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Jurnal SINTA 2

RANCANG BANGUN OPTIMASI KEBUTUHAN BAHAN BAKU MENGGUNAKAN ALGORITMA WAGNER-WHITIN

JUTI: Jurnal Ilmiah Teknologi Informasi · Vol. 7 No. 4 (2009) · pp. 177–182

DOI
10.12962/j24068535.v7i4.a87
ISSN
2406-8535, 1412-6389
Published
2009-07-01
Publisher
Institut Teknologi Sepuluh Nopember
Language
eng

Abstract

Lotting or purchasing raw materials is one step in Material Requirement Planning. Lotting technique that already known is the Wagner-Within algorithm. This algorithm is widely used because it provides optimal solutions for problem sizedeterministic dynamic reservation at a particular time period in which the needs of the entire period must be completed. It takes a application system of optimization planning raw material requirements using the Wagner-Whitin algorithm. The development of this process begins with building a power module of demand data using Arima method (1,1,1), then followed by forecasting modules of consumer demand for end product by using the multiplicative decomposition forecasting methods, and ends with the development of Materials Requirement Planning module (MRP I) using the Wagner-Whitin algorithm. The results of the test system with test data is the generation of data will form the same pattern that is likely up from week to week. Forecasting results have high accuracy registration of 99.48%, 99.64% and 99.68%. Wagner-Whitin algorithm always produces the combination of weeks. Result of the combination in the first week will produces the minimum cost for the entire week of production.

Collaboration network of the authors

15 authors · 23 co-authorship links · 2 across different organisations

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  • Institut Teknologi Sepuluh Nopember
  • University of Brawijaya
  • King Abdulaziz University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nanik SuciatiInstitut Teknologi Sepuluh Nopember2
Nanang Yudi SetiawanUniversity of Brawijaya1
Aulia BaharAffiliation unknown1
Ahmad Hoirul BasoriKing Abdulaziz University1
Wahyu Budi SurastyoAffiliation unknown1
Rully SoelaimanInstitut Teknologi Sepuluh Nopember1
Esther HanajaInstitut Teknologi Sepuluh Nopember1
Myke Noor ArianiAffiliation unknown1
Riyanarto SarnoInstitut Teknologi Sepuluh Nopember1
Nurul Fajrin AriyaniInstitut Teknologi Sepuluh Nopember1
Alief Yoga PriyantoInstitut Teknologi Sepuluh Nopember1
Rangga Kurnia Putra WiratamaInstitut Teknologi Sepuluh Nopember1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://juti.if.its.ac.id/index.php/juti/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en">RANCANG BANGUN OPTIMASI KEBUTUHAN BAHAN BAKU MENGGUNAKAN ALGORITMA WAGNER-WHITIN</dc:title>
	<dc:creator xml:lang="en">Saikhu, Ahmad</dc:creator>
	<dc:creator xml:lang="en">Sarwosri, Sarwosri</dc:creator>
	<dc:creator xml:lang="en">Laila, Nur</dc:creator>
	<dc:description xml:lang="en">Lotting or purchasing raw materials is one step in Material Requirement Planning. Lotting technique that already known is the Wagner-Within algorithm. This algorithm is widely used because it provides optimal solutions for problem sizedeterministic dynamic reservation at a particular time period in which the needs of the entire period must be completed. It takes a application system of optimization planning raw material requirements using the Wagner-Whitin algorithm. The development of this process begins with building a power module of demand data using Arima method (1,1,1), then followed by forecasting modules of consumer demand for end product by using the multiplicative decomposition forecasting methods, and ends with the development of Materials Requirement Planning module (MRP I) using the Wagner-Whitin algorithm. The results of the test system with test data is the generation of data will form the same pattern that is likely up from week to week. Forecasting results have high accuracy registration of 99.48%, 99.64% and 99.68%. Wagner-Whitin algorithm always produces the combination of weeks. Result of the combination in the first week will produces the minimum cost for the entire week of production.</dc:description>
	<dc:publisher xml:lang="en">Institut Teknologi Sepuluh Nopember</dc:publisher>
	<dc:date>2009-07-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://juti.if.its.ac.id/index.php/juti/article/view/87</dc:identifier>
	<dc:identifier>10.12962/j24068535.v7i4.a87</dc:identifier>
	<dc:source xml:lang="en">JUTI: Jurnal Ilmiah Teknologi Informasi; Vol 7, No 4, Juli 2009; 177-182</dc:source>
	<dc:source>2406-8535</dc:source>
	<dc:source>1412-6389</dc:source>
	<dc:source>10.12962/j24068535.v7i4</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://juti.if.its.ac.id/index.php/juti/article/view/87/83</dc:relation>
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