Judul: Klasifikasi Anak Putus Sekolah dengan Melibatkan Peubah Jaringan Sosial Menggunakan CART di Sulawesi
Abstrak: Education is one of the children’s rights as young generation successor to the nation that must be met by the government. According to Law No. 23 of 2002 Article 4 concerning the protection of children, child is defined as someone who hasn’t 18 years old. One of the rights of children which must be met by the government is the right to education. The government's success in meeting its obligations can be seen from how big the school dropout rate. One factor that can be measured by the low level of education is high dropout rates. In 2012, dropout rate for children 7-17 years old in all province at Sulawesi were still higher than national rate. To overcome these problems, efforts are required to identify and search factors that cause of dropouts. The socio-economic and demographic factors or environmental factors, especially social network effect in children’s live, so that the measures taken by the government can be precisely targeted. To determine the characteristics of dropout students require to clasify the children 7-17 year old using classification and regression tree (CART) method and then apply the Bagging techniques. This study aims to determine how the characteristics of dropout students 7-17 years old that more detailed in Sulawesi. Classification is built not only consider the socio-economic and demographic factors but also adds social network factors. Furthermore, it will be seen how the effect of these factors into the classification by looking the classification accuracy. The results showed that by adding the social network variables into the classification tree increase of 23.6% classification accuracy and application of Bagging techniques on single CART can improve the classification accuracy of 5.3%. The classification obtained some of the main characteristics of dropout students 7-17 years old in Sulawesi ie they are children who live in an environment that has quite high dropout rate, has a head of household who was not young anymore, and live with brother who also dropped out of school.
Keyword: classification of dropout student, classification and regression trees (CART), bootstrap aggregating (Bagging), accuracy of classification rate

Judul: Klasifikasi Keberhasilan Melanjutkan Pendidikan Jenjang SMA di Provinsi Banten dengan Metode CART dan Random Forest.
Abstrak: Tingkat putus sekolah di Indonesia memiliki persentase yang semakin tinggi ketika jenjang pendidikan semakin tinggi. Persentase melanjutkan pendidikan ke jenjang SMA di Indonesia berada di angka 77.50%. Banten merupakan salah satu provinsi yang memiliki persentase putus sekolah yang semakin tinggi ketika jenjang pendidikan juga semakin tinggi. Selain itu, Banten merupakan provinsi terendah kedua di Indonesia dalam persentase melanjutkan pendidikan ke jenjang SMA yaitu 68.92%. Penelitian ini mengkaji peubah penting dan kinerja klasifikasi yang dihasilkan oleh metode pohon klasifikasi dan random forest. Hasil kajian menunjukan bahwa peubah penting dari kedua metode sama yaitu pengeluaran per kapita (X8) dan proporsi anggota rumah tangga berpendidikan kurang dari SMA (X10). Kemudian, berdasarkan nilai AUC yang didapatkan dengan 10-fold cross validation menunjukkan metode random forest lebih baik dibandingkan pohon klasifikasi. Percobaan dengan melihat nilai akurasi, sensitivitas, dan spesifisitas pada beberapa nilai cuts off juga menunjukkan bahwa random forest dapat memberi kinerja prediksi yang lebih optimal dibandingkan pohon klasifikasi.
Keyword: AUC, cuts off, pohon klasifikasi, putus sekolah, random forest

Judul: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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