ABSTRAKPemeriksaaan detak jantung dan suhu tubuh dapat sangat membantu tenaga kesehatan untuk mendiagnosis kondisi kesehatan pasien. Untuk memudahkan tenaga kesehatan, maka dirancang alat pemantau detak jantung portabel dengan sistem IoT. Desain portabel ditujukan agar alat ini mudah dibawa, dan mudah digunakan oleh pasien yang sedang rawat jalan, sedangkan fungsi IoT, tenaga kesehatan dapat memantau kondisi pasien dari jarak jauh dan secara kontinyu. Detak jantung dideteksi menggunakan sensor ECG AD8232, dan suhu tubuh dideteksi menggunakan sensor DS18B20 terkoneksi ke mikrokontroler. Pengujian menunjukkan sensor ECG AD8232 dan sensor suhu DS18B20 sensor sangat layak digunakan. Sistem IoT yang dibangun dapat membantu tenaga kesehatan dan pasien untuk mendapatkan penanganan segera jika terjadi keaadan abnormal.Kata Kunci: pemantau detak jantung, pemantau suhu tubuh, sistem IoT kesehatan
In the era of the Industrial Revolution 4.0. this is where technology and technology have been very advanced demanding competent human resources who have high morale and discipline in carrying out their roles and functions for both the individual and the objectives of the organization. In the role and contribution of STTAL in the Industrial Revolution 4.0, the current conditions, where the quality of human resources both students, lecturers, and Antap STTAL are considered unable to answer the challenges in the cyber field so that strategic decision-making and steps are needed to be able to accompany the development of science and technology while carrying out missions STTAL is to hold a higher education program to produce human resources with Indonesian character and personality, quality and relevant science and technology based, with defense needs in the military, maritime and maritime fields. With SWOT analysis, a matrix will be obtained which shows the strengths and weaknesses as well as opportunities and threats which will later be used as a reference to make the right and appropriate strategies. Keywords: SWOT Analysis, STTAL HR Quality, Industrial Revolution 4.0
This paper presents the development of vision-based robotic arm manipulator control by applying Proportional Derivative-Pseudoinverse Jacobian (PD-PIJ) kinematics and Denavit Hartenberg forward kinematics. The task of sorting objects based on color is carried out to observe error propagation in the implementation of manipulator on real system. The objects image captured by the digital camera were processed based on HSV-color model and the centroid coordinate of each object detected were calculated. These coordinates are end effector position target to pick each object and were placed to the right position based on its color. Based on the end effector position target, PD-PIJ inverse kinematics method was used to determine the right angle of each joint of manipulator links. The angles found by PD-PIJ is the input of DH forward kinematics. The process was repeated until the square end effector reached the target. The experiment of model and implementation to actual manipulator were analyzed using Probability Density Function (PDF) and Weibull Probability Distribution. The result shows that the manipulator navigation system had a good performance. The real implementation of color sorting task on manipulator shows the probability of success rate cm is 94.46% for euclidian distance error less than 1.2 cm.
Soil water availability to the plants is a very important physical property of soil that controls water and nutrient absorption by the plant. It is defined as the difference between the maximum amount of water the soil can hold and the minimum condition that the plant can no longer extract water from the soil. However, soil factors that control the plant available water content (PAWC) in the soil have not been fully understood. The present study aims to analyze the relations between particle-size distributions and organic carbon with the available water of the soil and to develop a model of predicting PAWC. Five soil profiles at different land units were described up to the depth of 100 cm. Ten undisturbed soil samples were taken using the stainless-made core sampler from 10 cm increments for the soil water holding capacity analysis. A similar number of disturbed samples were also provided from the same depths for soil texture and organic carbon analysis. Results showed that the variance in PAWC could be explained by sand and clay fractions (R2>0.35) but not by silt and organic carbon contents. Therefore, we were able to develop a model for the prediction of available water content in the soil from the sand and clay parameters. The model will help decision-makers be able to propose conservation and management strategies for PAWC in agricultural practices as well as for the soil moisture retention at civil works.
ABSTRAKPenelitian ini melakukan perancangan aplikasi pengenalan gangguan ginjal dini melalui citra digital iris mata menggunakan metode convolutional neural network (CNN) dengan antarmuka Raspberry Pi 3 model B+. Hasil akurasi terbaik yang diperoleh dengan memvariasikan banyak epoch, nilai learning rate, ukuran kernel, komposisi database, dan fungsi pooling layer adalah 94% pada saat epoch 12, 92% pada nilai 0,0001, 95% pada ukuran 3x3, 95% pada komposisi 100 train dan 50 validation, 90% menggunakan fungsi max pooling. Kata kunci: gangguan ginjal, iridology, convolutional neural network, raspberry pi.
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