28Jul 2017

DEBIT MODELING USING ARIMA METHOD TO DETERMINE OPERATIONAL PATTERN OF SELOREJO DAM.

  • Lecturer of Water Engineering Department, Malang Brawijaya University.
  • Student of Water Engineering Magister, Faculty of Engineering, Malang Brawijaya University.
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Selorejo Dam is located in Pandansari Village, Ngantang District, Malang Regency. The exact spot is at Konto River, a tributary of Brantas River. This dam has very important functions such as for electric generation and irrigation. It is very old dam with construction completed in 1970 but now subjected to shallowing due to a high sedimentation rate. The decreasing reservoir volume of the dam has impacted dam function, and therefore, it is necessary to formulate a better plan for reservoir operational pattern to manage properly the existing water volume. Recently, in planning the operational pattern of the reservoir, Perum Jasa Tirta I (PJT-I) as the manager of Selorejo Dam uses feasible debit to predict debit inflow. In this study, debit inflow is predicted using ARIMA method from also which new operational pattern of the reservoir can be established. This study uses 10-years data of 10-days debit inflow. Of these data, 9-years data are used to generate ARIMA model while 1-year data are used for calibration. The best ARIMA model in predicting debit inflow is ARIMA (1,1,1)(2,1,1)36. Compared to other methods recently used, ARIMA has been proved as able to predict debit inflow in better way with smaller Relative Error (KR) than realized debit (Model?s KR is 5.5 and Operator?s (PJT-I) KR is 17.5)


  1. Arsyad, L. (1994). Peramalan Bisnis. Yogyakarta: BPFE.
  2. Box, G.E.P. and Jenkins, G.M. (1976). Time Series Analysis: Forecasting and Control. San Francisco: Holden Day.
  3. Cryer, J.D. (1986). Time Series Analysis. Boston: PWS-KENT Publishing Company.
  4. Hanke, J.E., Arthur G. Reitsch, and Dean W. Wichern. (2003). Peramalan Bisnis. Jakarta: PT. Prenhallindo.
  5. Makridakis, S., S. C. Wheelwright dan V. E. McGee. (1988). Metode dan Aplikasi Peramalan. Jakarta: Erlangga.
  6. Nigam, R., Sohail Bux, Sudhir Nigam, K.R. Pardasani, S.K. Mittal, Ruhi Haque. (2009). Time series modeling and forecast of river flow. Current World Environment Vol. 4(1), 79-87 (2009).
  7. Republik Indonesia. (2010). Peraturan Pemerintah Republik Indonesia Nomor 37 Tahun 2010 Tentang Bendungan. Lembaran Negara Republik Indonesia Tahun 2010 Nomor 45. Jakarta: Sekretariat Negara.
  8. Valipour, M., Mohammad Ebrahim Banihabib, Seyyed Mahmood Reza Behbahani. (2012). Parameters Estimate of Autoregressive Moving Average and Autoregressive Integrated Moving Average Models and Compare Their Ability for Inflow Forecasting. Journal of Mathematics and Statistics 8 (3): 330-338, 2012.

[Pitojo Tri Juwono, Widandi Soetopo and Bambang Pramujo. (2017); DEBIT MODELING USING ARIMA METHOD TO DETERMINE OPERATIONAL PATTERN OF SELOREJO DAM. Int. J. of Adv. Res. 5 (Jul). 1951-1961] (ISSN 2320-5407). www.journalijar.com


Pitojo Tri Juwono
brawijaya university

DOI:


Article DOI: 10.21474/IJAR01/4926      
DOI URL: http://dx.doi.org/10.21474/IJAR01/4926