The Global Action Report on Preterm Birth (2012) The United Nations Agency says, 15 million babies are born prematurely every year worldwide. Among them, more than one million babies die from complications due to premature birth. In 2010, Indonesia ranked fifth in the world with the highest number of premature babies in the world. The high birth rate for premature babies and the limited ability of parents to access health facilities to care for premature babies. The baby incubator serves to maintain a stable internal temperature and humidity so that it can help babies born prematurely to survive. This study aims to design and implement portable baby incubator control using fuzzy logic which consists of two fuzzy modules: based on Temperature and humidity. This baby incubator control uses fuzzy logic designed so that the system can display information on the baby's incubator temperature and humidity conditions, the baby's weight and the baby's heart rate without opening the incubator. The temperature in the system to be designed ranges between 36 ℃ -37 ℃, and the humidity is between 40% RH-60% RH. This incubator has a measurement and regulation system using temperature and humidity, namely the DHT22 sensor, the AC Dimmer Module to control PWM (Pulse Width Modulation), the acuator in the form of AC 220V incandescent lamps with a power of 60W and Arduino uno as a controlling microcontroller and an artificial fuzzy logic system Sugeno control method with a setting point value of 37 ℃ to maintain the stability of the temperature in the incubator in accordance with what is needed by premature babies. With the setting point at 37 ℃ the temperature in the baby incubator will survive in the range 37 ℃ -38 ℃.
LPG is an alternative fuel that is used for daily needs, it is caused not only because of its cheap price but also its easy installation. However, the characteristic of LPG gas which is flammable and heavier than oxygen makes LPG gas leakage is hard to be detected. Based on that problem, a system that is able to detect gas leakage is needed and the system itself has to pass the sensitivity level test to be gas sensor. In this study there are 3 sensors; MQ-2, MQ-5 and MQ-6 gas sensors which are connected to the Arduino Uno microcontroller as it can be used as a feature to classify the condition of the gas by the implementation of the Fuzzy Mamdani method. The output of the system is displayed on an LCD, marked with a buzzer and a fan as gas decoder. The Arduino Uno that was programmed using fuzzy logic was used to control the level of leakage and to give a solution level through the rotation of fan and the buzzer sound. From the test results, the system could determine various conditions of gas leakage with 93% accuracy. From the results of its simulation and test, MQ-5 had higher sensitivity rather than MQ-2 which had the lowest sensitivity toward gas leakage. Keyword : Leakage, LPG Gas, Fuzzy Logic,
In the modern world, electrical energy is very important to support all activities in office buildings, educational facilities, industrial complexes and household activities. The problem that occurs in the use of electricity is the lack of understanding of energy conservation from the consumer side. This causes the waste of electrical energy. An alternative solution to this problem is an effort to make efficient use of electrical energy from the consumer side. By applying Demand Side Management (DSM) to the building, an efficient and rational use of electrical energy is obtained. To implement DSM it is necessary to conduct an energy audit of the building. By conducting an energy audit then Energy Use Intensity (EUI ) and the profile of electrical energy usage is obtained. After EUI and the energy use profile are known then energy policy recommendations are determined in the building. By using the Analytical Hierarchy Process (AHP) an alternative set of decisions is made that is right in reducing electricity consumption so that it reaches the desired efficiency point in accordance with building management policies The results of processing from AHP obtained an alternative set of electrical energy efficiency according to its weight is the regulation of the use of office facilities by 48.5%, maintenance of existing equipment by 31.1%, utilization of new energy-saving technologies by 20.4%. Keywords : Energy Audit, EUI , DSM, AHP.
Vital signs are signs that show important functions of the human body, from these signs can be known whether a person is relatively healthy, has a serious illness, or suffers from a life-threatening disorder. Vital signs are the value of physiological functions consisting of blood pressure, temperature, oxygen saturation, pulse and respiratory rate. Vital sign monitoring tools researchers used four parameters, namely blood preasure, heart rate, oxygen saturation, and body temperature. The tool uses the IoT (Internet of Things) system, where this tool uses sensors used, namely the DS18B20 temperature sensor, the Heart Rate sensor and the SPO2 MAX 30100 sensor, the OMRON HME-7130 sensor, the ESP 32 microcontroller as a data processor and Wi-Fi connection. The patient's vital condition data will be displayed on the android smartphone and on the mydevices.com WEB page. This tool is rule-based with a Modified Early Warning Score (MEWS) system to determine the status of patients and assist medical personnel in monitoring the vital parameters of patient signs in real time at each location and responding quickly and precisely so as to improve the quality of life of patients. Comparison using patient monitor tools, body temperature measurements produce the highest and lowest percentage of error that is 0.19% and 0.08% with an average temperature of 36.06oC and 35.96oC, then heart rate measurements obtained the highest and lowest percentage of errors of 0.08% and 0.3% with an average heart rate of 74 bpm and 87.3. Then the measurement of SpO2 obtained the highest and lowest percentage of error of 1% and 0% with an average SpO2 of 97% and 97.3%, then the NIBP measurement obtained the highest and lowest percentage of error systole / diastole of 7.4% / 7.2% with NIBP with an average systole / diastole of 109.6 / 64 mmHg and the lowest error percentage is 0.3% / 1.1% with an average NIBP of 125 / 62.3 mmHg. Data transmission to the internet using the cayene application on Android smartphones and WEB is greatly influenced by the quality of the connection from the internet network. Key words: Vital Signs, Modified Early Warning Score (MEWS), DS18B20, MAX 30100, ESP32 Microcontroller, IoT.
Hypertension or the abnormal increase of blood pressure is a chronic disease which can damage the other parts of the body such as the kidneys, heart, and vessels. The high cost of treating the injuries caused by hypertension is undeniable. Various techniques exist for measuring the blood pressure. In recent years, machine learning models became more popular due to being non-invasive and their continuous supervision, remote use, and low cost. Several analyses were performed by the audio signals of cardiac palpitations, electrocardiograms, on photo plethysmogramy on software and hardware platforms. Researchers used machine learning techniques to present the alternative methods for aggressive and costly methods. Among the presented methods, regression algorithms, support vector machine (SVM), and neural network (NN) are highly popular. This study presented a method for analyzing ECG and PPG signals for diagnosing hypertension. The proposed method can improve the classification accuracy regardless of the classification algorithm by providing the combined features. In the conducted evaluation, the neural network algorithm was proposed for the data with continuous label while the C4.5 tree was proposed for the data with discrete label. In addition, the proposed generalized method was provided by calculating the cosine distance and optimizing the genetic algorithm for low data and noise conditions.
Crops rice is a thing he could never expected for sure, but could have predicted data in of existing. The availability of data about the outcome of rice harvesting is very substantial for use as yardstick in estimate and predicts crops rice as a gesture to fix the next planting. Artificial neural network method backpropagation often used to settle trouble complex relating to identification, predictions, pattern recognition and so on. In this study, backpropagation processing the data affecting rice crops from 2014 until 2016 to predict crop Pengkok, Kedawung, Sragen the future. After through process of training and testing and experiment some pattern architecture network, in the network get architecture best in a prediction.
Abstract This research present about a steering control system on a vehicle whicgh is called Electrical Power Steering (EPS) that aims to observe and compare the position of EPS system with and without using PID controller. The EPS system has a state space order by 6x6 with one of the motor outputs to be controlled by a Proportional-Integral-Derivative (PID) controller and uses the MATLAB application as a simulation of the EPS system. The simulation is carried out in two stages, namely the simulation of an EPS system without controlling and simulating an EPS system using a PID controller. The results show , that the position controller on EPS with the PID control method reaches the desired position with the parameter value Kp = 500, Ki = 500 and Kd = 200 while the input step is 1. The system output response has an overshoot value close s to 0, a rise time of 0.005 seconds. More over, EPS system which unutilized controllers, the output responseis can not reached the reference value. Keywords—Electric Power Steering (EPS), Proportional-Integral-Derivatif (PID), Simulation.
Processes of image quality enhancement often leave deficiencies in the image result. These deficiencies in the form of loss of local contrast and loss of detail in some parts of the image. These deficiencies resulted in some important information on the image become unreadable. The deficiency that caused from processes of image enhancement can be minimized by taking information back from the original image. Taking this information can be done by combining the original image with the image of the improvements. Before the fusion of image, the means of average value and standard deviation value from the result on image should be improved first enhancement, so that fusion of image can be maximum. From the tested of 500 (five hundred) images that consist of image lacks brightness, image lacks contrast, and image lacks brightness and contrast, there were 74 (seventy four) image that can not be full repaired by using the proposed method. But for the image of the other experiments, the proposed method could improve image deficiencies. In this success level from method which is proposed reaches 85 %. Key Word : image improvement, mean increament, standard deviation increament.
We have developed a low-cost participatory monitoring system for wildfire in peatland, that enables air pollutan referential parameters measurements based on a multilayer distributed parameter model with a Wido IoT platform. This is an Internet of Things (IoT) application, of which a physical object is embedded with electronics, software, sensors and GSM connectivity to allow monitoring participatory system (CO, CO 2 , PM10) on real-time based on cloud systems In this paper proposes a low-cost, rapid-deployment and energy-autonomous solution based on Wido IoT to improve the assessment and the understanding of air quality in developing monitoring peatland areas, thus helping policy makers and scientists to better handle air pollution. The proposal incorporates the use of a website to display collected data and processed information to empower citizens with knowledge about the air they breathe.
Rice plant which is a source of food for the people , it need s enough temperature, air humidity and high water for maximum growth. The irrigation system is a major requirement in the field of agriculture, especially for rice plant . Some constraints in conventional irrigation , so they need irrigation system automatically. Some previous studies about automatic irrigation were only use d one or two parameters and only use d fuzzy or IoT. The method offered in this study uses fuzzy logic using 3 inputs and combines the monitoring system in real time based on IoT. The purpose of this study is to determine the effectiveness of fuzzy logic using three inputs to control the automatic irrigation system by real time monitoring using IoT. D ata obtained by test ing in themorning, afternoon, evening, night and using heat and rain treatment then compared using M atlab calculation. From the tool testing, the average precision of the tool comparison using the calculation is 77.13%.
Software testing is one of the crucial processes in software development life cycle which will influence the software quality. One of the strategies to help testing process is predicting the part or module of software which is prone to defect. Then, the testing process can be more focused to those parts. In this research a classifier model for predicting software defect was built. One of the most important problems in software defect prediction is imbalance data distribution between samples of positive class (prone to defect) and of negative class. Therefore, in this research SMOTE is implemented to handle imbalance data problem and extreme learning machine is implemented as a classification algorithm. As a comparison to SMOTE-ELM, a modification of ELM which directly copes with imbalance problem, weighted-ELM, is also observed. This research used NASA MDP dataset PC1, PC2, PC3 and PC4. The results of experiment using 10-fold cross validation show that directly classification using ELM obtain the worse result compared to SMOTE-ELM and weighted-ELM. When the value of imbalance ratio is not very small, the SMOTE-ELM is better than weighted-ELM. When the value of imbalance ratio is very small, the g-mean of weighted-ELM is higher than the g-mean of SMOTE-ELM, but the accuracy of weighted-ELM is lower than the accuracy of SMOTE-ELM. Therefore, in this software defect prediction case it can be concluded that SMOTE is effective to increase the generalization performance of classifier in minority class as long as the value of imbalance ratio is not very small.
The prediction of the acquisition of national exam scores for Junior High School (JHS) students is intended to know the results of the student’s national exam early when students take the national examination. Knowledge gained from the results of this prediction will be important information for the school to take appropriate steps so that the acquisition of student national exam scores can be improved even better . The acquisition of student national exam scores is low and there is no prediction model that is used to predict the achievement of student national exam scores is a problem that needs to be addressed . This paper propose a p redicting student’s national ex a m scores for four national exam subjects ( INDONESIA N, ENGLISH, MAT HEMATICS and SCIENCE ) using K-Nearest Neighbor (k-NN) as a prediction method and compare it with Decission Tree method . The results of the study showed that the prediction k-NN model had better performance than the prediction model of Decission Tree . Performance results obtained by evaluating using derivatives of the confussion matrix terminology to determine the value of accuracy, sensitivity (recall), and precission each subjects . To measure the performance of predictive methods used the value of accuracy in each method and each subject . The greater the accuracy value ( max 1 ), then the better performance of the prediction model used. Performance of k-NN in average accuracy=0.85, precision=0.87, recall=0.91 is better than Decission Tree method performance with accuracy=0.82, precision=0.85, and recall=0.89.
In this era, in an application it is often found that a dynamic input form is a form that can be filled in a lot of data, the application user is free to fill the data according to his wishes. To handle this dynamic input form, the developer usually adds a new table in a database specifically for storing dynamic data, it has the potential to waste tables and records in a database. Applying the JSON conversion technique is a solution to overcome this, dynamic data is stored in a special field so that the use of tables and records can be minimized, as well as to compress the JSON string length applied by the Zlib algorithm. In this study, dynamic data is a images file uploaded on an input form. The results of this study in the case of handling multiple dynamic form upload images shows that the JSON conversion technique is better than conventional techniques in terms of faster data storage speeds of 72.6%, in terms of simpler database structures, and in terms of 22.7% more data size small, so database management becomes more efficient.
Tourism today is very potential to be developed as one source of local revenue by providing information both online and offline and online for the community so that increased regional revenue desired by the government. The number of tourist attractions in Bali to make many tourists from abroad and in the country feel confusion in determining the destination, the most beautiful and easy to reach the place. There are many criteria to be considered, then through this recommender system, tourists can find out what tours they will visit while in Bali. One of the problems of decision making with many criteria and attributes in choosing a tourist attraction is to provide detailed decisions that refer to the weight scale they have. The decision support system gives priority result of tourist attraction suitable for every tourist from abroad and in the country. This research is focused on applying multi-attribute decision making, for decision support system using the preferred method of organization for enrichment evaluation. This research uses the descriptive analytical method to present a summary of survey results made by spreading quizzers to domestic, foreign and foreign tourists, from tourists who want to choose the island of Bali tourism in accordance with cost, security, natural beauty, facilities and infrastructure and location the island of Bali
Queuing is a tedious activity and can spend a lot of time for some people, especially if it is a queue at a health clinic. The usual queue is the prospective patient (the person who is sick), have to undergo a queue process so long before can get health care. To facilitate the process of queuing at the health clinic and solve problems in the conventional queuing system, the author designed an Online Queue System at a health clinic using Waterfall system development method. The output of this queue system is divided into three components; namely Admin which serves as an Interface for the clinic to post all clinical information, Android Application which serves as an Interface for patients to see the queue number is running, queue the queue number online, get notification in the form of Pop Up notification and Maps for real-time direction to the clinic location, and Web Server which functions to integrate data from the Clinical Admin Website to the Android Patient App
Hijab is a female genital covering commonly used by adult women. The number of hijab wearing fashion modes is developing, this makes one of the factors lack of understanding about using the correct hijab. By utilizing image processing using classification techniques can be distinguished between veiled women and not veiled. Artificial Neural Network (ANN) is an artificial intelligence that presents like a human brain by means of learning. ANN can be embedded into a computer program for the calculation process. One of the uses of ANN is to process the image to be classified. Image processing stages are data acquisition, preprocessing, edge detection, training, testing and classification. Based on the tests that have been carried out as many as 20 experiments, the results of image classification using Artificial Neural Network algorithm and backpropagation learning methods show a good level of accuracy.
SMK Negeri 1 Rantau Alai is located at Ogan Ilir Regency, South Sumatera Province. In this Vocational High School (SMK), there are two majors namely Computer and Network Engineering (TKJ) and Software Engineering (RPL). SMK Negeri 1 Rantau Alai already has a computer network that used to communicate all users for file sharing called Local Area Network (LAN). It has been connected to the internet, but does not have a network security system so it`s very vulnerable to hacker intrusion who can do cyber crime. Therefore in this research, researcher built the network security on layer 2 Open System Interconnection (OSI) by utilizing DHCP Snooping technology to avoid cyber crime such as loss of important data from SMK Negeri 1 Rantau Alai database server. To implement DHCP Snooping, researcher need a routerboard Mikrotik device and also a switch that is one of hardware needed on the Data Link Layer. Besides that, Winbox and Putty software are also needed to help in the overall configuration of this research . The results obtained after DHCP snooping configuration done is the ability to recover IP addresse when converted to Fake IP will be able to return to its original IP address and limit the number of users who can access the internet at SMK 1 Rantau Alai Keywords : LAN, DHCP Snooping, Switch, Winbox, Putty
The lecture meeting is a face-to-face meeting between a teacher and the learners in the classroom in the implementation. In the rules that apply that every lecture meeting a teacher must put the signature on the sheet of paper attendance in the signature column. Checking the lecture meeting in this way has its weaknesses, namely easily manipulated. For this reason, there is an idea to design a system that can make automatic college meeting folders every time the teacher runs this system. The experimental results show that the system can automatically create lecture meeting folders for various subject names that are already available.
Behind Bitcoin’s, there is a technology that becomes its fundamental part, which is Blockchain. Bitcoin is the first cryptocurrency in the world. At present, blockchain technology is the subject of discussion and research among developers, business people and researchers. Basically, blockchain technology functions as a digital \u0027ledger\u0027 that records every transaction that occurs and what makes blockchain interesting is, data that has been recorded in it cannot be changed. Furthermore, various blockchain-based applications began to emerge, and are used in various fields, the first to implements blockchain technology is digital currency transactions, other fields, such as the Internet of Things, government, health services, education, and industries. However, like other emerging technologies, blockchain technology still faces several challenges such as scalability and security. To deepen the knowledge about blockchain technology, a literature study is needed using the Literature Review method. This research uses literature sources from Scopus reputable institutions, Thomson Reuters / Web of Science, Directory of Open Access Journals (DOAJ), EBSCO, and Google Scholar. The contribution of this paper is to convey how Blockchain technology works, the applications and challenges ahead that will be faced by blockchain technology.
We have developed a low-cost participatory monitoring system for wildfire in peatland, that enables air pollutan referential parameters measurements based on a multilayer distributed parameter model with a Wido IoT platform. This is an Internet of Things (IoT) application, of which a physical object is embedded with electronics, software, sensors and GSM connectivity to allow monitoring participatory system (CO, CO 2 , PM10) on real-time based on cloud systems In this paper proposes a low-cost, rapid-deployment and energy-autonomous solution based on Wido IoT to improve the assessment and the understanding of air quality in developing monitoring peatland areas, thus helping policy makers and scientists to better handle air pollution. The proposal incorporates the use of a website to display collected data and processed information to empower citizens with knowledge about the air they breathe.
