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All Journal JIKO (Jurnal Informatika dan Komputer) Jiko (Jurnal Informatika dan komputer) JURNAL PengaMAS Jurnal Abdimas Mandiri Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Ilmiah Ilmu dan Teknologi Rekayasa Jurnal Pengabdian UNDIKMA Green Intelligent Systems and Applications Journal of Computer Engineering, Electronics and Information Technology ITIJ
Munawir Munawir
(Scopus ID 57208758022), Data Mining, Text Mining, Universitas Pendidikan Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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DESIGN OF MICROSLEEP DETECTION SYSTEM IN 32-BIT MICROCONTROLLER-BASED MOTORISTS WITH RANDOM FOREST METHOD Maqdis, Syiva Awaliyah; Adiwilaga, Anugrah; Munawir, Munawir
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 2 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8539

Abstract

The number of motorcycle accidents has increased rapidly every year. Many occur due to drowsiness or fatigue because motorists force themselves to keep driving. The state of fatigue while driving is also known as microsleep. To overcome this problem, we propose a design of a prototype system that can be installed on the helmet of a motorized user so that the driver is more alert when driving a vehicle. This system utilizes machine learning technology with the Random Forest algorithm with two prediction results: prediction 1, which means the motorcyclist is tired, or prediction 0, which means the motorcyclist is in a normal state, embedded in the ESP32 microcontroller, and a tilt sensor that can detect signs of drowsiness in motorists. This system design will use the MPU6050 sensor to measure changes in the angle of the motorcyclist's head. The microcontroller will process the data obtained to identify head changes that indicate the possibility of drowsiness. If it occurs, the buzzer will beep as a warning to warn the driver to take a short break. The test results in drowsiness conditions with an angle of 10°–30° resulted in 100% accuracy, and normal conditions only at an angle of 0°–6° resulted in 100% accuracy. The result of the developed system is expected to reduce the number of accidents caused by drowsiness
Spam and Phishing Whatsapp Message Filtering Application Using TF - IDF and Machine Learning Methods Manurung, Ferdinand Aprillian; Munawir; Pradeka, Deden
Green Intelligent Systems and Applications Volume 5 - Issue 1 - 2025
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v5i1.551

Abstract

The rapid development of communication technology has led to an increase in the number of unwanted messages, such as spam and phishing attempts. However, this progress has not been accompanied by sufficient user awareness of the basics of technology use. Additionally, the enforcement of laws regarding internet-based crimes remains unclear, further increasing the risk for users of internet technology to fall victim to such crimes. As one of the media prone to spam and phishing, WhatsApp is the focus of this research, which aims to develop an application capable of filtering spam and phishing messages. The application employs the TF-IDF (Term Frequency-Inverse Document Frequency) method and machine learning using the Random Forest model. It is developed using the MVVM (Model-View-ViewModel) architecture, enabling the separation of business logic from the user interface, thereby improving development and maintenance efficiency. The research findings demonstrate that the combination of TF-IDF and Random Forest achieves high accuracy in classifying spam and phishing messages. Performance evaluation using a confusion matrix reveals an accuracy rate of 92%. For the safe message class, the precision, recall, and F1 scores are 89%, 95%, and 92%, respectively, while for the dangerous message class, the scores are 95%, 88%, and 92%, respectively. Furthermore, the integration of the model and application performed exceptionally well, as evidenced by black-box testing results. All test scenarios were met, successfully detecting test messages with 98% accuracy. Therefore, the developed application provides enhanced protection for WhatsApp users against digital threats.
Pelatihan Robotika Sebagai Upaya Meningkatkan Kompetensi Keahlian Siswa SMK Daarut Tauhiid Bandung Muhammad Taufik Dwi Putra; Deden Pradeka; Anugrah Adiwilaga; Munawir Munawir; Dhimaz Purnama Adjhi
Jurnal Pengabdian UNDIKMA Vol. 4 No. 1 (2023): February
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v4i1.6516

Abstract

The rapid scientific development of robotics technology must be in line with efforts to increase the creativity and skills of human resources. Responding to these challenges, it is necessary to implement a robotics technology-based learning curriculum as early as possible starting from the school. However, there are some problems such as curriculum with robotics technology which is still rarely found in Indonesian schools. The purpose of this service is to improve the skills of students of SMK Daarut Tauhid through Robotics training. This method of devotion uses the method of lectures, hands-on practice, and interactive discussions. The number of participants in this training was 20 (twenty) students with activity evaluation instruments using g-form surveys and was analyzed descriptively. The results of this service show that student participants tend to better understand the scientific concepts of robotics technology when faced with real hardware compared to simulations using software. With this training, it’s hoped that knowledge and skills in robotics technology and science among students will increase.
Co-Authors Abdullah Muadz Nadzir Anzhar Adi Nugroho, Afrizal Adiwilaga, Anugrah Ahmad Ali Alhafidz Alanshori, Fatih Nurrobi Alfarisi, Farhan Siddiq Ana Rahma Yuniarti Azizi, Muhammad Bilal Mardhiyyano Azzahra, Salsabila Nida Deden Pradeka Devi Aprianti Rimadhani Agustini Devi Rimadhani Agustini Dhimaz Purnama Adjhi Jezzy Putra Munggaran Jorgha Akram Aryadi Khoir, Farhan Ramadhan Manurung, Ferdinand Aprillian Maqdis, Syiva Awaliyah Martadisastra, Muhamad Rafi Pasya Maulana Taqy Mochamad Fabian, Reyhan Mochamad Iqbal Ardimansyah Mustofa, Rangga Ali Nurwahid, Prihatma Pararta, Muhammad Salam Perdana, Abdi Surya Pradja, Kimberly Alfa Di Priswati, Hasna Putri Putra, Muhammad Taufik Dwi Putri, Ghina Mawarni Raditya Muhammad Rahmawati Rahmawati Salsa Billa, Aidha Solihah, Zulfa Maylafaiza Hadiatus Subandri, Anatasia Aulienda Wirmanto Suteddy Yahya Aliman Aidil Basith Zuhairmawan, Muhammad Tiar