Penelitian ini bertujuan untuk mendeskripsikan pengaruh perhatian orangtua, motivasi belajar, dan lingkungan sosial siswa terhadap prestasi belajar matematika siswa kelas VIII SMP di Kota Mataram. Jenis penelitian yang digunakan adalah penelitian kuantitatif yang bersifat expost facto. Populasi dalam penelitian ini adalah siswa kelas VIII SMP Negeri se Kota Mataram pada semester gasal tahun ajaran 2013/2014. Sampel 12 sekolah dipilih dengan menggunakan teknik stratified random sampling berdasarkan tingkat nilai UN sekolah dan mewakili 6 kecamatan yang ada di Kota Mataram dengan jumlah responden sebanyak 364 orang siswa. Instrumen yang digunakan untuk pengambilan data adalah instrumen tes prestasi belajar matematika kelas VIII yang terdiri dari 25 soal, angket perhatian orangtua siswa, angket motivasi belajar, dan angket lingkungan sosial siswa. Hasil penelitian menunjukkan bahwa perhatian orangtua, motivasi belajar dan lingkungan sosial secara bersama-sama memberikan pengaruh yang signifikan terhadap prestasi belajar matematika siswa SMP dengan sumbangan sebesar 10,6%. Secara parsial perhatian orangtua dan motivasi belajar memberikan pengaruh terhadap prestasi belajar sementara lingkungan sosial tidak memberikan pengaruh terhadap prestasi belajar. Kata kunci: perhatian orangtua, motivasi belajar, lingkungan sosial, dan prestasi belajar matematika

This article discusses about the application of the discovery learning model supported by Cabri 3D program to improve the learning outcomes of students in the three dimensions subject. This research is motivated by the study of grade X students focused on three-dimensional material in academic year 2013/2014 in which it does not reach KKM rated in 75 point. In this case, only 5 of 54 learners of class X could complete it. Meanwhile, the overall average was 63.06 by 9.26% as result of the percentage of completeness. It is affected by students who have not mastered the three-dimensional concepts and difficulties in abstracting the model or problem in three dimensions. This study aims to answer the formulation of the problem: could the application of the discovery learning model assisted by Cabri 3D program improve the learning outcomes of students in the subject matter of the three dimensions XA class MA Al Bidayah Candi Bandungan in the academic year 2014/2015. The success of this research is indicated by the improvement of learning outcomes above KKM that is 75 and percentage of students' completeness in each cycle. This research is included in classroom action research. It is research interests are 20 learners class XA MA Al Bidayah Candi Bandungan District Semarang in the academic year 2014/2015. Data were collected by documentation, observation, and test method. The collected data was analyzed using descriptive analysis to determine the average of learning outcomes and the percentage of learning mastery. Based on the results of the study, the average result of learning from the first cycle to the second cycle increased from 63.89 to 83.13 or by 19.24 points and mastery learning increased from 3 8.89% to 80% or by 41.11%. Implementation of discovery learning model-assisted learning program Cabri 3D can enhance the learning outcomes of students but not necessarily be able to improve learning outcomes, because it can be affected by various factors such as classroom management, the ability of learners, learners' concentration, accuracy, and so forth. So it is suggested to teachers to do innovative and various learning methods and utilizing media in supporting the learning process.

Analisis multivariat adalah salah satu teknik dalam statistika yang digunakan untuk menganalisis secara simultan variabel lebih dari satu. Perhitungan dalam analisis data multivariat lebih kompleks dibandingkan dengan analisis univariat, sehingga penggunaan program statistika akan mempermudah dalam analisis.  Salah satu program statistika yang dapat diperoleh secara gratis (tanpa lisensi) adalah program R. Workshop program R untuk analisis data multivariat bagi para lulusan S1 Pendidikan Matematika/Matematika dan mahasiswa program pasca sarjana Pendidikan Matematika secara umum bertujuan untuk memberikan pengetahuan dan ketrampilan dasar penggunaan program R pada analisis data multivariat. Metode yang digunakan dalam pelatihan meliputi tutorial dan praktek secara langsung. Sebagian peserta belum pernah menggunakan program R, dan terlihat bahwa mereka antusias dalam mengikuti pelatihan. Berdasarkan pengamatan dan tanya jawab dengan peserta pelatihan, tampak bahwa peserta bersemangat mengikuti kegiatan pelatihan. Dengan pelatihan ini para peserta mendapat pengetahuan secara teoritis tentang analisis komponen utama, analisis faktor dan secara praktek meliputi ketrampilan tentang bagaimana menganalisis data multivariat dengan program R, dan menginterpretasikan hasil analisis dengan kedua metode tersebut. Kata kunci: analisis multivariat, program statistika R. Multivariate Data Analysis Using R Program Abstract           Multivariate analysis is a technique in statistics that is used to simultaneously analyze more than one variable. Dealing with multivariate data analysis calculations are more complex than the univariate analysis, so the use of statistical program will make it easier. One of the free statistical programs (free license) is R program. Workshop R program on the multivariate data analysis for people who had mathematics or mathematics education degree or graduate students in general aims to provide multivariate data analysis skills using statistics R program. The training methods were tutorial and practices in class. Some participants had never used the R program prior to the training, and they were enthusiastic during training. According to the observations and questions and answers session, the participants appeared to have passions on learning the usage of  the statistical R program on analyzing multivariate data. From the training, the participants gained theoretical knowledge about the principal component analysis, factors analysis, and practices about the skills on how to analyze mulivariate data, and interpret the results of the analysis with both methods using the  R program. Keywords: multivariat analysis, R statistical program

Brain cancer is one of the most dangerous cancers that can attack anyone, so early detection needs to be done so that brain cancer can be treated quickly. The purpose of this study is to develop a new procedure of modeling radial basis function neural network (RBFNN) using singular value decomposition (SVD) method and to apply the procedure to diagnose brain cancer. This study uses 114 brain Magnetic Resonance Images (MRI). The RBFNN model is constructed by using steps as follows; image preprocessing, image extracting using Gray Level Co-Occurrence Matrix (GLCM), determining of parameters of radial basis function and determining of weights of neural network. The input variables are 14 features of image extractions and the output variable is a classification of brain cancer. Before learning process, the input data is normalized. The modeling is done by using K-means clustering method where the activation function in the hidden layer is Gaussian function and by determining the optimum weights of the model using SVD method. The best RBFNN model is 14 input neurons, 10 hidden layer neurons, and 1 output neuron. The results show that the sensitivity, specificity, and accuracy of RBFNN diagnoses with backpropagation equal to those of RBFNN with SVD. However, the RBFNN-SVD delivers an advantage in the running speed of the program.Index Terms-Radial basis function neural network, diagnosis brain cancer, singular value decomposition.

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