Analisis Implementasi Musaqoh Terhadap Kesejahteraan Perspektif Ekonomi Syariah

Peneltian ini bertujuan untuk menganalisis penerapan musaqoh terhadap kesejahteraan penggarap pada pertanian kelapa sawit perspektif ekonomi syariah. Penelitian ini merupakan penelitian lapangan dengan pendekatan kualitatif. Teknik pengumpulan data menggunakan observasi, wawancara, dan dokumentasi. Teknik analisis data menggunakan deskriptif kualitatif. Hasil penelitian menunjukkan bahwa kerjasama musaqoh pada pertanian kelapa sawit di Kabupaten pelalawan telah dilakukan dengan baik serta telah memenuhi rukun dan syarat bagi hasil dengan mengikuti kebiasaan masyarakat setempat (adat). Dalam pemeliharaan kelapa sawit menggunakan akad kerja sama bagi hasil atas perolehan hasil pertanian. Besaran porsi bagi hasil yang dilakuakn petani dan penggarap yaitu dibagi 3 atau dengan persentase 70:30. Implementasi musaqoh kelapa sawit secara umum telah sesuai dengan Ekonomi Syariah, pihak petani menyerahkan lahan  pertanian yang sudah ditanami kelapa sawit kepada penggarap untuk dipelihara mulai dari pembersihan lahan pertanian, pemupukan, hingga memanen hasil perkebunan. Akad musaqoh yang dijalankan mendatangkan kesejahteraan bagi penggarap dengan terpenuhinya kebutuhan dasar (primer).  

Denoising and Enhancement of Medical Images

Medical imaging captures visual representation of human body’s structural and functional aspects like tissues, bones, blood flow etc. for clinical analysis and medical intervention. Optical Imaging, X-ray, Computer tomography, Magnetic Resonance Imaging (MRI), Ultrasound etc. are common medical imaging techniques used by physicians. Among them ultrasound is the most widely used imaging technique due to its cost effectiveness and human health friendly characteristic. But ultrasound images are inherently corrupted with speckle noise and thus makes physician’s interpretation complex and time-consuming. Therefore, in medical image analysis image denoising has more clinical value since it helps the physicians to reach correct, reliable and speedy diagnosis by mitigating noise from the image. Image denoising also facilitate image segmentation, image fusion, object detection and target recognition. Computer-aided image denoising and image enhancement techniques helps to improve efficiency and accuracy of physician’s interpretation. This research work focused on the development of reliable image denoising and enhancement techniques for echocardiographic images. It aimed to denoise an echocardiographic image without introducing noise distortion and loss of information. Fractional calculus has been used to efficiently mitigate noise of various levels from the echocardiographic image. Also rough set theory and fuzzy logic have been used to draw boundaries between image regions. These concepts helped to handle uncertainty caused by the speckle noise. Three image denoising methods have been proposed in thesis. First proposed denoising methodology performs image denoising in two stages. Stage-1 applies weighted fuzzy mean filter and stage-2 convolves every pixel of the image with a fractional integration filter. Second proposed approach intelligently selects appropriate filter for every image region. Fractional order differintegral filter is proposed in third image denoising methodology. All three proposed denoising schemes not only preserve details in the denoised image but also efficiently reduce noise. Image Enhancement further improves the visual quality of an image. This research also proposes two echocardiographic image enhancement schemes to effectively utilize gradient magnitude and eigenvalue hessian matrix calculations and fractional order derivative concept. Real echocardiographic b-mode images and standard images artificially corrupted with speckle noise have been considered in simulations for this research. Visual and quantitative analysis of simulation results presents significant improvement by the proposed schemes as compared to state-of-the art image denoising and image enhancement techniques.