2,604 research outputs found

    STRATEGI GURU DALAM MEMBENTUK KARAKTER SISWA DI MI AL-IRSYAD AL-ISLAMIYYAH KALIOMBO KOTA KEDIRI

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    ABSTRAK Skripsi dengan judul “Strategi Guru dalam Membentuk Karakter Siswa di MI Al-Irsyad Al-Islamiyyah Kaliombo Kota Kediri“ ini ditulis oleh Anis Hidayah, NIM. 1725143024, Pembimbing Dr. H. Abd. Aziz, M. Pd. I. Kata kunci: Strategi, Guru, Membentuk, Karakter Pendidikan berperan penting dalam menyalurkan hal-hal baru sebagai upaya perubahan positif kepada setiap orang. Perubahan tersebut dapat berupa cara bersikap, cara bersosialisasi, mengembangkan potensi dan lain sebagainya. Karakter merupakan watak atau kebiasaan yang dilakukan terus-menerus sehingga tertanam dalam diri. Terwujudnya nilai karakter yang baik salah satu aspek penting yang menjadi perubahan di dalam proses pendidikan, yang ditengarai sebagai keberhasilan proses pembelajaran yang dilakukan. Karakter akan mudah tertanam dalam diri peserta didik dengan kegiatan pembiasaan yang dilakukan berulang-ulang secara teratur. Untuk membentuk karakter yang baik, guru dituntut untuk terus mengembangkan berbagai strategi, cara dan inovasi baru yang sesuai perkembangan dan kebutuhan zaman. Fokus penelitian dalam penulisan skripsi ini adalah (1) Bagaimana guru membentuk karakter religius siswa di MI Al-Irsyad Al-Islamiyyah Kaliombo Kota Kediri? (2) Bagaimana guru membentuk karakter mandiri siswa di MI Al-Irsyad Al-Islamiyyah Kaliombo Kota Kediri? (3) Bagaimana guru membentuk karakter tanggung jawab siswa di MI Al-Irsyad Al-Islamiyyah Kaliombo Kota Kediri?. Adapun yang menjadi tujuan penelitian ini adalah untuk mendeskripsikan guru membentuk karakter religius, karakter mandiri , dan karakter tanggung jawab siswa dalam pelaksanaanya di MI Al-Irsyad Al-Islamiyyah Kaliombo Kota Kediri. Penelitian ini menggunakan jenis penelitian kualitatif. Teknik pengumpulan data dilakukan melalui observasi, wawancara mendalam, dan dokumentasi. Paparan dan analisis data dilakukan dengan tehnik reduksi data ,penyajian data, dan penarikan kesimpulan. Pengecekan keabsahan data dilakukan dengan cara perpanjangan keikutsertaan, ketekunan pengamatan, dan triangulasi. Hasil penelitian menunjukkan bahwa: berdasarkan paparan data dan diskusi hasil penelitian maka dapat ditarik kesimpulan bahwa (1) guru membentuk karakter religius dengan cara pemahaman, pembinaan, dan pengawasan melalui pembiasaan yang telah dilaksanakan di madrasah yaitu shalat dhuhur berjamaah, shalat dhuha setiap hari Jumat, membaca doa sebelum dan mengakiri pemebelajaran, hafalan surat pendek dan doa keseharian, bimbingan membaca Al-Qur’an setiap hari Jumat, dan pembelajaran tahfidz. (2) guru membentuk karakter mandiri dengan cara praktik di dalam dan di luar kelas melalui pembiasaan yang telah dilaksanakan yaitu, upacara bendera hari Senin, berbaris sebelum masuk kelas, dan kegiatan kepramukaan. (3) guru membentuk karakter tanggung jawab dengan cara menerapkan aturan yang telah dibuat bersama dengan memberikan konsekuensi jika tidak dilaksanakan melalui kebiasaan yang telah ada yaitu, tanggung jawab piket, tanggung jawab tugas , serta kas kelas setiap hari Jumat

    The MOSAiC ROV Program: One Year of Comprehensive Under-Ice Observations

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    The overarching goal of the remotely operated vehicle (ROV) operations during MOSAiC was to provide access to the underside of sea ice for a variety of interdisciplinary science objectives throughout an entire year. The M500 ROV was equipped with a large variety of sensors and operated at several sites within the MOSAiC central observatory. Despite logistical and technological challenges, over the full year we accomplished a total of ~60 days of operations with over 300 hours of scientific dive time. 3D ice bottom geometry was mapped in high resolution using an acoustic multibeam sonar covering a 300 m circle around the access hole complementing other ice mass balance measurements on transects, by autonomous systems, airborne laser scanning and from classical ablation stakes. Various camera systems enabled us to document features of sea ice growth and decay. From early March onwards, with the sun rising again, a main focus was the investigation of the spatial variability in ice optical properties. Light transmittance was measured with several hyperspectral radiometers under marked survey areas, including various ice types such as first-year ice, second-year ice, pressure ridges, and leads. Optical surveys were coordinated with surface albedo measurements, vertical snow profiles and aerial photography. The ROV also supported ecosystem research by deploying sediment traps underneath pressure ridges, sampling algal communities at the ice bottom and in ridge cavities with a suction sampler as well as the regular towed under-ice zooplankton and phytoplankton nets. Ice algal coverage was further investigated using an underwater hyperspectral imaging system, while the ROV video cameras enabled the observation of fish and seals living in ridge cavities. The ROV also carried further oceanographic sensors providing vertical and horizontal transect measurements of small-scale bio-physical water column properties such as chlorophyll content, nutrients, optical properties, temperature, salinity and dissolved oxygen. Here we present first highlights from the year-long operations: the discovery of platelet ice under Arctic winter sea ice during polar night and the extensive time series of multibeam derived ice draft maps, which allow together with airborne laser scanner data a full 3D documentation of ice geometry

    Relation between sea ice freeboard and draft and its seasonal evolution in the Central Arctic

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    Relating the sea-ice surface to the under-ice topography is a timely scientific effort in the Arctic. This relation is crucial for estimating the ice thickness distribution for large‐scale modelling, for assessing the mechanical force that ships need to overcome, for risk evaluation of offshore structures, for determining roughness characteristics to derive wind and water drag coefficients for dynamics modelling, for sound scattering, and for the confinement of under-ice oil spills. Existing relations are based on numerical modelling assuming estimates of snow depth, snow density, and ice density or are based on field observations confined to specific areas and short time periods. MOSAiC provided the first year-long, high-resolution dataset of sea-ice draft derived from a multibeam echosounder. In combination with co-located freeboard estimates from airborne mapping of the surface, we construct the 3D sea-ice topography to study the evolution of sea-ice geometry both at the surface and underside. We can obtain direct and high precision relations between draft and freeboard on an almost weekly basis for an ice floe continuously drifting from the North Pole to Fram Strait during winter, spring, and summer. A precise evaluation of total ice thickness, ice density, freeboard, draft and their respective relations on small scales is crucial information to future satellite remote sensing ice thickness retrievals, a key asset of climate monitoring in the Arctic

    Spectral Light Transmittance of Arctic Sea Ice

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    Light transmittance through Arctic sea ice has an important impact on both the ocean heat content and the ice associated ecosystem. Thus, it is crucial to investigate the optical properties of sea ice to assess the role of the surface energy budget and its change due to climate change. Measurements of spectral transmittance can be used to investigate the influence of surface and ice properties regulating radiative transfer, especially on a larger horizontal scale. Here, we concentrate on categorizing snow and sea ice based on spectral transmittance data. Transmitted radiance and irradiance are measured at the underside of sea ice using a remotely operated vehicle (ROV). The scientific payload also includes CTD, fluorometer, pH-, nitrate-, oxygen-, attenuation sensor, upward-looking single-beam sonar, and periodically a surface and under ice trawl for assessing the spatio-temporal variability of sea ice algae. Thus, data for all disciplines in sea ice research can be recorded. The main benefits using the ROV compared to point measurements are the larger spatial coverage in comparably short times and the undisturbed sampling even under very thin sea ice, with parameters all collected during the same time. Snow depth is derived from a combination of terrestrial laser scanner data and manual measurements, while ice draft is measured using the single-beam sonar. Here, we present first data from the Last Ice campaign off Alert in May 2018. This region is dominated by sea ice with a larger thickness due to dynamic thickening. We investigated different ice regimes, such as First Year Ice with a continuous thickness of about 1.5 m and structured Multi Year Ice with thicknesses up to 6 m over the duration of four weeks to study the differences between various ice types

    Biogeochemical and ecological variability during the late summer–early autumn transition at an ice‐floe drift station in the Central Arctic Ocean

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    As the annual expanse of Arctic summer ice‐cover steadily decreases, concomitant biogeochemical and ecological changes in this region are likely to occur. Because the Central Arctic Ocean is often nutrient and light limited, it is essential to understand how environmental changes will affect productivity, phytoplankton species composition, and ensuing changes in biogeochemistry in the region. During the transition from late summer to early autumn, water column sampling of various biogeochemical parameters was conducted along an ice‐floe drift station near the North Pole. Our results show that as the upper water column stratification weakened during the late summer–early autumn transition, nutrient concentrations, particulate dimethylsulfoniopropionate (DMSPp) levels, photosynthetic efficiency, and biological productivity, as estimated by ΔO2/Ar ratios, all decreased. Chemotaxonomic (CHEMTAX) analysis of phytoplankton pigments revealed a taxonomically diverse picoautotrophic community, with chlorophyll (Chl) c3‐containing flagellates and the prasinophyte, Pyramimonas spp., as the most abundant groups, comprising ~ 30% and 20% of the total Chl a (TChl a) biomass, respectively. In contrast to previous studies, the picoprasinophyte, Micromonas spp., represented only 5% to 10% of the TChl a biomass. Of the nine taxonomic groups identified, DMSPp was most closely associated with Pyramimonas spp., a Chl b‐containing species not usually considered a high DMSP producer. As the extent and duration of open, ice‐free waters in the Central Arctic Ocean progressively increases, we suggest that enhanced light transmission could potentially expand the ecological niche of Pyramimonas spp. in the region

    Interdisciplinary observations of the under-ice environment using a remotely operated vehicle

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    Improving our understanding of the climate and ecosystem of the sea-ice covered Arctic Ocean was a key objective during MOSAiC. We aimed for a better understanding of the linkages of physical and biological processes at the interface between sea ice and ocean. To enhance the quantification of these linkages, year-round observations of physical, biological, and chemical parameters are needed. We operated a remotely operated vehicle (ROV) equipped with an interdisciplinary sensor platform to simultaneously measure these parameters underneath the drifting sea ice. These observations were made synchronous in time and place enabling a description of their spatial and temporal variability. Overall, we completed more than 80 surveys covering all seasons and various sea ice and surface conditions. We focused on optical parameters, sea-ice bottom topography, and upper ocean physical and biological oceanography. In addition, visual documentation of the under-ice environment was performed, nets for zooplankton were towed, and the ROV was used for instrument deployment and maintenance. Here, we present all ROV sensor data, allowing for a comprehensive picture of the under-ice environment. We are inviting discussions on further collaboration in data analyses and usage, in particular co-location and merging with other datasets from MOSAiC and other (also future) projects
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