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"ABSTRACTInformation and communication technology (ICT) has been implemented in almost every division at the National Library. This implementation is supported by Undang Undang Nomor 43 tentang Perpustakaan. The aim of using ICT is to improve working performance and services of National Library. Pusat Pendidikan dan Pelatihan (Pusdiklat) is one of divisions that has not fully implemented ICT yet to increase the training quality and quantity, therefore management information system is required to support decision making related to the training. This research objective is to design a management information system using enterprise architecture framework, TOGAF. TOGAF provides a flexible framework to accommodate management information system design according to the organizations vision, mission and goals. This research yielded a blueprint of management information system of trainings program and evaluation. It is expected that this blueprint could be used to guide the development of management information system in Pusdiklat."

"The largest region that produces oil palm in Indonesia has an important role in improving the welfare an economy of the society. Oil palm production has increased significantly in Riau Province in every period. To determine the production development for the next few years, we proposed a prediction of the production results. The dataset were taken to be the time series data of the last 8 years (2005-2013) with the function and benefits of oil palm as the parameters. The study was undertaken by comparing the performance of Support Vector Regression (SVR) method and Artificial Neural Network (ANN). From the experiment, SVR resulted the better model compared to the ANN. This is shown by the correlation coefficient of 95% and 6% for MSE in the kernel Radial Basis Function (RBF), whereas ANN resulted only 74% for R2 and 9% for MSE on the 8th experiment with hidden neuron 20 and learning rate 0,1. SVR model generated predictions for next 3 years which rose 3%-6% from the actual data and RBF model predictionsDaerah penghasil kelapa sawit terbesar di Indonesia mempunyai peranan penting dalam peningkatan kesejahteraan dan ekonomi masyarakat. Produksi kelapa sawit mengalami peningkatan yang signifikan di Provinsi Riau dalam setiap kurun waktu, untuk menentukan perkembangan produksi beberapa tahun ke depan, kami mengusulkan suatu prediksi dari hasil produksi. Dataset yang diambil adalah data time series dari data yang diperoleh selama 8 tahun terakhir (2005-2013) dengan fungsi dan manfaat kelapa sawit sebagai parameter. Dalam implementasinya peramalan dilakukan dengan membadingkan kinerja metode Support Vector Regression (SVR) dan Artificial Neural Network (ANN). Dari percobaan, SVR menghasilkan model terbaik dibandingkan dengan ANN yaitu ditunjukkan dengan koefisien korelasi sebesar 95% dan MSE 6% pada kernel Radial Basis Function (RBF), sedangkan ANN hanya menghasilkan R2 sebesar 74% dan MSE 9% pada percobaan ke-8 dengan hidden neuron 20 dan learning rate 0,1. SVR model menghasilkan prediksi untuk 3 tahun kedepan yang memiliki kenaikan antara 3%-6% dari data aktual dan prediksi model RBF"