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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Transmisi: Jurnal Ilmiah Teknik Elektro Jurnal Teknik ITS Jurnal Sains dan Seni ITS Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Communications in Science and Technology SISFO Journal of Advanced in Information and Industrial Technology (JAIIT) Sewagati
Faizal Mahananto
Departemen Sistem Informasi Institut Teknologi Sepuluh Nopember Surabaya
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

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Studi Literatur Human Activity Recognition (HAR) Menggunakan Sensor Inersia Humaira Nur Pradani; Faizal Mahananto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (710.727 KB) | DOI: 10.29207/resti.v5i6.3665

Abstract

Human activity recognition (HAR) is one of the topics that is being widely researched because of its diverse implementation in various fields such as health, construction, and UI / UX. As MEMS (Micro Electro Mechanical Systems) evolves, HAR data acquisition can be done more easily and efficiently using inertial sensors. Inertial sensor data processing for HAR requires a series of processes and a variety of techniques. This literature study aims to summarize the various approaches that have been used in existing research in building the HAR model. Published articles are collected from ScienceDirect, IEEE Xplore, and MDPI over the past five years (2017-2021). From the 38 studies identified, information extracted are the overview of the areas of HAR implementation, data acquisition, public datasets, pre-process methods, feature extraction approaches, feature selection methods, classification models, training scenarios, model performance, and research challenges in this topic. The analysis showed that there is still room to improve the performance of the HAR model. Therefore, future research on the topic of HAR using inertial sensors can focus on extracting and selecting more optimal features, considering the robustness level of the model, increasing the complexity of classified activities, and balancing accuracy with computation time.
Co-Authors Ahmad Muklason Algracevian Andrea Gibran Syahrial Alvin Sahroni Amalia Utamima Amalinda Jayanty Andhika Prasandy Rachman Arif Djunaidi Arif Djunaidy Arif Wibisono Dio Afriansyah Putra Pradana Erma Suryani Hanif Mitsal Mahatta Hardhika Propitadewa Hendra Setiawan Humaira Nur Pradani Ika Nurkasanah Jeremy Diaz Prasetyo Jessica Patricia Halim Jihaan Harvi Habibah Kartika Zahretta Wijaya Laura Wilhelmina Theresia M. Fiqri Ananda M. Yusuf Sulaiman Mochamad Zidan Aqila Kamil Muhammad Ali Fikri Muhammad Arif Nuriman Muhammad Daffa Maulana Muhammad David Rahman Muhammad Hisyam Muhammad Nasrullah Muhammad Reza Pahlawan Nabihah Hanun Atikah Naufal Rafiawan Basara Nazriyah Deni Tsaniyah Nisa Dwi Angresti Nur Khofifah Nur Laila Nur Nindya Risnina Raffly Andico Devara Rahma Fauzia Raras Tyas Nurita Raras Tyasnurita Retno A. Vinarti Retno Aulia Vinarti Riksakomara, Edwin Rizka Wakhiddatus Sholikah Rully Agus Hendrawan Sayekti Harits Suryawan Septica Tiara Indah Permatasari Tri Achmadi Wiwik Anggraeni Wiwik Anggraeni Wiwik Anggraeni Zakaria, Hasballah