Estimasi Tingkat Bahaya Erosi dengan Menggunakan Metode USLE Pada Daerah Aliran Sungai (DAS) Amandit

Abstrak: Erosi tanah menjadi semakin meningkat setiap tahun yang disebabkan oleh terjadinya peningkatan kerusakan lahan. Daerah Aliran Sungai (DAS) Amandit mengalami kerusakan lahan yang ditandai dengan luasnya lahan kritis pada DAS tersebut yang akan berpengaruh pada tingginya tingkat bahaya erosi pada DAS tersebut. Penelitian ini bertujuan untuk menganalisis tingkat bahaya erosi yang terjadi pada Daerah Aliran Sungai (DAS) Amandit. Penelitian ini menggunakan peta bentuklahan sebagai dasar pengambilan sampel. Jumlah sampel dalam penelitian ini adalah 18 buah sampel. Analisa data yang digunakan adalah berdasarkan Metode Universal Soil Loss Equation (USLE) yang digunakan untuk mengetahui tingkat bahaya erosi yang terjadi pada wilayah penelitian. Hasil penelitian menunjukkan tingkat bahaya erosi yang terjadi di Daerah Aliran Sungai (DAS) Amandit termasuk dalam klasifikasi berat-sangat berat. Tingkat bahaya erosi yang paling tinggi adalah 1276.535 ton/ha/tahun. Faktor yang dominan yang mengakibatkan tingkat bahaya erosi pada Daerah Aliran Sungai (DAS) Amandit termasuk dalam klasifikasi berat-sangat berat adalah kemiringan lereng, nilai erodibilitas yang tinggi, dan tutupan lahan. Kata Kunci: Tingkat Bahaya Erosi (TBE), Bentuklahan, USLE, DAS Amandit Abstract: Soil erosion is increasing every year due to increased land degradation. The Amandit Watershed has suffered damage which affects critical land in the watershed which will affect the level of erosion hazard in the watershed. This study aims to analyze the level of erosion that occurs in the Amandit Watershed. This study uses a landform map as a basis for sampling. The number of samples in this study were 18 samples. The data analysis used is based on the Universal Soil Loss Equation (USLE) method which is used to see the level of erosion hazard that occurs in the study area. The results showed that the level of erosion that occurred in the Amandit Watershed was classified as heavy-very heavy. The highest level of erosion was 1276.535 ton/ha/year. The dominant factors resulting in the level of erosion in the watershed (DAS) included in the weight-very weight classification are the slope of the slope, high erodibility values and land cover. Keywords: Erosion Hazard Level, Landform, USLE, Amandit Watershed

MOBILE-BASED ONLINE EXAM APPLICATIONS USING PROBLEM WEIGHT CLASSIFICATION TECHNIQUES, GROUPING AND RANDOMIZING

Education is an agenda for designing the country's development. Implementation in the field of education is a joint responsibility of both the government and the community, educational institutions are one that plays an important role in the ongoing learning process activities one of which is the examination activities. The test is an evaluation of the learning process to obtain learning outcomes as a form of achievement recognition or completion in an educational unit. The test is still cheating, it is triggered by the lack of confidence in working on the exam questions and the same type of exam questions will provide an opportunity to chat and work together. The author aims to provide a solution in the form of the application of online-based online test applications using question weight classification techniques, grouping and randomization. This mobile-based online exam application was developed using the waterfall model. The results obtained from research on this mobile-based exam application has features to prevent screen capture or screenshots, prevent video recording or video recorder and prevent switching applications that can run multiplatform on Android and iOS. This application has been through the process of testing the user and distributing questionnaires to determine the feasibility of using the weight classification technique with a percentage of 80% so it is suitable for use in examination activities.

Customized versus population birth weight charts for identification of newborns at risk of long-term adverse cardio-metabolic and respiratory outcomes: a population-based prospective cohort study

Background Customized birth weight charts take into account physiological maternal characteristics that are known to influence fetal growth to differentiate between physiological and pathological abnormal size at birth. It is unknown whether customized birth weight charts better identify newborns at risk of long-term adverse outcomes than population birth weight charts. We aimed to examine whether birth weight classification according to customized charts is superior to population charts at identification of newborns at risk of adverse cardio-metabolic and respiratory health outcomes. Methods In a population-based prospective cohort study among 6052 pregnant women and their children, we measured infant catch-up growth, overweight, high blood pressure, hyperlipidemia, liver steatosis, clustering of cardio-metabolic risk factors, and asthma at age 10. Small size and large size for gestational age at birth was defined as birth weight in the lowest or highest decile, respectively, of population or customized charts. Association with birth weight classification was assessed using logistic regression models. Results Of the total of 605 newborns classified as small size for gestational age by population charts, 150 (24.8%) were reclassified as appropriate size for gestational age by customized charts, whereas of the total of 605 newborns classified as large size for gestational age by population charts, 129 (21.3%) cases were reclassified as appropriate size for gestational age by customized charts. Compared to newborns born appropriate size for gestational age, newborns born small size for gestational age according to customized charts had increased risks of infant catch-up growth (odds ratio (OR) 5.15 (95% confidence interval (CI) 4.22 to 6.29)), high blood pressure (OR 2.05 (95% CI 1.55 to 2.72)), and clustering of cardio-metabolic risk factors at 10 years (OR 1.66 (95% CI 1.18 to 2.34)). No associations were observed for overweight, hyperlipidemia, liver steatosis, or asthma. Newborns born large-size for gestational age according to customized charts had higher risk of catch-down-growth only (OR 3.84 (95% CI 3.22 to 4.59)). The direction and strength of the observed associations were largely similar when we used classification according to population charts. Conclusions Small-size-for-gestational-age newborns seem to be at risk of long-term adverse cardio-metabolic health outcomes, irrespective of the use of customized or population birth weight charts.

Self-Reported vs. Measured Height, Weight, and BMI in Young Adults

Self-reported height and weight, if accurate, provide a simple and economical method to track changes in body weight over time. Literature suggests adults tend to under-report their own weight and that the gap between self-reported weight and actual weight increases with obesity. This study investigates the extent of discrepancy in self-reported height, weight, and subsequent Body Mass Index (BMI) versus actual measurements in young adults. Physically measured and self-reported height and weight were taken from 1562 students. Male students marginally overestimated height, while females were closer to target. Males, on average, closely self-reported weight. Self-reported anthropometrics remained statistically correlated to actual measures in both sexes. Categorical variables of calculated BMI from both self-reported and actual height and weight resulted in significant agreement for both sexes. Researcher measured BMI (via anthropometric height and weight) and sex were both found to have association with self-reported weight while only sex was related to height difference. Regression examining weight difference and BMI was significant, specifically with a negative slope indicating increased BMI led to increased underestimation of weight in both sexes. This study suggests self-reported anthropometric measurements in young adults can be used to calculate BMI for weight classification purposes. Further investigation is needed to better assess self-reported vs measured height and weight discrepancies across populations.