796-1807

Abstract

In a company, inventory management is crucial due to the significant impact on various aspects of the business. Similarly, the Indonesian water supply company (PDAM) requires effective inventory management to ensure the supply of liquid aluminum sulfate chemicals. The probabilistic statistical inventory control (SIC) model is commonly used for inventory management. However, previous research on chemical inventory models in PDAMs often relied on simple linear regression to forecast demand data, which fails to capture the inherent volatility in demand. Therefore, this research aimed to predict demand data using the seasonal autoregressive integrated moving average (SARIMA) method and determine the optimal policy for supplying liquid aluminum sulfate chemicals. The results showed that the best demand forecasting model was SARIMA (2,1,2) (1,1,0)12 with a mean absolute percentage error (MAPE) value of 8.19%. The finding of the optimal inventory policy showed a safety stock value of 11,922.35 kg, a reorder point value of 49,511.20 kg, and an order quantity of 21,526.59 kg, leading to a total cost of IDR 11,132,034,145.45. The sensitivity test also showed that variations in lead time, price, μ, and σ parameters directly influence changes in total cost, reorder point, and safety stock. These calculations were conducted using Minitab and Python software.
Improve fractal interpolation function with Sierspinski triangle Susanti, Eka; Puspita, Fitri Maya; Supadi, Siti Suzlin; Yuliza, Evi; Fadhila Chaniago, Redina An
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1485-1492

Abstract

Interpolation techniques can be used to determine the approximate value of a parameter if it is known that two values are bound to a certain interval. Interpolation can be done numerically or fractal. The fractal interpolation value is influenced by the vertical scale factor and the fractal interpolation function (FIF). This research introduces fractal interpolation technique with FIF which is constructed from Sierspinski triangles. As an example of application, the interpolation technique is applied to determine the approximate value of the rice demand parameter in the inventory model. The accuracy of the interpolation results is determined using the mean absolute percentage error (MAPE). The number of triangles obtained and the interpolation values for each successive iteration are 3???? and 3????+1. MAPE values from 6 to 9 iteration were 24.603%, 24.603%, 23.858%, 23.772% respectively. There is a decrease in the value of MAPE, this indicates an increase in the value of the accuracy of the interpolation results. It can be concluded that the MAPE value is also influenced by the number of iterations of the interpolation technique.
OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD Susanti, Eka; Puspita, Fitri Maya; Yuliza, Evi; Supadi, Siti Suzlin; Dwipurwani, Oki; Dewi, Novi Rustiana; Ramadhan, Ahmad Farhan; Rindarto, Ahmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1215-1220

Abstract

Interpolation is a method to determine the value that is between two values and is known from the data. In some cases, the data obtained is incomplete due to limitations in data collection. Interpolation techniques can be used to obtain approximate data. In this study, the Lagrange interpolation method of degree 2 and degree 3 is used to interpolate the data on rice demand. A trapezoidal fuzzy number expresses the demand data obtained from the interpolation. The other parameters are obtained from company data related to rice supplies and are expressed as trapezoidal fuzzy numbers. The interpolation accuracy rate is calculated using Mean Error Percentage (MAPE). The second-degree interpolation method produces a MAPE value of 30.76 percent, while the third-degree interpolation has a MAPE of 32.92 percent. The quantity of order respectively 202677 kg, 384610 kg, 1012357 kg, 1447963 kg, and a Total inventory cost of Rp. 129231797951.
HOLT-WINTER METHOD FOR FORECASTING LIQUID ALUMINIUM SULFATE USAGE FOR PROBABILISTIC INVENTORY MODELING Q WITH ERLANG DISTRIBUTION Dwipurwani, Oki; Puspita, Fitri Maya; Supadi, Siti Suzlin; Yuliza, Evi; Qatrunnada, Dhiya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp453-464

Abstract

Water is a natural resource important for life and daily activities. Water distributed by the Regional Drinking Water Company (PDAM) should include a coagulation process using liquid aluminum sulfate as a coagulant before it can be consumed. Therefore, this research aims to predict the need for liquid aluminum sulfate in PDAM from 2023 to 2024 using Holt-Winter's method. It also aims to evaluate the optimum liquid aluminum sulfate chemical inventory policy using Q probabilistic inventory model with Normal and erlang probabilistic distributions in PDAM. The data was obtained from Tirta Musi PDAM in Palembang City, Indonesia. The results of forecasting liquid aluminum sulfate demand level data with the Holt-Winter multiplicative method provide the smallest MAPE value. The erlang probability distribution assumption has been met through the Kolmogorov Smirnov test method. The erlang probabilistic inventory model provides a more optimal policy solution than the normal probabilistic inventory model, with minimum total cost and higher service level.
Wolfram Alpha based-inventory model for damaged items of pharmaceutics by utilizing exponential demand rate Indrawati, Indrawati; Puspita, Fitri Maya; Supadi, Siti Suzlin; Yuliza, Evi; Tampubolon, Farah Nabilah
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1145-1154

Abstract

In this study, an inventory model is developed for pharmaceutical products that deteriorate over time with an exponential demand rate. The discussion of exponential demand is rarely explored but has the advantage that the demand value toward total cost remains positive. This study assumes allowable shortages and complete backlogging, making it necessary to design an optimal policy for deteriorating goods with an exponential demand rate. The model shows that the initial stock decreases over time, potentially leading to shortages before the next order arrives. The optimal solution indicates that the inventory reaches the zero point at ????1 = 0.0000011 and the cycle length ????1 = 0.012 resulting in an average minimum total cost of ????????̅̅̅̅ = $17,133.9 per cycle by Wolfram Alpha. Sensitivity analysis measures the changes of the results in the increasing value of ????????̅̅̅̅ for all parameters. Exponential function variables (???? and ????) produces ????1 and ????1 stable values. On increasing the cost of each damage (????????) and constant damage rate (????) produces a ????1 stable value, but the value of ????1 increases. An increase in storage costs (h) results in a decrease in the value of ????1 and ????1. Increasing in the cost of shortages (s) resulted in an increase in the value of ????1 and a decrease in the value of ????1.