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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Proceedings of KNASTIK Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika SPEKTRUM INDUSTRI Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknik Elektro Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Jurnal Pseudocode Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Teknologi Elektro INFORMAL: Informatics Journal Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) Edu Komputika Journal Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Informatika Jurnal Khatulistiwa Informatika Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal IT JOURNAL RESEARCH AND DEVELOPMENT InComTech: Jurnal Telekomunikasi dan Komputer Insect (Informatics and Security) : Jurnal Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Applied Information System and Management ILKOM Jurnal Ilmiah Compiler MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Sistem Informasi dan Aplikasi CYBERNETICS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi PHARMACY: Jurnal Farmasi Indonesia (Pharmaceutical Journal of Indonesia) JUMANJI (Jurnal Masyarakat Informatika Unjani) JURTEKSI RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Ilmiah Mandala Education (JIME) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Systemic: Information System and Informatics Journal Jurnal Teknologi Terpadu EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) Buletin Ilmiah Sarjana Teknik Elektro Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Journal of Robotics and Control (JRC) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Cyber Security dan Forensik Digital (CSFD) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal E-Komtek JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) International Journal of Advances in Data and Information Systems International Journal of Marine Engineering Innovation and Research Edunesia : jurnal Ilmiah Pendidikan JITU : Journal Informatic Technology And Communication Journal of Innovation Information Technology and Application (JINITA) Tematik : Jurnal Teknologi Informasi Komunikasi Infotech: Journal of Technology Information Jurnal Teknologi Informatika dan Komputer Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Humanism : Jurnal Pengabdian Masyarakat International Journal of Robotics and Control Systems J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Techno Wahana Jurnal Pengabdian Informatika (JUPITA) Sinteza Jurnal INFOTEL Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Accounting Information System (AIMS) Scientific Journal of Informatics Control Systems and Optimization Letters Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Signal and Image Processing Letters Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Edumaspul: Jurnal Pendidikan Methods in Science and Technology Studies JOCHAC Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Abdul Fadlil
Ahmad Dahlan University
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Optimalisasi Kinerja Convolutional Neural Networks VGG16 dalam Identifikasi Bangunan Adat Melayu Sri Winiarti; Sunardi, Sunardi; Fadlil, Abdul
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 8 No. 3 (2025): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v8i3.58210

Abstract

Penggunaan deep learning dalam mendeteksi berbagai objek sudah banyak diterapkan, namun untuk identifikasi kemiripan bangunan untuk gaya arsitektur masih terbatas. Analisis klasifikasi model desain arsitektur bangunan adat Melayu dapat dilakukan dengan menerapkan metode Convolusional Neural Network (CNN). Pendekatan yang digunakan untuk menganalisis klasifikasi dan kemiripan model bangunan adat melayu menggunakan model arsitektur VGG16. Ekstraksi fitur menggunakan model deep learning untuk mengidentifikasi jenis bangunan adat Melayu menggunakan parameter atap, jendela, dan ornamen bangunan. Dataset citra bangunan adat Melayu didapatkan dari pengambilan langsung ke lokasi bangunan adat melayu Riau di Kawasan Jalan Muhammad Arifin Pekanbaru Riau untuk training sebanyak 644 gambar dan testing model sebanyak 106 gambar. Model yang digunakan adalah VGG16. Parameter ukuran kinerja meliputi accuracy, precision, recall, dan F1-score. Akurasi yang didapatkan dalam penelitian ini adalah 98,77% dari total 106 data yang diuji, sedangkan precision 0,8678, recall 0,9633, dan F1-score 0,9877. Hasil yang didapatkan ini melalui setting parameter learning rate 0,0001, drop out 0,20, dan epoch sebesar 25. Secara keseluruhan model VGG16 yang digunakan dalam penelitian ini menghasilkan akurasi yang baik.
Weight Estimation of Broiler Ducks Based on Image Processing and Machine Learning with IoT Integration Mukti, Sindhu Hari; ardi, Ardi Pujiyanta; Fadlil, Abdul
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11259

Abstract

The broiler duck farming industry in Indonesia faces challenges in efficiently monitoring body weight, as traditional manual weighing methods are labor-intensive, time-consuming, and stressful for the animals. To address this issue, this study aims to develop a non-invasive and automated weight estimation system that integrates digital image processing, machine learning, and Internet of Things (IoT) technologies. The methodology involves acquiring multi-angle images of ducks, applying preprocessing steps such as resizing, normalization, and contrast enhancement, and extracting hand-crafted features, including Histogram of Oriented Gradients (HOG) and HSV color histograms. These features are then fused, reduced via Principal Component Analysis (PCA), and processed using a Support Vector Regression (SVR) model with optimized hyperparameters for weight prediction. While previous studies have focused on cattle, broilers, or fish, research specifically targeting meat-type ducks remains limited, particularly those that combine image-based regression with IoT-enabled real-time monitoring. Experimental results demonstrate that the proposed system achieves a mean absolute error (MAE) of approximately 110 grams on the validation set, with per-duck averaging improving stability compared to per-image predictions. Visualization through scatter plots, boxplots, and learning curves further confirms that the model effectively captures general weight distribution trends but exhibits higher errors in certain mid-weight ranges. The integration with IoT facilitates continuous, stress-free monitoring of duck growth, underscoring the system’s potential as a practical and sustainable solution for precision livestock farming.
Optimalisasi Pemetaan Klaster Kependudukan Provinsi di Indonesia Menggunakan Elbow Method dan Davies-Bouldin Index Nilam Tri Astuti; Sunardi; Fadlil, Abdul
Jurnal Informatika Polinema Vol. 12 No. 2 (2026): Vol. 12 No. 2 (2026)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i2.9162

Abstract

Ketimpangan distribusi dan dinamika pertumbuhan penduduk antarprovinsi di Indonesia menimbulkan tantangan serius dalam perencanaan pembangunan yang berkeadilan dan berkelanjutan. Perbedaan jumlah penduduk, laju pertumbuhan, serta kontribusi terhadap total populasi nasional berimplikasi pada variasi kebutuhan infrastruktur, layanan publik, dan kapasitas wilayah dalam menopang aktivitas sosial-ekonomi. Oleh karena itu, diperlukan pendekatan analitik yang mampu mengelompokkan provinsi berdasarkan kesamaan karakteristik demografis guna mendukung perumusan kebijakan yang lebih terarah. Penelitian ini bertujuan memetakan pola kependudukan antarprovinsi di Indonesia menggunakan algoritma K-Means berdasarkan tiga variabel utama, yaitu rata-rata jumlah penduduk, laju pertumbuhan penduduk, dan persentase distribusi penduduk. Data sekunder yang digunakan bersumber dari Badan Pusat Statistik (BPS) periode 2016-2023 dan dirata-ratakan untuk merepresentasikan kondisi demografi jangka menengah yang relatif stabil. Seleksi variabel dilakukan melalui analisis korelasi, kemudian data dinormalisasi menggunakan Z-score untuk memastikan kesetaraan skala antarvariabel. Penentuan jumlah klaster optimal dilakukan dengan Elbow Method dan divalidasi menggunakan Davies-Bouldin Index (DBI). Hasil analisis menunjukkan titik siku pada k = 4 dan nilai DBI minimum sebesar 0,4430 pada k = 4, yang lebih rendah dibandingkan k = 2 (0,4838) dan k = 3 (0,8006), sehingga empat klaster dinilai sebagai struktur pengelompokan paling representatif. Klasterisasi menghasilkan empat kelompok demografis yang mencerminkan karakteristik berbeda, mulai dari provinsi dengan populasi sangat besar, wilayah berpertumbuhan tinggi dengan jumlah penduduk relatif kecil, kelompok moderat, hingga wilayah dengan kepadatan ekstrem. Temuan ini menunjukkan bahwa pendekatan K-Means yang didukung validasi kuantitatif mampu menggambarkan heterogenitas demografi Indonesia secara lebih terstruktur serta berpotensi menjadi dasar dalam perencanaan pembangunan berbasis karakteristik wilayah.
PENGUJIAN APLIKASI MENGGUNAKAN WHITE BOX DENGAN METODE UNIT TESTING. STUDI KASUS: MAHATI Haksono, Muhammad Rizky; Nuryasin, Ilyas; Muthorihin, Bashor Fauzan; Titani, Mutiara; Akrom, Akrom; Fadlil, Abdul
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.7012

Abstract

Perkembangan pesat industri perangkat lunak secara signifikan dipengaruhi oleh kemajuan teknologi informasi dan digital. Salah satu aspek penting dalam perkembangan ini adalah peningkatan efisiensi pengujian perangkat lunak. Pengujian perangkat lunak saat ini tidak hanya berfokus pada aspek fungsionalitas, tetapi juga mencakup kinerja, keamanan, dan kompatibilitas. Penelitian ini berfokus pada peningkatan efisiensi pengujian perangkat lunak dengan menerapkan metode White-Box Testing. Penerapannya diuji pada aplikasi MAHATI melalui unit testing dengan teknik Branch Coverage dan Statement Coverage untuk memastikan cakupan fungsionalitas dan logika program secara komprehensif. Penelitian ini menekankan desain kode yang terstruktur dan mudah diuji, sehingga proses pengujian menjadi lebih efisien dan efektif dalam mendeteksi kesalahan. Hasil penelitian menunjukkan bahwa desain kode yang baik secara signifikan berkontribusi terhadap kualitas dan keandalan perangkat lunak melalui pengujian yang optimal dan efisien. Keberhasilan seluruh 12 suite pengujian dan 65 tes individu membuktikan bahwa setiap fungsi aplikasi bekerja sesuai dengan harapan, sehingga menunjukkan efektivitas metode pengujian yang diterapkan. Hasil ini menguatkan keyakinan bahwa White-Box Testing merupakan metode yang efektif dalam meningkatkan kualitas perangkat lunak dan dapat diaplikasikan untuk meningkatkan kualitas aplikasi lain.
User’s Satisfaction Analysis of the Academic Information Systems Quality using the Modified Webqual 4.0 Method and Importance-Performance Analysis Anwarudin, Aang; Fadlil, Abdul; Yudhana, Anton
ILKOM Jurnal Ilmiah Vol 15, No 1 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i1.1531.132-143

Abstract

Currently, the academic information system (AIS) at universities processes academic data to facilitate student’s activities. AIS was developed to provide maximum service to students. To optimize the use of information technology and to ensure the appropriateness of the provided AIS services, it is necessary to examine the level of service provided to improve quality. This study aimed to analyze the level of AIS service quality based on user perceptions and expectations. Dissemination of online questionnaires using Google Forms with a total of 100 students as respondents. This study used the modified Webqual 4.0 method as an indicator in the preparation of the questionnaire and the importance-performance analysis (IPA) method as an analysis method. The results of data were classified based on the percentage of user’s satisfaction with AIS services with three classifications, namely good, moderate, and poor. The results of the IPA analysis showed that the AIS had good quality. The results obtained from the analysis of the quality of the AIS system had a conformity level of 90.90%, where respondents perceived close to satisfaction with AIS services. The gap level was -0.3281 which was the result of the perception/performance of the AIS that was not in line with the expectations of the user. The results of this study contribute to Universitas Muhammadiyah Gombong as reference material and evaluation of AIS system services in the future.
ANALISIS EMPIRIS PERBANDINGAN KINERJA METODE HASHING PROGRESSIVE OVERFLOW DAN LINEAR QUOTIENT DALAM STUDI PEMBUATAN APLIKASI DEKSTOP ADMINISTRASI KEPEGAWAIAN Prianto, Eko; Yudhana, Anton; Fadlil, Abdul
ILKOM Jurnal Ilmiah Vol 8, No 3 (2016)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v8i3.66.174-181

Abstract

Administrasi merupakan kegiatan sehari-hari yaitu berupa kegiatan mencatat, mengumpulkan dan menyimpan suatu kegiatan atau hasil kegiatan sehingga membutuhkan memori guna menyimpan itu semua. Untuk memudahkan proses pencarian data yang telah disimpan dengan cepat, maka diperlukan suatu metode, yaitu menggunakan metode hashing. Penerapan manajemen memory bertujuan, agar mencegah adanya perulangan data yang sama, manajemen basis data yang baik, manajemen memori dan memberikan kemudahan untuk mengakses data dengan cepat walaupun data yang ada sangat banyak, dengan memasukkan kata kunci yang telah ditentukan dapat mencari data dan menampilkan dengan akurasi waktu yang dibutuhkan sebentar. Dengan metode progressive overflow dan linear quotient akan dianalisis nilai rata-rata dari setiap metode, nilai yang paling kecil dari metode tersebut adalah nilai yang terbaik akan digunakan sebagai pedoman seberapa besar nilai proses hashing dalam sebuat database suatu instansi dan sebagai studi kasus penentuan penyediaan memori yang dibutuhkan.
Digital Cockpit Multiplatform Modular dari Human Digital Twin Herman; Zein, Wahid Alfaridsi Achmad; Fadlil, Abdul
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

Teknologi Digital Twin (DT) telah diadaptasi menjadi Human Digital Twin (HDT) untuk pemantauan kesehatan secara real-time. Namun, sistem pemantauan kesehatan berbasis HDT saat ini terkendala masalah skalabilitas, fleksibilitas antarmuka, dan ketergantungan pada koneksi internet. Arsitektur monolitik konvensional menghambat integrasi fitur dan adaptasi platform, sementara kebutuhan akan layanan berkelanjutan seringkali tidak terpenuhi. Untuk mengatasi kesenjangan penelitian ini, studi ini mengusulkan solusi dengan merancang dan mengimplementasikan Digital Cockpit (DC) Multiplatform Modular untuk HDT kardiovaskular. Penelitian ini menerapkan arsitektur modular untuk memisahkan lapisan antarmuka depan dan antarmuka belakang. Struktur ini mempermudah integrasi layanan masa depan seperti AI dan LLM. Antarmuka depan diimplementasikan sebagai Progressive Web Application (PWA) untuk memastikan kompatibilitas lintas platform dan memberikan kemampuan offline penting menggunakan Service Worker untuk caching dan pengambilan data. Kami memvalidasi sistem melalui Blackbox Testing dan Compatibility Testing di lingkungan Laptop, iOS, dan Android. Pengujian Blackbox menunjukkan keberhasilan 100% pada seluruh fungsi inti, termasuk sinkronisasi data real-time dan caching offline. Penggunaan basis kode tunggal pada PWA secara signifikan mengurangi kompleksitas pengembangan antar platform dengan tetap mempertahankan skor kompatibilitas sebesar 89,58% di berbagai perangkat. Sistem DC berbasis PWA ini memberikan solusi yang terukur dengan menggabungkan fleksibilitas web dan kinerja aplikasi native bagi sistem pemantauan kesehatan digital.   Abstract Digital Twin (DT) technology has been adapted into Human Digital Twin (HDT) for real-time health monitoring. However, current HDT-based health monitoring systems are hampered by issues of scalability, interface flexibility, and dependence on internet connection. Conventional monolithic architecture hinders feature integration and platform adaptation, while the need for continuous service is often unmet. To address this research gap, this study proposes a solution by designing and implementing a Modular Multiplatform Digital Cockpit (DC) for cardiovascular HDT. This study applies a modular architecture to separate the front-end and back-end layers. This structure facilitates the integration of future services such as AI and LLM. The front-end is implemented as a Progressive Web Application (PWA) to ensure cross-platform compatibility and provides essential offline capabilities using Service Workers for data caching and retrieval. The system was validated through Blackbox Testing and Compatibility Testing on Laptop, iOS, and Android environments. Blackbox testing demonstrated 100% success across all core functions, including real-time data synchronization and offline caching. The use of a single codebase in PWAs significantly reduces cross-platform development complexity while maintaining a compatibility score of 89.58% across devices. This PWA-based DC system provides a scalable solution for digital health monitoring systems, combining the flexibility of the web with the performance of native apps.
Non-linear Kernel Optimisation of Support Vector Machine Algorithm for Online Marketplace Sentiment Analysis Abdul Fadlil; Imam Riadi; Fiki Andrianto
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.19798

Abstract

Twitter is a social media platform that is very important in the digital world. Fast communication and interaction make Twitter a vital information center in sentiment analysis. The purpose of this research is to classify public opinion about the presence of marketplaces in Indonesia, both positive and negative sentiments, using a Non-linear SVM algorithm based on 1276 tweets. This research involves the stages of data pre-processing, labeling, feature extraction using TF-IDF, and data division into three scenarios: 80% training data and 20% test data, 50% training data and 50% test data scenario, and 20% training data and 80% test data scenario. The last process, GridSearchCV, combines cross-validation and non-linear SVM parameters for model evaluation using a confusion matrix. The best SVM model resulting from the scenario was 80% training and 20% test data, with hyperparameters Gamma = 100 and C = 0.01, achieving 89% accuracy. When tested on never-before-seen data, the accuracy increased to 90%, with an f1-score of 91%, precision of 88%, and recall of 95% on negative sentiments. In conclusion, evaluating the performance of non-linear SVM kernels with a combination of hyperparameter values can improve accuracy, especially on public response information about online marketplaces and public sentiment.
KLASIFIKASI JENIS KULIT WAJAH MENGGUNAKAN ALGORITMA RANDOM FOREST Irwansyah Irwansyah; Anton Yudhana; Abdul Fadlil
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.423

Abstract

Skin can be considered the largest organ in the human body. Healthy skin is not only good for the body, but alsoenhances the appearance. Good skin care is essential at any age. In the first few decades of life, the skin has aconsiderable supply of elastin and collagen, but it will gradually decrease. In addition, daily lifestyle can also directlyaffect the appearance of human skin. The purpose of the research is to develop a model that classifies facial skin typesbased on physiological data using random forest algorithm and measure the results of accuracy, precision, and recall.This research uses Rapidminer tools and four facial skin types namely dry, combination, normal, and oily. The resultsof random forest research obtained accuracy results of 93.25%. dry precision 98.02%, combination precision 92.94%,normal precision 93.46%, and oily precision 88.79%. While dry recall 99%, combination recall 79%, normal recall100%, and oily recall 95%. The findings of this research can help create a skincare recommendation system that ismore suited to the needs of each individual.
Optimization of Convolutional Neural Network (CNN) Using Transfer Learning for Disease Identification in Rice Leaf Images Abdul Azis; Abdul Fadlil; Tole Sutikno
Jurnal E-Komtek Vol 8 No 2 (2024)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v8i2.2132

Abstract

Rice productivity, as one of the key commodities in Southeast Asia, is often hindered by various plant diseases such as Rice Blast, Bacterial Leaf Blight, and Brown Spot, which can cause significant economic losses for farmers. This study aims to develop an automated rice leaf disease detection system using deep learning, specifically leveraging the Convolutional Neural Networks (CNN) architecture with a transfer learning approach. The dataset used comprises 10,407 images of rice leaves categorized into 10 classes, including various diseases and healthy leaves. The dataset is divided into three parts: 80% (8,323 images) for training, 15% (1,557 images) for validation, and 5% (527 images) for testing. The trained EfficientNetB0 model was utilized for feature extraction and classification. The evaluation used accuracy, precision, recall, and F1-score metrics based on a confusion matrix. The results revealed that the model achieved a global accuracy of 98.86%, a micro precision of 100%, a micro recall of 99.42%, and a micro F1-score of 99.70%. These findings underscore the effectiveness of the proposed approach in automating rice leaf disease detection, providing a significant contribution to technology-based agricultural solutions.
Co-Authors Aang Anwarudin Abdul Azis Abdul Azis Achmad Nugrahantoro Aditiya Dwi Candra Adnan, Adnan Ahmad Naufal Ahmat Taufik Aji Pamungkas Akrom, Akrom Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Amiruddin, Nanda Fahmi Andi Zulherry Andrianto, Fiki Anggit Pamungkas Annisa, Putri Anton Yudhana Anton Yudhana Anwar Siswanto ANWAR, FAHMI Anwarudin, Aang Aqid Fahri Hafin ardi, Ardi Pujiyanta Arief Setyo Nugroho Arief Setyo Nugroho Arif Budi Setianto Arif Budiman Arif Budiman Arif Wirawan Muhammad Asep Ririh Riswaya Asno Azzawagama Firdaus Atmojo, Dimas Murtia Aulia, Aulia Az-Zahra, Rifqi Rahmatika Aznar Abdillah, Muhamad Bagus Primantoro Bambang Priambodo Bashor Fauzan Muthohirin Basir, Azhar Candra, Aditiya Dwi Darajat, Muhammad Nashiruddin Davito Rasendriya Rizqullah Putra Dedy Sumarhadi Dewi Soyusiawaty Dewi Soyusiawaty Dheni Apriantsani Budiman Dhimas Dwiki Sanjaya Dian Novianti Dian Permata Sari Dianda Rifaldi Dikky Praseptian M Dimas Murtia Atmojo Doddy Teguh Yuwono Dwi Susanto Dwi Susanto Edy Fathurrozaq Egi Dio Bagus Sudewo Eko Budi Cahyono Eko Prianto Eko Prianto, Eko Elvina, Ade Endang Darmawan Endang Darmawan Ermin Al Munawar Ermin Ermin Esthi Dyah Rikhiana Fahmi Anwar Fahmi Auliya Tsani Fahmi Auliya Tsani Fahmi Fachri Fanani, Galih Faqihuddin Al-anshori Faqihuddin Al-Anshori, Faqihuddin Fathurrahman, Haris Imam Karim Fauzi Hermawan Fiki Andrianto Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Yasin Fitri Muwardi Furizal Gusrin, Muhaimin Gustina, Sapriani Hafizh, Muhammad Nasir Haksono, Muhammad Rizky Hanif, Abdullah Hanif, Kharis Hudaiby Harman, Rika Helmiyah, Siti Hendril Satrian Purnama Herdiyanto, Erik Herman Herman Herman Herman Herman Yuliansyah Herman Yuliansyah, Herman Herman, - Ibnu Rifajar Ibrahim Mohd Alsofyani Ihyak Ulumuddin Ikhsan hidayat Ilhamsyah Muhammad Nurdin Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imroatul Khuluqi Izzah Indah Purnama Sari Irjayana, Rizky Caesar Irwansyah Irwansyah Itsnaini Irvina Khoirunnisa Izzan Julda D.E Purwadi Putra januari audrey Jayawarsa, A.A. Ketut Jody Yuantoro Jogo Samodro, Maulana Muhamammad Joko Supriyanto Joko Supriyanto Kamilah, Farhah Kartika Firdausy Khairul Nisa Panilestari Khoirunnisa, Itsnaini Irvina Kusuma, Nur Makkie Perdana Laura Sari Lestari, Yuniarti Lin, Yu-Hao Luh Putu Ratna Sundari M. Nasir Hafizh Maftukhah, Ainin Maulana Muhammad Jogo Samudro Mhd. Basri Miftahul Rozak Mini, Ros Mohd Hatta Jopri Muammar Mudinillah, Adam Mufaddal Al Baqir Muh. Fadli Hasa Muhaimin Gusrin Muhajir Yunus Muhamad Daffa Al Fitra Muhamad Rosidin Muhammad Arief Sutisna Muhammad Faqih Dzulqarnain Muhammad Faqih Dzulqarnain, Muhammad Faqih Muhammad Johan Wahyudi Muhammad Kunta Biddinika Muhammad Ma’ruf Muhammad Nasir Hafizh Muhammad Noko Darpito Muhammad Nuh Muhammad Nur Faiz Muhammad Nurdin, Ilhamsyah Muhammad Rizki Setyawan Mukti, Sindhu Hari Munawaroh Munawaroh Muntiari, Novita Ranti Murinto Murinto - Murinto Murinto Murni Musliman, Anwar Siswanto Mustofa Mustofa Muthorihin, Bashor Fauzan Mutiara Titani Mutiara Titani Muwardi, Fitri Nasution, Dewi Sahara Nasution, Musri Iskandar Nilam Tri Astuti Nopi Hidayat Nurwijayanti Nuryasin, Ilyas Pahlevi, Ryan Fitrian Ponco Sukaswanto Poni Wijayanti Prabowo Soetadji Prabowo, Basit Adhi Prayogi, Denis Putra, Fajar R. B Putri Annisa Putri Annisa Putri Purnamasari Ramadhani, Muhammad Ramdhani, Rezki Razak, Farhan Radhiansyah Rezki Rezki Rifqi Rahmatika Az-Zahra Rizky Andhika Surya Rochmadi, Tri Rohmat Ibrahim Roni Anggara Putra Rusydi Umar Rusydi Umar S Sunardi S, Sunardi Saad, Saleh Khalifah Safiq Rosad Saifudin Saifudin Saifullah, Shoffan Saleh khalifa saad Santi Purwaningrum Sarmini Sarmini Sarmini Sarmini Septa, Frandika Setyaputri, Khairina Eka Setyaputri, Khairina Eka Setyaputri, Khairina Eka Shinta Nur Desmia Sari Sri Winiarti Sri Winiarti Subandi, Rio Sugiyarto Surono Sugiyarto Surono Sukaswanto, Ponco Sukma Aji Sulis Triyanto Sunardi Sunardi Sunardi Sunardi Sunardi, Sunardi Surya Yeki Surya Yeki Syamsiar, Syamsiar Syarifudin, Arma Tole Sutikno Tresna Yudha Prawira Tri Ferga Prasetyo Tri Ferga Prasetyo Tri Rochmadi Tristanti, Novi Tuswanto Tuswanto Virdiana Sriviana Fatmawaty Wahju Tjahjo Saputro Wahyusari, Retno Winoto, Sakti Wulandari, Cisi Fitri Yana Mulyana Yana Mulyana Yanuar Wicaksono Yasidah Nur Istiqomah Yeki, Surya Yohanni Syahra Yossi Octavina Yulianto, Dinan Yulianto, Muhammad Anas Yuminah yuminah yuminah, Yuminah Yuminah, Yuminah Yuwono Fitri Widodo Zein, Wahid Alfaridsi Achmad Zulhijayanto -