Jurnal Online Informatika
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FoFA: Diet Information for Children with Autism with Semantic Technology in Android Based Application
Get PDFThe number of people with autism in Indonesia increases by 0.15% or 6,900 children per year. One of the actions that can be done to overcome developmental disorders of children with autism is to do Feingold and Failsafe Diet, Specific Carbohydrate Diet (SCD diet), and Casein-Free Gluten Free diet (CFGF diet) on foodstuffs given to children with autism. There is a need for socialization and presentation of information regarding the regulation of food items given to children with autism. Currently, there is no presentation of information in the form of mobile-based applications as a forum for parents to exchange information, especially those that utilize semantic technology. By utilizing semantic technology, the Food For Autism (FoFA) application was created to share knowledge for users related to food and beverage diet menus for children with autism. The test results show that the application of FoFA can apply semantic technology related to diet and food diets for children with autism
Website Based Greenhouse Microclimate Control Automation System Design
Get PDFMicroclimate control is very important for plants cultivation in a greenhouse, two of microclimate variables are temperature and humidity, this variable can be controlled using several methods, one option is to use the misting cooling system, but this process is still done manually. This study aims to create a greenhouse microclimate control system that can be automatically displayed and controlled via a website. This research uses engineering design methods. The results show that the system can automatically turn on the misting cooling system when temperatures are above 30 ℃ and RH below 80%. Greenhouse microclimate data can be displayed and controlled via a website. The UV index greatly influences the performance of the misting cooling system on temperature and RH conditions in the greenhouse, while the UV index rises to 12 the temperature cannot be lowered and RH cannot be increased, but when the UV index falls from 12 the temperature can be reduced by ± 3 ℃ and RH can be increased by ± 12%
Prototype Program Hand Gesture Recognize Using the Convex Hull Method and Convexity Defect on Android
Get PDFOne of the research topics of Human-Computer Interaction is the development of input devices and how users interact with computers. So far, the application of hand gestures is more often applied to desktop computers. Meanwhile, current technological developments have given rise to various forms of computers, one of which is a computer in the form of a smartphone whose users are increasing every year. Therefore, hand gestures need to be applied to smartphones to facilitate interaction between the user and the device. This study implements hand gestures on smartphones using the Android operating system. The algorithm used is convex hull and convexity defect for recognition of the network on the hand which is used as system input. Meanwhile, to ensure this technology runs well, testing was carried out with 3 scenarios involving variable lighting, background color, and indoor or outdoor conditions. The results of this study indicate that Hand gesture recognition using convex hull and convexity defect algorithms has been successfully implemented on smartphones with the Android operating system. Indoor or outdoor testing environment greatly affects the accuracy of hand gesture recognition. For outdoor use, a green background color with a light intensity of 1725 lux produces 76.7% accuracy, while for indoors, a red background color with a light intensity of 300 lux provides the greatest accuracy of 83.3%
Rupiah Exchange Prediction of US Dollar Using Linear, Polynomial, and Radial Basis Function Kernel in Support Vector Regression
Get PDFAs a developing country, Indonesia is affected by fluctuations in foreign exchange rates, especially the US Dollar. Determination of foreign exchange rates must be profitable so a country can run its economy well. The prediction of the exchange rate is done to find out the large exchange rates that occur in the future and the government can take the right policy. Prediction is done by one of the Machine Learning methods, namely the Support Vector Regression (SVR) algorithm. The prediction model is made using three kernels in SVR. Each kernel has the best model and, the accuracy and error values are compared. The Linear Kernel has C = 7, max_iter = 100. The Polynomial Kernel has gamma = 1, degree = 1, max_iter = 4000 and C = 700. The RBF kernel has gamma = 0.03, epsilon = 0.007, max_iter = 2000 and C = 100. Linear kernels have advantages in terms of processing time compared to Polynomial and Radial Basis Function (RBF) kernels with an average processing time of 0.18 seconds. Besides that, in terms of accuracy and error, the RBF kernel has advantages over the Linear and Polynomial kernels with the value R2 = 95.94% and RMSE = 1.25%
Optimization of Sentiment Analysis for Indonesian Presidential Election using Naïve Bayes and Particle Swarm Optimization
Get PDFTwitter can be used to analyze sentiment to get public opinion about public figures to find a trend in positive or negative responses, especially to analyze sentiments related to presidential candidates in the 2019 election in Indonesia. Naïve Bayes (NB) can be used to classify tweet feed into polarity class negative or positive, but it still has low accuracy. Therefore, this study optimizes the Naïve Bayes algorithm with Particle Swarm Optimization (NB-PSO) to classify opinions from twitter feeds to get a good accuracy of public figures sentiment analysis. PSO used to select features to find optimization values to improve the accuracy of Naïve Bayes. There are four steps to optimize NB using PSO, i.e., initializing the population (swarm), calculate the accuracy value that matched with selected features, selected the best accuracy of classification, and updating position and velocity. From this study, the group of tweets was obtained based on the positive and negative sentiments from the community towards two Indonesia presidential candidates in 2019. The NB-PSO test shows the accuracy result of 90.74%. The result of accuracy increases by 4.12% of the NB algorithm. In conclusion, the inclusion of the Particle Swarm Optimization algorithm for Naïve Bayes classification algorithm gives a significant accuracy, especially for sentiment analysis cases
Modelling the Measurement of Engagement Index of the Regional Governments\u27 Social Media in Indonesia
Get PDFSeveral types of engagement index and its variables can predict the engagement index of social media. However, no research has yet to use Structural Equation Modelling to model the engagement index of the variables from the prior researchers. This study was conducted to test the metrics of social media including like, comment, share and reply towards the online engagement variables that are measured by its affective engagement, cognitive engagement and behavioural engagement. The results indicate that the reply from the admin variable is the most significant factor in creating engagement on the social media of the Local Governments in Indonesia. This will then be used to increase the engagement index of the local governments in Indonesia
Feasibility Testing of a Household Industry Food Production Certificate Using an Expert System with Forward Chaining Method
Get PDFQuality and safe food products are the basic right of every consumer, including food products produced by small and medium industries. Good food production is an important factor in meeting quality standards or food safety licensing requirements. In setting standards, the government also plays an important role in providing direction and assistance to small and medium industries on achieving the specified quality standards. During this time the process is still carried out in a conventional manner directly to the industry. This conventional process is still considered ineffective by seeing the low level of business actors’ knowledge of the standards for Good Food Production Practice (GFPP). So, with this lack of knowledge, business actors’ interest in making food licensing is low. This study designed the application of an expert system that stimulates and provides an illustration for a standards assessment of Good Food Production methods. This research was conducted using Object Oriented Programming (OOP) engineering method for program development and using forward chaining for reasoning methods. This research proved that the application of an expert system for licensing due diligence can function in accordance with standards set by the government
Implementation of the Simple Multi Attribute Rating Technique Method (SMART) in Determining Toddler Growth
Get PDFToddler nutritional status is an important factor in efforts to reduce child mortality. The development of community nutrition can be monitored through the results of recording and reporting of community nutrition improvement programs reflected in the results of weighing infants and toddlers every month at the Pos Pelayanan Terpadu (Posyandu/ Integrated Service Post) , where these efforts aim to maintain and improve health and prevent and cope with the emergence of public health problems, especially aimed at toddlers. However, in carrying out the health service activities of Medical Officers, faced with an important problem that is still difficult in providing information related to the results of monitoring the growth and development of infants, because information on growth and development of infants owned is obtained from the data collection done manually such as; make records and calculations to find out the condition of a toddler declared good, less, or bad. Implementation of the SMART method in Toddler\u27s growth and development, this method can be used based on the weights and criteria that have been determined. The criteria used are based on the Anthropometric index assessment criteria. The results of the analysis are the results of ranking the greatest value to be used as the material in the decision-making process
Long Short-Term Memory Approach for Predicting Air Temperature In Indonesia
Get PDFAir temperature is one of the main factors for describing the weather behaviour in the earth. Since Indonesia is located on and near equator, then monitoring the air temperature is needed to determine either global climate change occurs or not. Climate change can have an impact on biological growth in various fields. For instance, climate change can affect the quality of production and growth of animal and plants. Therefore, air temperature prediction is important to meteorologists and Indonesian government to provide information in many sectors. Various prediction algorithms have been used to predict temperature and produce different accuracy. In this study, the deep learning method with Long Short-Term Memory (LSTM) model is used to predict air temperature. Here, the results show that LSTM model with one layer and Adaptive Moment Estimation (ADAM) optimizer produce accuracy which is 32% of , 0.068 of MAE and 0.99 of RMSE. Moreover, here, ADAM optimizer is found better than Stochastic Gradient Descent (SGD) optimizer
Possible System Architecture for Travel Recommender
Get PDFTravel recommender systems have been developed to meet the needs of users in the field of tourism. This system has several versions depending on the characteristics of the country, users and filtering techniques used. The development of recommendation filtering system techniques is very rapid so that the recommendation system has high enough complexity, but it also must have high usability. This paper discusses how the travel recommender system architecture is built by examining data structures, processing procedures and interaction design. The goal is to obtain the best usability in implementing a travel recommendation system. The system is built using the example case of finding the right tourist spot in Yogyakarta, Indonesia. This system applies several filtering techniques such as knowledge-based filtering, content-based filtering, and collaborative filtering. The evaluation results show that the system architecture optimized gets a usability level acceptable