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All Journal Jurnal Neutrino : jurnal fisika dan aplikasinya Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Spektra JOIN (Jurnal Online Informatika) Jurnal Pilar Nusa Mandiri JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Jurnal Informasi dan Komputer Communautaire: Journal of Community Service
Riza Ibnu Adam, Riza Ibnu
Departemen Fisika, FMIPA, Universitas Indonesia, Depok, 16424
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Physics Public Health Social Sciences Other

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Peningkatan Deteksi Kecelakaan di Jalan Raya Menggunakan Real-ESRGAN pada Citra CCTV Persimpangan Jalan Ikhsal, Muhammad Fachry; Dermawan, Budi Arif; Adam, Riza Ibnu
Journal of Applied Informatics and Computing Vol. 7 No. 1 (2023): July 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i1.5562

Abstract

The failure of the accident detection system on CCTV cameras can affect the increase in the death rate on the highway. The use of the CNN method in the construction of CCTV accident detection systems has been widely used before. However, common problems that are often encountered are dirty lenses and varifocal zooms that don't automatically focus, causing the quality of the resulting CCTV images to decrease, thus affecting system performance. In this research, a model was developed to detect accidents on CCTV images using the MobileNetV2 pre-trained model which was optimized by upscaling the dataset using the Real-ESRGAN model to produce more optimal performance. This study uses a CCTV image dataset totaling 989 and consisting of 2 types of prediction classes including accident and non-accident. The results showed that the MobileNetV2 model succeeded in producing 94% testing accuracy and an average inference time of 3.33 seconds in the GT test scenario. During the testing process, it was found that the model was not optimal if it identified new data with clustered objects. In addition, based on the test scenarios X2, X4, X8 it was found that the image quality calculated based on PSNR and SSIM values greatly influences classification performance such as accuracy, precision, recall, and AUC score.
Pengenalan Wajah Resolusi Rendah Menggunakan Arsitektur Lightweight VarGFaceNet dengan Adaptive Margin Loss Ramadani, Daffa Tama; Adam, Riza Ibnu; Jaman, Jajam Haerul; Rozikin, Chaerur; Garno, G.
Journal of Applied Informatics and Computing Vol. 7 No. 1 (2023): July 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i1.5831

Abstract

Face recognition is a modern security solution that is quickly and easily integrated into most existing devices, so this system is widely applied to several domains as one of the security authorizations. Developing face recognition models using mainstream architectures (AlexNet, VGGNet, GoogleNet, ResNet, and SENet) will make it difficult to implement the models on mobile devices and embedded systems. In addition, low resolution images, such as those from CCTV surveillance cameras or drones, pose challenges for the models to recognize faces, as the images lack sufficient details for identification. Therefore, this research aims to analyze the performance of a face recognition model developed using the lightweight VarGFaceNet architecture with the adaptive margin loss AdaFace on a low-resolution image dataset. Based on the evaluation results on the LFW dataset, an accuracy of 99.08% was achieved on high-resolution data (112x112 pixels), while on the lowest synthetic low-resolution data (14x14 pixels), an accuracy of 79.87% was obtained with the assistance of the Real-ESRGAN and GFP-GAN super-resolution models. On the TinyFace dataset, without fine-tuning, a Rank-1 accuracy of 46.08% was achieved without using super-resolution models and 45.03% when utilizing super-resolution models.
KLASIFIKASI RAS KUCING MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK Putri, Divasetya Pratama; Adam, Riza Ibnu
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.7364

Abstract

Cat breed identification is often challenging due to visual similarities between breeds, yet accurate recognition is crucial for proper care. This study aims to develop an accurate cat breed classification system using a Convolutional Neural Network (CNN) algorithm with a transfer learning approach. The model was built using the MobileNetV2 architecture on a dataset consisting of 2,387 images from 12 cat breeds. The research stages included data collection, pre-processing, model construction and training, and evaluation. Evaluation results on test data showed that the developed model achieved an accuracy of 84.52%. The model demonstrated superior performance in several classes with unique visual characteristics, but still faced challenges in other classes with similar visual characteristics. These results demonstrate that the CNN method with transfer learning is highly effective and competitive for cat breed classification tasks, with room for further development to improve performance in difficult-to-distinguish classes.
PERANCANGAN WEB INTERAKTIF UNTUK MEMAKSIMALKAN PENGALAMAN PELANGGAN DALAM PEMESANAN ONLINE PADA TOKO ASYAM FRIED CHICKEN Fikri, Raihan; Adam, Riza Ibnu; Irawan, Agung Susilo Yuda
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3S1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3S1.7585

Abstract

Abstrak. Penelitian ini bertujuan untuk mengembangkan sebuah web interaktif sebagai sistem pemesanan online pada Toko Asyam Fried Chicken dengan menggunakan algoritma content based filtering dan framework Laravel 11. Proses pengembangan dilakukan dengan metode Agile Scrum untuk meningkatkan efisiensi dan kualitas hasil. Sistem yang dikembangkan diuji menggunakan metode Black Box Testing dan Usability Testing guna memastikan fungsionalitas dan kemudahan penggunaan. Selain itu, evaluasi performa dilakukan dengan Lighthouse Testing untuk mengukur kecepatan, aksesibilitas, dan best practice website. Hasil pengujian menunjukkan bahwa sistem yang dikembangkan memenuhi kebutuhan pengguna serta mampu memberikan pengalaman pemesanan online yang optimal dan responsif. Abstract. This study aims to develop an interactive web system for online ordering at Asyam Fried Chicken using a content-based filtering algorithm and the Laravel 11 framework. The development process is carried out using the Agile Scrum method to improve efficiency and quality of the results. The developed system is tested with Black Box Testing and Usability Testing methods to ensure functionality and ease of use. Additionally, performance evaluation is conducted using Lighthouse Testing to measure the website's speed, accessibility, and best practices. The test results demonstrate that the developed system meets user needs and provides an optimal and responsive online ordering experience.
Pengembangan Laboratorium Virtual Fisika Osilasi Rizal, Adhi; Adam, Riza Ibnu; Susilawati, Susilawati
JOIN (Jurnal Online Informatika) Vol 3 No 1 (2018)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v3i1.140

Abstract

This research aims to develop a virtual lab application with oscillation concept. Oscillation concept in this application is described as pendulum motion. The application was developed by using the ADDIE model and Easy Java Simulations (EJSs) software. It has advantages compared with similar applications, which has a damping coefficient that similar with real world condition. Some other features of the application are the users can run and pause the simulation, observe the details of changes in pendulum movement angle by using step forward button, users can change pendulum mass, adjust the length of the rope, gravitational force, initial angle, damping coefficient, and can observe the change of pendulum angular position in parabolic graphs in real-time. The application was tested using the Technology Acceptance Model (TAM) concept. Based on the research results, the user satisfaction level is categorized as very useful. Therefore, it can be conclude that the application can be accepted and used well by the user.
ANALISIS SENTIMEN MASYARAKAT TERHADAP PROGRAM MAKAN SIANG GRATIS PADA MEDIA SOSIAL X MENGGUNAKAN ALGORITMA NAÏVE BAYES Sitanggang, Altolyto; Umaidah, Yuyun; Adam, Riza Ibnu
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4902

Abstract

Dalam era digital, media sosial seperti X, Facebook, dan Instagram telah menjadi bagian penting dari kehidupan modern, memungkinkan individu untuk berbagi pandangan dan opini dengan cepat. Salah satu topik hangat di X adalah program makan siang gratis dari pasangan calon presiden nomor urut 02, yang bertujuan meningkatkan gizi anak dan ibu hamil, mencakup 82,9 juta orang. Program ini memicu beragam tanggapan masyarakat. Penelitian ini bertujuan menganalisis sentimen masyarakat terhadap program tersebut menggunakan algoritma Naïve Bayes dan metode Knowledge Discovery in Database (KDD). Data dikumpulkan melalui crawling pada media sosial X, menghasilkan 2.211 tweet yang kemudian diseleksi dan diberi label sentimen positif dan negatif. Algoritma Naïve Bayes diuji dengan tiga skenario pembagian data training dan testing, dan dievaluasi menggunakan confusion matrix. Hasil evaluasi menunjukkan model mencapai hasil terbaik pada rasio data 60:40 dengan akurasi 72,2%, presisi 63,2%, recall 66,1%, dan F1-Score 64%. Keywords: Naïve Bayes, KDD, Makan Siang Gratis, X, Sentimen.
Co-Authors Anto Sulaksono Apriade Voutama Aprilia, Dita Budi Arif Dermawan Efelina, Vita Fikri, Raihan Garno, G. garno, Garno Ikhsal, Muhammad Fachry Iqbal Maulana Irawan, Agung Susilo Yuda Jaman, Jajam Haerul Mufid, Tsaqif Mu'tashim Putri, Divasetya Pratama Ramadani, Daffa Tama Ramadhan Sumantri, Muhammad Jodi Ramadhan, Bintang Zulfikar Rizal, Adhi Rizal, Adhi Rizal, Adhi Rozikin, Chaerur savina, savina Sitanggang, Altolyto Suci, Farradina Choria Susilawati, Susilawati Umaidah, Yuyun