International Journal of artificial intelligence research (IJAIR)
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Dependable flow modeling in upper basin Citarum using multilayer perceptron backpropagation
Get PDFTo determine the amount of dependable flow, a hydrological approach is needed where changes in rainfall become runoff. This diversification is a very complex hydrological phenomenon. Where this is a nonlinear process, with time changing and distributed separately. To approach this phenomenon, an analysis of the hydrological system has been developed using a model which is a simplification of the actual natural variables. The model is formed by a set of mathematical equations that reflect the behavior of parameters in hydrology. Modeling in this case uses artificial neural networks, multilayer perceptron combined with the backpropagation method is used to study the rainfall-runoff relationship and verify the model statistically based on the mean square error (MSE), Nash-Sutcliffe Efficiency (NSE) and correlation coefficient value (R2). Of the three models formed, model 3 provides optimum results with correlation levels using NSE per month as follows, in Cikapundung Sub-Basin NSE = 0,990703, R2 = 0,995008, and MSE = 0,00014443, while in Citarik Sub-Basin NSE = 0.9500, R2 = 0.97592, and MSE = 0.0010804 . From these results it can be seen that ANN has a fairly good ability to replicate random discharge fluctuations in the form of artificial models that have almost the same fluctuations and can also be applied in rainfall runoff modelization even though the results of the test results are not very accurate because there are still irregularitie
Artificial Intelligence Influence In Education 4.0 To Architecture Cloud Based E-Learning System
Get PDFBusiness Application Layer in the Architecture of E-learning cloud is an important part, because it is the part that differentiates it from the application of cloud in other fields. The development of education today recognizes the term Education 4.0 which is an adaptation of the Industrial era 4.0 where in this era the role of Artificial Intelligent is important. In this paper the author will review a part of the cloud-based architecture of E-Learning which will correspond with Education 4.0. The aim will be to produce a Cloud-Based E-learning system Architecture design that can be used as a guideline in the direction of Education 4.0
A Novel Method for L Band SAR Image Segmentation Based on Pulse Coupled Neural Network
Get PDFPulse Coupled Neural Network (PCNN) is claimed as a third generation neural network. PCNN has wide purpose in image processing such as segmentation, feature extraction, sharpening etc.  Not like another neural network architecture, PCNN do not need training. The only weaknes point of PCNN is parameter tune due to seven parameters in its five equations. In this research we proposed a novel method for segmentation based on modified PCNN.  In order to evaluate the proposed method, we processed L Band Multipolarisation Synthetic Apperture Radar Image. The Results showed all area extracted both by using PCNN and ICM-PCNN from the SAR image are match to the groundtruth. There fore the proposed method is work properly.Copyright © 2017  International Journal of  Artificial Intelegence Research.All rights reserved
Random and Synthetic Over-Sampling Approach to Resolve Data Imbalance in Classification
Get PDFHigh accuracy value is one of the parameters of the success of classification in predicting classes. The higher the value, the more correct the class prediction. One way to improve accuracy is dataset has a balanced class composition. It is complicated to ensure the dataset has a stable class, especially in rare cases. This study used a blood donor dataset; the classification process predicts donors are feasible and not feasible; in this case, the reward ratio is quite high. This work aims to increase the number of minority class data randomly and synthetically so that the amount of data in both classes is balanced. The application of SOS and ROS succeeded in increasing the accuracy of inappropriate class recognition from 12% to 100% in the KNN algorithm. In contrast, the naïve Bayes algorithm did not experience an increase before and after the balancing process, which was 89%.Â
An Implementation of Fuzzy PD Control Design for Five Flip Folders Folding Machine Using Arduino Mega2560
Get PDFThe arm manipulator application that has 1 degree of freedom (DOF) can be used to flip folders in folding machines. The used actuator in folding machine is a Brushed DC motor. The Fuzzy-PD control system in this application is using Arduino Mega2560 microcontroller. Application of Fuzzy-PD control system on folding machine is able to move 5 flip folders. This Fuzzy-PD control system is able to improve the system response when there is a load, where the difference is only 7.73% from the no load condition. In addition, to implement this flip folder, a stochastic based method (ARX) is also applied on this system so it can be simulated directly. The simulation results from this folding machine model have a time constant of 0.510s, rise time of 1.501s, settling time of 1.5320s and delay time of 0.353s
Counting the Number of Active Spermatozoa Movements Using Improvement Adaptive Background Learning Algorithm
Get PDFThe most important early stage in sperm infertility research is the detection of sperm objects. The success rate in separating sperm objects from semen fluid has an important role for further analysis. This research performed the detection and calculation of human spermatozoa. The detected sperm was the moving sperm in the video data. An improvement of Adaptive Background Learning was applied to detect the moving sperm. The purpose of this method is to improve the performance of Adaptive Background Learning algorithm in background subtraction process to detect and calculate moving sperm on the microscopic video of sperm fluid. This paper also compared several other background subtraction algorithms to conclude the appropriate background subtraction algorithm for sperm detection and sperm counting. The process done in this research was preprocessing using the Gaussian filter. The next was background subtraction process, followed by morphology operation. To test or validate the detection results of any background subtraction algorithm used, the foreground mask results from the morphological operation were compared to the ground truth of moving sperm image. For visualization purposes, every BLOB area (white object in binary image) on the foreground were given a bounding box to the original frame and the number of BLOB objects present in the foreground mask were counted. This shows that the system had been able to detect and calculate moving sperm. Based on the test results, Adaptive Background Learning method had a value of F-measure of 0.9205 and succeeded in extracting sperm shape close to the original form compared to other methods
Texton Based Segmentation for Road Defect Detection from Aerial Imagery
Get PDFRoad defect such as potholes and road cracks, became a problem that arose every year in Indonesia. It could endanger drivers and damage the vehicles. It also obstructed the goods distribution via land transportation that had major impact to the economy. To handle this problem, the government released an online complaints system that utilized information system and GPS technology. To follow up the complaints especially road defect problem, a survey was conducted to assess the damage. Manual survey became less effective for large road area and might disturb the traffic. Therefore, we used road aerial imagery captured by Unmanned Aerial Vehicle (UAV). The proposed method used texton combined with K-Nearest Neighbor (K-NN) to segment the road area and Support Vector Machine (SVM) to detect the road defect. Morphological operation followed by blob analysis was performed to locate, measure, and determine the type of defect. The experiment showed that the proposed method able to segment the road area and detect road defect from aerial imagery with good Boundary F1 score
Covid-19: Digital Signature Impact on Higher Education Motivation Performance
Get PDFAt present, the process of validating documents for certain purposes cannot be done face-to-face because of the Covid-19 pandemic. Therefore, this research aims to maximize the existence of smart digital signature technology that guarantees its safety and validity without having to meet face to face. Encrypted digital signatures with RSA-SHA256 with cloud storage features that can share documents. The waterfall method for building systems, the collection of data generated for analysis by observation, and online questionnaires using Google Form. Based on the characteristics of the system, the satisfaction factor analysis of the system with the Slovin formula processed by the SUS score resulted in a score of 95 > 70. The final result of this study is that the digital signature system has a significant impact on increasing motivation to facilitate authorization and secure documents
Predicting the Spread of the Corona Virus (COVID-19) in Indonesia: Approach Visual Data Analysis and Prophet Forecasting
Get PDFThe development trend of the coronavirus pandemic (COVID-19) in various countries has become a global threat, including in Southeast Asia, such as Indonesia, the Philippines, Brunei, Malaysia, and Singapore. In this paper, we propose an Exploratory Data Analysis (EDA) model approach and a time series forecasting model using the Prophet method to predict the number of confirmed cases and cases of death in Indonesia in the next thirty days. We apply the EDA model to visualize and provide an understanding of this pandemic outbreak in various countries, especially in Indonesia. We present the trends in the spread of epidemics from the countries of China from which the virus originates, then mark the top ten countries and their development and also present the trends in Asian countries. We present an analytical framework comparing the predicted results with the actual data evaluated using the MAPE and MAE models, where the prophet algorithm produces good performance based on the evaluation results, the relative error rate of our estimate (MAPE) is around 6.52%, and the model average false 52.7% (MAE) for confirmed cases, while case mortality was 1.3% for the MAPE and MAE models around 236.6%. The results of the analysis can be used as a reference for the Indonesian government in making decisions to prevent its spread in order to avoid an increase in the number of death
Comparison Analysis of K-Nearest Neighbor and Naïve Bayes in Determining Talent of Adolescence
Get PDFAdolescence always searches for the identity to shape the personality character. This paper aims to use the artificial intelligent analysis to determine the talent of the adolescence. This study uses a sample of children aged 10-18 years with testing data consisting of 100 respondents. The algorithm used for analysis is the K-Nearest Neigbor and Naive Bayes algorithm. The analysis results are performance of accuracy results of both algorithms of classification. In knowing the accurate algorithm in determining children's interests and talents, it can be seen from the accuracy of the data with the confusion matrix using the RapidMiner software for training data, testing data, and combined training and testing data. This study concludes that the K-Nearest Neighbor algorithm is better than Naive Bayes in terms of classification accuracy