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Proceedings of the 3rd Sriwijaya International Conference on Basic and Applied Sciences, SICBAS 2023, November 3, 2023, Palembang, Indonesia

Research Article

Chlorine Gas Inventory Model with Exponential Demand and Holt-Winters Forecasting

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  • @INPROCEEDINGS{10.4108/eai.3-11-2023.2347899,
        author={Oki  Dwipurwani and Fitri Maya Puspita and Siti Suzlin Supadi and Evi  Yuliza},
        title={Chlorine Gas Inventory Model with Exponential Demand and Holt-Winters Forecasting},
        proceedings={Proceedings of the 3rd Sriwijaya International Conference on Basic and Applied Sciences, SICBAS 2023, November 3, 2023, Palembang, Indonesia},
        publisher={EAI},
        proceedings_a={SICBAS},
        year={2024},
        month={8},
        keywords={water supply company (pdam) holt-winters forecasting exponential probabilistic inventory model},
        doi={10.4108/eai.3-11-2023.2347899}
    }
    
  • Oki Dwipurwani
    Fitri Maya Puspita
    Siti Suzlin Supadi
    Evi Yuliza
    Year: 2024
    Chlorine Gas Inventory Model with Exponential Demand and Holt-Winters Forecasting
    SICBAS
    EAI
    DOI: 10.4108/eai.3-11-2023.2347899
Oki Dwipurwani1, Fitri Maya Puspita2,*, Siti Suzlin Supadi3, Evi Yuliza2
  • 1: Science Doctoral Program Mathematics and Natural Science, Sriwijaya University, Indralaya, 30662, Indonesia
  • 2: Mathematics Department, Faculty of Mathematics and Natural Sciences, Sriwijaya University, Indralaya, 30662, Indonesia
  • 3: Institut of Mathematical Sciences, University of Malaya, Kuala Lumpur, 50603, Malaysia
*Contact email: fitrimayapuspita@unsri.ac.id

Abstract

Inventory management is very important to Water Supply Company (PDAM) to ensure the consistent availability and reliability of chlorine gas. Chlorine gas is important in the disinfecting process of clean water production. In addition, the demand for chlorine gas since 2020 has experienced high volatility. Therefore, this study aimed to develop a probabilistic Chlorine Gas inventory model, which used the (Q,r) and (R,T) model, with demand following exponential distribution. Demand data used in model were based on forecasts for multiple future periods. The results showed that the most accurate demand forecasting model for Chlorine Gas was achieved through the application of the Multiplicative Holt-Winters method. The optimal inventory management policy, as established by the (Q,r) model, prescribed a reorder point (r) of 1,933.76 kg, order lot size (Q) of 1,049.36 kg, and a total cost (Tc(Q,r)) amounting to IDR 2.706.523.392,76. This model also achieved a service level of 99.98%.

Keywords
water supply company (pdam) holt-winters forecasting exponential probabilistic inventory model
Published
2024-08-02
Publisher
EAI
http://dx.doi.org/10.4108/eai.3-11-2023.2347899
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