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All Journal Information Technology and Telematics Dinamik Jurnal Ilmiah Dinamika Teknik Elkom: Jurnal Elektronika dan Komputer Scientific Journal of Informatics Jurnal Ilmiah Giga Proceeding SENDI_U Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA CogITo Smart Journal JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Teknik Informatika UNIKA Santo Thomas INTECOMS: Journal of Information Technology and Computer Science Jurnal Teknologi Sistem Informasi dan Aplikasi IKRA-ITH ABDIMAS JURIKOM (Jurnal Riset Komputer) Jurnal Informasi dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JURNAL MAHAJANA INFORMASI Jurnal Abdimas Mandiri Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Pengabdian kepada Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal Pengabdian Pada Masyarakat Jurnal Kabar Masyarakat SmartComp Fundamentum: Jurnal Pengabdian Multidisiplin Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat Andan Jejama: Indonesian Journal Of Community Engagement Jurnal Teknik Informatika dan Teknologi Informasi
Veronica Lusiana
Universitas Stikubank (UNISBANK) Semarang
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DETEKSI MOTIF SARUNG TENUN GOYOR BOTOLAN KABUPATEN PEMALANG MENGGUNAKAN METODE KNN Tistantia Pusdita; Veronica Lusiana
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Sarung tenun goyor merupakan kerajinan tenun dalam bentuk sarung dan terbuat secara tradisional melalui alat tenun tradisional. Terdapat berbagai jenis, termasuk sarung tenun goyor botolan. Sarung goyor botolan memiliki motif sangat banyak dan beragam sehingga membuat orang awam sulit untuk membedakannya. Oleh karena itu, diperlukan sistem untuk mengidentifikasi motif sarung tenun goyor botolan agar mempermudah orang awam mengetahui motif pada sarung tenun goyor botolan. Penelitian ini bertujuan untuk mengidentifikasi motif sarung tenun goyor botolan dengan metode KNN memakai software MATLAB. Penelitian ini memanfaatkan data citra sarung tenun goyor botolan yang dipisahkan menjadi data pelatihan dan data pengujian. Data citra ini terdiri dari 79 jenis motif diantaranya 8 data bunga mawar, 7 data elips, 7 data garis zig-zag diagonal, 7 data kawung, 8 data bunga empat kelopak, 6 data segi enam, 6 data silang kombinasi, 7 data bunga enam kelopak, 8 data belah ketupat, 7 data garis zig-zag, dan 8 data titik-titik diagonal. Dalam pengujian sistem identifikasi sarung tenun goyor botolan menggunakan metode KNN memperoleh hasil tingkat akurasi sebesar 70,45%.
Implementasi Pengelompokan Citra Batik dengan Pendekatan Metode Graph-Based Multi-View Clustering Budi Hartono; Veronica Lusiana
TIN: Terapan Informatika Nusantara Vol 7 No 3 (2026): August 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v7i3.10967

Abstract

Batik is a cultural heritage of Indonesia characterized by a rich array of motifs, colors, geometric patterns, and complex textures. This visual complexity makes Batik images compelling subjects for analysis using image processing and machine learning approaches, particularly for unsupervised clustering. A primary challenge in this research is effectively representing Batik's visual characteristics so pattern similarities can be accurately identified. Three texture features contrast, entropy, and energy serve as distinct "views" of Batik characteristics. These feature values are obtained by extracting them using the Gray-Level Co-occurrence Matrix (GLCM) method. The study utilizes a Graph-based Multi-View Clustering approach to group Batik images based on inter-image similarity. The study constructs a combined consensus graph with 30 nodes and 219 edges by integrating contrast, energy, and entropy features. This graph exhibits a density of 0.503 and forms a single connected graph component. The density result indicates that 50.3% of all possible image pairs share a connection. The resulting graph forms a connected structure that incorporates information from all three views, yielding a more comprehensive clustering representation than any single view. The combined consensus graph establishes an interconnected structure that produces a representative clustering of Batik images.
Co-Authors Adi Nugroho, Hermawan Afian Ibnu Yuwono Aisyah Nur Ramadhayani Alfian, Riyan Antono Adhi ARIFUDIN, WAHYU Aryasatya, Rakryan Atmaja, Wahyu Priyo Budi Hartono budi hartono Budi Hartono Budi Hartono Deva Ega Marinda Dewi Handayani Untari Ningsih Dian Kristiawan Nugroho Dimas Wahyu Edy Supriyanto Edy Winarno Eka Ardhianto Eko Nur Wahyudi Endang Lestariningsih Febriana, Trissa Noor Aulia Felix Andreas Sutanto Hari Murti Hartono, Budi Hartono, Budi Hidayat, Agung Rizqi Ilham Ramadhan, Hafidh Imam Husni Al Amin Iskandar Zulkarnein Jefri Alfa Razak Krisna Aditya Pratama Kristianto, Teguh Ma’sum, Muhammad Ali Melly Anggraini Miftah Khul Janah Muhammad Muslimin Ningsih, Dewi Handayani .U Novita Mariana Oka Rosalin, Agnes Pratama, Krisna Aditya R. Soelistijadi Radyanto, Mohammad Riza Ramadhani, Insan Rara Sri Artati Redjeki Ratnaduhita, Aurellia Razak, Jeffri Alfa Retnowati Retnowati Rina Candra Noor Santi Saefurrohman Saefurrohman Sariyun Naja Anwar Setiaji, Isnan Sri Eniyati Sri Wahyuni Sumarno, Davis Danendra Tahta Febri P, Gilar Taufan Maynard Prananda Sancaka1 Teguh Khristianto Tistantia Pusdita Umi Kholifah WAHYU PRIYO ATMAJA Wahyu Priyo Atmaja Widiyanto Tri Handoko Widyawati, Lanjar Wismarini, Th Dwiati Wiwien Hadikurniawati Wulan Nur Afifah, Wulan Nur Zulkarnein, Iskandar