log 0log Berdasarkan data-data berikut ini buat Decision tree-nya Solusi: Node Awal

Transkripsi

1 olusi Quiz enin, Mei istem endukung Keputusan Berdasarkan data-data berikut ini buat Decision tree-nya olusi: de Awal [] Hitung awal Jumlah Instance Total = 7 Jumlah Instance Yes = 4 Jumlah Instance = ) = 4 4 = = =.57(.8).4(.8) [] Hitung dan Infromation Gain per Atribut untuk menentukan node awal Atribut Age <= Yes.. Yes > Yes ( Age <= ) = = = ( Age =..) = = = IF-UTAMA Ver/Re:/ Halaman: dari 7

2 olusi Quiz enin, Mei =.95 ( Age ) (.578).(.6) > = Yes Yes ( Age) = ( ) ( ) <= =. (.6).67(.578) { >=,.., > } istem endukung Keputusan.. > ( Age <= ) ( Age =..) ( Age > ).594 Atribut income High Yes Medium Yes Low Yes ( Income = High) = = = ( Income = Medium) = = =.95 ( Income = Low) = =.67.. (.578).(.6) IF-UTAMA Ver/Re:/ Halaman: dari 7

3 olusi Quiz enin, Mei istem endukung Keputusan ( Income) ( ) ( ) = { High, Medium, Low} High Atribut student Yes Yes Yes ( tudent ) = = = =.5( ).5( ) = tudent Yes = =.95 ( ) Medium Low ( High) ( Medium) ( Low) = (.578).(.6) Atribut Fair = Yes Yes.67.. Yes Excelent ( tudent) ( ) ( ) Leasing_rating Yes Yes = { Yes, } ( tudent = Yes) ( tudent = ) IF-UTAMA Ver/Re:/ Halaman: dari 7

4 olusi Quiz enin, Mei = 4 =.5 = ( Leasing_rating Fair) ( ).75(.45) (.578).(.6) = =.8 ( Leasing_rating = Excelent) = =.67.. ( Leasing_rating) ( ) ( ) Fair = { Fair, Excelent} istem endukung Keputusan Excelent ( Leasing_rating = Fair) ( Leasing_rating = Excelent). Atribut Information Gain Age.594 Income. tudent. Leasing_Rate. Karena Atribut Age memiliki Nilai Information Gain tertinggi maka Atribut tersebut dijadikan node awal, sehingga decision tree-nya menjadi [] Hitung dan Infromation Gain per Atribut untuk menentukan node cabang dari edge > IF-UTAMA Ver/Re:/ Halaman: 4 dari 7

5 olusi Quiz enin, Mei istem endukung Keputusan Jumlah Instance untuk Atribut Age > = Jumlah Instance Yes = Jumlah Instance = Atribut income High Yes Medium Yes Low Yes ( Income = High) = = = ( Income = Medium) = = = ( Income = Low) = = = =.5( ).5( ) = Income = Atribut Yes High ( ) ( ) ( ) student Yes Yes Medium Low ( High) ( Medium) ( Low) { High, Medium, Low} IF-UTAMA Ver/Re:/ Halaman: 5 dari 7

6 olusi Quiz enin, Mei = =.5 = ( ) ( tudent ) =.5.5 ( ).5( ).5 = = = ( tudent = Yes) = = =.986 Yes ( tudent) = ( ) ( ) (.578).(.6) Leasing_rating { Yes, } ( tudent = Yes) ( tudent = ).9 Atribut Leasing_rating Fair Yes Excelent Yes ( Leasing_rating = Fair) = =.67.. ( ) ( Excelent) = = = = istem endukung Keputusan IF-UTAMA Ver/Re:/ Halaman: 6 dari 7

7 olusi Quiz enin, Mei istem endukung Keputusan Fair ( Leasing_rating) = ( ) ( ) { Fair Excelent}, Excelent ( Leasing_rating = Fair) ( Leasing_rating = Excelent) Atribut Information Gain Income.9 tudent.9 Leasing_Rate.76 Karena Atribut Leasing_Rate memiliki Nilai Information Gain tertinggi maka Atribut tersebut dijadikan node cabang untuk edge >, sehingga decision tree-nya menjadi [4] Decision tree yang dihasilkan adalah IF-UTAMA Ver/Re:/ Halaman: 7 dari 7