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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

Bagaimana IoT Dapat diManfaatkan untuk Melatih Keterampilan Motorik Kasar Melalui Permainan Hopscotch? Irvan Naufali Rahmanto; Novian Anggis Suwastika; Rahmat Yasirandi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (504.581 KB) | DOI: 10.29207/resti.v4i3.1962

Abstract

Motor development is the result of changes caused by physical growth, muscle strengthening, and the ability to interact with the environment. There are two types of motor development, namely gross motor and fine motor. The best age for a child for motor development is 0 to 8 years. At the age of 4 to 6 years mostly of children's gross motor activities related to balance and coordination. Child’s development of gross motor can be achieved by stimulating using games. Hopscotch is type of game that implements balance and coordination skills that support the development of gross motor skills. In Indonesia, children aged 4 years to 6 years have started to enter the Early Childhood Education and Kindergarten level. When the child is at school, parents cannot provide motor stimulation and must wait for the child's motor development reports submitted by the teachers. In this study we implemented system to stimulate the development of gross motor balance and coordination in children aged 4 to 6 years using hopscotch game integrated with Internet of Things (IoT) technology. IoT provides the ability to read, record, and evaluate children's activities and publish their results online for parents to access. This system is evaluated based on the system's functionality and performance parameters. From the test results found that the functionality of the system runs 100% by the specified function. The system performance test results from the sensor readings are under 1 second and the accuracy of the assessment activity of the first test variation of the foot position in the middle of 68.75%, and the foot position at the edge of 81.25% with the program delay setting from the node to the IoT platform an average of 1 second.
Footstep Recognition Using Mel Frequency Cepstral Coefficients and Artificial Neural Network Thasya Nurul Wulandari Siagian; Hilal Hudan Nuha; Rahmat Yasirandi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (326.877 KB) | DOI: 10.29207/resti.v4i3.1964

Abstract

Footstep recognition is relatively new biometrics and based on the learning of footsteps signals captured from people walking on the sensing area. The footstep signals classification process for security systems still has a low level of accuracy. Therefore, we need a classification system that has a high accuracy for security systems. Most systems are generally developed using geometric and holistic features but still provide high error rates. In this research, a new system is proposed by using the Mel Frequency Cepstral Coefficients (MFCCs) feature extraction, because it has a good linear frequency as a copycat of the human hearing system and Artificial Neural Network (ANN) as a classification algorithm because it has a good level of accuracy with a dataset of 500 recording footsteps. The classification results show that the proposed system can achieve the highest accuracy of validation loss value 57.3, Accuracy testing 92.0%, loss value 193.8, and accuracy training 100%, the accuracy results are an evaluation of the system in improving the foot signal recognition system for security systems in the smart home environment.
Klasifikasi Data Aktivitas Setelah Joging Menggunakan Fuzzy Logic M. Deta Gian Faiz; Andrian Rakhmatsyah; Rahmat Yasirandi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (436.4 KB) | DOI: 10.29207/resti.v5i3.2938

Abstract

One of the routine activities that cause a lot of body fluids is jogging. Research shows that excessive jogging can disrupt the balance of body fluids so that you tire quickly in the long run. As a result, the body releases too much fluid. This makes someone forget or underestimate the need for fluids in the body. In this study, a detection system for body temperature, ambient temperature and heart rate was built for the classification of dehydration in the body to maintain fluid stability in the body. The system is built using the Pulse Sensor, Mlx90614, OpenWeatherAPI and the Android Platform. This study uses the Mamdani Fuzzy Logic method to determine the classification of user dehydration. The results of the research analysis contained a calibration test of the MLX90614 sensor against the Thermogun with an Error Rate value of 2.01% and an RMSE value of 0.9. Testing the Pulse Sensor against the Oximeter produces an Error Rate value of 1.54% and an RMSE value of 0.7. There is a difference in the difference in Deffuzification values ​​due to differences in the fixed points for each library. Matlab fixed point with a value behind the three digit point, 16 digit Fuzzy Sci-kit and the Builded System using a 15 digit point value.
Co-Authors Aji Gautama Putrada Alifudin, Ridhwan Andrian Rakhmatsyah Annisa Gustien Widowati Annisa Marwa Nursantoso Anom, Rahmat Indira Pratama Anwar, Muhlis Arif Indra Irawan Ariq Musyaffa Ramadhani Armadyana, Raihan Arrauf, Moh Fawwaz Arya Mandalika, Mohamad AS, Andi Annisa Shalsa Hardiyanti Azizah, Ainun Cintya Risquna Risquna Danu Fawwaz Gimnastian Devani Adi Permana Dhiaulhaq, Afif Dita Oktaria Doan Perdana Dwi Olyvia, Asyfa Emiya Fefayosa Br Tarigan Endro Ariyanto Erlandya, Moch Rizky Gumelar Erwin Susanto Febrianti, Amalia Rizki Guntur Utomo, Rio Hamzah Misbachul Adlan Hilal Hudan Nuha Irvan Naufali Rahmanto Isa Mulia Insan Jati Hiliamsyah Husen Jati, Riyan Kuncoro Joel Andrew M. K. Ginting Kailla, Kimberly Krisna Ardhi Tama Ladkoom, Kobthong M Alvie Helmuzar M. Deta Gian Faiz Maman Abdurohman Maslin Masrom Maulidatul Aulia Zahib Mirza Qusyairi, Mohammad Mohammad Mirza Qusyairi Muhammad Aditya Tisnadinata Muhammad Al Makky Muhammad Faris Ruriawan Muhammad Johan Alibasa Muhammad Karoma Yuda Muhammad Kukuh Alif Lyano Muhammad Rizki Adiwiganda Nafisa, Falea Amira Nasruddin, Itsna Siha Arzaqi Adma Novian Anggis Suwastika Nuha, Hilal H Parman Sukarno Prabowo, Hans Pratama Anom, Rahmat Indra Putra, Revi Raka Qonita, Qori Qusyairi, Mohammad Mirza Qusyairi, Muhammad Mirza Rahmat Irianto Ramadhan, Arga Ridha Muldina Negara Ridhwan Alifudin Rio Guntur Utomo Santiago Paul Erazo Andrade Saputra, Bernadus Ricardo Seiba Shonia Setiawan, Muhammad Faridz Sidik Prabowo Sri Rezeki Stelamaris, Bonefasia Salvatore Sukmaji, Muhammad Susanto, Fauzi Fadhlurrahman Thanasopon, Bundit Thasya Nurul Wulandari Siagian Wajdi, Halim Zahri, Alfitranta Armikha Zaky Jacoeb , Yusoff