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.
Articles
141 Documents
<![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.]]>
<![CDATA[Sentiment Analysis of Indonesian Figure using Support Vector Machine ]]>
<![CDATA[Suharyo Herwasto]]>;
<![CDATA[Imam Much Ibnu Subroto]]>;
<![CDATA[Badieah Assegaf]]>
<![CDATA[ Journal of Telematics and Informatics Vol 6, No 3: September 2018 ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v6i3.230-237
<![CDATA[On the political year 2018 will be mutually popping reverberated figures for Indonesian presidential candidate 2019. The figures recognition process generally are now using social media, so it would appear the opinions of social media users. Opinions that appeared not only contain positive and negative polarity, but also contain a sentence of subjective and objective. By using a machine learning algorithm, namely Support Vector Machine, made sentiment analysis. The results of the analysis of this sentiment more optimally use the kernel Linear with the F-Measure of Polarity 68%, 68%, 63%, and the F-Measure Subjectivity 73%, 77%, 75% for each figure Anies Baswedan, Joko Widodo, and Prabowo Subianto.]]>
<![CDATA[HAPPINESS ANALYSIS OF LIBYANS PEOPLE BASED ON TWITTER DATA USING ARTIFICAL NEURAL NETWORK ]]>
<![CDATA[khaled jemah basher]]>;
<![CDATA[Imam Much Ibnu Subroto]]>;
<![CDATA[Arief Marwanto]]>;
<![CDATA[Muhammad Qomaruddin]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 2 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i4.
<![CDATA[Information technology is always developing and has very rapid growth. The internet has become a very important online communication tool for many people today. Nowadays people tend to prefer anything that is practical, faster, and flexible. Social networking services have become a simple and universal concept in the internet environment. Purpose of this study are: To analyse happiness of Libyans people based on Twitter data using artificial neural network. This study is an analytical study of secondary data processing obtained without direct field experiments. MTE (Magister program of Electrical Engineering) UNISSULA must have experiment. This study is an analytical study of data based on social media specifically using twitter data. The result of this study is Libyan feel they write down their feelings when happy rather than unhappy. Social media has become an important part of modern life, and Twitter is again a center of focus in recent events. Whatever your opinion of social media these days, there is no denying it is now an integral part of our digital life. Twitter is a good starting point for social media analysis because people openly share their opinions to general public. This is very different from Facebook where social interactions are often private. In this paper, we propose a ANN model for Twitter opinion mining prediction and classification approach. Also, we used the ANN model for Twitter Opinion abstraction and visualization scheme. The main contribution of this work is to propose such a new visualization model for Twitter mood prediction based on ANN approach]]>
<![CDATA[A STEGANOGRAPHY LEAST SIGNIFICATION BITS (LSB) TECHNIQUE FOR HIDE TEXT DATA ENCRYPTION WITHIN IMAGE ]]>
<![CDATA[Riyadh Alnajih Alsayih]]>;
<![CDATA[Muhamad Qomaruddin]]>;
<![CDATA[Imam Much Ibnu Subroto]]>;
<![CDATA[Suryani Alifah]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 2 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i4.
<![CDATA[With the development of means of communication and the exchange of information over the Internet, and with the development of hacking operations, intruders became able to view, and change information, so the need to find means to preserve privacy and information exchange arose. Cryptography and steganography had a prominent role in this field Encryption distorts the message and steganography hides the message's presence. In this paper, the proposed system uses both steganography and cryptography to provide a double layer of security. In cryptography, we use both a substitution and RSA algorithm to encrypt the message. In steganography, we used LSB technology with a stego key to embed data in the image, all of this to improve data security. A scale of Mean Square Error (MSE) and a scale of peak signal-to-noise ratio (PSNR) assessed system performance. The results showed that the image quality is good, and it is difficult to notice any difference between it and the original image. The results of both MSE and PSNR were good, as the PSNR value was more than 56.]]>
<![CDATA[FUZZY LOGIC FOR DETERMINING THE POTENTIAL OF SOLAR ENERGY POWER PLANT IN SOUTH LIBYA ]]>
<![CDATA[Zakariya Ali Saeid Saeid]]>;
<![CDATA[Muhamad Haddin]]>;
<![CDATA[Arief Marwanto]]>;
<![CDATA[Muhammad Qomaruddin]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 2 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i4.
<![CDATA[Energy models also help in integrated assessment considering availability, potential, economics, emission, technology, social acceptance etc Libya is an oil exporting country located in the middle of North Africa, with 6 million inhabitants distributed over an area of 1,750,000 Km2. The problem of this research is the potential of solar energy that is used can be used to overcome the energy needs in South Libya where people are densely populated but need a lot of electrical energy. The potential energy needs of electricity are big because south of Libya many densely populated people need big electricity. Also whether the function of Fuzzy logic is to be able to do the right way to map an input space into an output space based on the concept of fuzzy. The objective of this research is to analyse potential of solar energy generation using fuzzy logic in South Libya. The authenticity of this research is using fuzzy logic in South Libya to overcome the problem that is the demand of huge electricity from solar energy generation. This research is quantitative research with simulation or experimental research to make verification with MATLAB simulation (Fuzzy logic approach). In his research will cover in 7 days’ simulation with Matlab, with Fuzzy logic approach, the target is to make simulation panel solar system in South Libya. The determination of potential solar energy power plant in South Libya using fuzzy logic can be seen in the simulation Matlab that proven the Fuzzy Logic approach have achieved the optimal solar energy power plant. The result showed that in Libya the consumption is 10020 MW with 3.504.000 homes and 2860 W, so need 67 solar panels. The low is when the humidity between 40%-60% (0.6 kW), Medium when the humidity 60%-80% (2.86kW) and High when humidity 80%-100% (3.9 kW).]]>
<![CDATA[FUZZY LOGIC FOR CONTROLLING SMOKE LEVEL ON SMART SMOKING ROOM ]]>
<![CDATA[fajar pujiyanto]]>;
<![CDATA[arief marwanto]]>;
<![CDATA[suryani alifah]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 2 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i2.
<![CDATA[Public space is one of the facilities that need in public areas. One of the public space facilities is a special smoking room. The existing smoking room is still conventional, meaning that there is without controlling system to maintain the air condition in the rooms. This study discusses a smart system to control air levels in smoking rooms based on fuzzy logic. Fuzzy analysis is carried out with input parameters, namely temperature, air humidity, CO levels, smoke levels and output parameters are supply fans, exhaust fans, and air ionizers. Based on the results of smart smoking model test compared wit the Matlab analysis, the Mean Squared Error (MSE) value on the supply fan = 0.0640, MSE on the exhaust fan = 0.0502 and MSE on the ionizer = 0.0604. The results for the MSE value are closed to zero, its means smart smoking rooms models is works properly.]]>
<![CDATA[IMAGE PROCESSING FOR PERCENTAGE ANALYSIS OF VESSELS FOR VESSELS IN CORONARY HEART DISEASE PATIENTS ]]>
<![CDATA[Agung Satrio Nugroho]]>;
<![CDATA[Sri Arttini Dwi Prasetyowati]]>;
<![CDATA[Arief Marwanto]]>
<![CDATA[ Journal of Telematics and Informatics Vol 8, No 2 (2020) ]]>
Publisher : <![CDATA[Universitas Islam Sultan Agung ]]>
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DOI: 10.12928/jti.v8i2.
<![CDATA[Cardiovascular disease is the highest cause of death worldwide, for this reason early detection is important to reduce mortality due to heart disease and blood vessels, so that a program is needed to calculate the narrowing that occurs in blood vessels experienced in patients affected by coronary heart disease, so can make it easier for a doctor to analyze and give a medical decision whether to do the ring installation or just administering drugs for blood thinning. This research uses the development of image processing technology from angiographic results by utilizing cropping to determine the area to be analyzed and image segmentation, where image segmentation is in the form of a denoise as a mean filter and increases the transmission of the image to be analyzed and thresholding which is a way of emphasizing the image by changing the image to black and white. Where the narrowing area is obtained from counting the number of logical pixels 1 of the image area that has been blocked and has been reconstructed while the normal area is calculated from the number of pixels having logic 1 plus the pixel area having logic 1, logic pixel 0 is an area of the vessel that is not narrowed. The results showed that the narrowing of the vessels in patients experienced by patients affected by coronary heart can be measured how narrowing is experienced. Of the 11 patient data measured, there were 4 patient data that were compared with the measurement results of the angiography instrument with the highest obtained error value of 3.9% and the lowest error value of 0.1% with an average value of error 1.8% where the error value is still within the tolerance value. Keywords: image processing, vessels for vessels, coronary heart disease]]>
