AbstrakPenelitian ini bertujuan untuk meningkatkan kompetensi guru SD dan SMP Negeri/Swasta di Kabupaten Ogan Ilir provinsi Sumatera Selatan. Peningkatan kompetensi guru dilakukan melalui Penelitian Tindakan Kelas (PTK). Pelatihan Penelitian Tindakan Kelas (PTK) dilakukan dengan strategi siklus yang dilakukan dengan tahapan dari identifikasi masalah, perencanaan, tindakan, observasi, dan refleksi. Berdasarkan identifikasi masalah bahwa masih banyak guru yang mengalami kesulitan dalam menyusun PTK dan melaksanakannya di kelas. Lemahnya kemampuan mereka dalam menyusun PTK disebabkan oleh keterbatasan pengetahuan atau pemahaman mereka tentang PTK secara praktek. Teknik pengumpulan data dalam penelitian ini menggunakan observasi, wawancara dan evaluasi. Dalam pelatihan menunjukkan bahwa para guru berpartisipasi aktif untuk memiliki keseriusan, kemauan, dan motivasi yang tinggi untuk mengembangkan penelitian tindakan kelas. Dalam meningkatkan keberhasilan pada proses pembelajaran salah satunya melalui penelitian tindakan kelas (PTK). Manfaat PTK di antaranya adalah membantu guru memperbaiki mutu pembelajaran, meningkatkan profesionalisme guru dan meningkatkan kompetensi guru. Kegiatan pelatihan Penelitian Tindakan Kelas ini memberikan dampak terhadap peningkatan pengetahuan yang signifikan tentang pemahaman penelitian tindakan kelas, pengolahan dan analisis data penelitian tindakan kelas. Hasil akhir dalam penelitian ini adalah proses pelatihan memberikan manfaat bagi guru, yaitu dapat meningkatkan pemahaman guru pada Penelitian Tindakan Kelas, menumbuhkan motivasi dalam menyusun PTK dan melaksanakan PTK, serta bagi sekolah dapat meningkatkan kinerja sekolah melalui peningkatan profesionalisme guru. Hasil dari penelitian ini dapat dijadikan sebagai bahan masukan guru di sekolah lainnya sebagai upaya untuk meningkatkan kompetensi guru melalui Penelitian Tindakan Kelas. Kata Kunci: Kompetensi Guru; Profesionalisme Guru; Penelitian Tindakan Kelas
Electric vehicles (EVs) could be used to address the issues of environmental pollution and the depletion of non-renewable energy resources. EVs, which are energized by a battery storage system, are becoming attractive because they keep the environment clean. Furthermore, the cost of EVs is becoming cheaper. Thus, EVs will become a significant load on utility distribution system in the future. EV chargers play a significant role in the expansion of EVs. The input current of an EV charger with a high total harmonic distortion (THD) and a high ripple distortion of the output voltage can impact battery life and battery charging time. Furthermore, the high cost and large size of the chargers are considered other issues in EV development. This work presents the complete design process of a universal EV charger with a special focus on its control algorithms. In this regard, a novel control algorithm based on the integration of voltage-oriented control (VOC) and the sinusoidal pulse-width modulation (SPWM) technique is proposed to ensure effective Levels 1, 2, and 3 battery charging. A simulation of the universal EV charger was conducted and assessed in MATLAB-Simulink. Moreover, a laboratory prototype was constructed with a TMS320F28335 digital signal processor (DSP) programmed as the controller to validate its operation and performance. The findings show that the proposed charger is able to provide a controllable and constant charging voltage for a variety of EVs, with an input current of low total harmonic distortion (THD) and an almost unity power factor.
In this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. The main goal of the ELD is to meet the load demand at minimum operating cost by determining the output of the committed generating unit while satisfying system equality and inequality constraints. The problem formulation is based on a multiobjective model in which the multiobjective are defined as fuel cost minimization and carbon emission minimization. MOCSA is based on the inspiration from the brooding parasitism of cuckoo species in nature. Three cases are considered to test the effectiveness of the proposed technique which are fuel cost minimization, carbon emission minimization and multiobjective function with fixed weighted sum. The effectiveness of the MOCSA’s performances are illustrated through comparative study with other techniques such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Particle Swarm Optimization (MOPSO) in terms of fitness functions. The proposed study was conducted on three generating unit system at various loading condition. The result proved that MOCSA provide better solution in minimizing fuel cost and carbon emission usage as compared to other techniques.
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