Time Series and Forecasting with R

Workshop Description  | Tentative Schedule  |  How to Register  | Fees  | Registration Form | Contact Us


This is a one-day hands-on workshop to introduce Time Series and Forecasting using R environment and programming language. In this workshop, you will learn the fundamental R commands necessary for time series and forecasting. R has extensive facilities for analyzing time series data. This workshop will describe the creation of a time series, seasonal decomposition, modeling with exponential and ARIMA models, and forecasting with the forecast package.

This is a pre-workshop held in conjunction with the International Seminar on Mathematics In Industry 2017 (ISMI2017). A discounted fee will be given for participants of ISMI2017.

This workshop is organised by the UTM Department of Mathematical Sciences, Faculty of Science and UTM- Centre for Industrial and Applied Mathematics (UTM-CIAM).


Dr. Suhartono has a B.Sc. in Statistics from Institut Teknologi Sepuluh November (ITS), Indonesia. He obtained an M.Sc. in Statistical Analysis and Stochastic Systems from University of Manchester Institute Science and Technology (UMIST), UK, and received M.S. Bartlet Price in this Master Program. After a stint in the UK at UMIST, Dr. Suhartono completed his PhD in Statistics at Gadjah Mada University in Yogyakarta. Then, he continued to pursue a Postdoctoral fellow at Universiti Teknologi Malaysia (UTM) in one year and now is a leading researcher at ITS University’s Department of Statistics in Surabaya.

Dr. Suhartono is a senior lecturer and head of Department of Statistics – ITS, where he has taught time series analysis, exploratory data analysis, multivariate analysis and research methodology for the past 20 years. He has presented numerous program and workshops to executives, educators, and research professionals in Indonesia, particularly about time series forecasting.

Tentative Schedule

0845              Registration

0900-1030     Introduction to Time Series Modeling and Forecasting.

                      Package Time Series using R.

                      Time Series Regression: Trend, Seasonal, Calendar Variation

1030-1040    Break

1045-1300    Introduction to ARIMA models for forecasting

1300-1400    Break

1400-1630     ARIMAX: ARIMA  with exogeneous variables.

                      Calendar Variation Model

                      Intervention analysis

                      Transfer function model

How to Register?

Fill in the online registration form below.

If you are an ISMI2017 participant, please upload proof of your participation at ISMI2017 to enjoy a discounted fee.


Fees*: ISMI2017 Participants RM170.  NON-ISMI2017 Participants RM 250

Participant can make payment by:

  1. Vote transfer (UTM staff only, an invoice will be given by the secretariat)
  2. Invoice (kindly notify the secretariat for an invoice)
  3. Bank transfer to:


Bank name: CIMB Bank Berhad (account no: 8006053536)

Kindly provide us your proof of payment: <NAME>_RTimeSeries.pdf to mohdfarid@utm.my

For further information please contact: Dr. Sharifah Suhaila Syed Jamaludin at suhailasj@utm.my

The fees are inclusive of online materials of the workshop. Certificate of Attendance will be given to all participants who completed the workshop.

Registration Form