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All Journal TEKNIK INFORMATIKA JREC (Journal of Electrical and Electronics) JOIV : International Journal on Informatics Visualization Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JOURNAL OF ELECTRICAL AND SYSTEM CONTROL ENGINEERING JOURNAL OF MECHANICAL ENGINEERING, MANUFACTURES, MATERIALS AND ENERGY Jurnal Komputer Terapan Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Computer Science and Informatics Engineering (J-Cosine) Jurnal Teknologi Terpadu MULTINETICS Management Studies and Entrepreneurship Journal (MSEJ) Jurnal Abdi Insani International Journal of Electrical, Energy and Power System Engineering (IJEEPSE) Bubungan Tinggi: Jurnal Pengabdian Masyarakat Information Science and Library Ekobis: Jurnal Ilmu Manajemen dan Akuntansi Mejuajua Indonesian Community Journal Asian Journal of Management Analytics IRA Jurnal Teknik Mesin dan Aplikasinya (IRAJTMA) Jurnal Genesis Indonesia Jurnal Pepadu Jurnal Ilmu Manajemen Dan Kewirausahaan (JIMK) IRA Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Teknik Mesin & Industri (JITMI) SWARNA: Jurnal Pengabdian Kepada Masyarakat Atestasi : Jurnal Ilmiah Akuntansi
INDRA HERMAWAN
Politeknik Negeri Jakarta
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Journal : JOIV : International Journal on Informatics Visualization

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Denoising Ambulatory Electrocardiogram Signal Using Interval Dedependent Thresholds based Stationary Wavelet Transform Hermawan, Indra; Sevani, Nina; F. Abka, Achmad; Jatmiko, Wisnu
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2428

Abstract

Noise contamination in electrocardiogram (ECG) monitoring systems can lead to errors in analysis and diagnosis, resulting in a high false alarm rate (FAR). Various studies have been conducted to reduce or eliminate noise in ECG signals. However, some noise characteristics overlap with the frequency range of ECG signals, which occur randomly and are transient. This results in shape alteration and amplitude reduction in P and R waves. The author proposed a framework for eliminating noise in ECG signals using the stationary wavelet transform method and interval-dependent thresholds (IDT) based on the change point detection method to address these challenges. The proposed framework decomposes the input electrocardiogram (ECG) signal at a specific level using the Stationary Wavelet Transform method, resulting in detail and approximation coefficients. Interval detection focuses on the initial detailed coefficient, d1, chosen due to its significant content of noise coefficients, especially high-frequency noise. Subsequently, threshold values are computed for each interval. Hard and soft thresholding processes are then applied individually to each interval. Finally, reconstruction occurs using the inverse stationary wavelet transform method on the threshold coefficient outcomes. Two measurement matrices, root mean square error (RMSE) and percentage root mean squared difference (PRD), were used to measure the performance of the proposed framework. In addition, the proposed framework was compared to stationary wavelet transform (SWT) and discrete wavelet transform (DWT). The test results showed that the proposed method outperforms DWT and SWT. The proposed framework obtained an average increase in RMSE scores of 18% and 45% compared to the SWT and DWT methods, respectively, and PRD values of 17% and 37% compared to the SWT and DWT methods, respectively. So, using IDT in the stationary wavelet transform method can improve the denoising performance. With the development of this new framework for denoising ECG signals, we hope it can become an alternative method for other researchers to utilize in denoising ECG signals.
Design of Livestream Video System and Classification of Rice Disease Agustin, Maria; Hermawan, Indra; Arnaldy, Defiana; Muharram, Asep Taufik; Warsuta, Bambang
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1336

Abstract

One of the agricultural products which is an important aspect of the life of Indonesian people is rice. Rice disease has a devastating effect on rice production, while detecting rice diseases in real-time is still difficult. Therefore, this study designed a Livestream video system that is equipped with a rice disease Classification system. The Livestream system utilizes 4G network communication and is assisted by the WebSocket protocol to communicate in real-time and for the rice disease Classification system using YOLO algorithm. In addition, Livestream uses the raspberry pi camera V2 to take video stream data. In analyzing the performance of the Livestream system, four tests were carried out, namely: functionality test, connectivity test, classification performance test, and implementation performance test. The test was carried out using the wireshark and conky tools, while the classification training used 5447 images from the Huy Minh do dataset that he provided on the Kaggle website. The results show that all programs run well and get a good QoS value according to the index of the parameter results, it is also found that sending non-base64 can reduce the size of the data to approximately 200,000 bytes/s and the performance of the classification system is good because it has an average accuracy of 80% even though it is quite burdening the raspberry pi. This system can still be optimized and developed further to support research in the field of data transmission and the performance of machine learning in a microcontroller.
Co-Authors Adiansyah, Romi Agnita Yolanda, Agnita Albarofi Fierelio Kinandes Sumarsono Amin, Astuti Muh Andi Reza Perdanakusuma, Andi Reza Ariawan Andi Suhandana Arijal, Muhamad Ariyudha, Andhika Asep Kurniawan Asep Kurniawan Asep Taufik Muharram Asfat, M Lutfi Asfat, M. Lutfi Aslam, Adrian Asmah Indrawati Ayu Rosyida Zain Azzahirah, Syifa Bobby Umroh Buana Lubis, Arya Chandra Cerah Ayunda Prawastiyo Darianto, Darianto Darwin, Felix Defiana Arnaldy Defiana Arnaldy Dimas Aulia Fachrudin Dimas Aulia Fachrudin Dipati Bangsa, Prianda Dula, Veronika Anjelina Efendi, Syah Rinal Eka Miharja, Mochamad Endang Sulistya Rini Erwin Erwin F. Abka, Achmad Fachroni Arbi Murad Fadil Azhar, Raden Muhammad Fiqryansyah, Muhammad Rizky Ginting, Hotman Habib Satria Hanggara, Buce Trias Harahap, Uun Novalia Iswandi Iswandi Iswandi Iswandi Jufrizal Jufrizal Jufrizal Jufrizal Junio, Fazel Kadarwati, Dinda Kasim, Abdulah Muis Lian Galed S. Lingga, Jimy M. Anwar Ma'sum Malik Matin, Iik Muhamad Marbun, Murahmad Parulian Mardiyono, Anggi Maria Agustin Maria Agustin Marwan Marwan Matin, Iik Muhamad Malik Muh. Amin, Astuti Muhammad Arlan Ardiawan Muhammad Idris Muhammad Idris Muhammad Yusuf Bagus Rasyiidin Mulyani, Meutia Tri Murad, Fachroni Arbi Nasution, Ahmad Syarif Nathanael, David Negara, Atma Nina Sevani Nisrina Tsany Sulthanah Noviandri, Dian paham ginting Prawastiyo, Cerah Ayunda Prihatin Oktivasari Putri, Audina Amalia Rachman Hanafi Rahman, Nur Azizah Ramadhan, Muh Syahru Ramadhan, Muhammad Bintang Ratna Widya Iswara, Ratna Widya Rauf, Faisal Rijal, Rijal Rijaluddin, Khalid Risma Nuraini Rosyida, Ayu Selvi Selvi Sembiring, Beby Karina Fawzea Setianto, Bayu Dwi Seviro Bima Sakti, Calvin Siddik, Ega Sihombing, Verianto Situmorang, Syafrizal Helmi Suarti, Suarti Sudarmi Sudarmi Suhandana, Ariawan Andi Sumarni Sumarni Supriatno, Supriatno Sutama, Muhammad Ilham Syarif Nasution, Ahmad Syarman, Muh. Iksan Tampubolon, Rizky Taufik Wal Hidayat, Taufik Wal Tino Hermanto Warsuta, Bambang Wibisono, Anggih Prasetyo Widya Iswara, Ratna Widyono, M. Farishanif wirawan, chandra Wisnu Jatmiko Yopan Rahmad Aldori Zain, Ayu Rosyida Zarmawan, Husri