Article Per Year (5 Year)
p-Index From 2020 - 2025
1.363
P-Index
This Author published in this journals
All Journal Journal of Applied Information, Communication and Technology (JAICT) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Techno Nusa Mandiri : Journal of Computing and Information Technology JURTEKSI Jurnal Mantik Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Sisfotek Global Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat
Reyhan Achmad Rizal
Universitas Prima Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 9 Documents
Search

 1 
Analysis of Tuberculosis (TB) on X-ray Image Using SURF Feature Extraction and the K-Nearest Neighbor (KNN) Classification Method Reyhan Achmad Rizal; Nurlela Octavia Purba; Lidya Aprilla Siregar; Kristina Sinaga; Nur Azizah
JAICT Vol 5, No 2 (2020)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v5i2.1979

Abstract

With current technological developments, machine learning has become one of the most popular methods, one of the popular machine learning algorithms is k-nearest neighbors (KNN). Machine learning has been widely used in the medical field to analyze medical datasets, in this study the k-nearest neighbors (KNN) machine learning algorithm will be used because of its good level of accuracy in recognition and is included in the supervised learning algorithm group. The results showed the k-nearest neighbors (KNN) method in recognizing x-ray images of tuberculosis (TB) using SURF feature extraction with an average accuracy of 73%.
ANALISIS GRAY LEVEL CO-OCCURRENCE MATRIX (GLCM) DALAM MENGENALI CITRA EKSPRESI WAJAH: ANALISIS GRAY LEVEL CO-OCCURRENCE MATRIX (GLCM) DALAM MENGENALI CITRA EKSPRESI WAJAH Reyhan Achmad Rizal; Suardin Gulo; Octavriana Della C. Sihombing; Ardi Bernandustahi Miduk Napitupulu; Amsal Yusuf Gultom; Taripar Jonibet Siagian
Jurnal Mantik Vol. 3 No. 2 (2019): Augustus: Manajemen, Teknologi Informatiak dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (757.602 KB)

Abstract

Ekspresi wajah merupakan cara pengungkapan atau proses menyatakan maksud tertentu seperti sedih, bahagia, terkejut, takut, marah dan bad mood. Perubahan fitur wajah pada bibir, mata, pipi, membesarkan alis dan mulut terbuka dapat dijadikan variabel dalam menentukan maksud dari ekpresi wajah. Dataset yang digunakan dalam penelitian ini yaitu citra wajah dengan ekspresi : sedih, bahagia, terkejut, takut, marah, netral dan bad mood dengan ukuran 256x256. File citra yang digunakan untuk pelatihan maupun pengujian diambil dari situs http://www.kasrl.org/jaffeimages.zip dengan total keseluruhan sampling 213 citra ekspresi wajah. Klasifikasi ekspresi wajah menggunakan metode gray level co-occurrence matrix (GLCM). Hasil Klasifikasi pada ekspresi wajah netral GLCM mampu mengklasifikasi dengan rata-rata tingkat akurasi 33%, ekspresi marah 48%, ekspresi bahagia 73%, ekspresi bad mood 44%, ekspresi takut 15%, ekspresi sedih 54%, dan ekspresi terkejut 68%.
ANALISIS PERFORMA KRIPTOGRAFI HYBRID ALGORITMA BLOWFISH DAN ALGORITMA RSA Sebastian Suhandinata; Reyhan Achmad Rizal; Dedy Ongky Wijaya; Prabhu Warren; Srinjiwi Srinjiwi
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 6, No 1 (2019): December 2019
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v6i1.395

Abstract

Abstract:Computer data security relies on preventing data theft from irresponsible parties by using cryptography method. Some cryptography algorithms have good and poor performance in encrypting and decrypting data depending on the key types. Therefore the purpose of this research is to measure the performance of the hybrid algorithm, consisting a symmetric keyBlowfish algorithm and an asymmetric key RSA algorithm, in encrypting and decrypting multiple types of data such as documents, photos, audios, and videos. The result is the performance of the hybrid algorithm is almost on par with Blowfish and provides a more secure data encryption and decryption by taking advantage of RSA algorithm. The average encryption performance of hybrid algorithm is 0.85s on document, 1.06s on photo, 3.38s on audio, and 15.56s on video. While the average decryption performance of hybrid algorithm is 1.01s on document, 1.38s on photo, 4.3s on audio, and 27.56s on video.            Keywords:Hybrid cryptography, Data security, Performance, Blowfish, RSA  Abstrak:Keamanan data komputer berhubungan dengan pencegahan dari pencurian data oleh pihak yang tidak bertanggung jawab, salah satu cara pengamanan data komputer yaitu dengan teknik kriptografi. Beberapa metode kriptografi memiliki performa yang baik dan buruk tergantung dengan tipe kuncinya. Maka dari itu, tujuan dari penelitian ini adalah mengukur tingkat kecepatan kriptografi hybrid, terdiri dari algoritma simetris Blowfish dan algoritma asimetris RSA, dengan beberapa tipe data seperti dokumen, foto, audio dan video. Hasil dari penelitian ini adalah algoritma hybrid memiliki performa yang tidak jauh berbeda dari algoritma Blowfish dan membuat proses enkripsi dan dekripsi data lebih aman dengan keunggulan dari algoritma RSA. Rata-rata kecepatan enkripsi algoritma hybrid untuk dokumen 0,85 detik, gambar 1,06 detik, audio 3,38 detik, dan video 15,56 detik. Sedangkan rata-rata kecepatan dekripsi algoritma hybrid untuk dokumen 1,01 detik, gambar 1,38 detik, audio 4,3 detik, dan video 27,56 detik. Kata kunci:Kriptografihybrid, Keamanan data, Performa, Blowfish, RSA 
Analysis Of Right And Wrong Use Of Mask Based On Deep Learning Rico Wijaya Dewantoro; Sonni Yudha Nugraha Arfan; Reyhan Achmad Rizal
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.7582

Abstract

Pandemic COVID-19 makes it important to apply the proper and correct use of masks. The correct use of a mask where its use can cover the nose mouth and chin. One of the problems in using masks is that there are still many people who have not used masks properly and correctly. The importance of the correct use of masks because the transmission of the Covid-19 itself does not only occur through splashes when sneezing or coughing between humans but can also occur when talking or breathing by spreading through fluid particles less than 0.0002 inches (5 microns) in diameter called aerosols that are emitted when people talk. From these problems  it is necessary to have a computational-based analysis system to be able to identify patterns and make decisions and perform certain tasks automatically so that the results obtained are more efficient and objective. In this study, a deep learning method with a resnet  50 will be used to obtain the correct and incorrect results of using masks. The results of this study indicate that the deep learning method with resnet 50 is able to achieve 98.41% accuracy in classifying the correct and incorrect use of masks.
Otomatisasi Pengawasan Penggunaan Masker Pada Siswa Yayasan Pendidikan Shafiyyatul Amaliyyah (YPSA) Reyhan Achmad Rizal; Marlince Novita Karoseri Nababan; Despaleri Perangin-Angin
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 1, No 2 (2021): Desember 2021
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (666.436 KB) | DOI: 10.54314/jpstm.v1i2.721

Abstract

In preparing for face-to-face meetings, the Shafiyyatul Amaliyah Education Foundation (YPSA) requires supervision in applying the use of masks in the school envi-ronment. There are two main problems that exist at YPSA, namely supervising students at YPSA it is difficult for one supervisor to do and the size of the pages at YPSA is difficult to reach every student because students at YPSA vary from kindergarten, elementary, junior high and high school. The solution offered by the PKMS team at Universitas Prima Indonesia is to build an automation system with a door opening and closing model and a warning alarm at the entrance to the school environment. The initial implementation of this activity was carried out on August 16, 2021 to conduct interviews with YPSA part-ners in order to obtain a model of the automation tool for monitoring the use of masks in accordance with the YPSA environment. Every student is protected from the transmission of the Covid-19 virus.
RECOGNITION OF REALTIME BASED PRIMITIVE GEOMETRY OBJECTS USING PERCEPTRON NETWORK Cut Lika Mestika Sandy; Taufik Ismail Simanjuntak; Ajulio Padly Sembiring; Reyhan Achmad Rizal; Ona Rizal Fahmi
Jurnal Techno Nusa Mandiri Vol 20 No 1 (2023): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v20i1.4104

Abstract

The purpose of this study is to analyze the perceptron model on pattern recognition of primitive geometric objects in real time based on video images. The samples used in this study were cubes, prisms, tubes and balls. The system was built using the Delphi 7 programming language with pre-processing stages system training includes the process of calculating matrix values from the original image, then proceed with the grayscale and edge detection processes using convolution with a kernel, namely the sobel operator and then the matrix results from the edge detection process are transformed using a perceptron network to obtain energy from the image of the object, then the resulting energy The transformation is stored in the database as a system test reference pattern recognition energy. Measurement of system performance evaluation in this study uses two parameters, namely detection rate and false positive rate. The recognition rate of primitive geometric objects using the perceptron network model in this study reaches 60.00% to 80.00%. The detection rate percentage shows that this model can be used as a supporting approach for the recognition of geometric objects in video.
Sistem Informasi E-Voting Berbasis Web Menggunakan Metode RSA dan Base64 Cut Lika Mestika Sandy; Fadlisyah Fadlisyah; Reyhan Achmad Rizal
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4753

Abstract

The current problem being faced by Gampong Cot Girek Kandang North Aceh Village is that the selection of Keuchiek is still done manually. Manual selection has many obstacles, one of which is being vulnerable to fraud in voting results because the results cannot be displayed in real-time. Based on these problems, this research will propose an online voting system with web-based e-voting. The web-based e-voting system in this study was created using the RSA and Base64 cryptographic methods to secure voting results data. The results of the study show that a web-based e-voting system using RSA and Base64 is very good for use in the election of Keuchiek besides saving costs because it does not require too many officers and can increase public interest in conducting elections.
Recognition Of Chicken Species Through Sound Using Weierstrass Transform Cut Lika Mestika Sandy; Reyhan Achmad Rizal; Muhathir Muhathir
JURNAL SISFOTEK GLOBAL Vol 13, No 1 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i1.3442

Abstract

Voice recognition is an applied technique in the field of digital signal processing that has been widely used, such as technology in the field of telecommunications which is now able to provide data transmission services not only text but can also serve data transmission using voice. Speech recognition studies to date have only focused on human speech recognition, so it is important to develop research on speech recognition in animals. In this research a speech recognition system will be developed for balenggek, pelung and bekisar ornamental chickens using the Delphi 7 programming language and the weiertrass transform method. The performance evaluation measurement of the speech recognition system in this study uses two parameters, namely the detection rate and the false positive rate. The results showed that the speech recognition system for ornamental chickens using the weierstrass transform method had an average detection rate of 83.00% and an average false positive rate of 16%.
REAL TIME DETECTION OF CHICKEN EGG QUANTITY USING GLCM AND SVM CLASSIFICATION METHOD Cut Lika Mestika Sandy; Asmaul Husna; Reyhan Achmad Rizal; Muhathir Muhathir
Jurnal Techno Nusa Mandiri Vol 20 No 2 (2023): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v20i2.4735

Abstract

A common problem currently being faced in the chicken egg production home industry is difficulty in counting the number of eggs. Currently, calculating the number of eggs is still done manually, which is less than optimal and prone to errors, so many entrepreneurs often experience losses. The manual system currently used also has the potential for this to happen. The use of technology on an MSME scale among laying hen breeders has not been widely adopted, this is due to limited access and understanding of technology. One alternative solution to deal with this problem is to build a real-time computerized system. The system that will currently be built in this research uses GLCM feature extraction and the SVM classification method. This system will detect egg production via CCTV cameras and will be stored in a database to be displayed on the website. The advantage of this system is that egg entrepreneurs can monitor chicken egg yields in real time. The results of trials that have been carried out using GLCM feature extraction and the SVM classification method in calculating the number of eggs using the SVM method with a polynomial kernel are highly recommended for use in this research because it can achieve 95% accuracy.
Co-Authors Abdi Zulfikri Ajulio Padly Sembiring Amsal Yusuf Gultom Ananda Faridhatul Ulva Ardi Bernandustahi Miduk Napitupulu Asmaul Husna Cut Lika Mestika Sandy Dedy Ongky Wijaya Despaleri Perangin-angin Fadlisyah Fadlisyah Kristina Sinaga Lidya Aprilla Siregar Marlince NK Nababan Muhathir Muhathir Mutammimul Ula Nur Azizah Nurlela Octavia Purba Octavriana Della C. Sihombing Ona Rizal Fahmi Prabhu Warren RICO WIJAYA DEWANTORO Sebastian Suhandinata Sonni Yudha Nugraha Arfan Srinjiwi Srinjiwi Suardin Gulo Taripar Jonibet Siagian Taufik Ismail Simanjuntak