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Journal : Journal of Soft Computing Exploration

An optimum hyperparameters of restnet-50 for orchid classification based on convolutional neural network Alvian Ideastari, Nukat; Atika Sari, Christy; Faisal, Edi; Arifin, Zaenal; Danang Krismawan, Andi; Muslih, Muslih
Journal of Soft Computing Exploration Vol. 5 No. 1 (2024): March 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i1.297

Abstract

There are many types of orchids in Indonesia, such as Phalaenopsis Amabilis (Moon Orchid), Cattleya, etc. Because the shape and color of each orchid flower looks the same, a system is needed that can classify orchid flowers. In this research, we will use a system using a Convolutional Neural Network with ResNet50 architecture to classify orchid species. There are 4 types of orchids that will be used, namely Moon Orchids, xDoritaenopsis Orchids, Cattleya Orchids, and Coelogyne Pandurata Orchids (1000 datasets for each type). The aim of this research is to implement deep learning using the Convolutional Neural Network method combined with the ResNet50 architecture and identifying the types of orchid flowers and calculating accuracy when identifying orchid flower types. This research uses 4000 orchid image datasets, with a data split of 80:20 so that 800 images are used as training data and 200 as test data. ResNet50 uses a confusion matrix evaluation, namely Accuracy, Precision, Recall, Specificity and F1-score with epochs 10, 20, 30, 40. From the research that has been carried out, it produces the highest accuracy on Test Data with the 30th epoch, reaching 98.87%. and the lowest accuracy on Test Data with the 10th epochs which produces an accuracy of 97.75%.
Breast tumor classification using adam and optuna model optimization based on CNN architecture Sari, Christy Atika; Rachmawanto, Eko Hari; Daniati, Erna; Setiawan, Fachruddin Ari; Hyperastuty, Agoes Santika; Mintorini, Ery
Journal of Soft Computing Exploration Vol. 5 No. 2 (2024): June 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i2.373

Abstract

Breast cancer presents a significant challenge due to its complexity and the urgency of the intervention required to prevent metastasis and potential fatality. This article highlights the innovative application of Convolutional Neural Networks (CNN) in breast tumor classification, marking substantial progress in the field. The key to this advancement is the collaboration among medical professionals, scientists, and artificial intelligence experts, which maximizes the potential of technology. The research involved three phases of training with varying proportions of training data. The first training phase achieved the highest accuracy rate of 99.72%, with an average accuracy of 99.05% in all three phases. Metrics such as precision, recall, and F1 score were also highly satisfactory, underscoring the model's efficacy in accurately classifying breast tumors. Future research aims to develop more complex and precise predictive models by incorporating larger and more representative datasets. This progression promises to improve understanding, prevention, and management of breast cancer, offering hope for significant advances in 2024 and beyond.
Real-time detection of indonesian sign language (ISL) gestures based on long short-term memory Sari, Christy Atika; Rachmawanto, Eko Hari; Saifullah, Zidan; Jatmoko, Cahaya; Sinaga, Daurat
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.452

Abstract

eaf people often encounter communication challenges, and sign language serves as a crucial tool for those who cannot speak. In Indonesia, Indonesian Sign Language (ISL) or Sistem Isyarat Bahasa Indonesia (SIBI) is officially recognized by the government and is taught in Special Schools (Sekolah Luar Biasa - SLB). The sign language dictionary comprises 3483 words, facilitating communication and participation in daily life for the deaf community. This research aims to convert ISL gestures within SIBI into understandable text, employing the Long-Short-Term Memory (LSTM) method as the primary approach. The study conducted experiments with two models: Model 1, using a smaller dataset, and Model 2, employing a larger dataset and implementing the k-fold method. The results indicate that Model 2 with k-fold accuracy achieved an accuracy of 98%, while Model 1 reached an accuracy of 85%. Nevertheless, challenges persist in these models, particularly in detecting words with similar gestures, such as’maaf’ (sorry) and 'cinta' (love), which may still be misidentified. Despite these challenges, this research contributes positively to the development of assistive technology for the deaf community, enabling more effective communication through sign language.
Eye disease classification using deep learning convolutional neural networks Rachmawanto, Eko Hari; Sari, Christy Atika; Krismawan, Andi Danang; Erawan, Lalang; Sari, Wellia Shinta; Laksana, Deddy Award Widya; Adi, Sumarni; Yaacob, Noorayisahbe Mohd
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.493

Abstract

This study begins with the analysis of the growing challenge of accurately diagnosing eye diseases, which can lead to severe visual impairment if not identified early. To address this issue, we propose a solution using Deep Learning Convolutional Neural Networks (CNNs) enhanced by transfer learning techniques. The dataset utilized in this study comprises 4,217 images of eye diseases, categorized into four classes: Normal (1,074 images), Glaucoma (1,007 images), Cataract (1,038 images), and Diabetic Retinopathy (1,098 images). We implemented a CNN model using TensorFlow to effectively learn and classify these diseases. The evaluation results demonstrate a high accuracy of 95%, with precision and recall rates significantly varying across classes, particularly achieving 100% for Diabetic Retinopathy. These findings highlight the potential of CNNs to improve diagnostic accuracy in ophthalmology, facilitating timely interventions and enhancing patient outcomes. For future research, expanding the dataset to include a wider variety of ocular diseases and employing more sophisticated deep learning techniques could further enhance the model's performance. Integrating this model into clinical practice could significantly aid ophthalmologists in the early detection and management of eye diseases, ultimately improving patient care and reducing the burden of ocular disorders.
Co-Authors AA Sudharmawan, AA Abdussalam Abdussalam Abdussalam Abdussalam, Abdussalam Abiyyi, Ryandhika Bintang Agustina, Feri Ahmad Salafuddin Ajib Susanto Akbar, Ilham Januar Alfany, Fauzan Maulana Ali, Rabei Raad Alifia Salwa Salsabila Alvian Ideastari, Nukat Alvin Faiz Kurniawan Anak Agung Gede Sugianthara Andi Danang Krismawan Anggraeny, Tiara Annisa Sulistyaningsih Anny Yuniarti Antonius Erick Handoyo Ardy, Rizky Damara Arfian, Aldi Azmi Aryanta, Muhammad Syifa Aryaputra, Firman Naufal Astuti, Yani Parti Auni, Amelia Gizzela Sheehan Bambang Sugiarto Briliantino Abhista Prabandanu Cahaya Jatmoko Candra Irawan Candra Irawan Chaerul Umam Chaerul Umam Cinantya Paramita D.R.I.M. Setiadi Danang Krismawan, Andi Danang Wahyu Utomo Danar Bayu Adi Saputra Danu Hartanto Daurat Sinaga Daurat Sinaga De Rosal Ignatius Moses Setiadi Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Didik Hermanto Dimas Irawan Ihya‘ Ulumuddin Doheir, Mohamed Doheir, Mohamed Doheir, Mohamed A S Dwi Puji Prabowo Edi Faisal Egia Rosi Subhiyakto Egia Rosi Subhiyakto Eko Hari Rachmanto Eko Hari Rachmawanto Eko Septyasari Elkaf Rahmawan Pramudya Eqania Oktayaessofa Ericsson Dhimas Niagara Erika Devi Udayanti Erlin Dolphina Erna Daniati Erna Zuni Astuti Erna Zuni Astuti Erna Zuni Astuti Ery Mintorini Etika Kartikadarma Farrel Athaillah Putra Fidela Azzahra Florentina Esti Nilawati Florentina Esti Nilawati Florentina Esti Nilawati Folasade Olubusola Isinkaye Folasade Olubusola Isinkaye Folasade Olubusola Isinkaye Giovani Ardiansyah Gumelar, Rizky Syah Guruh Fajar Shidik Gusta, Muhammad Bima Hadi, Heru Pramono Haqikal, Hafidz Hartono, Matthew Raymond Haryanto, Christanto Antonius Haryanto, Christanto Antonius Hasbi, Hanif Maulana Hayu Wikan Kinasih Hendra Sutrisno Heru Lestiawan Heru Lestiawan Himawan, Reyshano Adhyarta Hussain Md Mehedul Islam Hyperastuty, Agoes Santika Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ifan Rizqa Ikhsanuddin, Rohmatulloh Muhamad Imam Prayogo Pujiono Inzaghi, Reza Bayu Ahmad Isinkaye, Folasade Olubusola Islam, Hussain Md Mehedul Istiqomah, Annisa Ayu Ivan Stepheng Kas Raygaputra Ilaga Krismawan, Andi Danang Kumala, Raffa Adhi Kusuma, Edi Jaya Kusuma, Mohammad Roni L. Budi Handoko Laksana, Deddy Award Widya Lalang Erawan Latifa, Anidya Nur Liya Umaroh Liya Umaroh, Liya Lucky Arif Rahman Hakim Mabina, Ibnu Farid Maulana Malik Ibrahim Al-Ghiffary Md Kamruzzaman Sarker Md Kamruzzaman Sarker Mohamed Doheir Mohamed Doheir Mohamed Doheir Mohamed Doheir Mohammad Rizal, Mohammad Mohd Yaacob, Noorayisahbe Muchamad Akbar Nurul Adzan Muhammad Rikzam Kamal Mulyono, Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Wahyu Munis Zulhusni Musfiqur Rahman Sazal Muslih Muslih Mutiara Dolla Meitantya Mutiara Syabilla Nabila, Qotrunnada Neni Kurniawati Ningrum, Amanda Prawita Nisa, Yuha Aulia Noor Ageng Setiyanto Noor Ageng Setiyanto, Noor Ageng Noorayisahbe Mohd Yaacob Noorayisahbe Mohd Yaacob Noorayisahbe Mohd Yaacob Noorayisahbe Mohd Yacoob Nova Rijati Nur Ryan Dwi Cahyo Oktaridha, Harwinanda Ozagastra Caluella Prambudi Parti Astuti, Yani Parti Astuti, Yani parti astuti, yani Parti Astuti1, Yani Parti Astuti1, Yani Permana langgeng wicaksono ellwid putra Pradana, Luthfiyana Hamidah Sherly Pradana, Rizky Putra Pradnyatama, Mehta Praskatama, Vincentius Pratama, Zudha Pratiwi, Saniya Rahma Prayogi, Arditya Pulung Nurtantio Andono Purwanto Purwanto Puspa, Silfi Andriana Putri Mega Arum Wijayanti Rabei Raad Ali Rabei Raad Ali Rabei Raad Ali Rahmalan, Hidayah Raisul Umah Nur Ramadhan Rakhmat Sani Ratih Ariska Robert Setyawan Sabilillah, Ferris Tita Saifullah, Zidan Salma Shafira Fatya Ardyani Sania, Wulida Rizki Santoso, Bagus Raffi Sari, Wellia Shinta Sari Shinta Sarker, Md Kamruzzaman Setiarso, Ichwan Setiawan, Fachruddin Ari Shelomita, Viki Ari Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Solichul Huda, Solichul Sudibyo, Usman Sudibyo, Usman Sudibyo, Usman Sugianto, Castaka Agus Sumarni Adi, Sumarni Suprayogi Suprayogi Suprayogi Suprayogi Syafira, Zahra Ghina Tan Samuel Permana Tan Samuel Permana Tiara Anggraeny Titien Suhartini Sukamto Umaroh, Liya Umaroh, Liya Utomo, Danang Wahyu Velarati, Khoirizqi Vincentius Praskatama Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Widhi Bagus Nugroho Wintaka, Aristides Bima Yaacob, Noorayisahbe Mohd Yani Parti Astuti Yupie Kusumawati Yupie Kusumawati Zaenal Arifin