Journal of Telematics and Informatics
Journal of Telematics and Informatics (e-ISSN: 2303-3703, p-ISSN: 2303-3711) is an interdisciplinary journal of original research and writing in the wide areas of telematics and informatics. The journal encompasses a variety of topics, including but not limited to: The technology of sending, receiving and storing information via telecommunication devices in conjunction with affecting control on remote objects; The integrated use of telecommunications and informatics; Global positioning system technology integrated with computers and mobile communications technology; The use of telematic systems within road vehicles, in which case the term vehicle telematics may be used; The structure, algorithms, behavior, and interactions of natural and artificial systems that store, process, access and communicate information; Develops its own conceptual and theoretical foundations and utilizes foundations developed in other fields; and The social, economic, political and cultural impacts and challenges of information technologies (advertising and the internet, alternative community networks, e-commerce, e-finance, e–governance, globalization and security, green computing, ICT for sustainable development, ICT in healthcare and education, management and policymaking, mobile and wireless communications, peer-to-peer learning, regulation of digital technologies, social networking, special user groups, the 2.0 paradigm, the WWW, etc).
The journal is a collaborative venture between Universitas Islam Sultan Agung (UNISSULA), Universitas Ahmad Dahlan (UAD) and Institute of Advanced Engineering and Science (IAES) Indonesia Section.
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<![CDATA[Portable Baby Incubator Based On Fuzzy Logic ]]>
<![CDATA[Qory Hidayati]]>;
<![CDATA[Nur Yanti]]>;
<![CDATA[Nurwahidah Jamal]]>;
<![CDATA[Mey Adisaputra]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i1.
<![CDATA[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 ℃.]]>
<![CDATA[Analysis of Driver Position Control on Electronic Power Steering (EPS) Using PID ]]>
<![CDATA[Suprawikno Suprawikno]]>;
<![CDATA[Muhammad Haddin]]>;
<![CDATA[Arief Marwanto]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i1.
<![CDATA[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 closes 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.]]>
<![CDATA[Improvement of Enhanced Image Using Mean and Standard Deviation Increment Method Based on Visual Representation Statistics ]]>
<![CDATA[Faruk Alfian]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i1.
<![CDATA[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. ]]>
<![CDATA[VISUAL BASED HUMAN WEIGHT PREDICTION USING ARTIFICIAL NEURAL NETWORK ]]>
<![CDATA[Abdul Basit]]>;
<![CDATA[Imam Much Ibnu Subroto]]>;
<![CDATA[Sri Arttini Dwi Prasetyowati]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i1.
<![CDATA[Measuring instrument becomes very important to be able to know how much human weight is. Weight information is generally obtained from measurements by body scale. One of other methods to find out a person's weight is by image processing. This study aims to calculate body weight by image processing with the Artificial Neural Network algorithm using back propagation method to detect body weight. The results of testing, analysis, and system accuracy of 97% indicate that the method of calculating body weight is very possible through image processing with various provisions and restrictions. Key words: Weight, Computer Vision, Artificial Neural Network]]>
<![CDATA[A Novel Cuff-less Measurement Method for Noninvasive Blood Pressure Prediction using Body Vital Signals ]]>
<![CDATA[Shooka Shariat Mohreri]]>;
<![CDATA[Mona Moradi]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i1.
<![CDATA[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.]]>
<![CDATA[A Prediction Method Of Rice Harvesting Using Artificial Neural Network ]]>
<![CDATA[Fitri Anindyahadi]]>;
<![CDATA[Imam Much Ibnu Subroto]]>;
<![CDATA[Arief Marwanto]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 1 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i1.
<![CDATA[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.]]>
