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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Sinkron : Jurnal dan Penelitian Teknik Informatika JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknologi Jurnal Teknologi Informasi dan Pendidikan Sainstek : Jurnal Sains dan Teknologi REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Majalah Ilmiah UPI YPTK Jurnal Ipteks Terapan : research of applied science and education Jurnal Teknologi Jurnal Teknik dan teknologi tepat guna
Putra, Ondra Eka
Universitas Putra Indonesia YPTK Padang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Safe Security System Using Face Recognition Based on IoT Putra, Ondra Eka; Devita, Retno; Wahyudi, Niko
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12231

Abstract

Face recognition is widely used in various applications, especially in the field of surveillance and security systems. This study aims to design and build a safe security system using face recognition via camera based on internet of things. This system uses the Raspberry Pi 3B and the OpenCV library as face recognition data processing which produces output on the Selenoid to open and close the safe, LCD 16x2 to display system status, IoT-based email delivery when smugglers occur. This study performs face recognition through the face detection stage using the Viola Jones method, feature extraction using the PCA (Principal Component Analysis) method and face recognition, then matched with the existing profile data in the directory. The results of this study indicate that the safe is open when a face is detected and will send a face capture to the e-mail address of the owner’s safe if the detected face is not recognized. Tests carried out on the safe security system using face recognition based on IoT build reach validity 90,25%.
Improved adaptive multi-threshold method for automatic identification of rhinosinusitis in paranasal sinus images Putra, Ondra Eka; Sumijan, Sumijan; Tajuddin, Muhammad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i1.pp119-129

Abstract

Rhinosinusitis, characterized by inflammation of the mucosa or mucous membrane within the paranasal sinuses, anatomical cavities situated in the facial bones, is the focus of this investigation. This study employs computed tomography (CT)-scan images comprising sagittal slices of the paranasal sinuses, acquired through a CT device featuring a Philips Ingenuity CT model MRC880 tube type, identified by tube serial number 163889, with a pixel value resolution of 0.24 mm. The primary objective of this research is to automatically identify and delineate rhizosinusitis-affected areas. This involves the application of multi-threshold values during the segmentation process, utilizing the improved adaptive multi-threshold (IAMT) segmentation method. The research dataset encompasses 380 slices of CTscans derived from 10 patients displaying indications of rhinosinusitis. Analysis of the test results reveals that the smallest observed rhinosinusitis size in this study is 0.05 cm2 on the right side, while the largest size measures 1.81 cm2 , yielding an accuracy rate of 96.66%. The magnitude of rhinosinusitis sizes serves as an indicative measure of the extent of inflammation within the paranasal sinus region, thereby suggesting a potential need for more intensive treatment interventions for the affected patients.
PERBANDINGAN KERNEL PENAJAMAN, GAUSSIAN BLUR DAN DETEKSI TEPI PADA CITRA OTAK Devita, Retno; Putra, Ondra Eka; Rianti, Eva
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2271

Abstract

Citra otak merupakan gambar yang didapat dari proses pencitraan otak melalui teknologi medis seperti MRI (Magnetic Resonance Imaging), CT scan (Computed Tomography), atau PET scan (Positron Emission Tomography). Citra ini memberikan visualisasi dari struktur otak secara terperinci dan digunakan untuk mendeteksi atau mendiagnosa kondisi otak. Citra otak yang digunakan pada penelitian ini sebanyak 5 citra otak yang diproses menjadi 30 citra otak. Penelitian ini membandingkan kinerja kernel 7x7 dan 9x9 pada tiga jenis operasi utama dalam pengolahan citra otak yaitu penajaman, gaussian blur, dan deteksi tepi. Kernel penajaman diterapkan untuk memperjelas struktur halus dari citra, gaussian blur digunakan untuk mereduksi noise citra dan deteksi tepi bertujuan mengidentifikasi batas anatomi otak. Perbandingan dilakukan dengan mengevaluasi hasil dari dua ukuran kernel terhadap kualitas visual, tingkat detail, dan keberhasilan dalam mengidentifikasi fitur penting otak. Nilai tertinggi dari 5 citra yang didapat adalah kernel penajaman 7x7 pada citra 5 dengan MSE 4.832.932.323, RMSE 69.519.295 dan PSNR 11.288696 dB dan nilai terendahnya adalah kernel gaussian blur 9x9 pada citra 1 dengan MSE 16.747.259.747, RMSE 129.411.204 dan PSNR 5.891366 dB. Kesimpulannya, hasil terbaik pada penelitian ini adalah kernel 7x7 dilihat dari nilai PSNR.
EXPLANATION OF FEATURE EXTRACTION IN FACE RECOGNITION USING VIOLA JONES ALGORITHM Devita, Retno; Rianti, Eva; Yuhandri, Muhammad Habib; Putra, Ondra Eka
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 11, No 3 (2025): Juni 2025
Publisher : Universitas Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3844

Abstract

Face recognition has become a common thing used in the field of surveillance and security in computer technology and image devices. This study aims to identify the usefulness of a person's face on 3 test images. This study examines the methods of cropping techniques, image enhancement through intensity measurement, and histogram analysis to improve the contrast and distribution of image intensity. In addition, the Viola-Jones algorithm is used to detect key facial features such as eyes, nose, and mouth. The results of the analysis are then applied in the feature evaluation stage, where usually between facial features are applied to measure the ratio of facial proportions. Furthermore, the comparison of proportional ratios of several images was analyzed using bar graphs and line graphs to evaluate the trend and stability of facial proportions. The results showed the best ratio stability with a smaller variation of the on-off ratio of image 2 which is 0.4762 pixels to 0.4983 pixels. Image 2 is the most ideal for face measurement systems based on geometric ratios because it provides more consistent and visible results.
Penilaian Tingkat Kepuasan Masyarakat Terhadap Pelayanan Pada Kantor Wali Nagari Bunga Pasang Salido Menggunakan Algoritma K-Means Hidayatullah, Genta Magribi; Putra, Ondra Eka; Rahmi, Nadya Alinda Rahmi; Akhiyar, Dinul
Jurnal Teknik dan Teknologi Tepat Guna Vol. 4 No. 1 (2025): Jurnal Teknik dan Teknologi Tepat Guna
Publisher : Riset Sinergi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Assessing public satisfaction is crucial for evaluating the quality of services provided by government agencies. The purpose of this study was to analyze public satisfaction with the services provided by the Bunga Pasang Salido Village Head Office. This study used the K-Means algorithm, a clustering technique commonly used in data analysis, to categorize respondents' satisfaction levels. This algorithm effectively categorizes respondents into categories such as dissatisfied, satisfied, and very satisfied based on their responses in a satisfaction survey. The dataset used in this study was derived from questionnaires completed by 61 respondents who interacted with the population administration service. The questionnaire data covered various aspects of service quality, including service process efficiency, officer attitudes, and overall user experience. The results of the clustering analysis showed that 27.87% of respondents were dissatisfied, 42.62% were satisfied, and 29.51% were very satisfied with the services provided. This classification provides valuable insights into areas for improvement and helps the Bunga Pasang Salido Village Head Office improve service quality. This study highlights the importance of using data-driven methods, such as the K-Means algorithm, in improving public sector performance and overall service quality.
Rancang Bangun Media Pembelajaran Pengenalan Hewan Dalam Bahasa Inggris Pada Siswa Sekolah Dasar Berbasis Mikrokontroler J, Shafa Adillah; Retno Devita, Retno Devita; Putra, Ondra Eka; Rianti, Eva
Jurnal Teknik dan Teknologi Tepat Guna Vol. 4 No. 1 (2025): Jurnal Teknik dan Teknologi Tepat Guna
Publisher : Riset Sinergi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of digital technology is driving innovation in education, particularly in creating interactive and engaging learning media for elementary school students. This research aims to design and build a microcontroller-based English learning media for first-grade elementary school students. This system integrates an Arduino Mega 2560 as the main controller, connected to various components such as touch sensors, RFID, push buttons, LEDs, LCDs, and a DFPlayer module to support interaction and learning. This system offers two main features: visual and audio animal name recognition, and an interactive quiz mode that tests students' understanding by providing multiple-choice questions based on the story. When students touch an animal image, the system displays the animal's name in English and Indonesian, along with pronunciation sounds and descriptions. The quiz can be accessed using an RFID card, and students answer using the touch sensor. Feedback is displayed via LEDs and audio from the speaker. Test results indicate that the system operates well and is responsive, and is able to increase students' interest in English lessons. This research is expected to provide an alternative solution for enriching foreign language learning methods at the elementary level with a simple yet effective technological approach.
EXPLANATION OF FEATURE EXTRACTION IN FACE RECOGNITION USING VIOLA JONES ALGORITHM Devita, Retno; Rianti, Eva; Yuhandri, Muhammad Habib; Putra, Ondra Eka
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 3 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3844

Abstract

Face recognition has become a common thing used in the field of surveillance and security in computer technology and image devices. This study aims to identify the usefulness of a person's face on 3 test images. This study examines the methods of cropping techniques, image enhancement through intensity measurement, and histogram analysis to improve the contrast and distribution of image intensity. In addition, the Viola-Jones algorithm is used to detect key facial features such as eyes, nose, and mouth. The results of the analysis are then applied in the feature evaluation stage, where usually between facial features are applied to measure the ratio of facial proportions. Furthermore, the comparison of proportional ratios of several images was analyzed using bar graphs and line graphs to evaluate the trend and stability of facial proportions. The results showed the best ratio stability with a smaller variation of the on-off ratio of image 2 which is 0.4762 pixels to 0.4983 pixels. Image 2 is the most ideal for face measurement systems based on geometric ratios because it provides more consistent and visible results.
Co-Authors Afira, Riandana Andro Nugraha Awal, Hasri Devita, Retno Devita, Retno Dinul Akhiyar Febrianti, Eka Lia Hidayatullah, Genta Magribi Ipriadi Ipriadi - J, Shafa Adillah Purnama, Pradani Ayu Widya Rahmi, Nadya Alinda Rahmi Retno Devita, Retno Devita Rianti, Eva Ruri Hartika Zain Sepsa Nur Rahman Sri Rahmawati Sumijan Sumijan Tajuddin, Muhammad Teri Ade Putra Wahyudi, Niko Yuhandri, Muhammad Habib