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All Journal International Journal of Electrical and Computer Engineering International Journal of Evaluation and Research in Education (IJERE) Farmasains : Jurnal Farmasi dan Ilmu Kesehatan Journal of Food and Pharmaceutical Science Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Transmisi: Jurnal Ilmiah Teknik Elektro JURNAL SISTEM INFORMASI BISNIS Voteteknika (Vocational Teknik Elektronika dan Informatika) JTEV (Jurnal Teknik Elektro dan Vokasional ELKHA : Jurnal Teknik Elektro Jurnal Sistem Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Jurnal Algoritma Jurnal Teknologi Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Pseudocode Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Komunikator ICON-CSE CESS (Journal of Computer Engineering, System and Science) Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) Journal of Electrical Technology UMY Format : Jurnal Imiah Teknik Informatika Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal IT JOURNAL RESEARCH AND DEVELOPMENT Jurnal Sains dan Informatika Insect (Informatics and Security) : Jurnal Teknik Informatika JRST (Jurnal Riset Sains dan Teknologi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) ILKOM Jurnal Ilmiah Compiler KACANEGARA Jurnal Pengabdian pada Masyarakat Jiko (Jurnal Informatika dan komputer) Journal of Science and Engineering MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JSiI (Jurnal Sistem Informasi) CYBERNETICS Krea-TIF: Jurnal Teknik Informatika J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) Jurnal Teknik Elektro dan Komputer TRIAC Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Jurnal Ilmiah Mandala Education (JIME) JSI (Jurnal sistem Informasi) Universitas Suryadarma Systemic: Information System and Informatics Journal Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Jurnal Mantik JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Electronics, Electromedical Engineering, and Medical Informatics Buletin Ilmiah Sarjana Teknik Elektro RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Mobile and Forensics Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) Jurnal Riset Rekayasa Elektro Jurnal Repositor Respati Jurnal Abdi Insani Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) International Journal of Advances in Data and Information Systems JITU : Journal Informatic Technology And Communication Journal of Innovation Information Technology and Application (JINITA) Reswara: Jurnal Pengabdian Kepada Masyarakat SKANIKA: Sistem Komputer dan Teknik Informatika Innovation in Research of Informatics (INNOVATICS) Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Computer Science and Information Technology (CoSciTech) Journal Social Science And Technology For Community Service Jumat Informatika: Jurnal Pengabdian Masyarakat Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) Decode: Jurnal Pendidikan Teknologi Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Techno Jurnal Pengabdian Pada Masyarakat Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat SmartComp Journal of Food and Pharmaceutical Sciences Jurnal Informatika: Jurnal Pengembangan IT Control Systems and Optimization Letters Emitor: Jurnal Teknik Elektro Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Signal and Image Processing Letters Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi Scientific Journal of Engineering Research Dedikasi Nusantara Indonesian Journal on Learning and Advanced Education (IJOLAE)
Anton Yudhana
Universitas Ahmad Dahlan, Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Performance Analysis for Classification of Malnourished Toddlers Using K-Nearest Neighbor Lonang, Syahrani; Yudhana, Anton; Biddinika, Muhammad Kunta
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.45196

Abstract

Purpose: Malnutrition in toddlers is a nutritional issue that Indonesia is still dealing with. Toddlers can suffer from decreasing cognitive and physical abilities, as well as being categorized as having a high risk of death. Early detection is crucial for preventing this and providing appropriate treatment if malnutrition is detected. Classification is a machine-learning technique widely used in disease detection. Because it is simple and easy to implement, K-Nearest Neighbor is the most used classification algorithm. Detecting malnutrition can be done automatically and more quickly by utilizing classification and machine learning algorithms. The aim of this study was to analyze performance to find out which model is best for detecting malnutrition by evaluating the performance of classification using KNN with the Euclidean distance function.Methods: The dataset used in this study is the nutritional status of toddlers from Puskesmas Ubung. The classification method proposed in this research is the KNN algorithm with Euclidean distance. There are three scenarios for the classification model that will be used. Performance classification will compare each model in terms of accuracy, precision, recall, f1-score, and mean absolute error.Results: The experimental results show that KNN k = 15 using the first model generates excellent classification when classifying malnourished toddlers using the Euclidean distance function. The model obtains 91% accuracy, 86.6% precision, 83.8% recall, 85.2% recall, and a mean absolute error of 0.09.Novelty: In this experiment, we analyzed the performance of the KNN to classify malnourished children using a nutritional status dataset, which resulted in an excellent classification that could be used for early detection.
Analysis Impact of Rapid Application Development Method on Development Cycle and User Satisfaction: A Case Study on Web-Based Registration Service Riadi, Imam; Yudhana, Anton; Elvina, Ade
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49590

Abstract

Purpose: This research was conducted to respond to obstacles and inefficiencies in the new student registration system at RA Plus Rabbani. Currently, the conventional method of using physical documents for registration is vulnerable to damage and data loss. Therefore, the proposed solution is implementing a website-based online registration system using the Rapid Application Development (RAD) method. This aims to simplify the process, increase accessibility for prospective students, and reduce the costs and time required.Methods: This research commenced by identifying constraints within the conventional student registration system at RA Plus Rabbani through observations and interviews. The development, following the RAD methodology, involved testing with PHPUnit and Blackbox Testing to ensure the functionality of the system aligned with specifications. In addition, usability evaluation was conducted based on the ISO 9126 standard.Result: The research results show that testing on MVC indicated a 100% success rate for each architectural feature. Referring to expectations with a “valid” conclusion on functionality using Blackbox testing, based on ISO 9126 percentage displayed, it is known that the criterion with the most significant value is the understandability characteristic with a value of 83%. Novelty: This research makes a significant contribution by improving student registration services at RA Plus Rabbani through the implementation of various testing techniques, following the research flow offered by RAD. The study also provides substantial references for further research in web-based system development.
Multi-Label Opinion Mining Based on Random Forest with SMOTE and ADASYN Ardiansyah, Ricy; Yuliansyah, Herman; Yudhana, Anton
Compiler Vol 14, No 2 (2025): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i2.3185

Abstract

Multi-label classification is essential to categorize data into multiple labels simultaneously. However, data imbalance poses a challenge, where some labels have much less representation, thus reducing the model performance. This study aims to propose a candidate-based sentiment analysis model on the 2024 Jakarta Presidential and Gubernatorial Election review. The SMOTE and ADASYN oversampling methods are applied to handle class imbalance. Both oversampling methods are compared with the Random Forest machine learning method. The experimental results show that. The experimental results show that in the classification of Presidential candidates, Random Forest achieves an accuracy of 0.947 with SMOTE and 0.948 with ADASYN. For sentiment labels, the accuracy of Random Forest remains high with a result of 0.989 for both SMOTE and ADASYN. In the classification of Jakarta Gubernatorial candidates, Random Forest + SMOTE produces an accuracy of 0.975, while with ADASYN it decreases slightly to 0.973. For sentiment labels, both SMOTE and ADASYN have the highest accuracy of 0.993. The application of SMOTE and ADASYN helps to improve the distribution of the minority class without decreasing the overall accuracy, as well as improving the stability in recognizing various multi-label classes in a balanced manner.
Analisis Termal Kolektor Silinder dalam Sistem Penyimpan Panas PCM Parafin Berbasis Mikrokontroller Bahagiya, Multika Untung; Riadi, Imam; Yudhana, Anton
JTEV (Jurnal Teknik Elektro dan Vokasional) Vol 11, No 1 (2025): JTEV (Jurnal Teknik Elektro dan Vokasional)
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtev.v11i1.131645

Abstract

Energi adalah sesuatu yang tidak dapat pisah dari kondisi kehidupan manusia saat ini. Air memiliki peran yang sangat penting bagi kehidupan manusia bahkan udara dapat berfungsi sebagai nafas sehari-hari masyarakat. Faktor krusial dalam proses kerja yang sedang berlangsung dari mesin yang sudah tua adalah transparansi data dan representasi visualnya. Satu-satunya metode untuk mengirimkannya adalah melalui sistem internet. Mikrokontroler yang telah dilengkapi dengan Modul WiFi. Dari penelitian dalam pengujian kolektor silinder kita bisa mengetahui sumber energi terbarukan. Dalam penelitian analisis termal kolektor silinder dalam sistem penyimpan panas PCM parafin berbasis mikrokontroller memperoleh hasil dihari pertama temperatur pada titik puncak pada saat waktu menunjukan pukul 13.00 WIB memperoleh temperatur 37,1 ℃ dan pada saat penelitian dihari kedua temperatur pada titik puncaknya waktu menunjukan pukul sama dengan dihari pertama yaitu pukul 13.00 WIB memperoleh temperatur sampai 39,2 ℃. Lalu temperatur rata-ratanya dari penelitian terendah yang diperoleh pada PCM Parafin sebagai penyimpan kalor dengan penggunaan banyaknya PCM Parafin 500 ml temperatur yang diperoleh 32,6 ℃, sedangkan temperatur tertingginya diperoleh pada penggunaan dari segi banyaknya PCM Parafin 1000 ml dan temperatur yang diperoleh 33,3 ℃. Dari penelitian dalam pengujian ini dengan temperatur terpanas yang diserap parafin sebagai penyimpan panas semakin tinggi maka semakin lama juga temperatur panas yang didapat dan disimpan pada PCM Parafin. Hasil dalam penelitian yang terlihat bahwa PCM Parafin sangat dapat menyimpan panas/ kalor yang sangat lama. Keyword: Energi Terbarukan; Kolektor Silinder, PCM Parafin; Mikrokontroller; Sensor
Classification of Crystallization Images of Pharmaceutical Raw Materials Using Convolutional Neural Network Algorithm Yudhana, Anton; Reski, Julia Mega
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1440

Abstract

The rapid advancement of artificial intelligence (AI) has opened new opportunities for automation in the pharmaceutical industry, particularly in the classification of raw drug materials. Manual classification methods are time-consuming and prone to human error, highlighting the need for reliable automated solutions. This study applied a deep learning approach for classifying crystallization images of pharmaceutical raw materials using a Convolutional Neural Network (CNN). A dataset of 300 crystallization images of Nicotinamide and Ferulic Acid was obtained through hot-stage microscopy, preprocessed with normalization, resizing, and augmentation, and divided into training, validation, and testing subsets. The CNN model was trained for 10 epochs and evaluated using a confusion matrix and standard performance metrics (accuracy, precision, recall, and F1-score). The model achieved perfect recall for Ferulic Acid and 90% recall with 100% precision for Nicotinamide, resulting in an overall accuracy of 95%. While these results are promising, the relatively small dataset may limit generalization, and further validation with larger or external datasets is required. The findings indicate that CNN-based methods hold strong potential for automating crystallization classification, improving pharmaceutical quality control, and reducing reliance on manual assessment, in line with recent advances in medical and pharmaceutical image analysis.
ANALISIS ESTIMASI PENYAKIT TANAMAN TOMAT MENGGUNAKAN PENDEKATAN MACHINE LEARNING TINJAUAN PUSTAKA SISTEMATIS Rafdhi, Faiz; Riadi, Imam; Yudhana, Anton
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 4 (2025): EDISI 26
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i4.6779

Abstract

Deteksi dini penyakit pada tanaman buah sangat penting untuk menjaga produktivitas dan mutu hortikultura. Keterlambatan mengenali gejala dapat menimbulkan kerugian signifikan, baik dari sisi panen maupun ekonomi petani. Kemajuan machine learning (ML) dan deep learning (DL) menawarkan solusi inovatif melalui diagnosis otomatis berbasis citra daun. Penelitian ini meninjau literatur secara sistematis menggunakan kerangka PRISMA untuk mengkaji dataset, performa model, keterbatasan, tren algoritma, serta arah penelitian selanjutnya. Dari 176 artikel, 50 lolos seleksi, dengan 35 fokus pada penyakit tanaman buah. Hasil kajian menunjukkan bahwa Convolutional Neural Network (CNN) dan variasinya masih mendominasi lebih dari 75% studi. Akurasi model sangat tinggi pada dataset laboratorium (95–99%), menurun pada data lapangan (in-the-wild) seperti PlantDoc (90–96%). PlantVillage tetap menjadi dataset utama, meski uji generalisasi menuntut data lapangan yang lebih beragam. Tantangan meliputi domain shift, class imbalance, keterbatasan label tingkat severitas, serta kendala implementasi di perangkat edge. Kontribusi ilmiah kajian ini berupa rekomendasi riset masa depan diarahkan pada pengembangan dataset lapangan standar, integrasi hybrid CNN–GCN, domain adaptation, data sintetik, segmentasi untuk estimasi severitas, serta Edge AI yang real-time dan dapat dijelaskan (explainable AI). Kajian ini menekankan pentingnya inovasi algoritmik, dataset realistis, dan integrasi IoT/edge untuk sistem diagnosis yang akurat, adaptif,  dan berkelanjutan.
Measuring The Success of E-Learning In Universities Using The Technology Acceptance Model Yudhana, Anton; Riadi, Imam; Abe, Tuska
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 6 No 2 (2022): August 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v6i2.17509

Abstract

This study aims to determine the factors of acceptance of e-learning technology in students who use the technology acceptance model, namely perceived usefulness (PU), perceived ease of use (PEOU), an attitude of acceptance of use (ATU), and acceptance (IT) of the e-learning acceptance system. The population in this study were students of state Islamic religious institutes who had participated in the e-learning system. The respondents of this study were students of the Ambon State Islamic Institute of Religion, which collected 30 respondents. The method used in this study uses the technology acceptance model method in the process of data processing using quantitative analysis techniques in the process of analyzing data from research results. The analysis results show that the acceptance of e-learning technology by students of the Islamic Institute of Religion is very well received by users of the Ambon State Islamic Institute of Religion students. The study's results showed that the variable utilization percentage of 76.66% was stated to agree strongly. In comparison, the percentage of 61.66% agreed. Attitudes towards users 70.66% agreed. The study's results show that students in the learning process can accept using e-learning systems.
Impact of Fuzzy Tsukamoto in Controlling Room Temperature and Humidity Sunardi, Sunardi; Yudhana, Anton; Furizal, Furizal
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 7 No 2 (2023): August 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v7i2.19652

Abstract

Dry season is a season where the room temperature exceeds the needs of the body so that it is unpleasant, unhealthy and can interfere with human productivity. In addition, the efficiency of use and resource requirements are also a concern for some people. To overcome this problem, an automatic room temperature control device was created using the ESP32 microcontroller with Tsukamoto's fuzzy algorithm optimization as a data processing technique to produce optimal fan speeds in duty cycle units based on temperature and humidity conditions in realtime. Four tests by running a fan for 30 minutes on each showed that the average difference between the maximum and minimum temperatures in the room was 0.95°C, while the average difference between maximum and minimum humidity was 2.0%. In addition, the test graph shows that when the fan is rotated in a closed room without air circulation, the relative temperature change increases from the initial minute to the last minute of the test. Meanwhile, changes in relative humidity decrease, although fluctuations increase within 1-4 minutes. This study found that fans are not effective in lowering room temperature optimally. Therefore, it is recommended to replace with an exhaust fan in future research.
Improved Malnutrition Classification in Toddlers Using Mutual Information-Guided Feature Selection and Hybrid KNN–MLP Ensemble Learning Syahrani Lonang; Anton Yudhana; Shoffan Saifullah
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 2 (2025): JINITA, December 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i2.2831

Abstract

Malnutrition remains a significant public health challenge in Indonesia, with early detection being crucial for effective intervention. Previous studies utilizing the K-Nearest Neighbor (KNN) algorithm demonstrated promising results in classifying malnourished toddlers based on anthropometric data. However, single-model approaches often suffer from sensitivity to noise and limited generalization. This study proposes a hybrid ensemble model combining KNN and Multi-Layer Perceptron (MLP), integrated with mutual information-based feature selection, to improve classification performance. Using a dataset from Puskesmas Ubung, Bali, comprising 1,319 records with nine anthropometric features and a binary malnutrition label, the model was evaluated under stratified five-fold cross-validation. The proposed KNN–MLP ensemble with top-ranked features achieved 94.3% accuracy, surpassing both standalone KNN and MLP models. Additional metrics, including precision (91.7%), recall (89.4%), F1-score (90.5%), and MAE (0.05), confirmed the model's robustness and reliability. These findings demonstrate that ensemble learning combined with feature selection significantly improves early-stage malnutrition classification, offering a scalable approach for decision-support systems in public health interventions.
The Effect of Light Intensity, Camera Pixel Quality, Camera Distance, and Object Altitude on Detection Accuracy in a Real-Time Drone Surveillance System Using YOLOv5 Astika Ayuningtyas; Imam Riadi; Anton Yudhana
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 2 (2025): JINITA, December 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i2.2843

Abstract

This research evaluates the performance of the drone detection system based on YOLOv5 in a variety of environmental conditions. The four main variables under test were drone height, camera type, light intensity, and camera-to-object distance. Thirty-six different scenarios were used with three different camera types (1080p, 2K, and Canon 600D). The height of the drones varied from 1 to 14 meters, and the variations in illumination ranged from 0 to 46 lux. Results showed consistent YOLOv5 performance with an average accuracy of 60%, precision of 62%, recall of 58%, F1-score of 60%, and IoU of 75%. ANOVA revealed that light intensity, camera distance, and drone height all had a significant impact on detection accuracy (p < 0.05), but camera type was not statistically significant. The best results were obtained under the following conditions: high light levels (>40 lux), camera distances <10 m, and drone altitudes between 6 and 9 m. These findings demonstrate the importance of environmental setup in improving the performance of object detection systems based on deep learning. This research helps design a more reliable and adaptable drone detection system for real-world applications. This work provides practical guidelines for implementing deep learning-based aerial surveillance and highlights optimal operational parameters for YOLOv5 systems.
Co-Authors Aang Anwarudin Abd. Rasyid Syamsuri Abdel-Nasser Sharkawy Abdillah, Muhamad Aznar Abdul Azis Abdul Djalil Djayali Abdul Fadil Abdul Fadil Abdul Fadlil Abdul Fadlil Abe, Tuska Ade Firli Ansyori Adi Permadi Agung Dwi Nugroho, Agung Dwi Agus Jaka Sri Hartanta Agustin Rafikasari Ahmad Azhar Kadim Ahmad Ikrom Ahmad Ikrom Ahmad Syahril Mohd Nawi Ahmadi, Ahwan Akhwandi, Dasef AKRIMA, ASRA Alameka, Faza Alameka, Faza alders paliling Aldi Bastiatul Fawait Fawait Alfian Ma’arif Alin Khaliduzzaman Aminuyati Andhy Sulistyo Andiko Putro Suryotomo Andri Pranolo Anggara Ibnu Sidharta Annafii, Moch. Nasheh Anom Wahyu Asmorojati Anshori, Ikhwan Anton Satria Prabuwono Anton Satria Prabuwono Anwar Siswanto Anwarudin, Aang Any Guntarti Ardiansyah, Ricy Arief Setyo Nugroho Aris Rakhmadi Asep Ririh Riswaya Ashari, Irvan Asno Azzawagama Firdaus Asra Akrima Astika AyuningTyas, Astika Aulia, Muhammad Immawan Aznar Abdillah, Muhamad Azrul Mahfurdz Bahagiya, Multika Untung Balza Achmad Bella Okta Sari Miranda Belly Apriansyah Bintang, Rauhulloh Noor budi putra Budi Setianto, Arif Bulaka, Bardan Cahya Subrata, Arsyad Choirul Fajri Darso, Muhammad Daryono Daryono Dasef Akhwandi Deni Murdiani Denny Yoga Pratama Dewi Eko Wati Dian Nova Kusuma Hardani Didi Siprian Djou, M Rosyidi Drezewski, Rafal Dwi Susanto Dwi Susanto Dwi Susanto Dzakarasma Tazakka Ma’arij Edi Ismanto Eka Rahmat B Eko Prianto Eko Prianto, Eko Elvina, Ade Fadil, Abdul Fadlil, Abdul Fadlillah Mukti Ayudewi Fahmi, Miftahuddin Fahrizal Djohar Fakhri, La Jupriadi Fathoni, Listya Febri Fatma Nuraisyah, Fatma Faza Alameka Faza Alameka Febryansah, M. Iqbal Fitrah Juliansyah Fitri Anggraini Fitri Anggraini, Fitri Fitriyanto, Rachmad Furizal Furizal Furizal Furizal, Furizal Galih Pramuja Inngam Fanani H, Hermansa Habibah, Nurina Umy Habsah Hasan Hadi Sasongko, Hadi Halil, Nur Ihsan Hanif, Abdullah Hanif, Kharis Hudaiby Hartanta, Agus Jaka Sri Hartono, Susilo Helmiyah, Siti Herman Herman Herman Herman Herman Herman Yuliansyah Herman Yuliansyah, Herman Hermansa Herwindo Rahadian Hidayat, Lalu Amam Hikmatyar Insani Himawan I Azmi Igo Putra Pratama Iif Alfiatul Mukaromah Ikhsan Sugianto Ikhsan Zuhriyanto Ikhsan Zuhriyanto Ikhsan Zuhriyanto Ikhwan Anshori Ikrom, Ahmad Ilham Mufandi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Intan Puspitasari Irfan, Syahid Al Ivan Triyatno Jafri Din Jaka Dernata Jaka Dernata Jaka Japkowicz, Nathalie Jendri Juliansyah, Fitrah Kalbuadi, Dimas Baskoro Kartika Firdausy Kaspul Anwar Kaswijanti, Wilis Kawarul Hawari Ghazali Kgs Muhammad Rizky Alditra Utama Kgs Muhammad Rizky Alditra Utama Khaliduzzaman, Alin Khalif, Fajar Al Khoir, Syaiful Amrial Khoirul Anam Dahlan Kintung Prayitno, Kintung Kitagawa, Kodai Kurniawan, Gusti Chandra Kusuma , Damar Yoga Lestari, Agung Tri Listya Febri Fathoni Liya Yusrina Sabila Luh Putu Ratna Sundari Lutfatul Kholifah M Rosyidi Djou M. Rosyidi Djou Mahsun Mahsun Mardi Sugama Marlina Mustafa, Marlina Maulana, Irvan Mawadati, Siti Mawarni, Syifa’ah Setya Mega Reski4, Julia Mhd. Basri Miftahuddin Fahmi Miftahus Surur, Miftahus Miko Wardani Mitra Adhimukti Moch. Nasheh Annafii Muchamad Kurniawan Muchlas Muchlas Muchlas Muchlas, Muchlas Mudinillah, Adam Muflih, Ghufron Zaida Muh. Fadli Hasa Muhamad Caesar Febriansyah Putra Muhamad Caesar Febriansyah Putra, Muhamad Caesar Febriansyah Muhamad Fahrul Reza Muhamad Rosidin Muhammad Aris Fajar Ilmawan Muhammad Darso Muhammad Irfan Pure Muhammad Jundullah Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muhammad Miftahul Amri Muhammad Noor Fadillah Muhammad Noor Fadillah Muhammad Nur Faiz Muhammad Nur Faiz Muhammad Rizki Setyawan Muhammad Sabiq Dzakwan Muhammad Sabiq Dzakwan Muhammad, Khairul Muis, Alwas Mukaromah, Iif Alfiatul Murinto Murinto Mushab Al Barra Mushlihudin Mushlihudin Mushlihudin Mushlihudin Mushlihudin, Mushlihudin Mushlihudin, Mushlihudin Musliman, Anwar Siswanto Nathalie Japkowicz Novi Febrianti Novitasari, Putri Rachma Nuraeni, Eneng Nurina Umy Habibah Nurwijayanti Nuryana, Zalik Nuryono Satya Widodo Ockhy Jey Fhiter Wassalam Peryanto, Ari Phisca Aditya Rosyady Prasongko, Riski Yudhi Pratama, Denny Yoga Pratama, Genta Pratama, Gilang Ariya PRATAMA, IGO PUTRA prayudi, Andi Prianto, Eko Prihatmadi, Farhan Adyaqsa Priyatno Priyatno Purnamaningsih, Nur’Aini Puspitasari, Etika Dyah Putra, Aji Surya Kurniawan Putra, Marta Dwi Darma Putra, Satriya Dwi Putra, Seno Aji Putri, Dadva Pramesty Etsria Rachmad Fitriyanto Rachmad Very Ananda Saputra Raden Mohamad Herdian Bhakti Rafal Drezewski Rahmawan, Jihad Raja Bidin Raja Hassan Ramadhani, Muhammad Ramdhani, Rezki Rani Rotul Muhima Rauhulloh Ayatulloh Khomeini Noor Bintang Renangga Yudianto Reski, Julia Mega Resmi Aini Retnosyari Septiyani Reza, Muhamad Fahrul Rezki Ramdhani Ridho Ikhram Rio Subandi Riski Prasongko Yudhi Prasongko Riski Yudhi Prasongko Rivai, Zulki Yanto Rizky Andhika Surya Rosyady, Phisca Aditya Ruly Erwin AfanDika Rumagia, Yusril Rusdi Umar Rusydi Umar Rusydi Umar Rusydi Umar Rusydi Umar S, Sunardi Sabarudin Saputra Saberi Mawi Sabila, Liya Yusrina Safiq Rosad Sahta, Bobo Saifullah, Shoffan Samadri Samadri Saputra, Candra Deska Saputra, I Gede Purwana Edi saputro, tahap Sarjimin Sarjimin Sarjimin, Sarjimin Satriya Dwi Putra Sefindra Purnama Seno Aji Putra Septa, Frandika Septiyani, Retnosyari Septiyawan Rosetya Wardhana Sharipah Salwa Mohamed Shoffan Saifullah Sidharta, Anggara Ibnu Sidiq, Ahmad Fajar Sigit Wijaya Silmina, Esi Putri Siswaya Siswaya Siswaya, Siswaya Siti Hajar Siti Helmiyah Siti Helmiyah Son Ali Akbar sri suharti Sri Suharti Subandi, Rio Sulistyo, Andhy Sunardi Sunardi - Sunardi - Sunardi Sunardi sunardi sunardi Sunardi, Sunardi Susilo Hartono Suwanti Suwanti Suyadi Suyadi Syafiqoh, Ummi Syahid Al Irfan Syahrani Lonang Syed Abdullah Syinta Brata Tarisno Amijoyo Tiara Widyakunthaningrum Tole Sutikno Tri Wahono Tugiman Tugiman Umar, Rusydi Ummi Syafiqoh Utama, Kgs Muhammad Rizky Alditra Utama, Kiagus Muhammad Rizky Aditra W, Yunanri Wahidah Mahanani Rahayu Wahyu Prawoto Wahyu Sapto Aji Wardani, Miko Wicaksono Yuli Sulistyo Wicaksono Yuli Sulistyo Widhianto, Trisno Wijaya, Setiawan Ardi Wilis Kaswijanti Windra Putri, Anggi Rizky Wintolo, Hero Wiwiek Afifah Yudianto, Renangga Yuli Rahmawati Yusril Rumagia Zeehaida Mohamed