IMPLEMENTASI FUZZY INFERENCE SYSTEM METODE TSUKAMOTO PADA PREDIKSI JUMLAH PENYEDIAAN STOK VOUCER INTERNET (STUDI KASUS LAWU DATA)

Pribadi, Dewa (2023) IMPLEMENTASI FUZZY INFERENCE SYSTEM METODE TSUKAMOTO PADA PREDIKSI JUMLAH PENYEDIAAN STOK VOUCER INTERNET (STUDI KASUS LAWU DATA). Skripsi (S1) thesis, Universitas Muhammadiyah Ponorogo.

	Text (Surat Persetujuan Unggah Karya Ilmiah) Surat Persetujuan Unggah Karya Ilmiah_Ardiyanza Dewa Pribadi_18532936_TI.pdf Download (222kB)
	Text (Halaman Depan) HALAMAN-DEPAN.pdf Download (3MB)
	Text (BAB I) BAB-1.pdf Download (442kB)
	Text (BAB II) BAB-2.pdf Restricted to Repository staff only Download (862kB)
	Text (BAB III) BAB-3.pdf Restricted to Repository staff only Download (1MB)
	Text (BAB IV) BAB-4.pdf Restricted to Repository staff only Download (1MB)
	Text (BAB V) BAB-5.pdf Restricted to Repository staff only Download (361kB)
	Text (Daftar Pustaka) DAFTAR PUSTAKA.pdf Download (337kB)
	Text (IMPLEMENTASI FUZZY INFERENCE SYSTEM METODE TSUKAMOTO PADA PREDIKSI JUMLAH PENYEDIAAN STOK VOUCER INTERNET (STUDI KASUS LAWU DATA)) IMPLEMENTASI-FUZZY-INFERENCE-SYSTEM-METODE-TSUKAMOTO-PADA-PREDIKSI-JUMLAH-PENYEDIAAN-STOK-VOUCER-INT (1).pdf Restricted to Repository staff only Download (4MB)

Abstract

Konter Data is an individual retail business as an internet package provider. In conditions that are all online like now the use of the internet is needed. Increased buyer needs need to be balanced with the provision of a large stock of vouchers. Due to the various types of vouchers, it is necessary to have a prediction system that can estimate the number of vouchers that need to be provided each month. This aims to reduce losses due to internet vouchers that are not sold immediately. From these problems, a web-based prediction application system was created using the Tsukamoto fuzzy method to carry out the prediction process. This prediction application system has an accuracy of the average MAPE value for each product of 0.1111790895 so that it can be said that the system is very accurate. With this accuracy, the prediction system can help Konter Lawu Data owners determine the number of vouchers that must be provided each month.

Item Type:	Thesis (Skripsi (S1))
Uncontrolled Keywords:	Konter Data, Voucer Data, Prediction, Fuzzy Tsukamoto
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Engineering
Depositing User:	ft . userft
Date Deposited:	15 Sep 2023 04:16
Last Modified:	15 Sep 2023 04:16
URI:	https://eprints.umpo.ac.id/id/eprint/12812

Actions (login required)

View Item