Metode Komputasi Murah Untuk Sinkronisasi Fasa Optik Pada Optical Beamforming Networks

Optical Beamforming Networks (OBFNs) is used to optimized the received signal power in airplane-satellite communication by controlling the signal beams towards the desired direction.  The control of these OBFNs is a difficult and very complex nonlinear problem. The complexity of OBFN can be reduced by lowering the bandwidth of the modulated optical signals at its inputs. It can be achieved by performing optical single-sideband suppressed-carrier (SSB-SC) modulation. However, there is potential problem due to the fact that the phase relation between the optical carrier and the remaining sideband is lost when the group delay response is only optimized for the sideband frequency range. Optical phase synchronization is used to correct this issue by adding extra phase shifters. However, there is not any simple yet effective method to determine the value of the extra phase shifters needed for a certain OBFN. This paper propose a simple and computationally cheap feedback approximation approach to solve this problem

Peningkatan Kemampuan Membaca Permulaan Menggunakan Media Kartu Huruf pada Pembelajaran Tematik Kelas II Sekolah Dasar Negeri 02 Nanga Tebidah Tahun Pelajaran 2014/2015

Penelitian Tindakan Kelas ini dimaksudkan untuk mempermudah siswa dalam membaca permulaan menggunakan media kartu huruf. Penelitian dilakukan di kelas II SD Negeri 02 Nanga Tebidah dengan subyek 21 orang siswa. Hasil analisis terhadap data yang dikumpulkan melalui observasi, wawancara, dan tes menunjukkan bahwa di dalam pembelajaran membaca permulaan: (1) siswa perlu dibantu dalam membaca sebuah cerita karena masih banyak yang belum bisa mengenal huruf abjad. Kemampuan rata-rata membaca permulaan siswa pada siklus I adalah 58.85. Pada siklus II nilai rata-rata siswa 81.85. Hal ini dapat dilihat dari hasil tes siswa pada siklus I dengan ketuntasan 47,61% meningkat pada siklus II menjadi 90,47%. Hasil penelitian ini menyimpulkan bahwa penerapan media kartu huruf dapat meningkatkan kemampuan membaca permulaan

Pengaturan Torsi pada Hybrid Electric Vehicle (Hev) Menggunakan Metode Neuro-fuzzy Prediktif

In hybrid electric vehicle, there are two sources of energy, namely Internal Combustion Engine (ICE) and DC motor. ICE as the prime mover has a smaller capacity than conventional vehicles because of the work is assisted by the DC motor. The DC motor acts to help internal combustion engine reach the torque and the speed as desired. Torque control of hybrid electric vehicle provide of how much torque required by the DC motor to assist the performance of ICE. When the ICE are not able to maintain the speed, the DC motor will help to provide the power. To overcome these problems, neuro-fuzzy predictive methods using inverse models are used. Neuro-fuzzy controller has the advantage of adaptability when the parameters in the system change. HEV itself requires a quick response therefore predictive controller used in order to predict the future value of the torque. Testing results showed that neuro-fuzzy predictive method which combines neurofuzzy controller with inverse models, able to assist ICE follows the reference model. The use of neuro-fuzzy predictive showed better control performance. This is shown from the speed response in 0.25 seconds able to produce a torque of 0.161 N-m, so that the HEV system can follow the desired reference model