<mets:mets OBJID="eprint_76872" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2026-06-17T17:40:23Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>Institutional Repository UIN Sunan Kalijaga Yogyakarta</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_76872_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>PENGEMBANGAN APLIKASI PERENCANAAN PRODUKSI PRODUK BAKERY DENGAN MENERAPKAN SISTEM INFERENSI FUZZY METODE MAMDANI, SUGENO, DAN TSUKAMOTO (STUDI KASUS: CV CAHAYA CIPTA MAKMUR)</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">NIM.: 22106060032</mods:namePart><mods:namePart type="family">R. Rully Mahendra</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>CV Cahaya Cipta Makmur is a food processing company that offers that offers a&#13;
variety of bread products as new items marketed to the general public. As newly&#13;
introduced products, their demand is fluctuating and uncertain. The company&#13;
implements a make-to-order production system to align production quantities with&#13;
incoming demand while avoiding waste caused by overproduction. However, based&#13;
on an analysis of production data from January to March 2026, a discrepancy was&#13;
found between production targets and actual finished goods, indicating&#13;
inefficiencies in raw material usage within the company’s production planning.&#13;
Fuzzy logic was chosen as an approach capable of providing systematic&#13;
calculations to support production decision-making under conditions of uncertainty&#13;
and data fluctuation. This study compares three fuzzy methods, namely Mamdani,&#13;
Sugeno, and Tsukamoto, using historical production data from one of the bread&#13;
products with the highest demand frequency. The results show that the Mean&#13;
Absolute Percentage Error (MAPE) values for each method are 19.96% for&#13;
Mamdani, 2.81% for Sugeno, and 54.85% for Tsukamoto. The Sugeno method&#13;
yields the lowest MAPE value and is therefore identified as the best method with the&#13;
highest level of accuracy among the three. Based on these results, the Sugeno&#13;
method is used as the foundation for developing a decision support system for&#13;
production planning that can be utilized by the company to determine optimal&#13;
production quantities. This system takes into account the level of incoming demand&#13;
as well as the available stock, and is expected to help the company minimize the&#13;
risk of losses due to unsold products while maximizing the efficiency of raw material&#13;
usage and the potential profit gained.</mods:abstract><mods:classification authority="lcc">005.36 Software Development / Pengembangan Perangkat Lunak</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2026-05-20</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>UIN SUNAN KALIJAGA YOGYAKARTA;FAKULTAS SAINS DAN TEKNOLOGI</mods:publisher></mods:originInfo><mods:genre>Thesis</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_76872"><mets:rightsMD ID="rights_eprint_76872_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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