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All Journal Elektron Jurnal Ilmiah IPTEK The Journal for Technology and Science Prosiding Semnastek Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) InComTech: Jurnal Telekomunikasi dan Komputer Journal of Information Technology and Computer Engineering Jurnal Hilirisasi IPTEKS (JHI) Buletin Ilmiah Nagari Membangun Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks CHIPSET (Journal on Computer Hardware, Signal Processing, Embedded System and Networking)
Dodon Yendri
Universitas Andalas
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Rancang Bangun Sistem Keamanan Helm dan Berkendara Berbasis Mikrokontroler Demita, Syukurillah Paradiqma; Yendri, Dodon; Suwandi, Rifki
CHIPSET Vol. 5 No. 01 (2024): Journal on Computer Hardware, Signal Processing, Embedded System and Networkin
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/chipset.5.01.20-34.2024

Abstract

As a two-wheeled vehicle user, a problem that often occurs in the community is the loss of helmets when placed in the parking lot. This can happen due to lack of attention from security personnel at the parking location. Riders who do not use helmets can endanger themselves in the event of an accident. In addition to the use of helmets, speed in driving is one factor that needs to be considered because it has the potential to endanger yourself or others. This study aims to anticipate the occurrence of helmet theft and also provide safety in driving using survey research methods to determine the percentage of ease of use by users. Where the system designed consists of 4 functions, namely, detection of helmet location using the MQTT protocol where if the helmet position with the vehicle has a large distance of 40m then the helmet is detected to have been stolen so that it will issue a warning in the form of sound. The second system is vehicle speed detection using anemometer sensors, if the vehicle is detected to have a large speed of 50km / h then the helmet will issue a sound warning so that the driver can reduce driving speed. The third system is face detection around the helmet using ESP32-Cam, where if the helmet detects an unknown face through the face recognition feature with a distance of 15cm to 60cm from the helmet, the ESP32-Cam will take pictures. The last system is taking pictures periodically to find out the situation around the helmet. Based on research using a questionnaire with 30 samplers, a percentage of 74.95% was obtained, which means that the helmet is easy to use.
Co-Authors - Andrizal Adi Arga Arifnur Adnediel, Gery Afdholli Putra Aina Nurul Fitri Amalia Tiffany Andrizal Andrizal Anggraini, Yuni Anisa Irviana Annisa Yolanda Putri Antony Richardo Arrya Anandika Aulia Rossalina Budi Rahmadya Daputri Karmita Dedi Hermanto Demita, Syukurillah Paradiqma Derisma Derisma Derisma Derisma Emyr Riyanda Azra Ferdian, Rian Fitra Marta Yonas Hersyah, Mohammad Hafiz Ibrahim Saputra Indrapriyatna, Ahmad Syafruddin Irviana, Anisa Khairunnisa Khandra Fahmy Kiki Amelia Lathifah Arief, Lathifah Luthfan Maulana M. Hafiz Hersyah M. Ridho Heranof Maulana, Luthfan Muhammad Ridho Heranof Muhammad, Fauzan Nefy Puteri Novani Nefy Puteri Novani Nefy Puteri Novani Purwoko, Agus Putri, Annisa Yolanda Putri, Rani Pratama Rahmi Eka Putri Rahmi Eka Putri, Rahmi Eka Rakan El Fawwaz Ramadhan, Muhamad Noveri Rani Pratama Putri Ratna Aisuwarya Reyana Yunindya Sabilla Rezy Pratiwi Rifki Suwandi Rifki Suwandi Rifki Suwandi, Rifki Rizka Hadelina Shalsabilla Syaqila Tati Erlina Tati Erlina Werman Kasoep Werman Kasoep Werman Kasoep Wildian Wildian Yelchi Multri Meisya Yolanda, Desta Yoni, Muhammad Dzaky Yuni Anggraini