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All Journal Statistika Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Sains dan Teknologi JURNAL INSTEK (Informatika Sains dan Teknologi) Prosiding Seminar Nasional Unimus
Budi Warsito
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Nursing Public Health Other

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Journal : Jurnal Gaussian

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PERAMALAN DAYA LISTRIK BERDASARKAN JUMLAH PELANGGAN PLN MENGGUNAKAN MODEL FUNGSI TRANSFER DENGAN OUTLIER (Studi Kasus di PT PLN (Persero) Rayon Semarang Selatan) Retza Bahtiar Anugrah; Sudarno Sudarno; Budi Warsito
Jurnal Gaussian Vol 5, No 4 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (678.342 KB) | DOI: 10.14710/j.gauss.v5i4.14730

Abstract

Electrical energy is one of the components of Gross Domestic Product which able to stimulate the economic matter because it has been becoming a primary needs in the society. In order to meet the growing electrical energy, State-Owned Enterprises (SOEs) need to develop systems and proper planning. It needs a forecasting of electric power based on customer to meet a sufficient electricity supply. This study aims to predict the electrical power  by electric customers using transfer function model with outliers. The use of transfer function model is intended to determine the role of power users that have an impact on the electric power. One of the stages of modeling the transfer function is to set the order of the transfer function parameters, they are b, r, and s. And by modeling the outlier is useful to eliminate the effect of outliers itself. The analysis and discussion show that based on the AIC value, the best model is the transfer function model by weighting the impulse response of the parameter that is ω_0 = 55,55652  and the noise series model of the transfer function is ARIMA (1,0,1) with 8 outliers. The details of the outliers consist of one Additive Outliers type in the 33rd and seven Level Shift Outliers in the 14th, 31st, 9th, 10th, 21st, 22nd and 58th. Size forecasting accuracy using MAPE value 19.77%. Keywords: Transfer function, outliers, ARIMA, electrical power, AIC, MAPE
PEMODELAN RETURN PORTOFOLIO SAHAM MENGGUNAKAN METODE GARCH ASIMETRIS Muhammad Arifin; Tarno Tarno; Budi Warsito
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (669.39 KB) | DOI: 10.14710/j.gauss.v6i1.14766

Abstract

Investment in stocks is an alternative for investors and companies to obtain external funding sources. In the investment world there is a strong relationship between risk and return (profit), if the risk is high then return will also be high. Risks can be minimized by performing stock portfolio. Stock is the time series data in the financial sector, which usually has a tendency to fluctuate rapidly from time to time so that variance of error is not constant. Time series model in accordance with these condition is Generalized Autoregressive Conditional Heteroscedasticity (GARCH). This research will apply asymmetric GARCH covering Exponential GARCH (EGARCH), Threshold GARCH (TGARCH), and Autoregressive Power ARCH (APARCH) in stock data Indocement Tunggal Tbk (INTP), Astra International Tbk (ASII), and Adaro Energy Tbk (ADRO) commencing from the date of March 1, 2013 until February 29, 2016 during an active day (Monday to Friday). The purpose of this research is to predict the value of the volatility of a portfolio of three assets stocks. The best models used for forecasting volatility in asset stocks which have asymmetric effect is ARIMA ([13],0,[2,3]) EGARCH (1,1) on a single asset data INTP, ARIMA ([2],0,[2,3]) EGARCH (1,1) on the 2 asset portfolio data ASII INTP, and ARIMA ([3],0,[2]) EGARCH (1,1) on the 3 asset portfolio data INTP-ASII-ADRO.Keywords: Stocks, Portfolio, Return, Volatility, Asymmetric GARCH.
Co-Authors Abdul Hoyyi Alan Prahutama Anggita Puri Savitri Anisa Septi Rahmawati Annisa Pratiwi Arief Rachman Hakim Aris Sugiharto Cindy Wahyu Elvitra David Yuliandar Di Asih I Maruddani Diah Safitri DONNY IRAWAN MUSTABA Dwi Ispriyanti Endang Purbowati Fajar Hari Prasetyo Hasbi Yasin Hayuk Permatasari Juwanda, Farikhin Lenny Budiarti Moch Abdul Mukid Moch. Abdul Mukid MUHAMMAD ARIFIN Nia Puspita Sari Omy Wahyudi Rachmah Dewi Kusumah Retza Bahtiar Anugrah Rita Rahmawati Sri Sumiyati Sudarno Sudarno Sugito - Sugito Sugito Suparti Suparti Tarno Tarno Umi Sulistyorini Adi Yunita Pipiet Sugandhi