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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 6 Documents
 1 
Search results for , issue "Vol 13, No 2: Agustus (2020)" : 6 Documents clear
Pemantau Suhu Menggunakan NodeMcu, IoT dan Cayenne pada Rack Server Parma Hadi Rantelinggi; Fridolin Febrianto Paiki; Yosia Gadi
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.v13i2.1001

Abstract

The server is an essential part of the service provider that needs to be maintained. The server environment factor that needs to be monitored is the ideal temperature on the server rack. This study aims to implement temperature monitoring at the server rack. This research uses NodeMCU with DHT11 and IoT sensors to monitor and measure the temperature on the rack server. Temperature data on the rack server is monitored through Cayenne and displayed on smartphones and computers, so users can monitor the state of the rack server anywhere by accessing the internet. This study uses three rack servers connected with DHT11 sensors that can monitor temperature simultaneously. The results showed that the temperature increased accordingly due to the number of active servers in each rack, so it needed to be structured evenly on the server rack. Besides, the results of the study show that the application of NodeMCU with DHT11 and IoT sensors can monitor temperature well on the rack server, where the first rack server shows an average temperature of 19.3oC, for the second rack 17.4oC and the third rack 21.8oC.
E-Commerce Analysis of Customer Satisfaction and Hotel Reservation Quantity in Cilacap Regency Berlilana Berlilana; Fiby Nur Afiana
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.v13i2.1068

Abstract

This research aims to determine the effects of e-commerce implementation on customer satisfaction and room reservation quantity. The data is obtained from questionnaires distribution and analyzed using Multiple Regression Analysis where F-Test and T-Test tested the 168 samples of 290 population. From the result of analysis, Partial test on customer satisfaction shows that the three variables have t count> t table, the independent variable is quality of use (X1), namely 8,132> 1,974; the independent variable information quality (X2), namely 2.609> 1.974; the independent variable of interaction quality (X3) is 2.956> 1.974, so each H1 is accepted. Regarding the room reservation level, the partial test shows the three variables have t count> t table, the independent variable is the quality of use (X1), namely 2.181> 1.974; the independent variable information quality (X2), namely 2.021 <1.974; the independent variable of the quality of the interaction (X3), namely 3.497> 1.974, so H1 is accepted. It can be concluded  that the usability quality (X1), quality of information (X2), and quality interaction (X3) have significant effects on customer satisfaction (Y1) and room reservation quantity (Y2). Specifically, the quality of interaction shows a significant effect on the room reservation quantity as well as the quality of information and interaction on customer satisfaction. Based on this research, it can be concluded that the quality of interaction and quality of information have a positive effect on customer satisfaction, and only the interaction variable has a positive effect on the quantity of hotel room reservation.
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%.
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.
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).
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.

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