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Enhanced Vision Transformer and Transfer Learning Approach to Improve Rice Disease Recognition Rachman, Rahadian Kristiyanto; Setiadi, De Rosal Ignatius Moses; Susanto, Ajib; Nugroho, Kristiawan; Islam, Hussain Md Mehedul
Journal of Computing Theories and Applications Vol. 1 No. 4 (2024): JCTA 1(4) 2024
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.10459

Abstract

In the evolving landscape of agricultural technology, recognizing rice diseases through computational models is a critical challenge, predominantly addressed through Convolutional Neural Networks (CNN). However, the localized feature extraction of CNNs often falls short in complex scenarios, necessitating a shift towards models capable of global contextual understanding. Enter the Vision Transformer (ViT), a paradigm-shifting deep learning model that leverages a self-attention mechanism to transcend the limitations of CNNs by capturing image features in a comprehensive global context. This research embarks on an ambitious journey to refine and adapt the ViT Base(B) transfer learning model for the nuanced task of rice disease recognition. Through meticulous reconfiguration, layer augmentation, and hyperparameter tuning, the study tests the model's prowess across both balanced and imbalanced datasets, revealing its remarkable ability to outperform traditional CNN models, including VGG, MobileNet, and EfficientNet. The proposed ViT model not only achieved superior recall (0.9792), precision (0.9815), specificity (0.9938), f1-score (0.9791), and accuracy (0.9792) on challenging datasets but also established a new benchmark in rice disease recognition, underscoring its potential as a transformative tool in the agricultural domain. This work not only showcases the ViT model's superior performance and stability across diverse tasks and datasets but also illuminates its potential to revolutionize rice disease recognition, setting the stage for future explorations in agricultural AI applications.
Facial Expression Recognition using Convolutional Neural Networks with Transfer Learning Resnet-50 Istiqomah, Annisa Ayu; Sari, Christy Atika; Susanto, Ajib; Rachmawanto, Eko Hari
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8329

Abstract

Facial expression recognition is important for many applications, including sentiment analysis, human-computer interaction, and interactive systems in areas such as security, healthcare, and entertainment. However, this task is fraught with challenges, mainly due to large differences in lighting conditions, viewing angles, and differences in individual eye structures. These factors can drastically affect the appearance of facial expressions, making it difficult for traditional recognition systems to consistently and accurately identify emotions. Variations in lighting can alter the visibility of facial features, while different angles can obscure critical details necessary for accurate expression detection. This study addresses these issues by employing transfer learning with ResNet-50 and effective pre-processing techniques. The dataset consists of grayscale images with a 48 x 48 pixels resolution. It includes a total of 680 samples categorized into seven classes: anger, contempt, disgust, fear, happy, sadness, and surprise. The dataset was divided so that 80% was allocated for training and 20% for testing to ensure robust model evaluation. The results demonstrate that the model utilizing transfer learning achieved an exceptional performance level, with accuracy at 99.49%, precision at 99.49%, recall at 99.71%, and an F1-score of 99.60%, significantly outperforming the model without transfer learning. Future research will focus on implementing real-time facial recognition systems and exploring other advanced transfer learning models to further enhance accuracy and operational efficiency.
Pengembangan Website Desa Ratamba Kecamatan Pejawaran Kabupaten Banjarnegara Untuk Meningkatkan Pemasaran Dan Penjualan Produk Pertanian Mulyono, Ibnu Utomo Wahyu; Susanto, Ajib; Kusumawati, Yupie; Ningrum, Novita Kurnia; Umami, Zahrotul; Widyatmoko, Karis; Sudaryanto, Sudaryanto
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 7, No 2 (2024): MEI 2024
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v7i2.2076

Abstract

Dieng Kabupaten Banjarnegara memiliki iklim yang cocok untuk pertanian sayuran. Khususnya di Desa Ratamba Kecamatan Pejawaran Kabupaten Banjarnegara memiliki komoditas pertanian kentang dan wortel. Untuk saat ini hasil panen dipasarkan secara konvensional dengan mengumpulkan hasil panen pada pengepul dan mengirimkan ke pasar untuk selanjutnya dikirim ke beberapa daerah di sekitar kabupaten Banjarnegara. Pemasaran dengan metode konvensional sudah dilakukan dalam jangka waktu yang cukup lama. Akan tetapi ada celah kekurangan yang terjadi di rantai distribusi dalam proses bisnis pertanian tersebut. Salah satunya adalah petani tidak dapat menentukan harga sayuran hasil panennya karena distribusi sayuran harus melalui pengepul atau tengkulak terlebih dahulu. Sehingga yang menentukan harga di pasar adalah pengepul, bukan oleh petani secara langsung. Selain itu, petani juga tidak dapat memperluas jangkauan pemasaran hasil pertaniannya. Disebabkan distribusi barang tidak dilakukan oleh petani akan tetapi oleh dilakukan oleh pengepul juga. Oleh karena alasan tersebut maka pada pengabdian pada masyarakat ini dikembangkan website yang dapat diakses oleh petani di Desa Ratamba untuk memasarkan dan menjual hasil pertanian mereka secara langsung. Dengan adanya media online yang digunakan oleh petani diharapkan dapat meningkatkan pendapatan dan kesejahteraan para petani. Dengan demikian diharapkan petani dapat terus mempertahankan dan meingkatkan kualitas hasil pertanian mereka
Implementasi Content Placement pada Pemasaran Digital pada Program Kepemudaan PKKP Disporapar Jawa Tengah Ningrum, Novita Kurnia; Susanto, Ajib Susanto; Kusumawati, Yupie; Widyatmoko, Karis; WM, Ibnu Utomo
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 7, No 3 (2024): SEPTEMBER 2024
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v7i3.2472

Abstract

Pemerintah Provinsi Jawa Tengah melalui Program Kepedulian dan Kepeloporan Pemuda (PKKP) dari Dinas Pemuda dan Olahraga Jawa Tengah atau Dispora Jateng memberikan perhatian untuk mendukung pemuda di wilayah Provinsi Jawa Tengah berkembang dan mampu mengembangkan potensi yang ada di daerah masing masing. Pada bulan Mei 2024 Dispora Jateng bekerjasama dengan Udinus menyelenggarakan kegiatan workshop dan seminar dengan topik materi digital content. Salah satu aspek yang dimiliki pemuda dalam berpartisipasi di PKKP adalah memiliki ide atau konsep berupa produk yang dapat menunjang kemajuan daerahnya masing-masing. Produk dapat berupa produk barang ataupun jasa, begitupun dapat berupa hardware ataupun software. Adapula produk yang mereka baa berupa produk budaya local yang memiliki potensi wisata sehingga mampu mengundang masyarakat dari daerah lain untuk mengenal dan berkunjung ke daerah tersebut. Adapun ide dan konsep yang sudah ada baik yang udah berjalan maupun akan dijalankan menghadapi kendala berkaitan dengn penggunaan teknologi untuk meningkatkan efektifitas pengenalan dan pemasaran dalam lingkup yang luas. Salah satu hal yang belum dimiliki oleh para peserta PKKP adalah bagaimana memproduksi konten yang dapat memeberikan impact terhadap peningkatan pemasaran produk yang mereka miliki. Oleh karena pentingnya pemahaman dan ketrampilan menggunakan teknologi untuk digital marketing, maka pada  kegiatan seminar dan workshop yang diselenggarakan pada bulan Mei ini, salah satu ketrampilan yang dibagikan adalah content placement yaitu bagaimana menjadikan digital content yang diposting di media sosial dapat diakses oleh masyarakat luas. Dalam hal ini masyarakat yang dimaksudkan adalah bagaimana mengarahkan masyarakat sesuai dengan target market sehingga efektif dalam menggunakan sumberdaya untuk pemasaran produk. Efektifitas penggunaaan teknologi untuk digital marketing memberikan keuntungan dalam pengembangan produk yaitu kemampuan menjangkau pasar yang luas dengan waktu yang dibutuhkan relatif lebih efisien sehingga biaya pemasaran menjadi lebih murah dibandingkan dengan conventional marketing. 
Implementation of Tesseract OCR and Bounding Box for Text Extraction on Food Nutrition Labels Saputra, The Manuel Eric; Susanto, Ajib; Carmelita, Bastiaans Jessica
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6107

Abstract

This study focuses on implementing Optical Character Recognition (OCR) using the Tesseract engine, integrated with bounding box detection, to extract nutritional information from food nutrition labels. The research addresses the challenge of limited consumer access to and understanding of nutritional data, a factor contributing to health issues such as obesity and related metabolic disorders. Studies indicate that although Indonesian consumers generally have a good level of knowledge and positive attitudes toward nutritional labels, the actual behavior of reading and understanding these labels remains limited. Additionally, packaged foods consumed outside the home constitute a significant portion of daily caloric intake, which can lead to health complications if not properly managed. With obesity levels among adults in Indonesia rising to concerning rates, this study highlights the importance of providing accessible nutritional data. In this work, MobileNetV1 is used as the backbone model for bounding box detection, effectively identifying and isolating label regions to enhance OCR accuracy. Tesseract OCR, known for its LSTM-based architecture, is applied to predict sequential data patterns, such as rows of text on nutrition labels. Preprocessing techniques, including grayscale conversion, brightness adjustment, CLAHE (Contrast Limited Adaptive Histogram Equalization), and denoising, are used to improve text clarity and further refine OCR output accuracy. Post-processing steps involve rule-based and contextual error correction to handle common OCR inaccuracies. Evaluated on 10 different label images, the system achieved a maximum Word Error Rate (WER) of 10% and a Character Error Rate (CER) of 1.6%, demonstrating high accuracy in nutritional information extraction.
Implementation of Item-Based Collaborative Filtering Algorithm for Blangkon Product Recommendation on Web-Based E-commerce System Atmojo, Cahyo Tri; Susanto, Ajib
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6120

Abstract

In the development of technology at this time, especially in the trade sector, there is no escape from the development of information technology which has had a significant impact. The most obvious form in the development of information technology in the trade sector is e-commerce, which allows transactions between sellers and buyers to be easier. Not only that, the problem now is that users must be spoiled with features that help to recommend user desires. This requires a recommendation system to help select user desires based on products with high ratings. Therefore, it must continue to develop a system that has features to support the sales system. To achieve the system needs to require a method that supports such as using the collaborative filtering method. This method focuses the analysis on similarities between items, because it is more stable and not always sensitive to changing data with a large number of users. The collaborative filtering method is used in the recommendation system to predict inter-user preferences for blangkon products based on the similarity of other user patterns, so that product recommendations appear that they have never seen or bought before. This technique uses an item-based model in it. The results of the performance test to determine the level of prediction accuracy of the method in this study using the mean absolute error. With MAE for three times trying to get a value of 0.5, 0.3 and 0.2.
Javanese Character Recognition Based on K-Nearest Neighbor and Linear Binary Pattern Features Susanto, Ajib; Mulyono, Ibnu Utomo Wahyu; Sari, Christy Atika; Rachmawanto, Eko Hari; Ali, Rabei Raad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 3, August 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i3.1491

Abstract

Javanese script (Hanacaraka) is one of the cultures owned by Indonesia. Javanese script is found in temples, inscriptions, cultural and prehistoric sites, ancient Javanese manuscripts, Gulden series banknotes, street signage, and palace documents. Javanese script has a form with an article, and the use of reading above the script is a factor that affects the character detection process. Punctuation marks, clothing, Swara script, vowels, and consonants are parts of the script that are often found in Javanetest scripts. Preserving Javanese script in the digital era, of course, must use technology that can support the digitization of Javanese script through the script detection process. The concept of script image is the image of Javanese script in ancient manuscripts. The process of character detection using certain techniques can be carried out to extract characters so that they can be read. Detection of Javanese characters can be found by finding a testing image. Here, we had been used 10 words images consisting of 3 to 5 syllables with the vowel aiu. Dataset process by Linear Binary Pattern (LBP) feature extraction, which is used to characterize images and describe image textures locally. LBP has been used in r=4 and preprocessing is also done by thresholding with d=0.3. This process can be done using the K-Nearest Neighbor algorithm. In 10 datasets of Javanese script words, an average accuracy value of 90.5% was obtained. The accuracy value of 100% is the highest and 50% is the lowest.
Implementasi Digital Payment Gateway Midtrans Pada Sistem Agribisnis Di Temanggung (SIADIT) Ramadhan, Aditya Wahyu; Susanto, Ajib; Saraswati, Galuh Wilujeng
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.574

Abstract

The agribusiness system in Pagergunung Village has not been fully functioning properly. Based on the results of the survey that the author conducted, production was not optimal due to several factors including extreme weather changes, pest and disease attacks and low knowledge of the technology used and declining sales prices at harvest. In this era of the industrial revolution 4.0, all areas of life will involve the role of information and communication technology, one of which is in the field of agriculture. The application of technology in agriculture can be realized in the form of making a website for selling agricultural products so as to increase people's income through the creation of an agribusiness system, especially a marketing system through an e-marketplace that is connected to a paymet gateway. From the results of the blackbox test with a total of 25 respondents stated that online marketing media through the SIADIT e-marketplace application facilitates product promotion so as to increase farmers' income.
Implementasi Digital Payment Gateway Midtrans Pada Sistem Agribisnis Di Temanggung (SIADIT) Ramadhan, Aditya Wahyu; Susanto, Ajib; Saraswati, Galuh Wilujeng
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.574

Abstract

The agribusiness system in Pagergunung Village has not been fully functioning properly. Based on the results of the survey that the author conducted, production was not optimal due to several factors including extreme weather changes, pest and disease attacks and low knowledge of the technology used and declining sales prices at harvest. In this era of the industrial revolution 4.0, all areas of life will involve the role of information and communication technology, one of which is in the field of agriculture. The application of technology in agriculture can be realized in the form of making a website for selling agricultural products so as to increase people's income through the creation of an agribusiness system, especially a marketing system through an e-marketplace that is connected to a paymet gateway. From the results of the blackbox test with a total of 25 respondents stated that online marketing media through the SIADIT e-marketplace application facilitates product promotion so as to increase farmers' income.
High-Performance Face Spoofing Detection using Feature Fusion of FaceNet and Tuned DenseNet201 Zuama, Leygian Reyhan; Setiadi, De Rosal Ignatius Moses; Susanto, Ajib; Santosa, Stefanus; Gan, Hong-Seng; Ojugo, Arnold Adimabua
Journal of Future Artificial Intelligence and Technologies Vol. 1 No. 4 (2025): March 2025
Publisher : Future Techno Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/faith.3048-3719-62

Abstract

Face spoofing detection is critical for biometric security systems to prevent unauthorized access. This study proposes a deep learning-based approach integrating FaceNet and DenseNet201 to enhance face spoofing detection performance. FaceNet generates identity-based embeddings, ensuring robust facial feature representation, while DenseNet201 extracts complementary texture-based features. These features are fused using the Concatenate function to form a more comprehensive representation for im-proved classification. The proposed method is evaluated on two widely used face spoofing datasets, NUAA Photograph Imposter and LCC-FASD, achieving 100% accuracy on NUAA and 99% on LCC-FASD. Ablation studies reveal that data augmentation does not always enhance performance, particularly on high-complexity datasets such as LCC-FASD, where augmentation increases the False Rejection Rate (FRR). Conversely, DenseNet201 benefits more from augmentation, while the proposed method performs best without augmentation. Comparative analysis with previous studies further confirms the superiority of the proposed approach in reducing error rates, particularly Half Total Error Rate (HTER), False Acceptance Rate (FAR), and FRR. These findings indicate that combining identity-based embeddings and texture-based feature extraction significantly improves spoofing detection and enhances model robustness across different attack scenarios. This study advances biometric security by introducing an efficient feature fusion strategy that strengthens deep learning-based spoof detection. Future research may explore further optimization strategies and evaluate the approach on more diverse datasets to enhance generalization.
Co-Authors - Wijanarto - Wijanarto -, Wijanarto -, Wijanarto Abdussalam Abdussalam Abdussalam Abdussalam Abdussalam Abiyyi, Ryandhika Bintang Adrian Angga Pramono Afrizal Aziz Maulana Agus Winarno Agus Winarno, Agus Akhmad Rizaldy Ali Muqoddas Ali, Rabei Raad Alviana Dina Putri Anak Agung Gede Sugianthara Anggraeny, Tiara Antonio Ciputra Antonius Erick Handoyo Antonius Wibowo Atmojo, Cahyo Tri Bayu Wicaksono Briliantino Abhista Prabandanu Bustami, Sri Heri Cahyani, Anis Putma Carmelita, Bastiaans Jessica Christy Atika Sari Ciputra, Antonio D.R.I.M. Setiadi De Rosal Ignatius Moses Setiadi Desi Purwanti Desi Purwanti Kusumaningrum Dian Kristiawan Nugroho Didik Hermanto Dimas Irawan Ihya’ Ulumuddin Doheir, Mohamed Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Ericsson Dhimas Niagara Erwin Erwin Etika Kartikadarma Fakhriyan Nur Rofiq Farrel Athaillah Putra Febrian, Muhamad Rizky Fajar Fikri Budiman Fikri Budiman Galih Setyo Wibowo Gan, Hong-Seng Gilang Raharjito Haqikal, Hafidz Hayu Wikan Kinasih Hilmi, Muhammad Abror Auliya Ibnu Gemaputra Ramadhan Ibnu Utomo Ibnu Utomo W.M. Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Ibnu Utomo WM Ihya Ulumuddin, Dimas Irawan Imam Kurniawan Imam Prayogo Pujiono Indra Kusuma Islam, Hussain Md Mehedul Istiqomah, Annisa Ayu Karis Widyatmoko Khafiizh Hastuti Krismawan, Andi Danang Kusuma, Tiara Widya Kusumawati, Yupie L. Budi Handoko Laksono, Enggar Adji Lalang Erawan Latifah Diah Kumalasari Lutfi Madiono Marjuni, Aris Md Kamruzzaman Sarker Md Kamruzzaman Sarker Mega Bintang Hatmi Moch Arief Soeleman Mochammad Lukman Mohammad Arif Muttaqin Mohd Yaacob, Noorayisahbe Muhammad Atho’il Maula Muhammad Nur Haztinanto Mulyanto, Ibnu Utomo Mulyono, Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Wahyu Musfiqur Rahman Sazal Muslih Muslih Muslih Muslih Muslih Nabiha Riandika, Muhammad Afiq Ningrum, Novita Kurnia Nova Rijati Novita Kurnia Ningrum Novita Kurnia Ningrum Nugroho, Widhi Bagus Ojugo, Arnold Adimabua Ozagastra Caluella Prambudi Panjaitan, Yonathan Gani Panjaitan, Yonathan Gani Purwanto, Purwanto Putri, Clara Edrea Evelyna Sony Rachman, Rahadian Kristiyanto Raga Nufusula Raihan Yusuf Ramadhan, Aditya Wahyu Respatria, Nabila Maharani Rico Rian Alvian Rosyida, Ghaitsa Ardelia Sabilillah, Ferris Tita Saputra, The Manuel Eric Saraswati, Galuh Wilujeng Sarker, Md Kamruzzaman Sembiring, Rinawati Setiarso, Ichwan Sinaga, Daurat Sinaga, Daurat Sinar Setyawan Stefanus Santosa Sudaryanto Sudaryanto Sudaryanto Sudaryanto Sudaryanto Sudaryanto SUDARYANTO SUDARYANTO Suprayogi Suprayogi Teresa Enades Hari Setia Tiara Anggraeny Tiara Widya Kusuma Tri Wulandari Utomo W.M, Ibnu Utomo W.M, Ibnu Wellia Shinta Sari Widyatmoko Karis Wijanarto Wijanarto Wijanarto Wijanarto Wijanarto Wijanarto Yaacob, Noorayisahbe Mohd. Yupie Kusumawati Zahrotul Umami, Zahrotul Zainal Arifin Hasibuan Zuama, Leygian Reyhan