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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) JST ( Jurnal Sains Terapan ) INOVTEK Polbeng - Seri Informatika ILKOM Jurnal Ilmiah JURNAL TEKNOLOGI DAN OPEN SOURCE Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Riset Informatika Jurnal Informatika dan Rekayasa Elektronik Jurnal Sistem informasi dan informatika (SIMIKA) Zonasi: Jurnal Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) JISA (Jurnal Informatika dan Sains) Jurnal Computer Science and Information Technology (CoSciTech) Mitra Mahajana: Jurnal Pengabdian Masyarakat Jurnal J-PEMAS Jurnal Algoritma JAIA - Journal of Artificial Intelligence and Applications SATIN - Sains dan Teknologi Informasi The Indonesian Journal of Computer Science TENANG : Teknologi, Edukasi, dan Pengabdian Multidisiplin Nusantara Gemilang
Triyani Arita Fitri
STMIK Amik Riau
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Journal : Jurnal Computer Science and Information Technology (CoSciTech)

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Aplikasi pengenalan permainan tradisional nusantara (pandora) berbasis android Nurhadi; M. Mashudi; Perty Putriani Saragih; Praba Isna Tasya; Triyani Arita Fitri
Jurnal CoSciTech (Computer Science and Information Technology) Vol 3 No 3 (2022): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v3i3.4399

Abstract

Nusantara adalah negara kepulauan yang terbentang luas dari pulau Sumatera hingga Papua yang merupakan bagian dari wilayah Indonesia. Indonesia yang merupakan negara akan kaya akan budaya. Salah satu budaya yang dimiliki Indonesia adalah budaya permainan tradisional nusantara. PANDORA merupakan aplikasi android yang memberikan informasi berbagai permainan tradisional di Indonesia dan dilengkapi dengan adanya fitur-fitur Tentang PANDORA. Tujuan penelitian ini adalah membangun aplikasi PANDORA (Permainan Tradisional Nusantara) sebagai sarana penanaman pendidikan karakter melalui pelestarian kebudayaan bangsa. Metode penelitian yang di gunakan adalah Extreme Programming (XP). Penelitian ini menghasil sebuah aplikasi yang berisikan fitur – fitur dan informasi yang dapat membantu masyarakat mendapatkan informasi permainan tradisional nusantara.
Perbandingan Metode Learning Vector Quantization Dan Backpropagation Dalam Klasifikasi Personality Pada Anak Novita, Rita; Sujana, Teguh; Agusviyanda, Agusviyanda; Fitri, Triyani Arita; Susanti, Susanti
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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

Abstract

This research focuses on classifying children's personalities at Rumah Bermain Bilal using Artificial Neural Network algorithms, specifically Learning Vector Quantization (LVQ) and Backpropagation. The primary objective of this study is to evaluate the effectiveness of these algorithms in categorizing children's personality data and to identify the most accurate method for educational settings. The experiments were conducted with various configurations, including the number of iterations and learning rate, to assess the performance of each algorithm comprehensively. The findings show that the LVQ method demonstrates higher accuracy than Backpropagation. For training data, LVQ achieved an accuracy of 73.47%, whereas Backpropagation reached only 40.82%. For test data, LVQ achieved an accuracy of 84.62%, significantly outperforming Backpropagation's 53.85%. These results indicate that LVQ is more effective in personality classification, especially in an educational context. It is hoped that these findings will assist educational institutions in implementing artificial intelligence-based methods to understand children's personality traits better, thereby supporting the development of more targeted teaching strategies.
Co-Authors Agus Tri Nurhuda Agustin Agustin Agustin Agustin Agusviyanda Agusviyanda Ahmad Zamsuri, Ahmad Aldi Saputra Anam, M Khairul Boby Hasbul Fikri Bunga Nanti Pikir Cesmawati Cesmawati Cesmawati, Cesmawati Dewi Sari Wahyuni Edwar Ali Efrizoni, Lusiana Ega Ranaldi Pebriansyah Erleni - Erleni -, Erleni Erlin Erlin - Erlin -, Erlin Fatdha, Eiva Fika Felanda Ardelia Firdaus, Muhammad Bambang Fransiskus Zoromi Fransiskus Zoromi, Fransiskus Hadi Asnal, Hadi Hamdani Hamdani - Hamdani Hamdani Hanafiah, Anggi Hanafiah, Anggi Handoko Hazira, Nadila Herwin Herwin, Herwin Ismanizan, Ryan Johan Junadhi Junadhi Junadhi, Junadhi Karpen Kharisma Rahayu Koko Harianto Koko Harianto Kudadiri, Parlindungan Lusiana Lusiana Efrizoni M Naofal Arsyad M. Mashudi Muhammad Bambang Firdaus Muhammad Jamaris Nu'man, Nu'man Nurhadi Nurjayadi Nurjayadi Perty Putriani Saragih Praba Isna Tasya Rahmaddeni Rahmaddeni Rahmawati Rahmiati Rahmiati Rahmiati Rahmiati Rinaldi Yuslami Rini Yanti Rini Yanti, Rini Rio Ferdiansyah Rita Novita Safitri, Dea Susandri, Susandri SUSANTI Susanti Susanti Susanti, Susanti SUSI ERLINDA Syam, Salmaini Safitri T. Sy. Eiva Fatdha Teguh Sujana Torkis Nasution Widi Paramita Wirta Agustin Yuslami, Rinaldi Yusuf Nuron Zuriatul Khairi