مرحبا بكم في رمضان

مرحبا بكم في رمضان

welcome Ramadan. months full forgiveness and mercy. Love that always meet the longing of the soul unto God. this month I will submit everything to you my love. Not because of heaven or hell, but because you love ....

in this August 17 date 64 years ago, Ramadan is a silent witness the independence of Indonesia. Ramadan 5 years ago I can still see the girl that I love, and June 5 24 years ago, my birth date is

Ramadan is always so special for me

Filter Stop List

stop list is a text data that is contained in a particular list. Stop list is a list of words omitted in the text mining. Stop list is an example subject, pronoun, conjunction, etc..

Data in the stop list is not needed in search of information and knowledge to the text data. example a sentence "I love you", the world "I" and "you" do not have meaning in the text because knowledge is certainly the word love. I said you and data including the stop list.

in a system of text data mining more detail a list it will stop the better. this is because the process of stemming the words, Tagging, and keyword search text data will be shorter. effectiveness in time and memory to be the main goal of making stop list.

Stemming the sentences

"Stemming the sentence" is a process of splitting the sentence into words - the words. In programming languages are usually known by the name "tokenism". Why the sentence should be parsed into words? this process so that the introduction of the text is running with the pitch and fast measure. With the introduction of a data per text in the word can be ascertained that there is no data that is not in the process.

problems that arise is how the word back in the Indonesian language. Of course there must be reprocess for word - the word is back. Or can only, be a re-word a word itself or may be double counted. That's up to the case faced by a system analyst.

What is "Pre processing" ?

"Preprocessed" is a data cleaning process to be more easily processed by the system. Preprocessed is useful in order to extract the data before and taken his knowledge or keyword does not already have dirty data or data that are not needed. Example of dirty data such as:

• Digit
• Punctuation
• Bullets

Based on the research I do, numbers, punctuation marks, and bullets do not have a significant influence on a text data. This is because data in the text will eventually be in the ranking while the data is dirty data can not stand on its own.

Because it is the numbers, punctuation marks, and bullets need to be erased before the process of text mining that others do.

this is the scheme of prepossessing

The Text Mining

Text mining is a system to mine data as text. The mine here in the analogy can be like someone who is a gold mine. When the mine equipment was then a lot of clay, but we separated them and find where the existence of the gold is.

Same as text mining, we search for knowledge or important data from the data that a lot of text. The resulting data is a keyword or data that indicates the content of text data before.

Here is a text mining scheme:

to more clearly waiting next article

Searching Verse - Ayat Al - Qur'an Content Based on the belief Problems In Using Text Mining (My Final Project Prposal)

Internet world is very much sought by the community. Many of them are looking for solutions, tutorials, discussion, or browse through the discussion on the Internet. One is looking for the solution of the problem belief.

Verse - verse in Al - Qur'an is not organized based on a problem, so does the scatter, so it takes a long time to search verses - verses that are required for problem-solving faith.

So with the end of this project will help to find a verse reference and translation Al - Qur'an problems in belief, and are easily accessible because of web-based so it can be used by anyone

Keywords: Internet, Text Mining, Al - Qur'an, belief

Background authors take the title of this final project is difficulty implementing the Al-Qur'an in life - especially in the day by solving some of the people, as the form of Al-Qur 'an that conventional hard to learn.

Verse - verse in "Al - Qur'an" is not organized based on a problem, so does the scatter, so it takes a long time to search verses - verses that are required for problem-solving faith.
Search process clause - paragraph conventional "Al - Qur'an" way or with the Al - Qur'an during which digital is on the Internet (eg www. QuranDigital.Com-Al) is not enough to help, if the results we want is a paragraph -- paragraph in accordance with the particular problems that we face. With such a system is required to identify, find, and group problem diinputkan by the user. So that the system can display the verse - verse "Al - Qur'an" as a reference and solutions.

With the above problems, then you can use a process of introducing the text in a Text Mining. With the process so that problems in the user input performed with several methods such as parsing, stemming, and morphing To be able to recognize problems.
By the end of this project is expected to help find a verse reference and translation "Al - Qur'an" problems in belief, and are easily accessible because of web-based so it can be used by anyone.

Authors interested in writing and discuss the text mining al - Qur'an. Especially in extracting information about the problem of faith in verse - verse it. With the goal of producing a web application that can:

1. 1. Search for verse - verse al qur 'an issue of translation and belief
2. 2. Providing solutions to the problems of displaying text - verse and translated it.

The problem was that in the end of this project are:

• How to search for keywords from the problems that have?
• How can differentiate the problem, including a belief or not?
• How to related a problem with the belief paragraph - paragraph "Al - Qur'an" and translated?

TEXT MINING
text mining is the process of mine text data with a data source is usually from the document and find the goal is the word - a word that represents a document so that it can be done in the analysis relationship document [1] ..
Text data will be processed into numeric data that can be process further. So in terms of text mining is the data pre processing - that is the precursor that is applied to the text data that aims to generate numeric data [3].


On pre prosesing have conducted several phases, namely [4]:

• Removal and markup format document that is used if a text is not pure then this step is taken. Because the text document that usually we see a non-text formats such as html, pdf or in the form of a word. Format this format requires that a text has additional elements to be able to generate the view that our friendly eyes. Information is omitted because they do not need and do not reflect the contents of a text document
• Remove punctuation punctuation and numbers is also considered not important, because it happens in the research that I do not see the relevance words, sentences or the like, so the word is considered independently.
• Changing from capital letters to all lowercase.
• Parsing and Stemming. decomposition into the form of single words and words into the form of the establishment of the foundation, so that words that have a basic form of words will be the same.
• Weighting -> Starting with the calculation of the number of words in each document, which will then be calculated using the scheme weighting process desired.

Science belief according to Al - Digital Koran is a faith and confidence of Allah, which are grouped in a peaceful faith that we know [5] [6] [9]:

1. Faith in God

2. Faith to Angel of God

3. The faith of Scripture

4. The faith of the Messenger of Allah

5. Faith to the Day of Resurrection

6. The faith of destiny

Here is a system architecture design project end. Where users do request to the web server, web server and computing to explore with the authentication keyword database. Then the web server to provide the results to the user.

Process on the end of this project are:

1. The process is there is a prepossessing method to remove the punctuation mark, number, symbol, mark up, and make all the words with the uniform makes them all small letters.
2. Stemming the method is to split the sentence into words - words that stand alone. Because the word in the text mining in the sentence has no relevance.
3. Stemming the words of this process is cut so that the leading particle and the word - a word only in the form of basic words. So weighting valid.
4. Weighting or group weighting process word - a word basis.
5. Search for keyword keyword is the word - a word which is more than 2 and is a keyword in the belief

Conclusion

Based on the results of experiments and analysis carried out in the Project End this can be concluded that:

1) The system has been created as able to meet the needs of search applications verse - verse of the Holy "Qur'an"-related problems by using the belief Text Mining.
2) All the keywords that can be identified particle all except the word "kingdom" which is the "king".
3) This system does not save all the data "Al - Qur'an" on a problem, but taken at least 70% of the "Al - Qur'an". Data "Al - Qur'an" is considered to be taken to represent the other.


2. Advice

Here are some suggestions for the development of the system in the future, based on the results of the design, implementation, and testing that was done.:
1) Complete data paragraph "Al - Qur'an", of course, must at the same time with a larger database from "MYSQL".
2) Complete the data keyword belief problems
3) improve the stemming algorithm, that is the case in the word "kingdom". With:
a. First check in the database, including whether or not the basic word. If you are including the words do not have the basic process through stemming.
b. Perfect combination of particle algorithm.
4) The making of the application form of "WAP" or desktop applications, so that the web service can be accessed by the application of the various platforms.
5) The making of the feature entry words and basic word of particle with administrative authentication credentials.

Just Joke

a day, john was near death. with a pain he said to his wife, Alice.

John: My dear, after I die I want you to marry Bob. I will be quiet in heaven if you become his wife.

Alice: Bob enemies when you are young, why do you want me married to Bob?

John: Thus I want him to feel that I Suffering natural for this since I married You.