Time Series Analysis
Secondary Research Time Series Analysis
VARIABLE FACTOR THAT INCREASING MALAYSIA GDP
Prepared by:
Dina Maya Avinati
Wery Astuti
Faculty of Business
UNIVERSITAS SISWA BANGSA INTERNATIONAL
Mulia Business Park, JL. MT. Haryono Kav. 58-60 Pancoran- South Jakarta
Page | 1
CONTENT
I.
Introduction
1.1
Back Ground of Study
1.2
Problem
1.3
Research Problem
1.4
Research Objective
1.5
Scope and Limitation
1.6
Significant of Study
II.
Literature Review
III.
Methodology
2.1
Time and Place
2.2
Research Framework
2.3
Research Question and Hypothesis
2.4
Data
2.4.1
Type and Source of Data
2.4.2
Data Collection Method
2.4.3
Sampling Method
2.4.4
Data Analysis
2.4.5
Hypothesis Testing
IV.
Research and Discussion
V.
Conclusion and Recommendation
References
Appendix
Letter of Performance
Page | 2
INTRODUCTION
1.1
Back Ground of Study
Time Series Analysis (TSA) is one name of specific subjects that must be studied by college students majoring in Management at University of
Siswa Bangsa
International. Time Series can define as a sequence of numbers collected at regular intervals over a period of time. In addition, Time Series Analysis is method for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. However, TSA is really needed to interpret statistic data to forecast the event in the future such as forecast demand, sales, consumer preference, micro and macro-economic data. Further, time series forecasting is the use of a model to predict future values based on previously observed values. Finally, time series can become media interpretation use data plotting and regression.
Through this paper, students will try to find out the best method to analyze the
GDP of Malaysia based on time series data from secondary source. There are about seven different time-series forecasting
VARIABLE FACTOR THAT INCREASING MALAYSIA GDP
Prepared by:
Dina Maya Avinati
Wery Astuti
Faculty of Business
UNIVERSITAS SISWA BANGSA INTERNATIONAL
Mulia Business Park, JL. MT. Haryono Kav. 58-60 Pancoran- South Jakarta
Page | 1
CONTENT
I.
Introduction
1.1
Back Ground of Study
1.2
Problem
1.3
Research Problem
1.4
Research Objective
1.5
Scope and Limitation
1.6
Significant of Study
II.
Literature Review
III.
Methodology
2.1
Time and Place
2.2
Research Framework
2.3
Research Question and Hypothesis
2.4
Data
2.4.1
Type and Source of Data
2.4.2
Data Collection Method
2.4.3
Sampling Method
2.4.4
Data Analysis
2.4.5
Hypothesis Testing
IV.
Research and Discussion
V.
Conclusion and Recommendation
References
Appendix
Letter of Performance
Page | 2
INTRODUCTION
1.1
Back Ground of Study
Time Series Analysis (TSA) is one name of specific subjects that must be studied by college students majoring in Management at University of
Siswa Bangsa
International. Time Series can define as a sequence of numbers collected at regular intervals over a period of time. In addition, Time Series Analysis is method for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. However, TSA is really needed to interpret statistic data to forecast the event in the future such as forecast demand, sales, consumer preference, micro and macro-economic data. Further, time series forecasting is the use of a model to predict future values based on previously observed values. Finally, time series can become media interpretation use data plotting and regression.
Through this paper, students will try to find out the best method to analyze the
GDP of Malaysia based on time series data from secondary source. There are about seven different time-series forecasting
References: (Abdul, 2013). Student believe that that GDP growth is affected by several factors such as final consumption expenditure, government expenditure, exports of goods and