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All Journal Seminar Nasional Informatika (SEMNASIF) Sinkron : Jurnal dan Penelitian Teknik Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Penelitian Inovatif JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat KOMET Jurnal Pengabdian Masyarakat Terapan
Yuri Prima Fittryani, Yuri Prima
Institut Bisnis Dan Teknologi Indonesia, Denpasar, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Convolutional Neural Network Algorithm Implementation for Classifying Traditional Wood Carving Motifs of Patra Bali Widyatama, I Dewa Gede Surya; Sudipa, I Gede Iwan; Fittryani, Yuri Prima; Wulandari, Dewa Ayu Putri; Jayanegara, I Nyoman
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 3 (2025): Article Research July 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i3.14841

Abstract

This research develops an automatic classification system to recognize Balinese Patra carving motifs using deep learning method based on Convolutional Neural Network (CNN). The data used are images of Cina Patra, Mesir Patra, Punggel Patra, and Sari Patra motifs, which have gone through preprocessing stages such as cropping, resizing, and augmentation in the form of flip and rotation to increase data variation. Three pre-trained CNN models were used in testing, namely DenseNet169, InceptionResNetV2, and MobileNetV2. The training process was performed with Adam optimization, batch size 32, and 100 epochs. Model performance evaluation was performed using accuracy and confusion matrix metrics. The results show that all three models were able to achieve 100% accuracy on the test data, with MobileNetV2 recording the lowest loss of 0.75%, followed by DenseNet169 (1.14%) and InceptionResNetV2 (1.18%). Based on the confusion matrix, all motifs were recognized very well, although there was a slight misclassification of the Patra Sari motif by the InceptionResNetV2 model. These findings prove that CNN is effectively used in the recognition of traditional carving motifs and has the potential to support cultural preservation through interactive visual technology.
Pelatihan Desain Grafis dan Video Editing Anak Panti Untuk Meningkatkan Literasi Digital di Panti Asuhan Rumah Impian Denpasar Putra, I Gede Sujana Eka; Labasariyani, Ni Luh Putu; J Sastaparamita, Ni Nyoman Ayu; Dharma Suryawan, I Wayan; Fittryani, Yuri Prima
Jurnal Pengabdian Masyarakat Terapan Vol 2 No 2 (2025): JUPITER Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jupiter.2.2.62

Abstract

Panti Asuhan Rumah Impian, yang didirikan oleh Mr. Kim Young Gil pada tahun 2005 di Jalan Soka No. 99, Kesiman Kertalangu, Denpasar, menampung 17 anak yatim piatu dengan beragam latar belakang. Minimnya akses anak panti terhadap pelatihan teknologi dan pengembangan diri sebagai permasalahan di panti asuhan. Kegiatan INSTIKI Community Services bertujuan untuk mengembangkan keterampilan digital anak Panti Asuhan Rumah Impian melalui pelatihan desain grafis dan editing video, sehingga dapat meningkatkan kepercayaan diri, kreativitas, serta membuka peluang karier dan wirausaha mandiri. Kegiatan INSTIKI Community Services dilaksanakan pada tanggal 10–18 Mei 2025. Pelatihan dengan metode Pembelajaran Integratif Teori–Praktik meliputi pelatihan Desain Grafis berupa penggunaan Canva untuk pembuatan poster “Jaga Lingkungan Tidak Membuang Sampah Sembarangan”, dan Editing Video berupa pengenalan dan praktik menggunakan software CapCut. Pelatihan memberikan hasil mereka mampu menyelesaikan tugas desain poster dan editing video dengan kualitas baik, memahami alur kerja perangkat lunak, serta mampu menerapkan teknik dasar desain dan video editing secara mandiri. Pelatihan desain grafis dan video editing memberikan dampak secara signifikan meningkatkan keterampilan digital anak panti sehingga anak lebih percaya diri mandiri dan memiliki keterampilan dalam berwirausaha baik.
Video Company Profile Sebagai Media Promosi Pratama Widya Pasraman Rare Semesta Anggara, I Gede Adi Sudi; Setiawan, Antonio Henry; Indrawan, I Gusti Agung; Setiawan, I Ketut; Fittryani, Yuri Prima
Jurnal KOMET Vol 1 No 1 (2024): Jurnal Komet: Kolaborasi Masyarakat Berbasis Teknologi : Volume 1 Nomor 1, Juni 2
Publisher : Yayasan Sinergi Widya Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70103/komet.v1i1.10

Abstract

Pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan dan kesadaran masyarakat tentang Pratama Widya Pasraman Rare Semesta dan pentingnya pendidikan usia dini di Desa Besakih. Berdasarkan analisis situasi, ditemukan bahwa banyak orang tua tidak mengetahui keberadaan sekolah ini dan menganggap pendidikan usia dini tidak penting, yang berdampak pada rendahnya jumlah siswa. Solusi yang diambil adalah merancang dan memproduksi video company profile sebagai media promosi. Proses produksi meliputi pengumpulan data melalui wawancara, observasi, dan kuesioner, serta pembuatan video dalam tiga tahap: praproduksi, produksi, dan pascaproduksi. Hasil pengujian video menunjukkan penilaian sangat baik dari orang tua (98,2%), ahli konten (100%), dan ahli media (93,7%). Video ini efektif dalam menyampaikan informasi dan meningkatkan kesadaran orang tua tentang pentingnya pendidikan usia dini, serta berhasil memperkenalkan Pratama Widya Pasraman Rare Semesta kepada masyarakat.
Klasifikasi Data Penjualan Dengan Metode K-Nearest Neighbor Pada Pt. Terang Abadi Raya Novitadewi, Ni Made Ary; Sugiartawan, Putu; Fittryani, Yuri Prima
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 5 No 1 (2022): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.173

Abstract

PT. Terang Abadi Raya is a lighting company engaged in trading, with the many types of products to be sold the company has difficulty determining which product sells the most on the market. Making it difficult for the marketing department to offer products to be sold. PT. Terang Abadi Raya has various types of lighting products based on sales data for the last 1 year, using the K-Nearest Neighbor (K-NN) prediction to make it easier for companies to plan sales. To find out the best-selling sales using sales data classification and the K-Nearest Neighbor (K-NN) method, of the 19,290 items classified, the graphic results obtained were 12,420 categorized as best-selling labels, and 6,870 categorized as not-selling labels.
A Comparative Study of MobileNetV2 and ResNet50 for Multi-Class AI- Generated and Real Image Classification Pramudita, I Gusti Ngurah Agus Ega Patria; Sudipa, I Gede Iwan; Fittryani, Yuri Prima; Iswara, Ida Bagus Ary Indra; Aristamy, I Gusti Ayu Agung Mas
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15682

Abstract

This study aims to classify AI-generated and real images using Convolutional Neural Network (CNN) architecture by comparing the performance of MobileNetV2 and ResNet50. Previous studies on AI-generated image detection have primarily focused on binary classification without explicitly analyzing object-level context in multi-class scenarios, leaving a gap in understanding model performance across diverse visual categories. The dataset consists of 23,941 images divided into two main classes of real and fake and five subclasses of human, animal, art, view, and vehicle. The training process employs data augmentation and a K-Fold Cross Validation strategy on the training and validation set to maintain balanced class proportions, while a separate unseen test set is used exclusively for final performance evaluation. Model evaluation is performed based on accuracy, precision, recall, and F1-score metrics on test data. The results showed that MobileNetV2 achieved the best accuracy of 89% at the 10th epoch, but experienced a decline in performance at the 30th and 50th epochs, indicating overfitting. In contrast, ResNet50 showed the most stable performance with the highest accuracy of 93% at the 30th epoch and consistently high precision, recall, and F1-score values. Thus, ResNet50 was found to be the most effective architecture for classification of AI-generated and real images on multi-class datasets, while MobileNetV2 remains relevant for implementation on devices with computational limitations.
Co-Authors Ade Septryanti Aristamy, I Gusti Ayu Agung Mas Christina Purnama Yanti Desak Made Dwi Utami Putra Dewa Ayu Indah Cahya Dewi Hanny Hartanto Harrizki Arie Pradana Hendrawati, Theresia Henresia Khristiani Hilyah Magdalena I Gede Adi Sudi Anggara I Gede Iwan Sudipa I Gede Sujana Eka Putra, I Gede Sujana Eka I Gusti Agung Indrawan I Ketut Setiawan I Nyoman Jayanegara I Wayan Dharma Suryawan Ida Bagus Ary Indra Iswara J Sastaparamita, Ni Nyoman Ayu Made Suci Ariantini Maulidah, Salsa Bila Jihan Ngakan Putu Darma Yasa Ni Kadek Ariasih, Ni Kadek Ni Komang Ita Cahyani NI LUH PUTU LABASARIYANI Novitadewi, Ni Made Ary Petra Tauli Pasaribu Pramita, Dewa Ayu Kadek Pramudita, I Gusti Ngurah Agus Ega Patria PUTU SUGIARTAWAN Sandhiyasa, I Made Subrata Savitri, Ni Kadek Wiliya Setiawan, Antonio Henry Syafrul Irawadi Widiartha, Komang Kurniawan Widyatama, I Dewa Gede Surya Winatha, Komang Redy Wulandari, Dewa Ayu Putri Yuri Ari Jayanti