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All Journal HAYATI Journal of Biosciences JURNAL PENDIDIKAN KEPERAWATAN INDONESIA ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Sinergitas PkM & CSR KACANEGARA Jurnal Pengabdian pada Masyarakat Building of Informatics, Technology and Science Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Robotics and Control (JRC) Jurnal Teknologi Bahan dan Barang Teknik Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Jurnal Abdimas Kartika Wijayakusuma Jurnal Locus Penelitian dan Pengabdian eProceedings of Engineering Jurnal Rekayasa elektrika IJoICT (International Journal on Information and Communication Technology)
Bayu Erfianto
Universitas Telkom
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Enhancing Contactless Respiratory Rate Measurement Accuracy: Integration of 24GHz FMCW Radar and XGBoost Machine Learning Arisandy, -; Erfianto, Bayu; Setyorini, -
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2654

Abstract

Advancements in non-contact vital sign monitoring are crucial for enhancing patient measurements' accuracy and overall patient experiences. This research explores the integration of 24GHz Frequency-Modulated Continuous-Wave (FMCW) radar with the XGBoost machine learning algorithm to improve the detection of respiratory rate (RR). This innovative approach offers a promising alternative to traditional contact-based methods. The study utilizes FMCW radar to detect respiratory motion, while signal patterns are analyzed using XGBoost to ensure accuracy across various healthcare environments. The method involves collecting signals, pre-processing to remove noise and irrelevant data, and extracting features to be analyzed by the XGBoost algorithm. The collected dataset, which includes controlled and randomized respiratory rates from a diverse subject pool, establishes a solid basis for the algorithm's training and validation, ensuring extensive adaptability and precision. Empirical results show that XGBoost surpasses other machine learning models' accuracy and reliability. Importantly, this method significantly reduces error margins compared to established benchmarks, leading to substantial improvements in RR measurement. The implications of this study are wide-ranging, indicating that such a system could significantly enhance patient care standards by providing continuous, accurate, and non-intrusive monitoring, especially in settings where traditional methods are impractical or uncomfortable. Future research should aim to refine the system's real-world applicability, assess long-term reliability, and optimize the technology for integration into existing healthcare frameworks, thereby further transforming the landscape of patient monitoring technologies.
Pembelajaran interaktif melalui game edukatif selama masa pandemi di TK AL Ghifari Bandung Suryani, Vera; Erfianto, Bayu; Rakhmatsyah, Andrian; Yulianto, Fazmah Arif
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 5, No 1 (2022): Januari
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v5i1.979

Abstract

Kurikulum sekolah TK meliputi aspek motorik,maupun kognitif bagi anak usia pra-sekolah. Pembelajaran daring selama pandemi membuat anak cepat bosan, karena masa konsentrasi mereka belum bisa lama seperti halnya orang dewasa. Dibutuhkan perangkat bantu agar penyampaian materi lebih menarik dan tidak membosankan. Permainan merupakan salah satu cara penyampaian materi agar anak TK dapat belajar secara menyenangkan. Game edukatif merupakan perangkat bantu yang bersifat menarik bagi anak TK, dan melalui game ini materi pembelajaran dapat disampaikan secara menarik. Tujuan kegiatan pengabdian masyarakat ini ialah melakukan penyuluhan kepada guru PAUD TK Al-Ghifari Sukabirus mengenai cara penyampaian materi pembelajaran melalui game edukatif, serta pelatihan kepada anak TK mengenai cara penggunaan game edukatif tersebut. Game edukatif bertujuan untuk meningkatkan motivasi belajar melalui story telling, peningkatan konsentrasi, serta aspek computational thinking untuk usia pra-sekolah. Dari hasil pelaksanaan kegiatan pengabdian masyarakat di TK Al Ghifari Bandung di dapatkan bahwa perangkat dan modul pembelajaran yang diberikan sangat membantu proses belajar mengajar di TK Al Ghifari. Poin utama yang disasar adalah aspek motivasi dan konsentrasi anak usia TK.
Application of ARIMA Kalman Filter with Multi-Sensor Data Fusion Fuzzy Logic to Improve Indoor Air Quality Index Estimation Erfianto, Bayu; Rahmatsyah, Andrian
JOIV : International Journal on Informatics Visualization Vol 6, No 4 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.4.889

Abstract

Air quality monitoring is a process that determines the number of pollutants in the air, one of which is indoor air quality. The Fuzzy Indoor Air Quality Index was developed in this research. It is a method for determining the indoor air quality index using sensor fusion and fuzzy logic. By combining several different time series determinants of air quality, a fuzzy logic-based sensor fusion method is used to build a knowledge base about indoor air quality levels. Without the use of complicated calculation models, fuzzy logic-based fusion will make it easier to determine indoor air quality levels based on various sensor parameters. The input for fuzzy-based data fusion is obtained from the ARIMA method with Kalman Filter's air quality parameter values estimation. The application of ARIMA with a Kalman Filter was used to improve the accuracy of indoor air quality estimation in this study. ARIMA(3,1,3) had a MAPE of 0.1 percent on the CO2 dataset, and ARIMA(1,0,1) had a MAPE of 0.63 percent on the TVOC dataset based on approximately three experimental days. ARIMA (3,1,3) estimation with a Kalman Filter results in a MAPE of 0.03 percent for the CO2 dataset and a MAPE of 0.24 percent for ARIMA(1,0,1) Kalman Filter estimation on TVOC dataset. As a result, the Fuzzy Indoor Air Quality Index (FIAQI) developed in this research reasonably estimates indoor air quality. This can be seen by examining the percentage of estimation errors obtained from the experiment.
Klasifikasi Analisis Gerakan Squat untuk Pemula dan Profesional Menggunakan Metode SVM Berbasis Mediapipe Putra, Bima Andika; Purnama, Bedy; Erfianto, Bayu
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 12 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i12.4871

Abstract

Gerakan squat dianggap sebagai latihan yang sangat penting dalam kebugaran dan rehabilitasi, membutuhkan koordinasi serta postur tubuh yang benar. Pelaksanaan yang keliru, terutama oleh mereka yang baru mulai, dapat meningkatkan kemungkinan terjadinya cedera. Untuk mengatasi masalah ini, ada kebutuhan akan sistem otomatis yang dapat mengklasifikasikan keterampilan pengguna berdasarkan pose tubuh saat melakukan squat. Penelitian ini menggunakan teknologi visi komputer untuk mendeteksi dan menilai kualitas gerakan. Salah satu masalah utama dalam sistem evaluasi squat yang ada adalah kemampuannya yang terbatas dalam menilai tingkat keterampilan; banyak di antaranya hanya memberikan umpan balik dalam bentuk benar atau salah. Maka, sangat penting untuk mengembangkan sistem klasifikasi yang dapat membedakan antara pemula dan atlet berpengalaman, terutama dalam mendukung program latihan yang lebih adaptif dan memberikan informasi. Salah satu solusi yang diusulkan adalah mengintegrasikan MediaPipe sebagai alat untuk ekstraksi pose dan menggunakan algoritma Support Vector Machine (SVM) sebagai metode klasifikasi. Data video dari 40 pengguna diubah menjadi koordinat pose, yang kemudian digunakan untuk melatih model SVM dengan kernel RBF. Hasil dari pengujian menunjukkan tingkat akurasi yang baik, sebesar 99,1%, yang menunjukkan seberapa efektif sistem ini dalam secara otomatis dan akurat mengidentifikasi tingkat keterampilan.
Pose Classification in Archery Sports Based on YoloV8 Using SVM and Random Forest Methods Yuridikta Adha Muslim; Bedy Purnama; Bayu Erfianto
IJoICT (International Journal on Information and Communication Technology) Vol. 11 No. 1 (2025): Vol. 11 No. 1 Jun 2025
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v11i1.8996

Abstract

This research creates a YOLOv8-based pose classification system that can analyze and classify the movements of archery athletes. The system is combined with SVM and RF methods, and utilizes YoloV8 pose detection and machine learning techniques to provide more accurate classification. Video data collection, system design and implementation, and analysis of implementation results are some of the stages passed during system development. The process includes joint feature extraction using YOLOv8 and classification for Recurve and Barebow categories using SVM and RF. The test results show the difference in performance between the two classification methods. For the Recurve category, SVM had 90% accuracy for testing, while RF had 87% accuracy for testing. For the Barebow category, SVM had 76% accuracy for testing, while RF had 75% accuracy for testing. In terms of generalization, the two methods differed, with SVM showing better stability between testing and training performance. The results show that SVM is superior when testing when compared to RF which makes an anomaly with previous studies
Pengembangan Website Desa Wisata Berbasis Partisipasi Masyarakat untuk Penguatan Promosi dan Ekonomi Lokal: Studi Kasus Desa Banjarsari Selviandro, Nungki; Ramadhan, Nur Ghaniaviyanto; Lhaksmana, Kemas Muslim; Erfianto, Bayu
Jurnal Abdimas Kartika Wijayakusuma Vol 7 No 1 (2026): Jurnal Abdimas Kartika Wijayakusuma
Publisher : LPPM Universitas Jenderal Achmad Yani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26874/jakw.v7i1.1283

Abstract

Pengembangan desa wisata berbasis digital menjadi strategi penting dalam memperkuat promosi destinasi dan mendorong penguatan ekonomi lokal. Desa Wisata Banjarsari memiliki potensi wisata alam dan budaya yang beragam, namun pemanfaatan teknologi digital sebagai media promosi masih belum optimal. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mengembangkan website desa wisata berbasis partisipasi masyarakat guna meningkatkan visibilitas destinasi wisata serta mendukung pemberdayaan ekonomi lokal. Metode yang digunakan adalah pendekatan partisipatif melalui Participatory Action Research (PAR) yang dikombinasikan dengan prinsip Community-Based Tourism (CBT) dan pemberdayaan digital. Kegiatan dilaksanakan melalui tahapan pemetaan potensi, perencanaan partisipatif, pelatihan dan pendampingan pengelolaan konten digital, serta monitoring dan evaluasi. Hasil kegiatan menunjukkan bahwa masyarakat, khususnya pengelola BUMDes, pemuda desa, dan pelaku UMKM, mampu terlibat aktif dalam pengelolaan website desa wisata. Website yang dikembangkan berfungsi sebagai pusat informasi wisata dan etalase digital produk lokal. Kegiatan ini berkontribusi terhadap peningkatan kapasitas masyarakat dalam pengelolaan promosi digital serta membuka peluang penguatan ekonomi lokal berbasis pariwisata.
Usability Of “DFU Application” For Diabetic Foot Ulcer Prevention Purnama, Bedy; Lindayani, Linlin; Mutiar, Astri; Erfianto, Bayu; Darmawati, Irma
Jurnal Pendidikan Keperawatan Indonesia Vol 11, No 1 (2025): Volume 11, Nomor 1, Juni 2025
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jpki.v11i1.81809

Abstract

Introduction: The development of smart detection software may help reduce the number of decubitus ulcer infections by enabling early identification and management. Ensuring the usability and effectiveness of such technology is essential before widespread adoption. Objective: This study aimed to explore prospective users’ perceptions of the mobile app for detecting diabetic foot ulcer (DFU) infection, focusing on its usefulness, ease of use, and overall user satisfaction. Methods: The usability of the DFU app was assessed by experienced users. The evaluation included perceived usefulness, ease of use, and overall satisfaction. Standardized tools such as the System Usability Scale (SUS) and a specific app rating scale were used to collect user feedback. Results: The DFU app received usability ratings ranging from 0.50 to 0.88. The lowest rating was for performance quality (Mean = 0.50, SD = 0.12), while the highest was for integrity (Mean = 0.88, SD = 0.07). The overall usability score, as measured by SUS, was considered acceptable (Mean = 78.4, SD = 6.83). Most users reported no significant issues with using the app, except for difficulty understanding the language used in the interface, which was rated as a serious usability issue with a severity score of 3. Conclusions: Users perceived the DFU app as useful and efficient, particularly in detecting the risk of infection. Despite a noted language comprehension issue, the app demonstrated good overall usability and has the potential to support early intervention for decubitus ulcer prevention.
Co-Authors Adhan Mulya Rahmawan Adysti Adrianne Andrian Rahmatsyah Andrian Rakhmatsyah Angga Juliat Saputra Arisandy, - Bedy Purnama Benedictus Augusta Vianney Benedictus Augusta Vianney Cahyani, Niken Dwi Catur Wirawan Wijiutomo Darmawati, Irma Fauzi, Roki Fazmah Arif Y, Fazmah Gita Indah Hapsari Ilhamdaniah Ilhamdaniah Ilhamdaniah, Ilhamdaniah Indrarini Dyah Irawati Intan Muchtadi-Alamsyah Irma Yunita Masturi Juntriesta, Vera Kemas Muslim Lhaksmana Khoiri, Isfa' Bil Lindayani, Linlin Maman Abdurohman Mas'ud Adhi Saputra Monterico Adrian Muhammad Hanif Abdillah Mutiar, Astri Novian Anggis Suwastika Nugraha, Shinta Jitny Ayu Nungki Selviandro Nur Ghaniaviyanto Ramadhan Nusantara, Hadi Dharma Pahlevi , Rizka Reza Parman Sukarno Prihatni, Delita Putra, Bima Andika Rahmatsyah, Andrian Rahmawan, Adhan Mulya Ramzy Rashaun Arif Rendy Munadi Satrio Nurcahya SETIAWAN, ALDRY HERNANDA Setyorini Setyorini, - Shandikri, Rheza Sidik Prabowo Vera Juntriesta Vera Suryani Wirawan, Ilo Raditio Yuridikta Adha Muslim