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Pengenalan Pola Tulisan Tangan Suku Kata Aksara Sasak Menggunakan Metode Integral Projection dan Neural Network Eka Dina Juliani U M; I Gede Pasek Suta Wijaya; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 1 (2019): June 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1503.815 KB) | DOI: 10.29303/jcosine.v3i1.222

Abstract

This paper presents sasak ancient scripts using integral projection and neural network. The purpose of using these two methods is to find out how to work this methods and how much accuracy is obtained in pattern recognition of sasak ancient scripts. The data used is 1260 handwritten image data. Testing is done by knowing the effect of the number of nodes in a hidden layer and the effect of the number of hidden layers in a network. The highest accuracy on average is in the use of 2 hidden layers where 21 nodes for the first hidden layer and 14 nodes for the second hidden layer. The experiment resulted in the obtained accuracy rate of 41.38%.
Optimasi Augmentasi Data untuk Klasifikasi Motif Batik Indonesia Menggunakan Transfer Learning pada Convolutional Neural Network Baiq Anggita Arsya Rahmatin; Nazmi Wardiani; Syarif Hidayatullah; I Gede Pasek Suta Wijaya
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 10 No 1 (2026): June 2026
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v10i1.676

Abstract

Batik is an Indonesian cultural heritage that has various distinctive motifs from various regions. However, manual classification of batik motifs often requires special skills and considerable time.1 To overcome this, the Convolutional Neural Network (CNN)-based classification method with the help of transfer learning is a promising solution. This research uses a dataset of 500 batik images consisting of 10 different motif classes, each class containing 50 images. Data augmentation techniques are applied to expand the variety of training data with transformations such as rotation, zoom, and flipping to reduce overfitting and improve the generalization ability of the model. The MobileNetV2 model was selected as the base model of transfer learning due to its efficiency and ability to extract features from limited data. Experiments show that the MobileNetV2 model with fine-tuning produces the highest classification accuracy of 86%, which is superior to conventional CNNs that achieve accuracies between 59% and 65%. As a result, the combination of data augmentation and transfer learning in MobileNetV2 proved to be effective in improving the accuracy and efficiency of batik motif classification on small data.
Co-Authors Adi Sugita Pandey Afwani, Royana Agitha, Nadiyasari Ahmad Musnansyah Ahmad Zafrullah Mardiansyah Albar, Moh. Ali Aldian Wahyu Septiadi Aliyah Fajriyani Amdila Rahmadi Andy Hidayat Jatmika Anita Rosana MZ Annisa Mujahidah Robbani Anugrah, Febrian Rizky Aprilla, Diah Mitha Aranta, Arik Ariessaputra, Suthami Arik Aranta Arik Aranta Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo, Ario Yudo Ariyan Zubaidi Ariyan Zubaidi Ayu Rezki Azizah Arif Paturrahman Baiq Anggita Arsya Rahmatin Belmiro Razak Setiawan Budi Irmawati Budi Irmawati Bulkis Kanata Chaerus Sulton Chandra Adiguna Chandra Adiguna Cipta Ramadhani Darmawan, Riski David Arizaldi Muhammad Dedi Ermansyah Ditha Nurcahya Avianty Dwitama, Aditya Perwira Joan Eet Widarini Eka Dina Juliani U M Fachry Abda El Rahman Fadilah . Fahmi Syuhada Faqih Hamami Farhan Yakub Bawazir Fiena Efliana Alfian Firdaus, Asno Azzawagaam Fitrah, Muhammad Dinul Fitri Bimantoro Gibran Satria Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gou Koutaki Gunawan Haidra Rahman Halil Akhyar Hamidi, Mohammad Zaenuddin Hendy Marcellino Heri Wijayanto Heri Wijayanto Heri Wijayanto Hidayat, Lalu Ramdoni I B K Widiartha I Gde Putu Wirarama Wedaswhara W. I Made Budii i Suksmadana I Made Subiantara Putra I Putu Teguh Putrawan I Wayan Agus Arimbawa I Wayan Agus Arimbawa I Wayan Agus Arimbawa, I Wayan Agus Ida Bagus Ketut Widiartha Ida Bagus Ketut Widiartha Ida Bagus Ketut Widiartha Ida Nyoman Tegeh Adnyana Imam Arief Putrajaya Jayusman, Dirga Jo, Minho Kadriyan, Hamsu Kansha, Lyudza Aprilia Keeichi Uchimura Keiichi Uchimura Keiichi Uchimura L. A. Syamsul Irfan Lalu Sweta Arif Lalu Zulfikar Muslim Lidia Ardhia Wardani Made Agus Dwiputra Mayzar Anas Maz Isa Ansyori Mega Laely Moh Ali Albar Moh. Ali Albar Muhamad Nizam Azmi Muhamad Syamsu Iqbal Muhammad Azmi Muhammad Daden Kasandi Putra Wesa Muhammad Husnul Ramdani Muhammad Khaidar Rahman Muhammad Mukaddam Alaydrus Muhammad Naufal Rizqullah Muhammad Syulhan Al Ghofany Mulyana, Heru Murpratiwi, Santi Ika Mustiari, Mustiari Nazmi Wardiani Ni Nyoman Citariani Sumartha Ni Nyoman Kencanawati Nisa, Aisyah Khairun Novian Maududi Novita Nurul Fakhriyah Nugraha, Gibran Satya Nurhalimah Nurhalimah Obenu, Juanri Priskila Pahrul Irfan Pahrul Irfan Pandu Deski Prasetyo Putra, Chairul Fatikhin Rahmatin, Baiq Anggita Arsya Ramaditia Dwiyansaputra Ramdhani, Ghina Kamilah Ramlah Nurlaeli Rani Farinda Reza Rismawandi Rina Lestari Riska Yanu Fa’rifah Riska Yulianti Ristirianto Adi Romi Saefudin Rosalina Rosalina Salsabila Putri Rajani Said Salsabila, Raissa Calista Santi Ika Murpratiwi Saputra, Muhammad Harpan Teguh Satya Nugraha, Gibran Selvira Anandia Intan Maulidya Setiawan, Lalu Rudi Siti Faria Astari Sri Endang Anjarwani Sri Endang Anjarwani Sri Endang Arjarwani Suhada, Destia Suksmadana, I Made Budi Sulfan Akbar Syaifullah Syaifullah Syarif Hidayatullah Topan Khrisnanda Tri Erna Suharningsih Ulandari, Alisyia Kornelia Wahyu Alfandi Wahyuni Sulastri Widodo, Agung Mulyo Wirarama Wedashwara Wisnujati, Andika Yogi Permana Yudo Husodo, Ario Zafrullah, Ahmad Zakiyah Rahmiati Zubaidi, Ariyan Zuhraini, Marlia Zul Rijan Firmansyah