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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Penelitian Pendidikan IPA (JPPIPA) Jurnal Ekobistek JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknologi Informasi dan Pendidikan Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Journal of Electrical Engineering and Computer Science Jurnal UNITEK Journal of Computer Scine and Information Technology Jurnal Ipteks Terapan : research of applied science and education Jurnal Sains Informatika Terapan (JSIT) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Teknologi Jurnal Quancom: Jurnal Quantum Komputer Jurnal Teknik dan teknologi tepat guna The Indonesian Journal of Computer Science Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Ilmu Komputer dan Informatika Culture education and technology research
Retno Devita
Universitas Putra Indonesia YPTK Padang
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CANNY EDGE DETECTION AND IMAGE SEGMENTATION FOR PRECISION FACE RECOGNITION SYSTEM Retno Devita; Sumijan Sumijan
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 2 (2024): Maret 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.3059

Abstract

Abstract: Facial recognition is widely used in areas such as video surveillance and database management. Facial images have been used as a preferred biometric feature in many identity recognition systems to obtain good image results in image segmentation. A good image must pay attention to several factors, namely high resolution, good contrast, image sharpness, consistent colors, lack of noise and appropriate lighting conditions. In this face recognition research, using canny edge detection method for 10 original images paired with 10 other images. The original faces taken are male and female. Canny edge detection has a low error rate in image segmentation compared to other edge detections. The purpose of this study is to determine the edge of the image in I-rat and can display the results of a good segmentation of facial images. The results of the test data with data stored in the database in the study is 1 face image produces 67.69% accuracy and 26.92% and 8 other face images produce 100% accuracy. The average success rate of 10 experiments using image segmentation is 89.461%. In conclusion, the canny edge detection method can provide accurate results in the face recognition process.            Keywords: accuracy; canny edge detection; face recognition; image; segmentation  Abstrak : Pengenalan wajah banyak digunakan dalam diberbagai bidang seperti pengawasan video dan manajemen basis data. Gambar wajah telah digunakan sebagai ciri biometrik yang disukai di banyak sistem pengenalan identitas untuk mendapatkan hasil citra yang bagus dalam segmentasi citra. Citra yang baik harus memperhatikan beberapa faktor yaitu resolusi tinggi, kontras yang baik, ketajaman citra, warna yang konsisten, kurangnya noise dan kondisi pencahayaan yang sesuai. Pada penelitian pengenalan wajah ini, menggunakan metode deteksi tepi canny untuk 10 citra asli yang dipasangkan dengan 10 citra lainnya. Wajah asli yang diambil berjenis kelamin laki-laki dan perempuan. Deteksi tepi canny memiliki tingkat kesalahan rendah dalam segmentasi citra dibandingkan dengan deteksi tepi lainnya. Tujuan dari penelitian ini adalah menentukan tepi gambar secara akurat dan dapat menampilkan hasil segmentasi citra wajah yang baik. Hasil dari data uji dengan data yang tersimpan di database dalam penelitian adalah 1 citra wajah menghasilkan akurasi 67,69% dan 26,92% dan 8 citra wajah lainnya menghasilkan akurasi 100%. Rata-rata tingkat keberhasilan dari 10 kali percobaan dengan menggunakan segmentasi citra adalah 89,461%. Kesimpulan, metode deteksi tepi canny dapat memberikan hasil yang akurat dalam proses pengenalan wajah. Kata Kunci : akurasi; deteksi tepi canny; citra; pengenalan wajah; segmentasi
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%.
PERANCANGAN PROTOTIPE KEAMANAN PINTU RUMAH MENGGUNAKAN KAMERA TTL DAN APLIKASI TELEGRAM BERBASIS ARDUINO Retno Devita; Nanda Tommy Wirawan; David Agustri Syafni
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 2 No. 2 (2022): Juli : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (834.251 KB) | DOI: 10.55606/juisik.v2i2.199

Abstract

Penelitian ini bermaksud untuk merancang dan membangun sebuah sIstem keamanan pintu rumah sehingga menjadikan pintu rumah lebih aman, nyaman, efisien, serta menghindari dari bentuk kejahatan yang sering terjadi. Sistem ini dibuat dengan merancang, membuat dan mengimplementasikan komponen-komponen sistem yang meliputi Arduino Mega 2560 sebagai pengendali proses, RFID dan Button sebagai media kontrol pada pintu, Kamera TTL dan Sensor PIR sebagai media pemantau adanya tamu, Sensor Ultrasonic sebagai pendeteksi apabila ada halangan ketika pintu terbuka, Reed Switch berperan sebagai pendeteksi apabila pintu dibuka secara paksa, dan aplikasi telegram sebagai media pemantauan sekaligus kontrol pada pintu rumah serta penggunaan Motor Servo sebagai pengunci dan penggerak pintu. Hasil penelitian menunjukkan alat yang dibuat dapat berfungsi dengan baik dan dapat dikembangkan untuk skala yang lebih besar.
Optimalisasi Pemanfaatan Android pada Sistem Peringatan dan Monitoring Keamanan Perlintasan Kereta Api Masril, Mardhiah; Retno Devita; Hasri Awal; Lusi Andriani
JURNAL QUANCOM: QUANTUM COMPUTER JURNAL Vol. 2 No. 1 (2024): Juni 2024
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jqc.v2i1.324

Abstract

Railroad crossing security on highways is an important issue for road user safety. The current security system still has limitations, such as a lack of timely response and negligence of crossing guards, resulting in a high number of accidents at railroad crossings, which often claim lives. The high rate of accidents that occur today causes safety to be one of the most important things. Therefore, it is necessary to apply sophisticated technology to minimize the risk of accidents. The utilization of computer technology in the railway crossing security system can be an optimal solution. The system will work by using sensors that are able to detect the arrival of trains and send information about the state of the crossing to the crossing guards in real time. Thus, the crossing guards can take appropriate and quick action if there is a malfunction in the system. By integrating advanced technology, it is hoped that accidents at railway crossings can be minimized and the safety of road users can be guaranteed.
Development and modification Sobel edge detection in tuberculosis X-ray images Devita, Retno; Fitri, Iskandar; Yuhandri, Yuhandri; Yani, Finny Fitry
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp1191-1200

Abstract

Tuberculosis (TB), a major global health threat caused by mycobacterium tuberculosis, claims lives across all age groups, underscoring the urgent need for accurate diagnostic methods. Traditional TB diagnosis using X-ray images faces challenges in detection accuracy, highlighting a critical problem in medical imaging. Addressing this, our study investigates the use of image processing techniques-specifically, a dataset of 112 TB X-ray images-employing pre-processing, segmentation, edge detection, and feature extraction methods. Central to our method is the adoption of a modified Sobel edge detection technique, named modification and extended magnitude gradient (MEMG), designed to enhance TB identification from X-ray images. The effectiveness of MEMG is rigorously evaluated against the gray-level co-occurrence matrix (GLCM) parameters, contrast, and correlation, where it demonstrably surpasses the standard Sobel detection, amplifying the contrast value by over 50% and achieving a correlation value nearing 1. Consequently, the MEMG method significantly improves the clarity and detail of TB-related anomalies in X-ray images, facilitating more precise TB detection. This study concludes that leveraging the MEMG technique in TB diagnosis presents a substantial advancement over conventional methods, promising a more reliable tool for combating this global health menace.
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.
Desain Smart Delivery Box : Sterilisasi Otomatis dan Notifikasi Real-Time Berbasis Arduino Mega 2560 Retno Devita; Nanda Tommy Wirawan; Altof Fito
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 1 (2025): Februari: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i1.731

Abstract

The increase in online buying and selling due to government appeals during the Covid-19 pandemic has created a new habit in society, which also serves to reduce physical contact and prevent the spread of the virus. However, with the increase in delivery of goods, challenges arise in maintaining the cleanliness and safety of received packages. To address this, a smart package receiving system was developed that features automatic sterilization using ultraviolet (UV) lights and disinfectant spraying on incoming packages. This system aims to prevent the transmission of viruses that may be attached to the package. In addition, the system helps monitor and secure packages, especially when the owner is not at home. The system uses a microcontroller as the control center, equipped with an ESP32-CAM camera to document photos of the sender, as well as an ultrasonic sensor to detect whether the package is in the box or not. The process starts when the courier presses the “there is a package” button, which sends an OTP code to the receiver's Telegram. The courier enters the OTP code, places the package in the box, and closes it. After that, the UV lamp turns on for sterilization, the ESP32-CAM photographs the package, and the ultrasonic sensor detects the package status. If the package is detected, a photo notification of the sender is sent to Telegram, informing the recipient that the package is ready for pickup.
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.
Improved feature extraction method and K-means clustering for soil fertility identification based on soil image Ramadhanu, Agung; Hendri, Halifia; Enggari, Sofika; Andini, Silfia; Devita, Retno; Rianti, Eva
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp2001-2011

Abstract

This research is conducting analysis of digital land images using digital image processing techniques. The main purpose of the research is to classify soil fertility based on two-dimensional RGB colored digital soil images. The research is done by extracting features and shapes from the soil image. The research uses methods of segmentation, extraction, and identification against digital soil images. This research is carried out in three stages. The first phase of this research is image pre-processing which begins with the conversion of RGB color image to Grayscale then color conversion to binary which subsequently performs noise reduction with the method Three-layer median filter. The second stage is a process that is divided into the first two stages, namely the process of segmentation by grouping RGB color images into L*a*b which is continued by clustering using the K-means clustering method. The second is the extraction of characteristics of the soil image which is characteristic of shape and texture. The final stage is the identification of soil images that are clustered into two types: fertile soils and unfertile soil. The study achieved an accuracy of 85% which could accurately identify 20 images while inaccurately classifying 5 images out of a total of 25 input images.
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.
Co-Authors Adif Violenta Arpa Akbar Lusman Alifa Carradya Altof Fito Aulia Fitrul Hadi David Agustri Syafni Defnizal . Deval Gusrion Ega Firsty Ayu Pratiwi Enggari, Sofika Eva Rianti Fajar Alvin Tariq Fajrul Islami Finny Fitry Yani Gustina Putri Hadi Syahputra Halifia Hendri Haniva Budiana Deswary Hasri Awal Ibnu Michael Jasman Ilham Saputra Ipriadi - Ipriadi Ipriadi, Ipriadi Iskandar Fitri, Iskandar J, Shafa Adillah Jeffrey Christian Effendi Julius Santony Lusi Andriani Mardhiah Masril Mardiah Masril Naf’an, Emil Nanda Tommy Wirawan Nurhadi, Nurhadi Nurul Afifah Okta Andrica Putra Ondara Eka Putra Ondra Eka Putra Ondra Eka Putra Ramadhan Kamil Ramadhanu, Agung - Ratna Gusrianti Rionaldo Willian Putra Ruri Hartika Ruri Hartika Zain Ruri Hartika Zain Sarjon Defit Silfia Andini Silky Safira Sovia, Rini Sri Rahmawati Sumijan Sumijan Sumijan Sumijan Tika Syafriani Wahyudi, Niko Wirawan, Nanda Tommy Yogi Wiyandra Yogi Wiyandra Yuhandri Yuhandri, Yuhandri