SISTEM PENDUKUNG KEPUTUSAN PERAMALAN HARGA JUAL TERNAK MENGGUNAKAN METODE TRIPLE EXPONENTIAL SMOOTHING
dc.contributor.author | Revan, Mohammad | |
dc.contributor.supervisor | Bahri, Zaiful | |
dc.date.accessioned | 2022-10-13T04:52:18Z | |
dc.date.available | 2022-10-13T04:52:18Z | |
dc.date.issued | 2022-06 | |
dc.description.abstract | Forecasting selling prices helps to plan for the future so that the price of free-range chicken meat on farms can optimize existing conditions for calculations during one harvest. Decision support systems can help make the right decisions where calculations and planning can be done better and more efficiently.The making of a domestic chicken selling price forecasting system aims to predict the selling price of native chicken at Agung Farm and design a system that can help determine the selling price of native chicken using the Triple Exponential Smoothing method. Calculations using the Triple Exponential Smoothing method will be able to analyze several factors that can be known about an event in the future with the time of the previous event. The system design stage has three diagrams such as use cases, class diagrams, and sequence diagrams. The forecasting results using Triple Exponential Smoothing method for the selling price of free-range chicken at Agung Farm, which is found at alpha 0.1 with a selling price of Rp. 38.198 and MAPE 4.9%. | en_US |
dc.description.sponsorship | Fakultas Matematika dan Ilmu Pengetahuan Alam | en_US |
dc.identifier.citation | Perpustakaan | en_US |
dc.identifier.other | Elfitra | |
dc.identifier.uri | https://repository.unri.ac.id/handle/123456789/10700 | |
dc.language.iso | en | en_US |
dc.publisher | Elfitra | en_US |
dc.subject | Decision Support System | en_US |
dc.subject | Forecasting | en_US |
dc.subject | Agung Farm | en_US |
dc.subject | Triple Exponential Smoothing | en_US |
dc.subject | and MAPE | en_US |
dc.title | SISTEM PENDUKUNG KEPUTUSAN PERAMALAN HARGA JUAL TERNAK MENGGUNAKAN METODE TRIPLE EXPONENTIAL SMOOTHING | en_US |
dc.type | Article | en_US |
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