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        <dc:title>PENGEMBANGAN APLIKASI PERENCANAAN PRODUKSI PRODUK BAKERY DENGAN MENERAPKAN SISTEM INFERENSI FUZZY METODE MAMDANI, SUGENO, DAN TSUKAMOTO (STUDI KASUS: CV CAHAYA CIPTA MAKMUR)</dc:title>
        <dc:creator>R. Rully Mahendra, NIM.: 22106060032</dc:creator>
        <dc:subject>005.36 Software Development / Pengembangan Perangkat Lunak</dc:subject>
        <dc:description>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.</dc:description>
        <dc:date>2026-05-20</dc:date>
        <dc:type>Thesis</dc:type>
        <dc:type>NonPeerReviewed</dc:type>
        <dc:format>text</dc:format>
        <dc:language>id</dc:language>
        <dc:identifier>https://digilib.uin-suka.ac.id/id/eprint/76872/1/22106060032_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf</dc:identifier>
        <dc:format>text</dc:format>
        <dc:language>id</dc:language>
        <dc:identifier>https://digilib.uin-suka.ac.id/id/eprint/76872/2/22106060032_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf</dc:identifier>
        <dc:identifier>  R. Rully Mahendra, NIM.: 22106060032  (2026) PENGEMBANGAN APLIKASI PERENCANAAN PRODUKSI PRODUK BAKERY DENGAN MENERAPKAN SISTEM INFERENSI FUZZY METODE MAMDANI, SUGENO, DAN TSUKAMOTO (STUDI KASUS: CV CAHAYA CIPTA MAKMUR).  Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.   </dc:identifier></oai_dc:dc>
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