maTdishoLic

Expert System Design in Prolog

2009-12-14T05:30:00.000-08:00

EXPERT SYSTEM DESIGN FOR KNOWING THE CHARACTERISTIC OF BLOOD TYPE in SWI PROLOG

Pada Final Project 4, kita telah membuat desain system pakar yang berguna untuk mengetahui karakteristik atau komponen apa saja yang terdapat di dalam setiap golongan darah. Karakteristik tiap golongan darah pun telah kita jelaskan pada final project 4 beserta prolog nya. Namun, kami menganggap prolog yang kami buat sebelumnya belum sempurna. Oleh karena itu, kita akan menunjukkan desain system pakar baru yang kami buat di prolog. Mari kita perhatikan desain system pakar yang telah kami buat:

Sistem Pakar Karakteristik golongan darah ini memiliki data-data sebagai berikut:

Tipe A:

Memiliki Aglutinogen A
Memiliki Aglutinin B
Jika darah ditetesi zat Anti A maka darah akan menggumpal dan Jika darah ditetesi zat Anti B maka darah tidak akan menggumpal.

Tipe B:

Memiliki Aglutinogen B
Memiliki Aglutinin A
Jika darah ditetesi zat Anti A maka darah tidak akan menggumpal dan Jika darah ditetesi zat Anti B maka darah akan menggumpal.

Tipe AB:

Memiliki Aglutinogen A dan B
Tidak memiliki agglutinin
Jika darah ditetesi zat Anti A maka darah akan menggumpa dan Jika darah ditetesi zat Anti B maka darah juga akan menggumpal.

Tipe O:

Tidak Memiliki Aglutinogen
Memiliki Aglutinogen A dan B
Jika darah ditetesi zat Anti A ataupun zat Anti B maka darah tidak akan menggumpal.

Untuk menyimpan Data-Data tersebut dalam notepad agar bisa dijadikan program di prolog maka dapat ditulis atau diketik rule nya pada notepad sebagai berikut:

bloodtype(type_A,aglutinogen_A,aglutinin_B,clump,not_clump).

bloodtype(type_B,aglutinogen_B,aglutinin_A,not_clump,clump).

bloodtype(type_AB,aglutinogen_A_and_B,no_aglutinin,clump,clump).

bloodtype(type_O,no_aglutinogen,aglutinin_A_and_B,not_clump,not_clump).

NB(forgive us if its make you confuse):

type=menjelaskan tentang tipe darah

aglutinogen=menjelaskan aglutinogen yang dimiliki

aglutinin= menjelaskan aglutinin yang dimiliki

clump/not clump=clump/not clump setelah aglutinin menyatakan reaksi darah setelah ditetesi zat Anti A, sedangkan pada clump/not clump bagian akir menyatakan reaksi darah setelah ditetesi zat Anti B.

Kemudian, kami akan membuat program dimana saat di masukkan sebuah kondisi maka dapat disimpulkan jenis golongan darah tersebut. Misalnya:

1. JIKA : Memiliki Aglutinogen A

MAKA : Jenis Golongan Darah adalah Golongan Darah A.

2. JIKA : Memiliki Aglutinin A

MAKA : Jenis Golongan Darah adalah Golongan Darah B.

3. JIKA : Ditetesi zat Anti A menggumpal dan saat ditetesi zat Anti B tidak menggumpal

MAKA : Jenis Golongan Darah adalah Golongan Darah A.

Program pertama yang kami buat yaitu menentukan kondisi aglutinogen yang dimiliki oleh tiap tipe golongan darah. Maka dapat ditulis atau diketik caranya atau rule pada notepad sebagai berikut :

aglutinogen_A:-bloodtype(Darah,Aglutino,_,_,_),Aglutino=aglutinogen_A,

write('Blood Type is '),write(Darah),nl,fail.

aglutinogen_A.

Cara ini juga bisa dilakukan pada setiap golongan darah namun harus merubah persyaratannya terlebih dahulu. Untuk rule selengkapnya, lihat gambar di bawah ini:

Program kedua yang kami buat yaitu menentukan kondisi aglutinin yang dimiliki oleh tiap tipe golongan darah. Maka kita dapat mengetik rulenya pada notepad sebagai berikut :

no_aglutinin:-

bloodtype(Darah,_,Aglutinin,_,_),Aglutinin=no_aglutinin,write('Blood Type is '),write(Darah),nl,fail.

no_aglutinin.

Cara ini juga bisa dilakukan pada setiap golongan darah namun harus merubah persyaratannya terlebih dahulu. Untuk rule selengkapnya, lihat gambar di bawah ini:

Program ketiga yang kami buat yaitu menentukan kondisi saat ditetesi zat anti a dan zat anti b yang terjadi pada tiap tipe golongan darah. Kita dapatt mengetik rulenya pada notepad sebagai berikut :

clump_not:-

bloodtype(Darah,_,_,clump,not_clump),

write('Blood Type is '),write(Darah),nl,fail.

clump_not.

NB: clump_not memiliki arti clump = menggumpal saat ditetesi Zat anti A dan

not = tidak menggumpal saat ditetesi zat anti B.

more example: not_not memiliki arti not = tidak menggumpal saat ditetesi zat anti A dan not= tidak menggumpal saat ditetesi zat anti B.

Cara ini juga bisa dilakukan pada setiap golongan darah namun harus merubah persyaratannya terlebih dahulu. Untuk rule selengkapnya, lihat gambar di bawah ini:

Selain ketiga program diatas, kita juga membuat satu lagi yaitu untuk memunculkan semua karakteristik setiap golongan darah. Caranya yaitu:

tipeO:-bloodtype(type_O,Forename,Surname,Forename1,Surname1),write('The characteristic are: '),nl,write(Forename),nl,write(Surname),nl,write('when its dropped'),write(' by Anti A'),write(' ,its will be '),write(Forename1),nl,write('when its dropped'),write(' by Anti B'),write(' ,its will be '),write(Surname1),nl,fail.

tipeO.

NB: forgive us if this rule too complicated to make you understand.

Cara ini juga bisa dilakukan pada setiap golongan darah namun harus merubah persyaratannya terlebih dahulu. Untuk rule selengkapnya, lihat gambar di bawah ini:

Then, setelah kita menyimpan semua rule yang telah kita kerjakan menjadi satu di notepad dengan format .pl atau prolog, maka kita dapat melihat tampilan program kita dalam SWI Prolog sebagai berikut:

1. Kondisi Aglutiogen

NB: keyword yang digunakan yaitu aglutinogen_(tipe aglutinogen) jika tidak ada maka no_aglutinogen.

2. Kondisi Aglutinin

NB: keyword yang digunakan yaitu aglutinin_(tipe aglutinogen) jika tidak ada maka no_aglutinin.

3.Kondisi saat ditetesi zat Anti A dan zat Anti B

NB: keyword yang digunakan yaitu (kondisi darah saat ditetesi zat antiA)_ (darah kondisi darah saat ditetesi zat antiA) jika tidak menggumpal=not, dan jika menggumpal=clump

4. Menampilkan seluruh karakter yang dimiliki oleh golongan darah

NB: keyword yang digunakan yaitu tipe(jenis golongan darah).

This program inspirated by Logic Programming chapter 6

LOOPS

2009-12-07T20:32:00.000-08:00

Most conventional programming languages have a looping facility that enables a set of instructions to be executed repeatedly either a fixed number of times or until a given condition is met. In Prolog, this can be done in a variety of ways, using backtracking, recursion, built-in predicates, or a combination of these.

1. Looping a Fixed Number of Times
No such facility is available in Prolog (directly), but a similar effect can be obtained using recursion,

2. Looping Until a Condition Is Satisfied
Again, no such facility is available directly in Prolog, but a similar effect can be obtained in several ways.
1. Recursion
The function of recursion is to read terms entered by the user from the keyboard and output them to the screen, until end is encountered. This recursive program repeatedly prompts the user to enter a term until either yes or no is entered.
2. Using the 'repeat' Predicate
Recursion is not always the easiest way to provide the types of looping required in Prolog programs. Another method that is often used is based on the built-in predicate repeat.
The goal repeat does not repeat anything; it merely succeeds whenever it is called. The great value of repeat is that it also succeeds (as many times as necessary) on backtracking. The effect of this, as for any other goal succeeding, is to change the order of evaluating goals from 'right to left' (i.e. backtracking) back to 'left-to-right'. This can be used to create a looping effect.
This program repeatedly prompts the user to enter a term until either yes or no is entered. It is an alternative to the recursive program shown at the end of the previous section. In this case it is debatable whether using repeat is an improvement on using recursion.
Goals to the left of repeat in the body of a clause will never be reached on backtracking. The next program reads a sequence of terms from a specified file and outputs them to the current output stream until the term end is encountered. This program shows how to implement a menu structure which loops back repeatedly to request more input. Entering go at the prompt causes Prolog to output a menu from which the user can choose activities one at a time until option d is chosen. Note that all inputs are terms and so must be followed by a full stop character.
3. Backtracking with Failure
As the name implies, the predicate fail always fails, whether on 'standard' evaluation left-to-right or on backtracking. Advantage can be taken of this, combined with Prolog's automatic backtracking, to search through the database to find all the clauses with a specified property.
1. Searching the Prolog Database
2. Finding Multiple Solutions

This chapter describes how a set of goals can be evaluated repeatedly in Prolog, either a fixed number of times or until a specified condition is met, and how multiple solutions can be arrived at using the technique of 'backtracking with failure'.

LOOPS

2009-12-07T08:01:00.000-08:00

LOOPS
The Answer of Exercise 6

1. if we want to define the values of the squares of the integers from N1 to N2 inclusive and test it with N1 = 6 and N2 = 12. So, first we must write the rule or program in notepad. we can use writesquares to find the value of its squares.In our program, we change N1 to A, and N2 to B (but it's not problem).
then, You can see the rule in the picture below:

So, the result will be shown on our SWI Prolog if we write writesquares(6,12). on our SWI Prolog. Lets see the picture below:

2. If we want to define and test a predicate to read in a series of characters input by the user and output all of those before the first new line or ? character. So, first we must write the rule or program in notepad. we can use this rule to solve this problem. You can see the rule in the picture below:

then, the result will be shown if we write go., and then we can write anyword that we want, for the example; we write MatdisHolic on our SWI Prolog. Lets see the picture below:

3. if we want to find the professions of all those in data which have age over 40, So, for the first we must write the rule or program in notepad. we can use rule like in example 6.3.1 to solve this problem. You can see the rule in the picture below:

Notes: we can change "allover40" to other word that we want because its can't make the result will be error.

then, the result will be shown in our SWI Prolog if we write "allover40." before. Lets see the picture below:

SUMMARY OF CHAPTER 5

2009-11-25T05:13:00.001-08:00

SUMMARY OF INPUT AND OUTPUT

1. Outputting Terms
The main built-in predicate provided for outputting terms is write/1. The write/1 predicate takes a single argument, which must be a valid Prolog term. Evaluating the predicate causes the term to be written to the current output stream, which by default is the user's screen. The built-in predicate nl/0, It takes no arguments. Evaluating a nl goal causes a new line to be output to the current output stream. for examples;

?- write(26),nl.
26
yes

2. Inputting Terms
The built-in predicate read/1 is provided to input terms. It takes a single argument, which must be a variable. Evaluating it causes the next term to be read from the current input stream,
which by default is the user's keyboard. When a read goal is evaluated, the input term is unified with the argument variable. If the variable is unbound (which is usually the case) it is bound to the input value. for example;

?- read(X).
: 26.
X = 26

If the argument variable is already bound (which for most users is far more likely to occur by mistake than by design), the goal succeeds if and only if the input term is identical to the previously bound value.

?- X=fred,read(X
: fred.
X = fred

3. Input and Output Using Characters
Although input and output of terms is straightforward, the use of quotes and full stops can be cumbersome and is not always suitable. A much better approach for problems of this kind is to input a character at a time.
All printing characters and many non-printing characters (such as space and tab) have a corresponding ASCII (American Standard Code for Information Interchange) value, which is an integer from 0 to 255. The table below gives the numerical ASCII values corresponding to the main printable characters and some others.

4. Outputting Characters
Characters are output using the built-in predicate put/1. The predicate takes a single argument, which must be a number from 0 to 255 or an expression that evaluates to an integer in that range. Evaluating a put goal causes a single character to be output to the current output stream. This is the character corresponding to the numerical value (ASCII value) of its argument, for example

?- put(97),nl.
a
yes

5. Inputting Characters
The get0 predicate takes a single argument, which must be a variable. Evaluating a get0 goal causes a character to be read from the current input stream. The variable is then unified with the ASCII value of this character. Assuming the argument variable is unbound (which will usually be the case), it is bound to the ASCII value of the input character.

?- get0(N).
: a
N = 97

The get predicate takes a single argument, which must be a variable. The variable is then unified with the ASCII value of this character in the same way as for get0.

6. Input and Output Using Files

Prolog takes all input from the current input stream and writes all output to the current output stream. By default both of these are the stream named user, denoting the user's terminal.

The user may open and close input and output streams associated with any number of named files but there can only be one current input stream and one current output stream at any time. Note that no file can be open for both input and output at the same time (except user) and that the user input and output streams

cannot be closed.

7. file Output: Changing the Current Output Stream

The current output stream can be changed using the tell/1 predicate. This takes a single argument, which is an atom or variable representing a file name. Evaluating a tell goal causes the named file to become the current outputstream.

If the file is not already open, a file with the specified name is first created.

The default current output stream is user, i.e. the user's terminal. This value can be restored either by using the told predicate or by tell(user).

The built-in predicate told/0 takes no arguments. Evaluating a told goal causes the current output file to be closed and the current output stream to be reset to user, i.e. the user's terminal.

The built-in predicate telling/1 takes one argument, which must be a variable and will normally be unbound. Evaluating a telling goal causes the variable to be bound to the name of the current output stream.

8. File Input: Changing the Current Input Stream

The current input stream can be changed using the see/1 predicate. This takes a single argument, which is an atom or variable representing a file name, e.g. see('myfile.txt').

Evaluating a see goal causes the named file to become the current input stream. If the file is not already open it is first opened (for read access only). If it is not possible to open a file with the given name, an error will be generated.

Note that the file corresponding to the previous current input stream remains open when a new current input stream is selected. Only the current input stream can be closed (using the seen predicate described below).

The default current input stream is user, i.e. the user's terminal. This value can be restored either by using the seen predicate or by see(user).

The built-in predicate seen/0 takes no arguments. Evaluating a see goal causes the current input file to be closed and the current input stream to be reset to user, i.e. the user's terminal.

The built-in predicate seeing/1 takes one argument, which must be a variable and will normally be unbound. Evaluating a seeing goal causes the variable to be bound to the name of the current input stream.

11.Reading from Files: End of File

If the end of file is encountered when evaluating the goal read(X), variable X will be bound to the atom end_of_file.

12.Reading from Files: End of Record

Typically the end of a line of input at the user's terminal will be indicated byt the character with ASCII value 13. The end of a record in a file will generally be indicated by two ASCII values: 13 followed by 10. The following program shows how to read in a series of characters from the keyboard and print them out, one per line.

INPUT AND OUTPUT

2009-11-25T05:13:00.000-08:00

The Answer of Practical Exercise 5 Page : 82-83.

1. Number 1 is about predicate makelower

if we want to convert any upper case letters to lower case, we must write some rules or program in notepad use predicate makelower in order that we can consult it in SWI Prolog. for the first we can write some rules in notepad like the picture below:

After you write its program, you must write makelower . and enter character that you want on your SWI Prolog. So, you can see the result will be shown in SWI Prolog like the picture below:

2. Number 2 is about predicate copyterms
if we want to reads all the term in a text file and outputs them as terms to another text file one by one on separates lines, we must use predicate copyterms. for the first we must make a file in notepad for input file and save as with txt. format. we give name "infile" for our file.

second, we must make a new file again in notepad for output file, we give name "outfile" for our file.
third, we must make some rules in notepad like this picture below in order that we can consult it to SWI Prolog.
After you write its program, you must write copyterms(‘infile.txt’,'outfile.txt’) . or enter the file's name of your file on your SWI Prolog. So, you can see the result will be shown in SWI Prolog like the picture below:

3. Number 3 is about predicate readfile

if we want to convert a characters to the ASCII value, we can use predicate readfile. according to question number 3, we must make a file in notepad which we must write:

Giving name of the file "tesla" and save it with .txt fomat.
in order we can consult on SWI Prolog, so we must make some rules in notepad like this picture below:

After you write its program, So, you can see the result will be shown in SWI Prolog like the picture below:

4. Number 4 is about predicate combine

create 2 text files in1.txt and in2.txt, each comprising a number of terms terminated by end. you can see this picture below:

to define a predicate combine that takes names of two input files as its first two arguments and the name of an output file as its third argument. in order that the output file contain the terms in the first input file followed by the terms in the second, you must write some rules using predicate combine in notepad like the picture below:

After you write its program, So, you can see the result will be shown in SWI Prolog like the picture below:

5. Number 5 is about predicate compare

in order that we can reads that two text files term by term and each pair of corresponding terms output a messsage saying that they are the same or different, we must make two text files which contain the same number of terms and the final term in each is end. Look the picture below:

then, we must make some rules in notepad using predicate compare like this picture below in order that we can consult it to SWI Prolog.

After you write its program, So, you can see the result will be shown in SWI Prolog like the picture below:

Slide 4

Expert System Design

2009-11-23T18:02:00.000-08:00

Expert System Design for knowing

the characteristic of blood types.

Everyone in the world have different blood type. Karl Landstainer had divide blood into 4 types. The blood types are A, B, AB, and O. In usually, we will know what type of our blood when we check our blood in a hospital or when we want to transfuse our blood in an Indonesia Red Cross Committee. But, after we check what type of our blood, we just know our blood type but we don’t know how a blood can said type A, type B, type AB, or type O. Because of the problem, we make expert system design for knowing characteristic and component of blood types in order to everyone can know how a blood can said type A, type B, type AB, or type O. Before, we show our expert system design, we will explain the characteristic and component of each blood types.

1. Blood type A: when the blood is dropped by Anti A substance (agglutinin A), the blood will make some lumps and when the blood is dropped by Anti B substance (agglutinin B), the blood can’t react or can’t make a lump. It caused by blood type A have aglutinogen A and agglutinin B..

2. Blood type B: when the blood is dropped by Anti A substance, the blood will not react or can’t make a lump and when the blood is dropped by Anti B substance, the blood will make some lumps. It caused by blood type B have aglutinogen B and aglutinin A.

3. Blood type AB: when the blood is dropped by Anti A substance, the blood will make some lump and when the blood is dropped by Anti B substance, the blood will make some lumps, too. It caused by blood type AB have aglutinogen A and B but have not aglutinin A or B.

4. Blood type O: when the blood is dropped by Anti A substance, the blood will not react or can’t make a lump and when the blood is dropped by Anti B substance, the blood can’t make a lump, too. It caused by blood type O have not aglutinogen A or B but have aglutinin A and B.

After we explain to you about the characteristic and component of each blood types, we will show you the program of our expert system design in notepad:

In this picture, it can show our expert system design in SWI Prolog:

Knowing our blood type is very useful, maybe one day someone need our blood which our blood have same type with them, So, we can tranfuse our blood to them. beside that, if we know the characteristic and component of each blood type, it will help us to check our blood type by self in laboratory without medical worker.

SUMMARY Operators and Arithmetic

2009-11-12T05:25:00.000-08:00

Operators and Arithmetic

1. Operator
Any user-defined predicate with two arguments (a binary predicate) can be converted to an infix operator.
Any user-defined predicate with one argument (a unary predicate) can be converted to a prefix operator. This enables the functor to be written before the argument with no parentheses.
a unary predicate can be converted to a postfix operator. This enables the functor to be written after the argument
Any user-defined predicate with one or two arguments can be converted to an operator by entering a goal using the op predicate at the system prompt. This predicate takes three arguments, for example

?-op(150,xfy,likes).

1. The first argument (150) is the 'operator precedence'. Operator precedence values are
used to determine the order in which operators will be applied when more than one
is used in a term. In most other cases it will suffice to use an arbitrary value such as 150.

2. The second argument should normally be one of the following three atoms:
xfy meaning that the predicate is binary and is to be converted to an infix operator
fy meaning that the predicate is unary and is to be converted to an prefix operator
xf meaning that the predicate is unary and is to be converted to a postfix operator

3. The third argument specifies the name of the predicate that is to be converted to
an operator.

2. Arithmetic
Prolog provides facilities for doing arithmetic using a notation similar to that which will already be familiar to many users from basic algebra.
There are some of the arithmetic operators and arithmetic functions available in Prolog:
1.X+Y the sum of X and Y
2.X-Y the difference of X and Y
3.X*Y the product of X and Y
4.X/Y the quotient of X and Y
5.X//Y the 'integer quotient' of X and Y (the result is truncated to then earest integer betwe it and zero)
6.X^Y X to the power of Y
7.-X the negative of X
8.abs(X) the absolute value of X
9.sin(X) the sine of X (for X measured in degrees)
10.cos(X) the cosine of X (for X measured in degrees)
11.max(X,Y) the larger of X and Y
12.sqrt(X) the square root of X

is predicate is normally used in the way described here, the first argument can also be a number or a bound variable with a numerical value. In this case, the numerical values of the two arguments are calculated. The goal succeeds if these are equal. If not, it fails.

1. first argument is an unbound variable, it is bound to the value of the second argument (as a side effect) .
2. first argument is a number, or a bound variable with a numerical value.
3. first argument is an atom, a compound term, a list, or a variable bound to one of these (none of which should happen), the outcome is implementation-dependent.
It is likely that an error will occur.

Operator Precedence in Arithmetic Expressions
Operators with relatively high precedence such as * and / are applied before those with lower precedence such as + and -. The effect is to give an expression such as A+B*C-D the meaning that a user who is familiar with algebra would expect it to have, i.e. A+(B*C)-D or (A+B)*(C-D).

Relational Operators
The infix operators =:= =\= > >= < =<>

3. Equality Operators
There are three types of relational operator for testing equality and inequality available in Prolog. The first type is used to compare the values of arithmetic expressions. The other two types are used to compare terms.

a. Arithmetic Expression Equality =:=
E1=:=E2 succeeds if the arithmetic expressions E1 and E2 evaluate to the same value.
b. Arithmetic Expression Inequality =\=
E1=\=E2 succeeds if the arithmetic expressions E1 and E2 do not evaluate to the same value.
c. Terms Identical ==
Both arguments of the infix operator == must be terms. The goal Term1==Term2 succeeds if and only if Term1 is identical to Term2. Any variables used in the terms may or may not already be bound, but no variables are bound as a result of evaluating the goal.
d. Terms Not Identical \==
Term1\==Term2 tests whether Term1 is not identical to Term2. The goal succeeds if Term1==Term2 fails. Otherwise it fails.
e. Terms Identical With Unification =
The term equality operator = is similar to == with one vital (and often very useful) difference. The goal Term1=Term2 succeeds if terms Term1 and Term2 unify, i.e.
there is some way of binding variables to values which would make the terms identical. If the goal succeeds, such binding actually takes place.
f. Non-Unification Between Two Terms \=
The goal Term1\=Term2 succeeds if Term1=Term2 fails, i.e. the two terms cannot be unified. Otherwise it fails.

4. Logical Operators
This section gives a brief description of two operators that take arguments that are call terms, i.e. terms that can be regarded as goals.
a. The not Operator
The prefix operator not/1 can be placed before any goal to give its negation. The negated goal succeeds if the original goal fails and fails if the original goal succeeds. The following examples illustrate the use of not/1. It is assumed that the database contains the single clause

b. The Disjunction Operator
The disjunction operator ;/2 (written as a semicolon character) is used to represent 'or'. It is an infix operator that takes two arguments, both of which are goals. Goal1;Goal2 succeeds if either Goal1 or Goal2 succeeds.

The Answer of Exercise 4 about OPERATOR and ARITHMETIC

2009-11-12T05:12:00.000-08:00

OPERATORS AND ARITHMATIC
1. Program yang harus dibuat dengan menggunakan bentuk operator untuk menghasilkan hasil yang sama seperti Animal Program pada chapter 2 dapat dibuat dengan beberapa rumus pada notepad, cara yaitu sebagai berikut:

a. - Karena argumen yang digunakan lebih dari satu argumen maka agar dapat dirubah atau dikonvert menjadi sebuah operator maka dengan memasukkan perdikat op pada system prompt. Predikat ini digunakan untuk tiga argumen. ?-op(150, fy, isa_dog).
- argument pertama menjelaskan Operator Precedence dimana merupakan sebuah integer dengan nilai dari 0 sampai ke atas.
- argumen kedua menggunakan fy dimana untuk mengkonversikan predikat unary menjadi operator prefix.
-argumen ketiga yang digunakan disesuaikan dengan argumen kedua karena argumen kedua mengkonversikan predikat unary menjadi operator prefix , maka bentuk argumen ketika adalah sebagai berikut: isa_dog.
Sehingga yang program bisa dibuat pada notepad adalah sebagai berikut:

b. Selanjutnya mendeklarasikan data sesuai pada animal program pada chapter 2 dengan cara merubah bentuk penulisan menjadi seperti berikut:

NB: digunakan bentuk isa_dog(fido) agar bisa mengkonversikan predikat unary menjadi operator prefix sesuai dengan argumen yang telah dideklarasikan sebelumnya.

c. Selanjutnya operator notation yang digunakan adalah sebagai berikut:

Jadi program yang harus dibuat pada notepad agar "animal program" bisa dieksekusi pada SWI prolog adalah sebagai berikut:

Tampilan program pada SWI Prolog adalah seperti gambar di bawah ini:

2. Program yang digunakan untuk menghitung rata-rata, akar dan mengetahui nilai maksimum dari 2 angka dapat langsung di buat pada SWI Prolog tanpa harus membuat program terlebih dahulu pada notepad.

a. Tampilan Program pada SWI Prolog untuk menghitung rata-rata dari 2 angka:

b. Tampilan Program pada SWI Prolog untuk menghitung akar dari perkalian 2 angka :

NB: Ada 2 cara berbeda yang dapat digunakan untuk menemukan akar dari hasil perkalian 2 angka yaitu pada no.1 dan no.2

c. Tampilan Program pada SWI Prolog untuk mengetahui nilai maksimum dari 2 angka :

Expert System (Sistem Pakar)

2009-10-25T05:32:00.000-07:00

Sistem Pakar

An expert system is a narrow slice of computer intelligence and knowledge-based application. Sebuah sistem pakar adalah sebuah kecerdasan komputer dan aplikasi berbasis pengetahuan. Its program are designed to emulate human decision-making expertise in a particular domain. Program yang dirancang untuk meniru keahlian manusia dalam pengambilan keputusan pada domain tertentu. Expert systems belong to a group of systems known as knowledge-based systems. Sistem pakar milik sekelompok sistem yang dikenal sebagai sistem berbasis pengetahuan. Knowledge-based systems contain the facts and procedures representing the rule of thumb (heuristic) decision-making processes of an expert. Sistem berbasis pengetahuan mengandung fakta-fakta dan prosedur yang mewakili Aturan (heuristik) proses pengambilan keputusan dari seorang ahli. That collection is kept in a knowledge base that is separate from a control program. Koleksi tersebut disimpan dalam basis pengetahuan yang terpisah dari program kontrol.

Apa itu Sistem Pakar?

Saat ini, bentuk yang paling umum dari sistem pakar

Structure of a Rule-based Expert System Aturan struktur berbasis sistem pakar

User Interface User Interface

Friendly Ramah
Maybe "Intelligent" Mungkin "Cerdas"

Knowledge of how to present information Pengetahuan tentang bagaimana untuk menyajikan informasi
Knowledge of user preferences...possibly accumulate with use Pengetahuan tentang preferensi pengguna ... mungkin terakumulasi dengan menggunakan

Databases Database

Contains some of the data of interest to the system Berisi beberapa data yang menarik bagi sistem
May be connected to on-line company or public database Dapat dihubungkan ke on-line database perusahaan atau publik
Human user may be considered a database Pengguna manusia dapat dianggap sebuah database

Inference Engine Kesimpulan Engine

general problem-solving knowledge or methods pemecahan masalah umum pengetahuan atau metode
interpreter analyzes and processes the rules penerjemah proses menganalisis dan aturan
scheduler determines which rule to look at next scheduler menentukan aturan untuk melihat selanjutnya
the search portion of a rule-based system bagian pencarian peraturan sistem berbasis

takes advantage of heuristic information mengambil keuntungan dari informasi heuristic
otherwise, the time to solve a problem could become prohibitively long sebaliknya, waktu untuk menyelesaikan suatu masalah bisa menjadi panjang prohibitively
this problem is called the combinatorial explosion masalah ini disebut ledakan kombinatorial

expert-system shell provides customizable inference engine sistem pakar shell menyediakan mesin inferensi customizable

Knowledge Base (rule base) Knowledge Base (peraturan dasar)

contains much of the problem solving knowledge mengandung banyak pengetahuan pemecahan masalah
Rules are of the form IF condition THEN action Aturan bentuk tindakan IF kondisi THEN

condition portion of the rule is usually a fact - (If some particular fact is in the database then perform this action) kondisi bagian dari aturan biasanya fakta - (Jika kenyataannya tertentu dalam database kemudian melakukan tindakan ini)
action portion of the rule can include tindakan bagian dari aturan dapat mencakup

actions that affect the outside world (print a message on the terminal) tindakan yang mempengaruhi dunia luar (mencetak pesan pada terminal)
test another rule (check rule no. 58 next) menguji peraturan lain (cek aturan no. 58 berikutnya)
add a new fact to the database (If it is raining then roads are wet). menambahkan fakta baru ke database (Jika hujan maka jalan-jalan basah).

Rules can be specific, a priori rules (eg, tax law . . . so much for each exemption) - represent laws and codified rules Aturan dapat spesifik, a priori aturan (misalnya, hukum pajak... Begitu banyak untuk setiap pengecualian) - mewakili dikodifikasi undang-undang dan peraturan
Rules can be heuristics (eg If the meal includes red meat then choose red wine). "rules of thumb" - represent conventional wisdom. Aturan dapat heuristik (misalnya Jika makanan termasuk daging merah kemudian pilih anggur merah). "Aturan praktis" - mewakili kebijaksanaan konvensional.
Rules can be chained together (eg "If A then B" "If B then C" since A--->B--- >C so "If A then C"). Aturan dapat dirantai bersama-sama (misalnya "Jika A maka B" "Jika B maka C" karena A ---> B ---> C sehingga "Jika A maka C").
(If it is raining then roads are wet. If roads are wet then roads are slick.) (Jika hujan maka jalan-jalan basah. Jika jalanan basah maka jalan yang licin.)
Certainty factors represent the confidence one has that a fact is true or a rule is valid Faktor kepastian mewakili keyakinan seorang pun bahwa fakta itu benar atau sebuah aturan yang berlaku

Classification of Expert Systems Klasifikasi Expert Systems
In an attempt to classify expert system for discussion purpose, schemas have been devised that are based on the number of rules. Dalam upaya untuk mengklasifikasikan sistem pakar untuk tujuan diskusi, skema yang telah dirancang didasarkan pada jumlah aturan. These classification systems suggest that there are three basic classes of expert system : small, medium, and large. Sistem klasifikasi ini menunjukkan bahwa ada tiga kelas dasar sistem pakar: kecil, sedang, dan besar. A small systems has been defined as one that uses a knowledge base comprising fewer than 500 rules. Sebuah sistem yang kecil telah didefinisikan sebagai salah satu yang menggunakan basis pengetahuan yang terdiri dari kurang dari 500 peraturan. A medium system consists of up to 10,000 rules, and large system has in excess of 10,000 rules. Sebuah sistem terdiri dari media hingga 10.000 peraturan, dan sistem besar memiliki lebih dari 10.000 peraturan.

Tutorial part2

2009-10-25T05:30:00.000-07:00

Jawaban Exercise 2:

Number 1:

a). Untuk mengetahui jenis binatang mamalia berdasarkan data yang ada , maka dapat diketahui dengan cara mengetik prolog di notepad sebagai berikut:

Dan tampilan pada SWI Prolog adalah sebagai berikut:

b) Untuk mengetahui jenis binatang mamalia yang karnivora berdasarkan data yang ada , maka dapat diketahui dengan cara mengetik prolog di notepad sebagai berikut:

Dan tampilan pada SWI prolog adalah sebagai berikut:

C). Untuk mengetahui jenis binatang mammalia yang memiliki badan berwarna belang atau garis-garis (stripes) berdasarkan data yang ada , maka dapat diketahui dengan cara mengetik prolog di notepad sebagai berikut:

Dan tampilan pada SWI prolog adalah sebagai berikut:

d). Untuk mengetahui apakah ada jenis binatang reptile yang memiliki bulu tengkuk pada data yang ada , maka dapat diketahui dengan cara mengetik prolog di notepad sebagai berikut:

Dan tampilan pada SWI prolog adalah sebagai berikut:

Number 2:
Untuk mengetahui pasangan lelaki dan perempuan pada data yang telah tersedia, maka dapat diketahui dengan mengetik prolog pada notepad sebagai berikut:

Dan tampilan pada SWI Prolog adalah sebagai berikut:

TUTORIAL

2009-10-13T05:22:00.000-07:00

Combinations of two sets

example:

a = {1,2}

b= {3,4}

So, there four combinations of two sets. they are {1,3}, {1,4}, {2,3}, and {2,4}.

if we use "prolog" to find the combinations of the sets, we can write in notepad like this:

a(1).

a(2).

b(3).

b(4).

sets(x):-a(x).

sets(y):-b(y).

combination(x,y):-a(x),b(y).

Then, its prolog is showed by this picture:

Our Biography

2009-10-13T00:07:00.000-07:00

Personal data

Name : Lilis Ernawati
NRP: 5209100085
Place, Date of Birth: Bojonegoro, 9th April 1991
Age: 18 years
Sex: Female
Religion: Islam
Civics: Indonesian
Address:Turi,Tambakrejo,Bojonegoro,Indonesia,62166
Telephone: -
Cell Phone: 085232295249
e-mail: ernawatililis@ymail.com

Formal education
1997 - 2003: SDN Turi 1
2003 - 2006: SMPN 1 Ngambon
2006 - 2009: SMAN 1 Padangan
2009: Information System, ITS

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Name: Riyan Adelia Suryaningati
NRP: 5209100096
Place, Date of Birth: Sidoarjo, 12th January 1992
Age: 17 years
Sex: Female
Religion: Islam
Civics: Indonesian
Address: Perum. Griya Candi Asri S.44, Sidoarjo, Indonesia, 61271
Telephone: 031 - 8061105
Cell Phone: 085733088024
e-mail: adellavigne@yahoo. co. id
adelia09@mhs.is.its.c.id

Formal education
1997 – 2003: SD Muhammadiyah 1 Sidoarjo
2003 – 2006: SMPN 1 Candi, Sidoarjo
2006 – 2009: SMAN 2 Sidoarjo
2009: Information System, ITS

Organisational experiences
*Osis / MPK 's administrator - SMAN 2 Sidoarjo Years: 2007-2008
*PHKRI vice chairman - SMAN 2 Sidoarjo Years: 2007-2008
*Karya Ilmiah Remaja ‘s member - SMAN 2 Sidoarjo Years: 2006-2008

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Name: Nurul Fakhria
NRP: 5209100097
Place, Date of Birth: Sidoarjo, 12th September 1991
Age: 18 years
Sex: Female
Religion: Islam
Civics: Indonesian
Address: jl. Kol. Soegiono Ngingas 79 RT/RW 5/II Waru, Sidoarjo
Telephone: 031 - 70696006
Cell Phone: 08563146006
e-mail: riachan_emoetch@yahoo. co. id
nurul.fakhria09@mhs.is.its.c.id

Formal education
1997 – 2003: MI NU Ngingas, Waru, Sidoarjo
2003 – 2006: MTs "Darul Ulum" Kureksari, Waru, Sidoarjo
2006 – 2009: SMAN 1 Waru, Sidoarjo
2009: Information System, ITS

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Name: Yuni Dwi Kurniawati
NRP: 5209100099
Place, Date of Birth: Sidoarjo, 17th June 1991
Age: 18 years
Sex: Female
Religion: Islam
Civics: Indonesian
Address: jl. nanas rt 10 rw 03 Dsa. Geluran, kec. Taman-Sidoarjo, Jatim-Indonesia
Telephone: 031 - 7886589
Cell Phone:085645142642
e-mail: yuni_dwika@yahoo.com
yuni09@mhs.is.its.co.id

Formal education
1997 – 2003: SD Geluran III
2003 – 2006: SMPN 1 Taman, Sidoarjo
2006 – 2009: SMAN 1 Sidoarjo
2009: Information System, ITS

Organisational experiences
*Youth Red Cross's secretary - SMAN 1 Sidoarjo Years: 2007-2008
*SKI's member - SMAN 1 Sidoarjo Years: 2006-2008
*Karya Ilmiah Remaja ‘s member - SMAN 1 Sidoarjo Years: 2006-2008