Zaitun Time Series booklet

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Zaitun Time Series booklet
Zaitun Time Series
Developed by:
Zaitun Time Series Developer Team
http://www.zaitunsoftware.com
Background
Today, time series analysis
has become of the most
important and widely used
branches of mathematical
statistics.
Time
series
analysis consists of some
methods which attempt to
understand such time series
data, to understand the
relationship or the influence
of some events, include estimating the strength of influence among events.
Time series data is also used to forecast future events based on known past
events by using regression line and trend.
Time series analysis fields of application range from physics to
neurophysiology and it covers such well known areas of economic forecasting,
study of biological data, control system, selling forecasting, process and
quality control, finance analysis, stock market analysis, and census analysis.
A tool to help the analysis of time series is very required. It can help the
process of analysis to be easier. A tool which can help the analysis of time
series is a time series application which provides a simple way in modeling
and forecasting time series data.
Today, there are a lot of time series applications which have been developed
to help the analysis of time series data. But then, there are a lot of time
series applications which are developed for commercial use and expensively
sold. Free time series applications are also available, but they are not easy to
use.
The required time series application is the application which is simple, user
friendly, easy to use, understandable, and free.
Zaitun Time Series Application
Zaitun Time Series is a free application
which is designed to help and solve the
problem about the time series data.
Zaitun Time Series is originally
developed by “Time Series” team as
the final project of four years diploma
in Sekolah Tinggi Ilmu Statistik (STIS),
Jakarta, 2007. The team consisted of
some
student
from
statistic
computation major. Until today, the
development of Zaitun Time Series is
still being continued by the developer
team in zaitunsoftware.com.
The first version of Zaitun Time Series (version 0.1.1) was finished at August
2008, and in October 2008 Zaitun Time Series was published and could be
downloaded freely at http://www.zaitunsoftware.com. Now, the latest version
of Zaitun Time Series is version 0.1.4.
Zaitun Time Series is designed to help the analysis of time series data. It
provides the easy way in modeling and forecasting time series data.
Compared to another time series application, Zaitun Time Series is a time
series application which is free, easy to use, user friendly, and can be used for
any purposes. It provides several analysis of statistics and neural network, it
also provides graphical tool to help the analysis of time series becoming
easier. The analysis of statistics and neural network consisted of trend
analysis, decomposition, moving average analysis, exponential smoothing,
correlogram, and neural network. The graphical tools consisted of time series
plot, actual and predicted plot, Actual and Forecasted Plot, Actual vs Predicted
Plot, Residual Plot, Residual vs Actual Plot, and Residual vs Predicted Plot.
The Uniqueness of Zaitun Time Series
1. Simple and easy to use
The interface is designed by considering
the ease of user. The interface is
consisted of three main views, they are
project view, variable view, and result
view which simplify the management of
the time series data and the analysis or
forecasting result.
2. The ease of pre-analysis of the data
Variable view is consisted of three views, they are spreadsheet view,
graphic view, and statistics view. These help the pre-analysis of the
characteristics of a variable through the graphical view and the value of
statistics.
3. The ease of understanding the analysis and forecasting result
The result of analysis is viewed in two ways; they are table and graphical
view which help the user to understand the statistics value in the model.
4. A simple way to do data forecasting
Data forecasting can be done in an easy
way, only by clicking the Forecasted option
and fill the number of data forecasting step.
The result of forecasting in graphical view
can be showed only by clicking the Actual
and Forecasted option (see the picture
beside).
5. The model of statistics and neural network are available
The model of statistics and
neural networks are available
to do the analysis and
forecasting of time series data.
The models are:
Trend Analysis.
Linear, Quadratic, Cubic,
and Exponential
Decomposition.
Multiplicative and Additive
Moving Average.
Single Moving Average and
Double Moving Average
Exponential Smoothing.
Single Exponential Smoothing, Double Exponential Smoothing (Brown),
Double Exponential Smoothing (Holt), and Triple Exponential
Smoothing (Winter)
Correlogram. Level, First Difference, Second Difference
Neural Networks.
6. External data
To connect with the external
data through this application is
quite easy. This application is
facilitated with the import and
export data feature which
import and export the data
from and to excel and CSV file.
The Features of Zaitun Time Series
1. Creating a time series data in certain frequency.
Zaitun Time Series has facility that
helps user to make the new project
which will be filled with time series
data in certain frequency. The
frequencies consists of annual, semi
annual, quarterly, monthly, weekly,
daily, daily (1 week, 6 days), daily
(1 week, 5 days), and the sequence
of time series data which has an
unidentified frequency.
2. Variable and Group
Time series data in Zaitun tme Series is
organized into variable and group. The variable
in Zaitun Time Series represents a single
time series variable. Group represents the
collection of time series variables.
3. Spreadsheet View, Graphic View, and Statistics View
To simplify the user’s job, user can view the value of variable and group in
three views, they are spreadsheet view, graphic view, and statistics view.
Spreadsheet view shows the value of variable in a grid which will
simplify the process of entry or change the value of variable. Graphic
view will show the variable in a graphic line which will simplify the
graphical analysis of the component of the time series variable (e.g. trend,
cycle, seasonal, and irregular). Statistics view shows the descriptive
statistics which simplify the analysis of statistical characteristic of a
variable.
4. Time series analysis model
The model of statistics and neural network to do the analysis and
forecasting of time series data are available, they are:
Trend Analysis
Zaitun Time Series provides the feature to do the trend component
analysis of a time series data. Several type of trends are available,
they are linear, quadratic, cubic, and exponential.
Decomposition
Zaitun Time Series provides the feature to do decomposition analysis of
time series data.
Moving Average
Zaitun Time Series provides the feature to do moving average analysis.
Single and double moving average analyses are available.
Exponential Smoothing
Zaitun Time Series provides the feature to do the analysis of
Exponential Smoothing. The supported model of Exponential
Smoothing consists of Single Exponential Smoothing, Double
Exponential Smoothing (Brown), Double Exponential Smoothing (Holt),
and Triple Exponential Smoothing (Winter).
Correlogram
Zaitun Time Series provides the feature to view the value of Auto
Correlation Function (ACF) and Partial Auto Correlation Function (PACF)
of time series data, include the graphic.
Neural Networks
Zaitun Time Series provides the feature to make a neural network
model of time series data.
5. Graph
There are some graphs which help the
user to understand the data and the
result of analysis, they are:
Time Series Plot. Viewing a line
graph of a variable.
Actual and Predicted Plot. Viewing
line graph for actual and predicted
value of a model.
Actual and Forecasted Plot. Viewing
line graph for actual and forecasted
value of a model.
Actual vs Predicted Plot. Viewing the scatter plot between actual and
predicted value.
Residual Plot. Viewing the line graph for residual value of a model.
Residual vs Actual Plot. Viewing the scatter plot between residual
and actual value.
Residual vs Predicted Plot. Viewing scatter plot between residual
and predicted value.
6. Variable Transformation
Zaitun Time Series provides the facility to transform the variable.
Several types of supported transformation are differencing, seasonal
differencing, logarithm, and quadratic equation.
7. Import and Export the Data
Zaitun Time Series is
facilitated
with
the
import and export data
feature which are able to
import and export the
data from and to excel
and CSV file. This feature
will make the work
easier,
especially
for
user
with
different
format of data.
The Methodology
The methodology of Zaitun Time Series consists of:
1. Computation based on matrices.
Most of the computation calculation of Zaitun Time Series is based on
matrices. The matrices operations such as summation, multiplication,
and determinant are used to count the value of analysis.
2. Numerical computation
The method of numerical computation such as the calculation of
integral, differential, the method of optimization are used to calculate
the value of statistics function, statistics distribution, and the
optimization of the value of parameter model.
3. Neural Network
Zaitun Time Series uses Encog-CS external library to make a neural
network model. Encog is a LGPL licensed library which is used in neural
network programming and robot programming. Encog-CS can be
downloaded at http://code.google.com/p/encog-cs.
4. Object Oriented Programming
Zaitun Time Series is developed by using the object oriented
programming method.
Every data and function in this method is classified into classes and
objects. Each object can receive the message, process the data, and
send message to another object. Object oriented programming
approach gives more flexibility way to manage the program and the
codes.
5. C# Language and .NET Framework 2.0
More than 40.000 lines of C# codes in .NET Framework 2.0 have been
written to develop Zaitun Time Series. C# Language and .NET
Framework 2.0 have been developed by Microsoft and widely used to
develop a lot of application include a scientific application.
Awards
1. Indonesia ICT Award 2009, Research and
Development Category
Zaitun Time Series won the Indonesia ICT Award 2009,
Research and Development Category given by
Department of Communication and Information,
Republic of Indonesia.
2. Softpedia 100% Clean Award
Softpedia guarantees that Zaitun Time Series is 100%
clean, not containing any malware, spyware, virus,
Trojan or backdoor.
3. Free Download Manager User Choice Award
This award is achieved from Free Download Manager
website since many website visitors choose Zaitun Time
Series to be downloaded.
Statistics of Website Visitor
Here is the statistics of http://www.zaitunsoftware.com visitor based on
country since October 2008 until February 2009. The top five website visitor
based on original country is counted by the highest hits count. The number of
the visitor is obtained from the report of Advanced Web Statistics 6.9
which has been installed in Zaitun Time Series website server located in US.
October 2008
No
Country
1.
United States
2.
Hong Kong
3.
Spain
4.
Germany
5.
Indonesia
Other Countries
Total
November 2008
No
Country
1.
United States
2.
Hong Kong
3.
Germany
4.
Indonesia
5.
Brazil
Other Countries
Total
December 2008
No
Country
1.
United States
2.
Hong Kong
3.
Australia
4.
Canada
5.
Indonesia
Other Countries
Total
Hits
16,232
918
439
317
174
1,098
19,178
Hits
10,472
6,727
565
399
296
3,929
22,388
Hits
16,457
2,044
633
542
257
4,721
24,654
January 2009
No
Country
1.
United States
2.
Indonesia
3.
Hong Kong
4.
Australia
5.
Great Britain
Other Countries
Total
February 2009
No
Country
1.
Thailand
2.
United States
3.
Indonesia
4.
Australia
5.
Brazil
Other Countries
Total
March 2009
No
Country
1.
United States
2.
Indonesia
3.
Russian Federation
4.
Egypt
5.
Italy
Other Countries
Total
April 2009
No
Country
1.
United States
2.
Indonesia
3.
Russian Federation
4.
India
5.
Spain
Other Countries
Total
Hits
50,744
965
910
733
678
10,070
64,100
Hits
10,319
7,309
6,015
1,773
1,019
11,757
38,192
Hits
6,126
5,905
1,985
1,287
1,116
16,084
32,503
Hits
5,760
2,934
1,681
876
782
10,307
22,340
May 2009
No
Country
1.
United States
2.
Indonesia
3.
Russian Federation
4.
Saudi Arabia
5.
France
Other Countries
Total
June 2009
No
Country
1.
United States
2.
Indonesia
3.
Poland
4.
Russian Federation
5.
Germany
Other Countries
Total
July 2009
No
Country
1.
United States
2.
Indonesia
3.
Poland
4.
Russian Federation
5.
India
Other Countries
Total
August 2009
No
Country
1.
Indonesia
2.
United States
3.
Russian Federation
4.
Great Britain
5.
Poland
Other Countries
Total
Hits
6,582
4,514
3,733
2,205
993
15,306
33,333
Hits
7,688
5,909
3,208
3,062
901
14,094
34,842
Hits
13,451
10,095
5,275
4,551
1,889
21,385
56,646
Hits
14,493
7,946
3,429
1,329
1,037
12,966
41,200
Users and visitors comments
Here are the comments of Zaitun Time Series’ users and site visitors:
“…I have to say a very big CONGRATULATIONS to you all in the team for
producing such a wonderful useable piece of software free to the world and
of course to your teachers and supervisors. You have done a good thing and
you may never know all the good that will come of what you have done. I
can't tell you how impressed I am. ….” [Joe Kenyon]
“…many thanks for the amazing software you had done…” [Ahmed Hamdy]
“… I think the software is marvelous, and I can use it frequently in my daily
work. Thanks for putting it together….” [Tim Altom]
“… I use time series analysis of various metrics for clients. Most are very
simple and can be described with regression lines, but many are erratic and
require more sophisticated analysis, such as moving average or exponential
models. Major packages will do these things, but they are generally very
expensive, and the company cannot afford them right now. Others, like R, are
powerful, but difficult for others in my company to use. Your software is free,
easy to use, and very fast. It helps me a lot. I also teach statistics to college
students, and I have recommended Zaitun Time Series to others on
campus…” [Tim Altom]
“Curretly i'm using the software and it's doing well especially in my job”
[Anonymous]
“…Really nice software…” [André Carlucci]
“Your package is unusual and takes a bit of getting used to. Nevertheless I
am grateful for it.” [Mike London]
“….I dont expect that u guys are so cool …” [Azzy Brastorm]
“…good job guys…” [Hanung Pramusito]
Next Development
1. Statistics Model
Adding more complex statistics models and statistics tests to do the
analysis and forecast time series data. Some models which can be added
into Zaitun Time Series:
- Auto Regressive Integrated Moving Average (ARIMA)
- Auto Regressive Conditional Heteroscedasticity (ARCH)
- Generalized Auto Regressive Conditional Heteroscedasticity
(GARCH)
- Vector Auto Regression (VAR)
- Unit Root Test
- Co-integration Test
2. Neural Network Model
Expanding the Neural Network Model in Zaitun Time Series - which is Fully
Connected Feed Forward Neural Network with Back Propagation Training to increase the performance of data forecasting. It can be done by using
the other topology of neural network such as Radial Basis Network, and
Non Fully Connected Neural Network, using another training algorithm
such as QuickProp, RPROP, and Lavenberg Marquardt, adding the other
method of Artificial Intelligence such as genetic algorithm or fuzzy logic.
3. Automatic Forecasting
Statistics models and neural network model need the involvement of user
in determining the best model which will be used to do the data
forecasting. The users should determine the certain parameter until they
can obtain a good result of forecasting. The limitation can be solved by
developing an intelligent technique to do an automatic forecasting. The
intelligent techniques such as expert system, fuzzy logic, and the genetic
algorithm can be combined with the current model in determining the best
value of parameters of the model which is able to set a good result of
forecasting.
4. The connection to the external database
The connection to the external database is very useful for user who saves
his data inside a certain database application. The facility to import and
export from and to the database will simplify the job to do the data
analysis.
5. Live Stock Market
Today, some sites provide data of the
fluctuation of the current stock market,
such as Google Finance and Yahoo
Finance. The facility to import the data
from these sites will simplify the user who
wants to see the fluctuation of stock
market. It also helps to do the analysis of
time series of the data include to forecast
the data by using the model which is
available in the application. The result of
forecasting can be used to help the process of stock exchange transaction.
Zaitun Time Series v 0.2.1 Release Plan
Some features which will be included in Zaitun Time Series v 0.2.1:
1. Multiple Regression Analysis
2. New Data Type to help visualization of sock market and forex data
3. New Import Feature to acquire live stock market data and forex data from
online data provider like Google Finance or Yahoo Finance
The Developer Team
Rizal Zaini Ahmad Fathony
Core Development, Programmer
Suryono Hadi Wibowo
Interface Designer, Programmer
Lia Amelia
Website, Documentation
Past Developers:
Almaratul Sholihah, Muhamad Fuad Hasan, Rismawaty, Wawan Kurniawan,
Aris Wijayanto, Dewi Andriyanti.

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