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All Journal JURNAL SISTEM INFORMASI BISNIS Jupiter Elsains : Jurnal Elektro Jurnal Komputer, Informasi dan Teknologi J-SIGN (Journal Of Informatics, Information System, And Artificial Intelligence)
Ica Admirani, Ica
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science

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Journal : JURNAL SISTEM INFORMASI BISNIS

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Model Heuristic Time Invariant Fuzzy Time Series dan Regresi Untuk Prediksi Laba dan Analisis Variabel yang Mempengaruhi Admirani, Ica; Gernowo, Rachmat; Suryono, Suryono
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 6, No 2 (2016): Volume 6 Nomor 2 Tahun 2016
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (980.47 KB) | DOI: 10.21456/vol6iss2pp144-153

Abstract

Model of prediction with fuzzy time series method has ability to capture the pattern of past data to predict the fu ture of data does not need a complicated system, making it easier to use. The research aims to built prediction system using model of  heuristic time invariant fuzzy time series and multiple linear regression to predict profit and analysis of variables that affect profit. Profit forecasting aims to determine the company's prospects in the future in order to remain exist in doing its business. The variables that use in the modelling are profit as the dependent variable, and sales, cost of goods sold, general and administrative expenses, selling and marketing expenses and interest income as the indepent variables. Profit forecasting modelling begins by defining universe of discourse and interval actual data of profit, then determine fuzzy set and actual data fuzzified. Furthermore, fuzzy logical relationship and fuzzy logical relationships group to fuzzified data. The prediction process consist of two prediction phase there are training phase aimed to determine trend predictor and testing phase to determine prediction results. By using 24 profit data samples resulted prediction error by using Mean Absolute Percentage Error is 11,64% and added 13 data for testing obtained prediction error is 22,27%.  In analysis of variables that affect profit is known that sales variable most effect on profit than other variables with a regression coefficient 0.976.
Co-Authors Adelia, Dian Dona Alan Novi Tompunu Ami, Hidayati Ayu Dasilpha, Mutiara Azizah, Laeli Dewi Azwardi Azwardi Darlies, Meiyi Delima Ayu Anugrah Destari, Salsabilla Herlambang Saputra Irpansyah, Irpansyah Khairunisa, Fildza Maulana, Ahmad Renaldi Novi Tompunu, Alan Rachmat Gernowo Restuningsih, Cindy Suryono Suryono