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All Journal International Journal of Electrical and Computer Engineering JIPTEK : Jurnal Ilmiah Pendidikan Teknik dan Kejuruan Jurnal Sains dan Teknologi Bulletin of Electrical Engineering and Informatics IJIE (Indonesian Journal of Informatics Education) Jurnal ULTIMATICS Indonesian Journal of Applied Informatics DEDIKASI: Community Service Reports Journal of Informatics and Vocational Education JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Media Informasi Teknologi Media of Computer Science
Prakisya, Nurcahya Pradana Taufik
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

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Preprocessing Image for License Plate Detection: A Systematic Literature Review Prasetyo, Riyan Bagas Dwi; Abdullayev, Vugar; Prakisya, Nurcahya Pradana Taufik; Sujana, Yudianto; Siswanto, Rahmat
Media of Computer Science Vol. 2 No. 2 (2025): December 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i2.241

Abstract

Rapid population growth contributes to an increase in the volume of vehicles, creating major challenges in their management. One potential solution is the application of deep learning-based artificial intelligence technology for automatic detection of vehicle license plates. This research uses a Systematic Literature Review (SLR) approach to evaluate the performance of various deep learning architectures in the detection process. Out of 125 articles identified, 20 articles were selected based on specific selection criteria. The analysis revealed that preprocessing techniques, such as HE, AHE, ECHE, CLAHE, and ECLACHE, have significant contributions in the processing of vehicle license plate datasets. These techniques were able to improve the visual quality of the images, thus supporting the detection process with an accuracy rate of more than 95%. This research also identified challenges, such as high computational requirements and large-scale data processing. Further research is recommended to apply preprocessing on standardized datasets to develop a reliable, efficient and sustainable detection system.
Rancang Bangun Aplikasi Career Mentoring dan Bootcamp Berbasis Website dengan Framework Next.JS Zaqli, Abi Khoir Naufal; Prakisya, Nurcahya Pradana Taufik; Budianto, Aris
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 14, No 1 (2026)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v14i1.94093

Abstract

Penelitian ini bertujuan untuk (1) mengidentifikasi dan menganalisis proses pengembangan aplikasi career mentoring dan bootcamp berbasis website menggunakan framework Next.JS dan metode Scrum.; (2) Mengevaluasi kinerja dan kepuasan pengguna terhadap aplikasi career mentoring dan bootcamp yang dikembangkan dengan framework Next.JS dan metode Scrum. Penelitian ini termasuk dalam jenis penelitian Research and Development (R&D) dengan menggunakan framework Next.JS dan model pengembangan Scrum. Dalam penelitian ini, framework Next.JS membuktikan kelayakannya sebagai kerangka kerja aplikasi website. Dibuktikan dengan serangkaian tahap penelitian mulai dari proses pengembangan yang cepat dan tepat, uji kelayakan sistem yang memadai, hingga kepuasan pengguna yang terbilang tinggi. Penelitian ini berhasil melibatkan serangkaian tahap dalam pengembangan aplikasi website dengan menerapkan model Scrum, mencakup tahap product backlog, sprint planning, sprint backlog, sprint, sprint review, dan sprint retrospective. Dibuktikan dengan hasil dari evaluasi pengembangan pada tahap sprint retrospective yang mendapat hasil akhir nilai focus factor sebesar 77%. Hasil dari uji kelayakan sistem dengan black box testing terpenuhi 95% yang membuktikan bahwa sistem yang dibangun dapat berfungsi sesuai kebutuhan. Dan hasil evaluasi kegunaan sistem mendapatkan nilai rata-rata usability 77 yang berada pada di posisi Good. Sehingga hasil uji dan evaluasi tersebut menunjukkan bahwa sistem yang dikembangkan sangat layak digunakan sebagai aplikasi career mentoring dan bootcamp berbasis website.
Comparative analysis of ResNet backbones in single shot detector for visual-based waste detection Salsabila, Zahra Khalila; Prakisya, Nurcahya Pradana Taufik; Liantoni, Febri
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10540

Abstract

Waste has become a serious environmental issue that requires effective and efficient management systems. This study compares three residual network (ResNet) variants (ResNet-34, ResNet-50, and ResNet-101) within the single shot detector (SSD) framework for visual waste detection. The dataset consists of 800 images in four categories—food, plastic, paper, and wood—with a 70:20:10 split for training, validation, and testing. The backbone architecture, optimizer (stochastic gradient descent (SGD) and Adam), and learning rate are varied to evaluate fifteen experimental configurations. Model performance is assessed using precision, recall, F1-score, and mean average precision (mAP). The results show that SSD–ResNet-34 with SGD and a learning rate of 0.0005 works best, with a mAP of 91.02%, which is better than deeper backbones. Deeper backbone architectures do not consistently improve accuracy; instead, they increase the risk of overfitting on small datasets. These findings highlight that lightweight architecture, when used with the right hyperparameter settings, strikes a better balance between accuracy, computational efficiency, and generalization for small-scale waste detection tasks.
Rekayasa Perangkat Lunak Aplikasi Presensi Mobile Menggunakan Metode Deep Learning Setiawan, Ragil; Prakisya, Nurcahya Pradana Taufik; Ariyuana, Rosihan
JIPTEK: Jurnal Ilmiah Pendidikan Teknik dan Kejuruan Vol 17, No 1 (2024): January
Publisher : Faculty of Teacher Training and Education Universitas Sebelas Maret Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jiptek.v17i1.76556

Abstract

Facial recognition research has its challenges due to faces complexity, ranging from facial expressions and certain conditions that make facial recognition an exciting research experiment. Moreover, many-oriented applications of machine learning have moved to devices edge, and-based facial recognition is no exception mobile. Seeing the ongoing development of facial pattern recognition algorithms such as Viola Jones, Backpropagation, this research uses the MobileFaceNet  mobile CNN model which is currently popular to be implemented in the mobile-based facial recognition presence application at the Information and Computer Engineering Education (PTIK) FKIP UNS. The deep learning method is a method for understanding and classifying objects. In the developed application, a face is captured in an image. This research uses the help of the flutter framework and the Tensorflow Lite library to develop a presence application mobile facial recognition in real-time. This paper aims to determine the value of the memorization and generalization algorithms model of CNN MobileFaceNet  on the application.  A trial of the system has been carried out by involving 30 volunteers in the testing from 2016-2019 PTIK students by random sampling. Each test was carried out for 10 iterations. From the test results, the system memorization value is 84.5%. On the other hand, the generalization results get 70% in recognizing identical but not similar images correctly. In terms of memorization and generalization, these results are better than similar studies using backpropagation
A Comparative Study of Digital Image Segmentation Algorithms for Acute Myeloid Leukemia M1 White Blood Cells Images Prakisya, Nurcahya Pradana Taufik; Setiawan, Andika
IJIE (Indonesian Journal of Informatics Education) Vol 4, No 2 (2020): IJIE (Indonesian Journal of Informatics Education)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v4i2.48448

Abstract

Various types of algorithms have been widely used for image segmentation in digital image processing. Every algorithm has features that make it unique to be applied to specific cases. One of the applications of image segmentation is to detect white blood cells. Certain objects such as blood cells must be able to be well segmented because their existence is very crucial to support the accuracy of disease detection related to haematology or the branch of medical science that studies the morphology of blood and blood-forming tissues. Three image segmentation algorithms were compared through this study: Seed Region Growing, Otsu Thresholding and Active Contour Without Edge. Comparative analysis of the three algorithms was done by counting the number of white blood cell objects that were successfully segmented with the actual number of cells that were counted manually. A total of 30 images of blood smears were taken from people suffering from acute myeloid leukemia M1. The average accuracy values from each algorithm were used to determine which image segmentation algorithm is the most suitable for application in the case of white blood cells segmentation. The results showed that Active Contour Without Edge is the most appropriate among the other algorithms
Hand Detection on HSV Color Space Model and Syntactic Extraction of Fingertip by Thinning Method for Hand Gesture Recognition Aristyagama, Yusfia Hafid; Liantoni, Febri; Prakisya, Nurcahya Pradana Taufik
IJIE (Indonesian Journal of Informatics Education) Vol 5, No 2 (2021): IJIE (Indonesian Journal of Informatics Education)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v5i2.51693

Abstract

In the discussion of computer vision, detection and recognition are an interesting topic to discuss. Basically, advanced computer vision technology requires a high-level interaction method above the text-based console interaction. Hand detection and gesture recognition is one of the interaction cases in computer vision. In this study, an experiment of hand detection and syntactic hand gesture recognition method are discussed. HSV (Hue Saturation Value) space color model is used as the basis of hand detection and segmentation. Then, the thinning method is used to get endpoint features of each fingertip.The proposed design is designed to meet with real-time video processing. The experiment intended to find some issues usually happened when the ZS thinning method is used to gain the detection and recognition. The result shows that the proposed design able to detect and recognize some gesture, but unstable hand movement may lead into a fault called by extra endpoint. In this research, extra endpoints are considered as a challenge that must be anticipated when using thinning method especially ZS algorithm to perform syntactic hand gesture recognition.
The Role of Artificial Intelligence in Enhancing Critical Thinking in Education : A Systematic Literature Review Tarwanto, Rahmat Alvin; Sujana, Yudianto; Prakisya, Nurcahya Pradana Taufik
IJIE (Indonesian Journal of Informatics Education) Vol 9, No 2 (2025): (IJIE) Indonesian Journal of Informatics Education - December
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijie.v9i2.103868

Abstract

The emergence of generative AI, particularly language models like ChatGPT, has revolutionized educational practices by enhancing lesson planning and fostering critical thinking. This systematic literature review investigates the application of generative AI in creating effective lesson plans and its broader role in improving the educational process. By synthesizing findings from multiple studies, this research highlights AI's ability to personalize learning, provide adaptive feedback, and simulate real-world scenarios, which collectively promote analytical and reflective thinking among students. Additionally, the integration of ethical considerations in AI-supported education fosters responsible use and critical evaluation of AI systems. Despite its potential, challenges such as ethical dilemmas, dependency on technology, and algorithmic biases remain significant. This study underscores the transformative role of generative AI in modern education, offering practical insights and recommendations for integrating AI tools effectively. The findings contribute to understanding AI's impact on pedagogy, student engagement, and the development of higher-order thinking skills, emphasizing the importance of a balanced approach that aligns AI capabilities with human.
Otomasi Pemeliharaan Tanaman Hidroponik Sistem Wick Berbasis Arduino Uno Salamah, Umi; Septianto, Bimo Adrian; Prakisya, Nurcahya Pradana Taufik
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 1 (2024)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i1.93772

Abstract

Abstrak:Hidroponik Sistem Wick merupakan sistem budidaya tanaman yang mudah diterapkan karena tidak memerlukan banyak biaya dan tempat. Tantangan penggunaan sistem ini adalah pengendalian terhadap kualitas air berupa pH air, ppm air, suhu, serta kelembaban udara yang harus dilakukan secara periodik untuk menjaga kelangsungan hidup tanaman. Untuk itu pada penelitian ini akan dibangun Internet of Things (IoT) untuk memastikan kebutuhan pertumbuhan tersebut selalu terpenuhi dengan cara penambahan air dalam wadah dan penambahkan cairan pH buffer untuk mengontrol kadar pH dalam air secara otomatis dan menampilkan data dari sensor secara real time melalui smartphone. Ada tiga tahapan untuk pengembangan system pemeliharaan tanaman hidroponik dengan IoT yaitu koleksi kebutuhan sistem, desain dan implementasi menggunakan Arduino Uno, dan pengujian untuk mengembangkan sistem secara keseluruhan. Hasil pengujian menunjukkan penggunaan IoT yang diusulkan berhasil melakukan otomasi dengan tingkat akurasi pengujian pada sensor DHT11 untuk pengukuran suhu dan kelembaban masing-masing sebesar 98% dan 92%. Akurasi sensor jarak HC-SR04 dan sensor pH DFRobot V2 masing-masing sebesar 96% dan 98.6%, sehingga total akurasi sensor sebesar 96.53% selama 22 hari masa tanam. Hasil tanaman sehat diiringi dengan pertumbuhan yang bagus dan subur sampai masa panen.================================================Abstract:The Wick Hydroponic System is a plant cultivation system that is easy to implement because it does not require a lot of money and space. The challenge of using this system is controlling water quality in the form of water pH, water ppm, temperature and air humidity which must be carried out periodically to maintain plant survival. For this reason, in this research, the Internet of Things (IoT) will be built to ensure that growth needs are always met by adding water to the container and adding pH buffer fluid to control the pH level in the water automatically and displaying data from sensors in real time via smartphone. There are three stages for developing a hydroponic plant maintenance system with IoT, namely collection of system requirements, design and implementation using Arduino Uno, and testing to develop the system as a whole. The test results show that the proposed use of IoT has successfully carried out automation with a test accuracy level on the DHT11 sensor for measuring temperature and humidity of 98% and 92% respectively. The accuracy of the HC-SR04 distance sensor and the DFRobot V2 pH sensor was 96% and 98.6% respectively, so that the total sensor accuracy was 96.53% during the 22 days planting period. The results of healthy plants were accompanied by good and fertile growth until harvest time
Desain dan Pemanfaatan Media Pembelajaran Flash Card dengan Canva untuk Disabilitas Yuana, Rosihan Ari; Budiyanto, Cucuk Wawan; Prakisya, Nurcahya Pradana Taufik; Hatta, Puspanda; Aristyagama, Yusfia Hafid; Liantoni, Febri
DEDIKASI: Community Service Reports Vol 6, No 1 (2024): DEDIKASI: Community Service Report - January
Publisher : FKIP Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/dedikasi.v6i1.77139

Abstract

Students with disabilities require suitable educational materials. Hence, one of the essential skills that a teacher must possess is the ability to provide suitable instructional materials for students. A workshop was organized by this community service activity at SLB YPCM Boyolali, focusing on creating educational media for instructors using Canva. The training instructs teachers on how to design flashcards specifically tailored for students with disabilities to facilitate their learning process. The advantage of this activity is the enhanced proficiency of SLB YPCM Boyolali teachers in creating digital educational materials. Another advantage is assessing instructor perspectives when employing digital media for educational purposes. The school will provide students with exceptional needs the opportunity to develop the skill of product branding using the processed foods they create. The post-workshop evaluation results indicate that this activity is highly successful and positively influences participants. Evidence demonstrates that 90% of participants can generate flashcard learning media products using Canva. The participants had a favorable opinion of Canva due to its user-friendly interface and comprehensive range of functions, despite most participants having limited computer proficiency. The session presented was met with a high level of satisfaction from most attendees.
Peningkatan Kreatifitas Dan Kemampuan Algoritma Melalui Workshop Game Development Liantoni, Febri; Budiyanto, Cucuk Wawan; Aristyagama, Yusfia Hafid; Hatta, Puspanda; Prakisya, Nurcahya Pradana Taufik
DEDIKASI: Community Service Reports Vol 7, No 1 (2025): DEDIKASI: Community Service Report - January
Publisher : FKIP Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/dedikasi.v7i1.93557

Abstract

Workshop pengabdian masyarakat ini bertujuan untuk memberdayakan para pendidik dalam menciptakan media pembelajaran yang lebih menarik dengan memanfaatkan teknologi digital, khususnya melalui pendekatan game-based learning. Tantangan yang dihadapi adalah rendahnya kreativitas dan pemahaman algoritma di kalangan pendidik, serta minimnya implementasi pembelajaran berbasis game di sekolah. Dilaksanakan di SMP Al Qolam Muhammadiyah Gemolong, workshop ini memanfaatkan fasilitas kelas yang tersedia, meliputi paparan teori, praktik langsung, dan pendampingan intensif dalam pengembangan game menggunakan Construct 2. Para peserta tidak hanya belajar membuat media pembelajaran interaktif, tetapi juga memperdalam pemahaman tentang literasi digital dan algoritma. Hasil kegiatan ini menunjukkan peningkatan yang signifikan dalam kemampuan desain pembelajaran, serta kepercayaan diri dalam menggunakan teknologi untuk mendukung proses mengajar. Dari pelatihan ini, terlihat bahwa penggunaan pendekatan berbasis game dapat merangsang kreativitas dan memperkuat pemahaman algoritma dalam konteks pembelajaran.
Co-Authors Abdullayev, Vugar Adhiatma, Paulus Lestyo Agus Efendi Andika Setiawan, Andika Arief Hermanto Aris Budianto, Aris Cucuk Wawan Budiyanto Dwi Maryono Fadliansah, Arafik Nur Fawaidil Wafa, Alfian Febri Liantoni, Febri Herianto, Tulus Joseph Jimsan Jimsan Kusmanto, Bintang Timur Lestari Rahayu Nurulita, Khiara Prasetyo, Riyan Bagas Dwi Puspanda Hatta Ramadhan, Firdaus Ditio Ramadhan, Raqael Fisabillah Rosihan Ari Yuana, Rosihan Ari Rosihan Ariyuana, Rosihan Rustanto, Diki Wahyudi Salsabila, Zahra Khalila Septianto, Bimo Adrian Setiawan, Ragil Sidauruk, Deardo Satria Ristiawan Siswanto, Rahmat Tarwanto, Rahmat Alvin Umi Salamah Yudianto Sujana Yusfia Hafid Aristyagama Zaqli, Abi Khoir Naufal Zulfikar, M Luthfi