IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)
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Kelas Cendekia Versi Mobile yang Terintegrasi dengan Sistem Rekomendasi
Get PDFUrgency usefulness of online learning system based on social constructivism which is the mobile virtual classroom learning philosophy is of concern, because the system is built on the pattern of reciprocity between users in order to produce the most quality materials see the absence of a system that provides online learning for it. Content of lecture materials that have been divided into certain categories are processed into virtual versions and delivered lightly. The recommendation system is designed to respond users who have rated it by providing good quality course material. Software is created with Unity Engine and incorporated the recommended system protocol with data stored in a scholarly research database. The recommendation system implemented is the items based collaborative filtering with the specification of training data used are 401 rating data, 51 records and 17 users. With sparsity data training amounted to 53.74%, tested the prediction accuracy resulted RMSE 0.91523 and the accuracy of 81.69%. The mobile version of virtual class that has been planted with recommendation system is tried and tested on several brands of android smartphone. Results obtained on the questionnaire resulted in a rating of 4,762 on performance and 4,572 against the intellectual class software interface. Whereas the level of user enthusiasm for the virtual class reaches 4,0588 on a scale of 1 to 5
Low Cost Sensor Node Device for Monitoring Landslides
Get PDFLandslides are one of the natural disasters that often occur in Indonesia. Therefore, this disaster cannot be eliminated, but it can minimize the disadvantage caused by an early warning mechanism. Early warning systems rely on a sensor node used to read soil conditions with specific parameters. Those parameters that are read lead to the detection of mass movements. With the tightness of the monitoring process, of course, a reliable sensor node is needed. However, there are challenges in how to minimize losses that occur due to damage to sensor nodes when landslides occur. Sensor nodes are made using IMU sensors to monitor mass movements and its use two processors, namely microcontroller and mini SBC, which are inexpensive to manufacture and do not require large space in the installation
Segmentation of White Blood Cells and Lymphoblast Cells Using Moving K-Means
No full textOne of the diagnosis procedures for acute lymphoblastic leukemia is screening for blood cells by expert operator using microscope. This process is relatively long and will slow healing process of this disease which need fast treatment. Another way to screen this disease is by using digital image processing technique in microscopic image of blood smears to detect lymphoblast cells and types of white blood cells. One of essential step in digital image processing is segmentation because this process influences the subsequent process of detecting and classifying Acute Lymphoblastic Leukemia disease. This research performed segmentation of white blood cells using moving k-means algorithm. Some process are done to remove noise such as red blood cells and reduce detection errors such as white blood cells and/or lymphoblastic cell that’s appear overlap. Postprocessing are performed to improve segmentation quality and to separate connected white blood cell. The dataset in this study has been validated with expert clinical pathologists from Sardjito Regional General Hospital, Yogyakarta, Indonesia. This research produces systems performance with results in sensitivity of 85.6%, precision 82.3%, Fscore of 83,9% and accuracy of 72.3%. Based on the results of the testing process with a much larger number of datasets on the side of the variations level of cell segmentation difficulties both in terms of illumination and overlapping cell, the method proposed in this study was able to detect or segment overlapping white blood cells better
Sistem Klasifikasi Tingkat Keparahan Retinopati Diabetik Menggunakan Support Vector Machine
Get PDFDiabetic retinopathy is a vision disorder disease that can cause damage to the retina of the eye that will have a direct impact on the disruption of vision of the patient. The diabetic retinopathy phase is classified into four types (normal, mild NPDR, moderate NPDR (Non-Proliferative Diabetic Retinopathy), and severe NPDR). Retinal of eye data of diabetic retinopathy patients treated from the MESSIDOR database. By applying image processing, the retinal image of the eye in extraction using the area features extraction from the detection of exudate, blood vessels, microaneurysms, and texture feature extraction Gray Level Co-occurrence Matrix. The extracted results classified using the Support Vector Machine method with the Radial Basis Function (RBF) kernel. Classification evaluated with these parameters: Accuracy, specificity, and sensitivity.The results of classification show the best value using 6 statistical features ie, contrast, homogeneity, correlation, energy, entropy and inverse difference moment in the direction of 45 degrees with the RBF kernel. The result of classification research system on 240 data training and 60 data testing yields an average accuracy is 95.93%, the value of specificity is 97.29%, and a sensitivity rating is 91.07%. From the research result, using RBF kernel get the best accuracy result than using kernel polynomial or kernel linear
Brain Tumor Classification Using Gray Level Co-occurrence Matrix and Convolutional Neural Network
Get PDFImage are objects that have many information. Gray Level Co-occurrence Matrix is one of many ways to extract information from image objects. Wherein, the extracted informations can be processed again using different methods, Gray Level Co-occurrence Matrix is use for clarifying brain tumor using Convolutional Neural Network. The scope in this research is to process the extracted information from Gray Level Co-occurrence Matrix to Convolutional Neural Network where it will processed as Deep Learning to measure the accuracy using four data combination from TI1, in the form of brain tumor data Meningioma, Glioma and Pituitary Tumor. Based on the implementation of this research, the classification result of Convolutional Neural Network shows that the contrast feature from Gray Level Co-occurrence Matrix can increase the accuracy level up to twenty percent than the other features. This extraction feature is also accelerate the classification process using Convolutional Neural Network
Hybrid Support Vector Machine to Preterm Birth Prediction
Get PDFPreterm birth is one of the major contributors to perinatal and neonatal mortality. This issue became important in health research area especially human reproduction both in developed and developing country. In 2015 Indonesia rank fifth as the country with the highest number of premature babies in the world. The ability to reduce the number of preterm birth is to reduce risk factors associated with it. This research will be made the prediction model of preterm birth using hybrid multivariate adaptive regression splines (MARS) and Support Vector Machine (SVM). MARS used to select the attributes which suspected to affect premature babies. The result of this research is prediction model based on hybrid MARS-SVM obtains better performance than the other model
Perancangan Alat Ukur Massa Jenis Zat Cair Menggunakan Cepat Rambat Gelombang Ultrasonik
Get PDFDensity is a measure of the mass of volume unity. How to measure density in general by measuring the weight and dividing it by the volume of liquid, so in this way the measurement is not. Measurement of the density of the liquid based on the ultrasonic velocity becomes an alternative so that the measurement can be done directly, accurately, practically, and easily.Ultrasonic velocity becomes the variable to determine the density of the liquid. Time synchronization begins when the ultrasonic transmitter emits ultrasonic and is terminated when the receiver receives ultrasonic. The discrete ultrasonic wave transmission method is performed when the ultrasonic receiver receives transmittance from the ultrasonic transmitter then the 40KHz signal pulse is stopped and ultrasonic transmission is repeated up to 10 times the measurement data.From this study obtained some conclusions. Ultrasonic velocity is influenced by the viscosity of the liquid, ultrasonic velocity through 1394m / s aquades, ultrasonic velocity through cooking oil 1387m / s, ultrasonic velocity through liquid soap 1175m / s, ultrasonic velocity through liquid soap solution 40% 1317m / s , Ultrasonic velocity through liquid soap solution 70% 1257m / s, velocity measurement deviation of 0.43% and 0.01% density calculation type
Collaborative Filtering Recommender System pada Virtual 3D Kelas Cendekia
Get PDF Intelligent Clasrooms is a concept of modern learning process where users can perform collaborative learning wherever and whenever. With learning in Intelligent Classroom, users can get different learning experience where learning process is expected to run more effectively and efficiently. One application of the Intelligent Classrooms concept is learning by utilizing the virtual world. The information collected in the Intelligent Classroom will increase so that a system is needed. The recommendation system of collaborative filtering is the most appropriate system with the intellectual class. With the sparsity of training rate of 80%, it is implemented a collaborative filtering recommendation system with error rate which if calculated with RMSE is 1.060709 or it can be said that the accuracy level is 78.79%
Perancangan Flowmeter Ultrasonik untuk Mengukur Debit Air Pada Pipa
Get PDF Measurement of water discharge using ultrasonic wave properties ensures the stability of measured water profile because of its non-intrusive nature. In this study, a water discharge measuring device has been developed by utilizing ultrasonic wave properties to determine its speed. The device is designed using two pairs of ultrasonic transmitters and receivers at upstream and downstream positions toward the direction of the water flow. 40 kHz ultrasonic waves are generated with AD9850 DDS sinusoidal pulse generating module. The sensor data processor uses an Arduino Due microcontroller module by calculating the measured ultrasonic wave travel time difference. Measurements were made on a 57 mm diameter pipe with flow rates varied using 25%, 50%, 75%, and 100% tap openings. The measurement resulte shows the lowest water debit calculation value of 4.42×10-4 m3/s at 25% faucet opening and highest discharge of 2.15×10-3 m3/s at 100% faucet opening with the values of coefficient of correlation and coefficient of determination on 25%, 50%, 75% and 100% faucet openings respectively 0.9715, 0.9669, 0.9604 and 0.9647 and 94.37%, 93.49%, 92 , 24%, and 93.07%
Analisis Perbedaan Pola Sinyal EEG Berdasarkan Jenis Kelamin Yang Berbeda Saat Numerical Stroop Task
Get PDFCognitive process show how brain work from stimulus reception until stimuls reaction. With electroencephalogram (EEG) device, cognate process can be observerd in brain signal or EEG signal form. In cognitive process different kind of stimulus could affect generated brain signal. Also, given interference in cognitive prcess could affect brain signal. In this research, conducted observation whether gender difference has effect in cognitive process. Numerical stroop task with three kinds of conditions (congruence, incongruence, and neutral) are used as reference in signal observation process which is generated when the cognitive process in difference genders are done. The resulting EEG signal then conducted three kinds of analysis that is ERP analysis, reaction time, and energy analysis. The result of ERP analysis show both subject class have difference in response time that indicated with P3 peak time. On average, respons time in female (kongruent = 623,34 ms; inkongruent = 645,18 ms ; neutral = 614,91 ms)subject class is faster than male (kongruent = 709,67 ms; inkongruent = 745,00 ms; neutral =715,37 ms) subject class. Energy analysis show when numerical stroop task takes place, left side of the brain (51,36%) and cetral side of the brain (50,65%) more dominant than others parts of the brain