ANALISIS INTERVENSI FUNGSI STEP PADA HARGA SAHAM (STUDI KASUS SAHAM PT FAST FOOD INDONESIA Tbk)

  • Ratna Novita Sari Universitas Negeri Semarang
  • Scolastika Mariani Universitas Negeri Semarang
  • Putriaji Hendikawati Universitas Negeri Semarang
Keywords: Forecasting; ARIMA; step functio; stock price

Abstract

The analysis of the intervention is analysis a time series data that is affected by events outside the control of which may result in a change in the time series. Intervention analysis is used to analyze the data time series data of known intervention time. The main objective of this research is to determine the best intervention model on price of stock data PT Fast Food Indonesia Tbk period December 2013-January 2014, so the best forecasting method can be used to predict price of stock data PT Fast Food Indonesia Tbk for the next period with the help of SAS software program. Based on the analysis of the obtained the best intervention model that is a model of ARIMA (2,4,2) with the order of b = 20, s = 5, r = 0. The model of forecasting results obtained with the model of the step function intervention shows that the value of his predictions are within the threshold interval 95% confident with the results of the Eastern 70.82, MSE amounting to 386.94, and the RMSE of 19.671. So the forecast results can be used to estimate the daily price of stock data PT Fast Food Indonesia Tbk on 23 January 2014 to 20 February  2014 post intervention due to the occurrence of a policy dividend that caused significantly decreased just around the time the intervention only.

References

Abdullah. 2012. Model Intervensi untuk Mengetahui Dampak Kenaikan Tarif Dasar Listrik Juli 2010 Terhadap Pemakaian Listrik di Kota Samarinda. Skripsi, Universitas Mulawarman.
Amelia, C. 2014. Analisis Intervensi Fungsi Step (Studi Kasus Pada Jumlah Pengiriman Benda Pos ke Semarang Pada Tahun 2006-2011). Jurnal Gaussian, Vol.3, No.3.
Aritara, R. 2011. Analisis Intervensi Fungsi Step Pada Kenaikan Tarif Dasar Listrik (TDL) Terhadap Besarnya Pemakaian Listrik. Skripsi. Yogyakarta: FMIPA Universitas Negeri Yogyakarta.
Box, G.E.P., G.M. Jenkins, & G.C. Reinsel. 1994, Time Series Analysis: Forecasting and Control, 3th edition, Prentice Hall, New Jersey.
Box, G.E.P & G.C. Tiao. 1975, Intervention Analysis with Applications to Economic and Environmental Problems, Journal of the American Statistical Association, Vol. 70, hal. 70-79.
Budiarti, L., Tarno & B. Warsito. 2013. Analisis intervensi dan Deteksi Outlier pada Data Wisatawan Domestik (Studi Kasus di Daerah Istimewa Yogyakarta). Jurnal Gaussian, Vol.2, No.1.
Sari, D. R. 2015. Peramalan Indeks Harga Konsumen Menggunakan Model Intervensi Fungsi Step. Skripsi. Semarang: FSM Universitas Diponegoro.
Nuvitasari, E., Suhartono, & H.S. Wibowo. 2009. Analisis Intervensi Multi Input Funsi Step dan Pulse untuk Peramalan Kunjungan Wisatawan ke Indonesia. Thesis. Institut Teknologi Sepuluh November, Surabaya.
Rosadi, D. 2012. Ekonometrika & Analisis Runtun Waktu Terapan dengan Eviews. Yogyakarta. Penerbit ANDI.
Sudarsana, I.G.B. 2007. Pengaruh Insiden Bom Bali I dan Bom Bali II Terhadap Banyaknya Wisatawan Mancanegara yang Datang ke Bali, Skripsi, Institut Teknologi Sepuluh Nopember, Surabaya.
Utami, E.B. 2001. Analisis Intervensi Krisis Ekonomi dan Travel Warning terhadap Jumlah Kedatangan Wisman Melalui Bandara Juanda dan Ngurah Rai, Skripsi, Institut Teknologi Sepuluh Nopember, Surabaya.
Wei, W.W.S. 1990. Time Series Analysis.Addison Wisley Publishing Company. Canada.
Wei, W.W.S. 2006. Time Series Analysis: Univariate and Multivariate 2nd Edition. New Jersey: Pearson Education.
Published
2017-02-27
Section
Articles