Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/10297
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dc.contributor.authorMaria Ompusunggu, Vina-
dc.contributor.authorDewi Kartini Ompusunggu, Vera-
dc.contributor.authorRiahta Br Tarigan, Selvida-
dc.contributor.authorChindy Lawken Br Tarigan, Silvani-
dc.date.accessioned2025-06-04T02:08:46Z-
dc.date.available2025-06-04T02:08:46Z-
dc.date.issued2024-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/10297-
dc.description.abstractBusinesses, whether in commerce, industry, or services, must continue to optimize their operations in an attempt to gain market share due to the business world's rapid expansion. Laundry is one of the businesses in the service industry. A company that offers washing and ironing services is called Laundry. Finding the laundry business's greatest profit in Sudirejo I Village is the aim of this study. One strategy for resolving optimization issues, such as linear or integer programming issues, is the Branch and Bound method. This approach can be used to identify the best course of action when it comes to optimizing laundry service profitability. For instance, it can be used to determine the ideal mix of laundry services to maximize income while accounting for a number of current restrictions, including capacity, time, and other resources. There is currently a good allure to Sudirejo I Village's existence. In the neighborhood, there are roughly 19 laundry services. 53 kilogram suits, 32 kg dolls, 95 kg blankets, 105 kg bedcoverings, 91 kg curtains, and 805 kg clothing yield the best laundry profit results, which total Rp 4,027,000. The laundry owner's previous profit, estimated at Rp 4,000,000, represents a 0.7% gain. Keywords: Branch and Bound, Integer Linier Programming, Laundry, Advantagesen_US
dc.subjectBranch and Bound, Integer Linier Programming, Laundry, Advantagesen_US
dc.titlePENERAPAN METODE BRANCH AND BOUND UNTUK MENINGKATKAN KEUNTUNGAN LAYANAN JASA LAUNDRYen_US
dc.typeArticleen_US
Appears in Collections:VOL 5 NO 2 2024

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