Judul: Identification of Affecting Factors on the GPA of First Year Students at Bogor Agricultural University Using Random Forest
Abstrak: Academically, the success of a student can be demonstrated by Grade Point Average (GPA). The performance of a student can be seen from the academic achievements, potential and motivation from themselves. Success in obtaining a high GPA can not be separated from the factors that affect the intellectual factor (the score of final examination in high school) and non-intellectual factors (gender, enrollment scheme to university, age when enrolled to university, senior high school status, etc). The data used for this research is the secondary data obtained from Student Affairs Directorate Bogor Agricultural University. Random forest method is an ensemble classifier using many decisions tree models. It can be used for classification or regression. This research is aimed to determine the size of the random forest and sample size of the explanatory variables that produces random forest with high prediction accuracy and stability that can identify the most important influential factors in student's academic achievements (GPA). High accuracy and stability can be obtained if size of the explanatory variable (m) and the size of the random forest (k) is determined by the right value. The values of m used in this study are 3, 4, 5 and 6. The values of k used in this study are 100, 500 and 1000. The smallest misclassification rate is at m = 4 and k = 100 with misclassification rate is 39.36%. Optimum random forest trees is used to get the best identifier variables. The most influential variable of the GPA of student at Bogor Agricultural University in the first year study by ranking criteria used Mean Decrease Gini (MDG) value of random forest.
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Judul: Data Hilang Dalam Analisis Pohon Regresi (Studi Kasus: Tingkat Keberhasilan Mahasiswa Pascasarjana IPB)
Abstrak: The objective of this research are to build regression tree which is contains of missing value to estimate efficacy level of Bogor Agricultural University’s post graduate students and to study about factors that influence efficacy level of Bogor Agricultural University’s post graduate students for each major. Missing value in Classification and Regression Trees (CART) could be handled by nonparametric approach based on iteration of regression tree classification. Each major contains of missing value in their predictor variable. Therefore, surrogates variable is been used to impute this missing value. This variable has high association with primer variable that contains of missing value that will be use as surrogate variable. Efficacy level that researcher want to see is Bogor Agricultural University’s post graduate students academic abilities. This point can be count by post graduate GPA and period of post graduate study. Therefore, factors which are influence efficacy level of Bogor Agricultural University’s post graduate students will be done by regression tree approaching. This research shows that missing value in large amount of value causes increasing of error level in regression tree classification and decreasing of prediction accuracy. This shows that missing value still become a serious problem in CART. The variable that has high association with primer variable that contains missing value will be use as surrogate variable. Regression tree that built from missing value with surrogates will give the best result if we compare it with regression tree that built without surrogates. As a result, post graduate degree in Bogor Agricultural University need to consider age, gender, accreditation, bachelor degree’s Grade Prediction Academic (GPA), profession, and duration from bachelor to post graduate degree variables, because this factors influence students efficacy level in each 16 majors for a period of study. While to produce higher post graduate’s GPA, they need to concern about duration period from bachelor to post graduate degree, earlier college status, acceptance status, age, and accreditation variables. Bogor Agricultural University’s post graduate need to consider all variables that mentioned to produce quality students in future.
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Judul: Desain Sistem Transfer Energi Nirkabel Berbasiskan Tesla Coil
Abstrak: Tesla coil merupakan alat yang ditemukan oleh Nikola Tesla yang dapat mentransmisikan daya tanpa kabel dengan memanfaatkan prinsip induksi elektromagnetik. Pada penelitian ini dibuat sebuah prototype Tesla Coil dengan menggunakan transistor C1970 dan receiver menggunakan rangkaian LC. Identifikasi alat meliputi pengaruh daya input transmitter terhadap receiver, bentuk signal yang dipancarkan transmitter, pengaruh jarak transmitter dan receiver, nilai efisiensi serta efek alat terhadap perangkat lain. Hasil pengamatan menunjukkan bahwa semakin besar daya input maka semakin besar daya yang dipancarkan oleh transmitter. Bentuk sinyal yang dipancarkan oleh transmitter berupa gelombang listrik AC sinusoidal dengan frekuensi ~2.9 MHz. Semakin jauh jarak receiver terhadap transmitter maka semakin kecil amplitudo gelombang AC yang diterima oleh receiver, menyebabkan semakin kecil daya yang diterima oleh receiver. Adapun nilai efisiensi terbesar penangkapan daya oleh receiver yaitu sebesar 0.00516 % serta terdapat gangguan pada alat-alat tertentu seperti monitor komputer dan radio.
Keyword: rangkaian LC, receiver, tesla coil, transistor C1970, transmitter