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The Telematika, with registered number ISSN 2442-4528 (online) ISSN 1979-925X (print) is a scientific journal published by Universitas Amikom Purwokerto. The journal registered in the CrossRef system with Digital Object Identifier (DOI) prefix 10.35671/telematika. The aim of this journal publication is to disseminate the conceptual thoughts or ideas and research results that have been achieved in the area of Information Technology and Computer Science. Every article that goes to the editorial staff will be selected through Initial Review processes by the Editorial Board. Then, the articles will be sent to the Mitra Bebestari/ peer reviewer and will go to the next selection by Double-Blind Preview Process. After that, the articles will be returned to the authors to revise. These processes take a month for a minimum time. In each manuscript, Mitra Bebestari/ peer reviewer will be rated from the substantial and technical aspects. The final decision of articles acceptance will be made by Editors according to Reviewers comments. Mitra Bebestari/ peer reviewer that collaboration with The Telematika is the experts in the Information Technology and Computer Science area and issues around it.
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Telematika
Published by Universitas Amikom Purwokerto
ISSN : 1979925X     EISSN : 24424528     DOI : 10.35671/telematika
Core Subject : Education,
Education
Jl. Letjend Pol. Soemarto No.126, Watumas, Purwanegara, Kec. Purwokerto Utara, Kabupaten Banyumas, Jawa Tengah 53127
Arjuna Subject : -
Articles 235 Documents
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Peningkatan Ekstrasi Ciri Sinyal Epilepsi Menggunakan Teknik Sampling Ade Eviyanti; Hindarto Hindarto; M. Abror
Telematika Vol 13, No 2: Agustus (2020)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v13i2.964

Abstract

Epilepsy is a brain disorder characterized by repeated seizures. Epileptic seizures are episodes that can vary from short periods to long periods and are almost undetectable. Electroencephalography (EEG) is a way to record the activities of the human brain. EEG is a brain sensor that can be used to determine epilepsy. The purpose of this study is to classify the signals of people who have epilepsy disease and the signals of people in good health. The method used is a sampling technique method to find the characteristics of EEG signals and the K-Nearest Neighbor (KNN) method to find the classification of EEG signals. The data used is EEG signal data consisting of five data sets (data set A, data set B, data set C, data set D, and data set E), this data comes from public data. Each data set contains 100 EEG signal data on one EEG sensor channel. This study only uses two classes, the first is Data Set A and the second is Data Set E. Data Set A is a person in normal condition and data set E is a person in a state of having epilepsy. In the sampling technique process, the values taken are the average value and the standard deviation value. Research that has been done yields an accuracy rate of 100%.
Students Grade Grouping to Optimize On-Time Graduation Predictions by Combining K-Means and C4.5 Algorithms (Case Study: University Potensi Utama) Bob Subhan Riza; Sarjon Defit
Telematika Vol 14, No 1: February (2021)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v14i1.1109

Abstract

Graduating on time is the dream of every student who studies in universities. Some factors that can lead to failure in graduating on time, such as grades, though students are sometimes careless and underestimating this factor, despite knowing that problematic Grade will hinder the student from graduating on time. This research helps the study program to predict which students will graduate on time. There are 2 stages in the research, first is the process of clustering students' data using the K-Means algorithm, while the second stage predicts students' graduation using the C4.5 algorithm. Variable used are Grade, Failing Grade, Specialization, Internship, Thesis, Undergraduate Thesis 1, Undergraduate Thesis 2, and Passing Grade. Using RapidMiner and processing these data using this software can predict students that graduate on time.
An Analysis of COVID-19 using X-ray Image Segmentation based Graph Cut and Box Counting Fractal Dimension Faiz Ainur Razi
Telematika Vol 14, No 1: February (2021)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v14i1.1217

Abstract

COVID-19 is a disease that spreads relatively quickly. So that many victims are infected by this virus. There are various ways to diagnose the body's infection with the coronavirus. One of them with X-ray results. Detecting COVID-19 with the help of an X-ray sometimes has problems determining the location of the lesion because it is possible because of the large amount of noise in the image. Therefore, the X-ray results will be segmented images using the graph cut algorithm to analyze normal lungs and lungs infected with COVID-19. After obtaining the segmentation results in the form of binary images, the next step is to analyze using the box-counting method's fractal dimensions. From the fractal Dimension results, normal lungs have an average dimension of 1.7890, and lungs infected with COVID-19 have an average dimension of 1.5834. Normal lungs have dimensions larger than lungs infected with the coronavirus due to the lungs' covering by lesions or abnormal conditions in body tissues. This is what causes COVID-19 patients to have complaints of difficulty breathing.
Klasifikasi Kanker Kulit Berdasarkan Fitur Tekstur, Fitur Warna Citra Menggunakan SVM dan KNN Muhammad Faruk; Nur Nafi’iyah
Telematika Vol 13, No 2: Agustus (2020)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v13i2.987

Abstract

Skin cancer is one type of cancer that is quite serious that can not be controlled completely, so that many still result in death, disability and high medical costs. The diagnosis process carried out by dermatologists generally uses the Biopi process which is expensive, painful and requires a long recovery time for the wound, due to taking body tissue that scratches a small piece of tissue or by using a syringe to get a sample. Therefore we need a tool or system that can speed up helping to find out the type of skin cancer suffered, so that it can find out its treatment early by using digital image processing techniques. The purpose of this study is to classify the types of skin cancer based on texture and color image features using the SVM and KNN algorithm. The benefits are expected to help the skin medicine team in diagnosing skin cancer early. The features used are grayscale imagery taken by the average value, standard deviation, skewness, entropy, variance, contrast, energy, correlation, and homogeneity. Furthermore, the value of these features is trained and classified. The classification results using the SVM algorithm have an accuracy value of 69.85%. And accuracy using the KNN algorithm, with a value of K = 2 67.27%, K = 3 67.88%, K = 4 70.15%, K = 5 70.61%, K = 6 69.55%. Thus the best K on KNN is 5, the accuracy is 70.61%. Where the data used are 2637 training dataset images, and 660 test data images. And classified as a class of malignant, benign skin cancer.
Prediction Model Grade Point Average using Backpropagation Neural Network and Multiple Linear Regression Lusiana Efrizoni; Sarjon Defit
Telematika Vol 14, No 1: February (2021)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v14i1.1113

Abstract

Education in the 21st century equips students with knowledge and information and the success of achieving academic achievements during the learning process. Students' academic achievement can be seen from various aspects: the Grade Point Average. So far, efforts to predict GPA have not been made. In fact, if the student's Grade Point Average can be predicted from an early age, the study program can implement a policy to improve graduates' quality and make planning, study escort, and guidance more intensive. Based on this urgency, this study aims to produce a predictive model for the GPA of STMIK Amik Riau students in the odd semester of 2019, using the Backpropagation Neural Network algorithm and Multiple Linear Regression. Backpropagation's architectural model is 8 architectures, and 4-5-1 is the best architectural model with MSE at the time of training = 0.00099965532 and MSE during network validation = 0.0038793 with an epoch of 102 iterations and the resulting accuracy value of 95.24%. Meanwhile, the GPA prediction results, after testing using the Multiple Linear Regression algorithm, obtained an MSE value of 0. 0.27966667%, with a Multiple Correlation coefficient (R) of R = 0.9774925 and a coefficient of determination (R2) = 0.95549159. Thus the prediction of student GPA using MLR is accurate because the value of the coefficient of determination (R2) is close to 1.
Comparison of Inverse Kinematics and Forward Kinematics Methods on Walk Cycle Animation Characters Afifah Nur Aini; Ema Utami; Suwanto Raharjo
Telematika Vol 14, No 1: February (2021)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v14i1.888

Abstract

The 3D animation industry is currently growing rapidly, but the process of animating 3D characters is not always fast, because it is often constrained at the animation stage due to the complexity or irregularity of the function of each rig on the 3D character object, therefore it takes a proper rig creation stage to support the animation process that is more efficient in terms of process and time. Kinematics in animation is used for reference when an object is moving. The animation uses a Kinematics approach to display natural results. This research aims to study the level of effectiveness in terms of the time span required to drive the 3D Walk cycle animation using the attached Kinematics & Advanced Kinematics methods. The animation reference used was a standard human Walk cycle with the extent for each part of the body to be animated such as head animation, hand animation, foot animation, and bed animation to complete a walking compilation of animated Walk cycle. The execution of each part is carried out by the inverse kinematics method and then proceed with the advanced kinematics method. Based on the results of the implementation in each section of the walk cycle by comparing the two methods, Inverse Kinematics is an effective method for animating the legs and the head. While the Forward Kinematics method is more effective in animating the hands, body parts, and finishing movement. The results of the comparison show that the level of time effectiveness in human character 3D animation movements using the inverse kinematics method compared to forward kinematics are 31.18% in body animation, 40.46% in foot animation, 13.94% in hand animation, 2.04% in head animation motion, and 7.61% for finishing walk cycle movement.
Sistem Komunikasi Augmentatif dan Alternatif Berbasis Tracking Realtime Mata Yogi Ramadhani; Dita Dayu AW; Retno Supriyanti
Telematika Vol 13, No 2: Agustus (2020)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v13i2.979

Abstract

Communication focuses on understanding of a person to another person, a simple communication can occur if there are similarities between the delivery of messages and people who receive messages. However, there are some people who lose communication skills or language and speech disorder which is a side effect of some diseases. One think to facilitate the problem is building a Augmentative and Alternative Communication (AAC) Systems. AAC is a communication method to support speaking or writing abilities for someone who have oral and writing disorders. In this research, eye-gaze boards used to implant AAC method. The computer programs created to implement that methods, with centroid iris tracking as input variable. The tests were carried out on various respondents with various eye shapes. The result of this research show that iris centroid could represent eyes direction, with six classifications (left – middle – right and upper – lower).
Image Quality Analysis of PNG Images on WhatsApp Messenger Sending Fahmi Anwar; Abdul Fadlil; Imam Riadi
Telematika Vol 14, No 1: February (2021)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v14i1.1114

Abstract

Technology is growing rapidly, especially in communication with various types of information services such as internet-based messages. One of the most popular internet-based messages in Indonesia is WhatsApp Messenger. WhatsApp is a chat application that can be used on many platforms. Message sending on WhatsApp is carried out end-to-end encryption from the sender to the message recipient. The sending of messages in PNG images is secured using end-to-end encryption and compressed according to predefined rules. This study analyzes Image Compression and Alpha channel in PNG by comparing PNG images before being sent with PNG images that have gone through the sending process on WhatsApp using the test-driven development (TDD) method. The analysis results contain comparisons based on the RMSE, SSIM, PSNR, and MD5 hash values. Delivery with a gallery image attachment type using an image transparent background changes to a white image background. While those with a background other than transparent have good image quality because it has a PSNR value of more than 35 dB, and submissions with document attachment types do not experience changes in MD5 hash value and image quality.
Smart-Cane for The Blind with A Sensor Detection Approach Rahmat Tullah; Syaipul Ramdhan; Reza Nabili Akbar; Fahmi Yusuf
Telematika Vol 13, No 2: Agustus (2020)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v13i2.991

Abstract

Not all humans are created with normal eyes. Blindness is not only interfered with daily activities but also has socio-economic impacts on the environment, society, and the country. Those who have visual impairment usually have difficulty when walking and doing activities, while they still generally use traditional and manual walking sticks to help them. This research aims to help blind people carry out activities and improve facilities to use more sophisticated technology. The method used in this study is to use the prototype method. It is a process where simple modeling allows visually impaired people to have a primary picture of the program and conduct initial testing on tools, and facilitate the blind to interact with each other during the manufacturing process so that developers can easily model the software to be made. The results of this study constructed an automatic stick that can detect obstructions in front and top and detect puddles using a buzzer as a notification if the tool detects a barrier object. With seven tests using different materials, the average front sensor error value is 0.68%, the sensor works well, with two testing trials using other materials the average sensor error value is above 0.95% and can detect water in front of the tool user.
Topic Modeling of Online Media News Titles during COVID-19 Emergency Response in Indonesia Using the Latent Dirichlet Allocation (LDA) Algorithm M Didik R Wahyudi; Agung Fatwanto; Usfita Kiftiyani; M. Galih Wonoseto
Telematika Vol 14, No 2: August (2021)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v14i2.1225

Abstract

Online media news portals have the advantage of speed in conveying information on any events that occur in society. One way to know what a story is about is from the title. The headline is a headline that introduces the reader's knowledge about the news content to be described. From these headlines, you can search for the main topics or trends that are being discussed. It takes a fast and efficient method to find out what topics are trending in the news. One method that can be used to overcome this problem is topic modeling. Topic modeling is necessary to help users quickly understand recent issues. One of the algorithms in topic modeling is Latent Dirichlet Allocation (LDA). The stages of this research began with data collection, preprocessing, forming n-grams, dictionary representation, weighting, validating the topic model, forming the topic model, and the results of topic modeling. The results of modeling LDA topics in news headlines taken from www.detik.com for 8 months (March-October 2020) during the COVID-19 pandemic showed that the best number of topics produced each month were 3 topics dominated by news topics about corona cases, positive corona, positive COVID, COVID-19 with an accuracy of 0.824 (82.4%). The resulting precision and recall values indicate that the two values are identical, so this is ideal for an information retrieval system.

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