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Journal : Building of Informatics, Technology and Science

Game Edukasi Pengenalan Huruf Hiragana Untuk Meningkatkan Kemampuan Berbahasa Jepang Nurcholis, Rifki; Purnamasari, Ade Irma; Dikananda, Arif Rinaldi; Nurdiawan, Odi; Anwar, Saeful
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (444.357 KB) | DOI: 10.47065/bits.v3i3.1091

Abstract

Educational games are very interesting to develop, because of the diversity that can be done. Some of the advantages of educational games compared to conventional educational methods, one of the main advantages of educational games is the visualization of real problems. Based on the pattern possessed by the game, players are required to learn so that they can solve existing problems. Game status, instructions, and tools provided by the game will guide players actively to explore information so that they can enrich their knowledge and strategies while playing. One of the interesting educational games to focus on is an educational game that discusses the introduction of foreign languages ​​focused on Japanese. With this educational game, it is hoped that it can help students to understand and memorize the hiragana letters in Japanese. This study aims to create a windows-based educational game application as an alternative medium for learning to recognize Japanese Hiragana letters. This game can later be used as an alternative learning media for the general public who just want to learn Japanese, by knowing the basics of Hiragana letters. The research method that can be used for this research can use the MDLC development method. The stages in this research process are Concept, Design, Material Collecting, Assembly, Testing, Distribution. The result of the research is an educational game of Japanese hiragana letters which introduces the basic Japanese hiragana letters and how to write them. In addition there is a quiz game of stacking letters into words to train children after knowing the basic letters of Japanese hiragana. Thus it can help children learn Japanese more easily. With this educational game, it is hoped that it can help children to understand and memorize the hiragana letters in Japanese
Penerima Manfaat Bantuan Non Tunai Kartu Keluarga Sejahtera Menggunakan Metode NAÏVE BAYES dan KNN Putri, Haidah; Purnamasari, Ade Irma; Dikananda, Arif Rinaldi; Nurdiawan, Odi; Anwar, Saeful
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (681.586 KB) | DOI: 10.47065/bits.v3i3.1093

Abstract

The Prosperous Family Card is one of the government's programs in accelerating poverty which functions as a marker for the underprivileged. The implementation of the PSC policy is still not optimal due to factors, namely the lack of socialization and information from village and sub-district officials to the community regarding programs issued by the government. This research to classify the beneficiaries of the Prosperous Family Card, because there are still many other disadvantaged families who have not had the opportunity to receive this assistance program. The method used in this research is the Naive Bayes method and the K-NN method. The results of this study are the classification of beneficiaries from 6,491 KKS recipients with the K-NN Algorithm method yielding an accuracy value of 66.46% with a distribution in 5 villages, including pred Argasunya class precision 64.90% pred Harjamukti class precision 65.18% pred Kalijaga class precision 66.64% pred Kecapi class precision 68.44% pred Prohibition class precision 68.34% while the Naïve Bayes algorithm is classified with true in each kelurahan with true Argasunya distribution of 1,196 KKS class precision 100%, true Harjamukti 1,339 KKS class precision 100%, true Kalijaga 2,067 KKS class precision 100%, true Kecapi 1,137 KKS class precision 100%, true Prohibition 744 KKS(1 KKS true Argasunya, 1 KKS true Harjamukti, 3 KKS true Kalijaga, 3 KKS true Kecapi) class precision 98.64%. the accurasy value of the Naïve Bayes algorithm model is 99.88%.
Co-Authors Abdul Rauf Chaerudin Abdul Robi Padri abdullah, nur syarief Ade Irma Purnamasari Ade Irma Purnamasari Ade Irma Purnamasari Ade Kurnia, Dian Ade Rizki Rinaldi Adisty Tri Putra Agis Maulana Robani Agung Nugraha Agus Surip Ahmad Faqih Ahmad Faqih Ahmad Faqih Ahmad Faqih Ahmad Zam Zami Ainnur Rahman, Rizal Amar, Mohammad Rosihin Amarda, Juan Amri, Hajijin Ananda Rafly Andi Setiawan Andi Setiawan Anwar Musaddad Aria Pratama Arif Fitriyanto, Goffar Arif Rinaldi Dikananda baihaqqi, Farisky Bambang Irawan Basysyar, Fadhil Muhammad Basysyar, Muhammad Fadhil Cep Lukman Rohmat Cep Lukman Rohmat Cep Lukman Rohmat Dadang Sudrajat Deasiva, Imanda Dewanty Rafu, Maria Dias Bayu Saputra Dikananda, Arif Rinaldi Dilla Eka Lusiana Dita Rizki Amalia Dodi Solihudin Dwi Teguh Afandi Edi Tohidi Edi Wahyudin Eko Wiyandi Fadhil M. Basysyar Fadrin Helmi FANDI ACHMAD Faturrohman, Faturrohman Fauzi Fauzi Febriansyah, Feggy Fidya Arie Pratama Fidya Arie Pratama Firmansyah Firmansyah Fitriyani, Nur Sifa Gifthera Dwilestari Haidar Fakhri Hanafi, Muhammad Salman Hayati, Umi Heliyanti Susana Herdiana, Ruli Herdiana, Rully Heriyawan, Ikhsan Himawan, Irvan Hira Wahyuni Azizah Ibnu Ubaedila Irfan Ali Irfan Ali Irfan Ali, Irfan Irma Purnamasari, Ade Irvandi Irvandi IRVANDI, IRVANDI Jaelani Sidik Jamalul'ain, Abdul Jayawarsa, A.A. Ketut Julia Eka Yanti Juliadi, Diky Karlina, Lita Kaslani Khamim Surya Hadi Kusuma Al Atros Khoirul Insan, Moh Khoirul Kurniawan Fajar Abdulloh Laturrizqi, Washi Lukmanul Hakim M. Basyisyar, Fadhil M. Iqbal Fadhilah, Aji Mamluah, Karimatul Martanto . Mauludin, Muhammad Rifqi Medina Aprilia Putri Melia Melia Melia Melia Melisa Hikari Mia Fijriani Muchamad Sobri Sungkar, Muchamad Sobri Muhalim, Alvy Mulyana Mulyana Mulyawan Mulyawan Musliyadi, Mar'i Nana Suarna Nana Suarna Nana Suarna Nanda Permatasari Nining Rahaningsih Noval Salim Nur Atikah Nurcholis, Rifki Nurhadiansyah Nurhadiansyah Nurhadiansyah, Nurhadiansyah Nurrohmat, Iman Pratama, Fidya Arie Pratama, Irfan Pratiwi, Fitriyani Prihartono, Willy Purnamasari, Ade Irma Putri, Haidah R, Nining Riansah, Adam Rinaldi Dikananda, Arif Rinaldi Dikanda, Arif Riyan Suryatana Riyan, Ade Bani Rizki, Dicky Miftakhul Rohmat, Cep Lukman Rokhmatan Khaerullah, Rizal Rudi Hartono Rudi Kurniawan Ruli Herdiana Rully Pramudita Saeful Anwar Saeful Anwar Saeful Anwar, Saeful Saepul Hadi Salsa Billa Agistina Suarna, Nana Subandi, Husein Syafi'i, Syafi'i Taufik Hidayat Tengku Riza Zarzani N Tio Prasetiya Tio Prasetya TOMAS TOMAS Topan Hadi Tuti Hartati Tuti Hartati Wiyandi, Eko Yudhistira Arie Wijaya Yunus, Shofian Zeya Sebastian, Muhammad