Penerapan fuzzy time series dalam peramalan data seasonal

Brata, Adika Setia (2016) Penerapan fuzzy time series dalam peramalan data seasonal. Undergraduate thesis, Universitas Islam Negeri Maulana Malik Ibrahim.

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Abstract

INDONESIA:

Salah satu metode peramalan yang paling dikembangkan saat ini adalah time series seasonal, yakni menggunakan pendekatan kuantitatif dengan data masa lampau yang dijadikan acuan untuk peramalan masa depan. Proses peramalan sangat penting pada data time series seasonal karena diperlukan dalam proses pengambilan keputusan. Pada bidang perekonomian peramalan dapat digunakan untuk memantau pergerakan data jumlah omset berpola seasonal yang akan datang. Perkembangan metode peramalan data time series seasonal yang cukup pesat mengakibatkan terdapat banyak pilihan metode yang dapat digunakan untuk meramalkan data sehingga perlu membandingkan metode yang satu dengan metode yang lainnya untuk mendapatkan hasil ramalan dengan akurasi yang baik.

Penelitian ini menjelaskan masalah peramalan jumlah omset koperasi menggunakan Fuzzy Time Series (FTS) yang dikembangkan dengan Orde Tinggi. Pengembangan metode dilakukan dengan cara meningkatkan metode FTS dengan kaidah matematis dan diterapkan pada tahapan proses peramalan data seasonal jumlah omset koperasi. Hasil pengujian menunjukkan bahwa model peramalan Fuzzy Time Series Orde Tinggi memiliki nilai akurasi peramalan lebih baik dengan persentase perhitungan metode Akurasi Mean Square Deviation (MSD), Mean Absolute Deviation (MAD), dan Mean Absolute Percentage Error (MAPE) terbaik.

ENGLISH:

One of the most developed forecasting method at this time is time series seasonal, that is using a quantitive approach to the data of the past that used as a reference for future forecasting. Forecasting proces is very important at seasonal time series data because it is required in the decision making procces. On the economic field, forecasting can be used to monitor data movement turnover amounts seasonal pattern that will come. The rapid development of time series seasonal data forecasting method as quitly rapidly inflict so many choice for methode can used for forecasting data so it is neccesary to compare one method to other method to obtain accurate forecast result.

This reseach explains about the problem of forecasting of the amount of cooperative turnover using Fuzzy Time Series (FTS) developed with higher order. The development of method performed by increasing the FTS with the rules of mathematical methods and applied in the procces of data forecasing seasonal of cooperative turnovers. The test result show that the high order Fuzzy time series forecasting model has better value of forecasting accuracy than previous seasonal method, with percentage of accuracy using Mean Square Deviation (MSD), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE) accuracy method.

Item Type: Thesis (Undergraduate)
Supervisor: Rozi, Fachrur and Alisah, Evawati
Keywords: Peramalan; Seasonal; Fuzzy Time Series; Orde Tinggi; Forecast; Seasonal; Fuzzy Time Series; High Order
Departement: Fakultas Sains dan Teknologi > Jurusan Matematika
Depositing User: Imam Rohmanu
Date Deposited: 21 Mar 2017 12:48
Last Modified: 21 Mar 2017 12:48
URI: http://etheses.uin-malang.ac.id/id/eprint/5777

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