Sociolla merupakan e-commerce terlengkap dan terpercaya di Indonesia yang menjual produk kecantikan dan perawatan kulit dan tubuh. Demi mempermudah akses untuk mendapatkan kosmetik yang diinginkan, website Sociolla dibuat pada tahun 2015. Website sociolla bertujuan memudahkan konsumen untuk mendapatkan informasi mengenai kandungan dan harga kosmetik. Permasalahan yang terjadi pada website Sociolla adalah setiap pengguna yang melakukan interaksi pada website merasa bahwa website Sociolla memerlukan waktu yang cukup lama untuk setiap tugas. Dampak dari kesalahan sistem yang berulang tersebut, membuat banyaknya pengguna enggan melakukan aktivitas pada website. Dari permasalahan tersebut, maka dilakukanlah evaluasi usablity untuk mengetahui pengalaman pengguna menggunakan pengujian skenario Usability Testing, kuesioner SUS dan metode UEQ. Hasil pengujian skenario parameter Task Completed memiliki nilai keberhasilan sebesar 0.91, parameter Error Rate memiliki rata-rata jumlah kesalahan sebesar 0.05467, parameter Time per Completed Task memiliki rata-rata waktu sebesar 45.313 detik dan parameter Number of Clicks memiliki rata-rata sebesar 5 klik. Hasil kuesioner SUS mendapatkan skor 75.75 yang termasuk dalam kategori Acceptable. Hasil pengalaman pengguna menunjukkan yaitu pada metode UEQ, aspek pragmatic quality dengan nilai sebesar 3.05, dan aspek hedonic quality dengan nilai sebesar 2.23. Dalam penelitian ini dapat disimpulkan bahwa website Sociolla dapat diterima dengan baik oleh pengguna.
The Brantas Watershed located in East Java has the vulnerability of drought as one of hydrometeorological disasters. The Vegetation Health Index (VHI) as one of remote sensing index was used to analyse drought. VHI can be derived based on both the Land Temperature Surface (LST) and Normalized Differenced Vegetation Index (NDVI). This research aimed to determine the influence of LST and NDVI, respectively, to VHI, especially in dry season of 2008 - 2017. The data used were MODIS Vegetation Indices (MOD13A1) and MODIS Land Surface Temperature (MOD11B1). The influence of LST and NDVI to VHI in the Brantas Watershed was analysed using correlation and regression testing. The LST - NDVI correlation of Brantas Watershed was negative (-0.73). The high temperature distribution was dominantly located in the low-density vegetation areas. The LST - VHI correlation was 0.35, and NDVI - VHI correlation was 0.63. This illustrated that the influence of land surface temperature to the vegetation drought was weak. Drought indicated by VHI was more likely to be influenced by internal conditions of vegetation and other environmental elements.
Great Malang region is developing rapidly with the population increase and inhabitant`s activity, like migration and urbanization. Other activities like agricultural expansion as well as an uncontrolled residential development need to be monitored to avoid any negative impact in the future. The availability of free and open-source software, spatial high-resolution satellite imagery datasets, and powerful algorithms open the possibilities to map, monitor, and predict the future trend of land use land cover (LULC) changes. However, the accuracy and precision of this model is still in doubt, especially in the Great Malang region. Research is needed to provide a foundational basis and documentation on how the changes occur, where did the changes occur, and the accuracy of the predicted model. This study tries to answer those questions using the high spatial resolution of Sentinel-2 imageries. Combination of the fuzzy algorithm, artificial neural network, and cellular automata was utilized to process the datasets. We analysed four different scenarios of simulation and the result then compared. The different number of hidden layers and iteration was used and evaluated to understand the effect of different parameters in the prediction result. The best scenario was then used to predict future land use changes. This study has successfully produced the future LULC model of Great Malang region with high accuracy level (87%). The study also found that the land use transformation from agriculture to urban built-up area is relatively low, where changes of the built-up area over three periods of analysis are below than 5%. This is due to the physical condition of Great Malang region where mountainous areas are dominated.
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