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Jurnal INFOTEL
Published by Universitas Telkom
ISSN : 20853688     EISSN : 24600997     DOI : https://doi.org/10.20895/infotel.v15i2
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal INFOTEL is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto, Indonesia. Jurnal INFOTEL covers the field of informatics, telecommunication, and electronics. First published in 2009 for a printed version and published online in 2012. The aims of Jurnal INFOTEL are to disseminate research results and to improve the productivity of scientific publications. Jurnal INFOTEL is published quarterly in February, May, August, and November. Starting in 2018, Jurnal INFOTEL uses English as the primary language.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol 12 No 4 (2020): November 2020" : 6 Documents clear
EVALUASI SISTEM INFORMASI PENGGUNAAN E-LEARNING SEBAGAI SISTEM PERKULIAHAN PERGURUAN TINGGI Uswatun Hasanah; Syahroni Hidayat; Danang Tejo Kumoro
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.475

Abstract

This study aims to evaluate the use of technology to support teaching and learning activities. Lecturers and students have applied e-learning to teach subjects. The purpose of this evaluation is to measure the success of the use of STMIK Bumigora e-learning by using the Technology Acceptance Model (TAM) approach, which is an approach that can explain user behavior towards the use of technology. Evaluation of the use of e-learning is formulated into a model based on the TAM model, while SEM (Structural Equation Modelling) is used for data analysis. Based on the measurement analysis in this study, several factors most influenced the effectiveness of e-learning, namely the usage tutorial for users, ICT facilities related to the Ease of accessing the internet network. Meanwhile, in structural analysis, it was found that attitudes toward the use and perceived usefulness were strongly correlated with real use factors. The actual use is a real condition of the use of e-learning measured by the frequency and duration of time in using the technology, which is influenced by the user's belief in accepting the existence of e-learning in STMIK Bumigora and user beliefs related to the benefits when using it. Therefore, attitudes toward the use and perception of usefulness are the main determining factors in measuring the frequency and duration of e-learning use.
Doppler Shift Effect at The Communication Systems with 10 GHz around Building Andrita Ceriana Eska
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.483

Abstract

This research described the Doppler shift effect for the communication systems. The mobile station moves with various velocities around the building’s environment. Doppler’s shift influences the communication systems. The frequency communication was used 10 GHz and its influenced by atmospheric attenuation. This research consisted of propagation with LOS and NLOS conditions, mobile station velocity variation, height buildings variation, and transmitter power variation. This research described frequency maximum at Doppler shift, coherence time, and signal to noise ratio. More increase Doppler shift of coherence time caused signal noise ratio to decrease.
Performance Analysis of CRC-Polar Concatenated Codes Lydia Sari; Masagus M. Ikhsan Assiddiq U.P.; Syah Alam; Indra Surjati
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.494

Abstract

Polar code has been proven to obtain Shannon capacity for Binary Input Discrete Memoryless Channel (BIDMC) and its use has been proposed as the channel coding in 5G technology. However, its performance is limited in finite block length, compared to Turbo or LDPC codes. This research proposes the use of various CRC codes to complement Polar codes with finite block length and analyses the performance based on Block Error Rate (BLER) to Es/N0 (dB). The CRC codes used are of degrees 11 and 24, with 3 different polynomial generators for each degree. The number of bits in the information sequence is 32. The list sizes used are 1, 2, 4, and 8. Simulation results show that the concatenation of CRC and Polar codes will yield good BLER vs Es/N0 performance for short blocks of codeword, with rates 32/864 and 54/864. Concatenating CRC codes with Polar codes will yield a BLER performance of 10-2 with Es/N0 values of -9.1 to -7.5 dB when CRC codes of degree 11 is used, depending on the SC list used. The use of CRC codes of degree 24 enables a BLER performance of 10-2 with Es/N0 values of -7 to -6 dB when the SC list used is 1 or 2. The use of CRC codes of degree 24 combined with SC list with sizes 4 or 8 will improve the BLER performance to 10-2 with Es/N0 values of -8 to -7.5 dB
Navigating Bitcoin Panic-Selling using Linear Approach Agi Prasetiadi
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.543

Abstract

COVID-19 affects significant human activity around the globe, including Bitcoin prices. The Bitcoin price is well known for its volatility, so it is not a big shocker when the panic-selling occurs during the pandemic. However, the mechanism to cope with these breakouts, especially the bearish one, is contentious. The experts give numerous pieces of advice with different conclusions in the end. It is also the same with Machine Learning. Various kernels show different results regarding how the price will move. It depends on the window size, how the data is being preprocessed, and the algorithm used. This paper inspects the best combination that various machine learning can offer with a linear approach to navigate the price prediction based on its depth interval, window size until the algorithms themselves. This paper also proposed a new approach to seeing the prediction range called s-steps ahead prediction using a linear model. The result shows that simple machine learning can herd 99.715% profit even during the bearish breakout.
Design and Implementation of Boost Voltage Doubler for Maximum Power Point Tracker Application Using STM32F1038CT Laras Triefena; Leonardus H. Pratomo; Slamet Riyadi; F. Budi Setiawan
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.545

Abstract

Photovoltaic is an absolute device in the solar power plant system. A DC-DC converter with a maximum power point tracker (MPPT) algorithm is required to obtain the maximum power of photovoltaic. In general, solar power plant applications used a two-stage converter: the first stage is boosting DC-DC converter, and the second stage is the multilevel Inverter. Boost DC-DC converter is usually implemented singly, which causes many boost DC-DC converters to be implemented in a solar power plant application. The voltage doubler type boost DC-DC converter proposed in this paper is to simplify the circuit so that there is only one converter in a solar power plant application. This converter principle combines two conventional boost converters, which are integrated into one so that the power circuit and control circuit form become simpler. This proposal is verified through computation simulation and hardware design using the STM32F1038CT microcontroller for the final verification. The efficiency algorithm of the simulation is 99.7%, and the hardware experimental is 85.65%
Accuracy Analysis of K-Nearest Neighbor and Naïve Bayes Algorithm in the Diagnosis of Breast Cancer Irma Handayani; Ikrimach Ikrimach
JURNAL INFOTEL Vol 12 No 4 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v12i4.547

Abstract

In the medical field, there are many records of disease sufferers, one of which is data on breast cancer. An extraction process to fine information in previously unknown data is known as data mining. Data mining uses pattern recognition techniques such as statistics and mathematics to find patterns from old data or cases. One of the main roles of data mining is classification. In the classification dataset, there is one objective attribute or it can be called the label attribute. This attribute will be searched from new data on the basis of other attributes in the past. The number of attributes can affect the performance of an algorithm. This results in if the classification process is inaccurate, the researcher needs to double-check at each previous stage to look for errors. The best algorithm for one data type is not necessarily good for another data type. For this reason, the K-Nearest Neighbor and Naïve Bayes algorithms will be used as a solution to this problem. The research method used was to prepare data from the breast cancer dataset, conduct training and test the data, then perform a comparative analysis. The research target is to produce the best algorithm in classifying breast cancer, so that patients with existing parameters can be predicted which ones are malignant and benign breast cancer. This pattern can be used as a diagnostic measure so that it can be detected earlier and is expected to reduce the mortality rate from breast cancer. By making comparisons, this method produces 95.79% for K-Nearest Neighbor and 93.39% for Naïve Bayes

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