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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Penelitian Pendidikan Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol J-Dinamika: Jurnal Pengabdian Kepada Masyarakat TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika MULTINETICS Jurnal Teknik Informatika (JUTIF) Charity : Jurnal Pengabdian Masyarakat eProceedings of Engineering Jurnal INFOTEL Jurnal Nasional Sains dan Teknik
Favian Dewanta
Universitas Telkom
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences

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Journal : Jurnal INFOTEL

 1 
Construction of cardiac arrhythmia prediction model using deep learning and gradient boosting Dhanar Bintang Pratama; Favian Dewanta; Syamsul Rizal
JURNAL INFOTEL Vol 13 No 3 (2021): August 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i3.683

Abstract

Arrhythmia is a condition in which the rhythm of heartbeat becomes irregular. This condition in extreme cases can lead to fatal heart attack accidents. In order to reduce heart attack risk, appropriate early treatments should be conducted right after getting results of Arrhythmia condition, which is generated by electrocardiography ECG tools. However, reading ECG results should be done by qualified medical staff in order to diagnose the existence of arrhythmia accurately. This paper proposes a deep learning algorithm method to classify and detect the existence of arrhythmia from ECG reading. Our proposed method relies on Convolutional Neural Network (CNN) to extract feature from a single lead ECG signal and also Gradient Boosting algorithm to predict the final outcome of single lead ECG reading. This method achieved the accuracy of 96.18% and minimized the number of parameters used in CNN Layer.
All-in-one computation vs computational-offloading approaches: a performance evaluation of object detection strategies on android mobile devices Muhammad Abdullah Rasyad; Favian Dewanta; Sri Astuti
JURNAL INFOTEL Vol 13 No 4 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i4.700

Abstract

Object detection gives a computer ability to classify objects in an image or video. However, high specified devices are needed to get a good performance. To enable devices with low specifications performs better, one way is offloading the computation process from a device with a low specification to another device with better specifications. This paper investigates the performance of object detection strategies on all-in-one Android mobile phone computation versus Android mobile phone computation with computational offloading on Nvidia Jetson Nano. The experiment carries out the video surveillance from the Android mobile phone with two scenarios, all-in-one object detection computation in a single Android device and decoupled object detection computation between an Android device and an Nvidia Jetson Nano. Android applications send video input for object detection using RTSP/RTMP streaming protocol and received by Nvidia Jetson Nano which acts as an RTSP/RTMP server. Then, the output of object detection is sent back to the Android device for being displayed to the user. The results show that the android device Huawei Y7 Pro with an average FPS performance of 1.82 and an average computing speed of 552 ms significantly improves when working with the Nvidia Jetson Nano, the average FPS becomes ten and the average computing speed becomes 95 ms. It means decoupling object detection computation between an Android device and an Nvidia Jetson Nano using the system provided in this paper successfully improves the detection speed performance.
A study of secure communication scheme in MQTT: TLS vs AES cryptography Favian Dewanta; Baiq Yuniar Yustiarini; Bangun Indrakusumo Radityo Harsritanto
JURNAL INFOTEL Vol 14 No 4 (2022): November 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i4.807

Abstract

The Internet of Things (IoT) technology requires low latency communications. One of the lightweight protocols in the IoT is the MQTT protocol. However, the MQTT protocol is not equipped with the appropriate security mechanism. As a consequence, the MQTT messages are easily eavesdropped and modified by the attackers. This research studies the use of AES cryptography-based communication scheme against the TLS-based communication scheme, which can be used to create end-to-end secure communication channels from the MQTT publishers to the MQTT subscribers. Experimental results show that the TLS-based communication scheme possess the highest cost in terms of communication delay and network cost among all schemes in the experiment. Eventually, the AES-based MQTT communication scheme is more appropriate for IoT environments because of its communication delay and network cost, which are considerably equal to the plaintext-based MQTT communications.
Co-Authors Adhirajasa, Radhiyya Putra Adi Nugroho Aditya Karyadi Kusuma Ahmad Tri Hanuranto Angga Rusdinar Anggun Fitrian Isnawati Anita Rosdina Nasution Arif Indra Irawan AULIA ARIF WARDANA Bagus Aditya Bagus Aditya Bagus Aditya Baiq Yuniar Yustiarini Barends, Julian Kevin Danang Triantoro Murdiansyah Deny Kurniawan Devi Pratami Dhanar Bintang Pratama Dhea Dearly Herman Dimas, I Gusti Ngurah Bagus Doan Perdana Dong-Sung Kim Evander Alfa Bahana Fajrin, Alvin Nur Farah Afianti Farah Afianti Hanif, Nasywan Harsritanto, Bangun Indrakusumo Radityo Hilal Hudan Nuha Hilman Fauzi, Hilman Ibrahim, Khalif Ika Arum Puspita Istikmal Izzulhaq, Muhammad Hilmi Jesikapna Kristina Br Tarigan Kautsar , Rifki Ikbar Litasari Widyastuti, Litasari Loudry Achmad Tiransri Mabruroh, Anggun Mugi Manalu, Jesseline Regina Mera Kartika Delimayanti Muhammad Abdillah Muhammad Abdullah Rasyad Muhammad Bagas Arya Darmawan Muhammad Hafiz Amrullah Muhammad Zuhairi Naning Hertiana, Sofia Nasution, Muhammad Surya Alghifary Niken Dwi Wahyu Cahyani Nuha, Hilal H Nurislami, Rifky Nudhar Nurul Ikhsan Nyoman Bogi Aditya Karna Parulian, Christian Antonius Puji Dwika Pradana Purwiko, Daniel Perdana Putra Putra, Fadly Firmansyah Putri, Vicha Octavia Dewanto Putri, Winda Ezranata Raffinaldy, Muhammad Zaky Ranunegoro, Adimas Fachri Rendy Munadi Retno Hendryanti Reza Rendian Septiawan Rezeki, Putri Ayu Ridha Muldina Negara Rissa Mellani Nur Wulandari Rizky, Muhamad Wildan Salma Salma Salsabila, Balqis Hasna Saputra, Maulana Reza Sitepu, Dharma Agung Sofia Naning Hertiana Sri Astuti Sri Astuti Subagyo, Lutfi Bramantio Sussi Syamsul Rizal Tarigan , Jesikapna Kristina Br Umar Ali Ahmad Wardana, Fareza Arya ZK Abdurahman Baizal