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HOLT-WINTER METHOD FOR FORECASTING LIQUID ALUMINIUM SULFATE USAGE FOR PROBABILISTIC INVENTORY MODELING Q WITH ERLANG DISTRIBUTION

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 19 No. 1 (2025) · hlm. 453–464

DOI
10.30598/barekengvol19iss1pp453-464
ISSN
2615-3017, 1978-7227
Terbit
2025-01-13
Penerbit
PATTIMURA UNIVERSITY
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

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  • Sriwijaya University
  • University of Malaya
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Rekan penulisOrganisasiArtikel bersama
Indrawati IndrawatiSriwijaya University4
Eka SusantiSriwijaya University4
Novi Rustiana DewiSriwijaya University4
Ahmad Farhan RamadhanSriwijaya University4
Ahmad RindartoSriwijaya University4
Sisca OctarinaSriwijaya University3
Robinson SitepuSriwijaya University2
Yusuf HartonoSriwijaya University2
Nadia Zuliaty SyaputriSriwijaya University2
Weni Dwi PratiwiSriwijaya University2
Putra BJ BangunAfiliasi tidak diketahui2
Bambang SuprihatinSriwijaya University2
Divasanda ArmaliaSriwijaya University2
Endro Setyo CahyonoSriwijaya University2
Anggi Nurul PratiwiSriwijaya University1
Icha Puspita NovyastiSriwijaya University1
Irmeilyana IrmeilyanaSriwijaya University1
Rahayu Tamy AgustinSriwijaya University1
Sri ErlitaSriwijaya University1
Inosensius NadeakSriwijaya University1
Elika KurniadiSriwijaya University1
Yunita YunitaSriwijaya University1
Shintya ApriliyaniSriwijaya University1
Ani Sahara Br. SimanjuntakSriwijaya University1
Rima MelatiSriwijaya University1
Ning EliyatiSriwijaya University1
Sri Indra MaiyantiSriwijaya University1
Shaly Wanda HamidahSriwijaya University1

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Sumber metadata: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, pertama di-harvest 5 Nov 2026, terakhir terlihat 5 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">HOLT-WINTER METHOD FOR FORECASTING LIQUID ALUMINIUM SULFATE USAGE FOR PROBABILISTIC INVENTORY MODELING Q WITH ERLANG DISTRIBUTION</dc:title>
	<dc:creator>Dwipurwani, Oki</dc:creator>
	<dc:creator>Puspita, Fitri Maya</dc:creator>
	<dc:creator>Supadi, Siti Suzlin</dc:creator>
	<dc:creator>Yuliza, Evi</dc:creator>
	<dc:creator>Qatrunnada, Dhiya</dc:creator>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2025-01-13</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14252</dc:identifier>
	<dc:identifier>10.30598/barekengvol19iss1pp453-464</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application; 453-464</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol19iss1year2025</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/14252/9569</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2025 Oki Dwipurwani, Fitri Maya Puspita, Suzlin Supadi, Evi Yuliza, Dhiya Qatrunnada</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>