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All Journal Jurnal Sarjana Teknik Informatika Jurnal Teknologi Informasi dan Ilmu Komputer ELINVO (Electronics, Informatics, and Vocational Education) Creative Information Technology Journal Voice Of Informatics Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat SENSITEK JATI (Jurnal Mahasiswa Teknik Informatika) IT (INFORMATIC TECHNIQUE) JOURNAL Informatics and Digital Expert (INDEX) JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) Jurnal Prajaiswara JPEG PUBLIDIMAS CSRID Jurnal Pengabdian Masyarakat (JURDIMAS) Jurnal Sistem Informasi dan Teknologi Informasi ADVANCE INFORMATICS RESEARCH JOURNAL
Dede Syahrul Anwar
Universitas Perjuangan Tasikmalaya
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : csrid

 1 
PENERAPAN DATA MINING CLASSIFICATION UNTUK PENENTUAN JENIS BANTUAN SOSIAL MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Shinta Siti Sundari; Evi Dewi Sri Mulyani; Cepy Rahmat Hidayat; Dede Syahrul Anwar; Teuku Mufizar
Computer Science Research and Its Development Journal Vol. 16 No. 1 (2024): February 2024
Publisher : LPPM Universitas Potensi Utama

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

Abstract

The social assistance program is a program held by the government as an effort to overcome poverty. Mekarjaya Village is one of the villages running the program. In carrying out this social assistance process, there are obstacles in terms of collecting data on its citizens because there are often discrepancies in the recipient data collected by the community with the type of assistance. To make it easier to determine the appropriate type of social assistance, an analysis of the data on the recipients of the social assistance is needed. The data analysis method in this research uses Data Mining including Data Selection and Preprocessing, while the classification method uses the Naïve Bayes Classifier. Testing using the Confusion Matrix produces an accuracy of 94.53% with a comparison of training data and testing 80:20. With this model, it is hoped that village officials can determine the type of social assistance that is appropriate for the community.
PENERAPAN DATA MINING CLASSIFICATION UNTUK PENENTUAN JENIS BANTUAN SOSIAL MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Shinta Siti Sundari; Evi Dewi Sri Mulyani; Cepy Rahmat Hidayat; Dede Syahrul Anwar; Teuku Mufizar
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 1 (2024): February 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.16.1.2024.13-24

Abstract

The social assistance program is a program held by the government as an effort to overcome poverty. Mekarjaya Village is one of the villages running the program. In carrying out this social assistance process, there are obstacles in terms of collecting data on its citizens because there are often discrepancies in the recipient data collected by the community with the type of assistance. To make it easier to determine the appropriate type of social assistance, an analysis of the data on the recipients of the social assistance is needed. The data analysis method in this research uses Data Mining including Data Selection and Preprocessing, while the classification method uses the Naïve Bayes Classifier. Testing using the Confusion Matrix produces an accuracy of 94.53% with a comparison of training data and testing 80:20. With this model, it is hoped that village officials can determine the type of social assistance that is appropriate for the community.
Rancang Bangun Game Edukasi Eksplorasi Wisata dan Budaya Tasikmalaya Anwar, Dede Syahrul; Mufizar, Teuku; Shafarulloh, M. Hisyam; Maulana, Akmal
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.127-135

Abstract

Tasikmalaya, a region rich in tourism and cultural diversity, is still not widely recognized by the public. In the digital era, interactive media such as games can serve as an effective tool to introduce and promote its potential. This research focuses on designing and developing an educational adventure game that explores the tourism and cultural aspects of Tasikmalaya. The novelty of this study lies in its interactive and educational approach, specifically designed to educate users, particularly the younger generation, about Tasikmalaya's tourist attractions and cultural heritage. By utilizing game technology, it is expected to provide an engaging and informative learning experience.The research method used is the Multimedia Development Life Cycle (MDLC). The concept stage involves identifying the game's needs and objectives. The design stage includes story development, character creation, and user interface design. The material collection stage focuses on gathering necessary information and media assets. The assembly stage involves the technical development of the game. Testing is conducted to ensure the game's quality and functionality, while the distribution stage delivers the game to users.The final result of this research is an educational game aimed at enhancing public knowledge and appreciation of Tasikmalaya's tourism and culture, while also contributing to scientific development through research publication.
Pengembangan Virtual Assistant (Chatbot) Bebrbasis NLP (Natural Language Processing) Untuk Portal Informasi Terpadu Pariwisata Tasikmalaya Hidayat, Cepi Rahmat; Sumaryana, Yusuf; Syahrul Anwar, Dede; Fadilah, Ai Linda Nurahmah; Saputra, Muhammad Randika
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.136-148

Abstract

Tasikmalaya, known for its natural beauty and cultural richness, has great potential as an attractive tourist destination. One of the main challenges faced is how to convey accurate and integrated information to tourists quickly and easily so that it can be used to improve marketing strategies and destination development. This study aims to develop a virtual assistant (chatbot) based on Natural Language Processing (NLP) for the integrated Tasikmalaya tourism information portal in handling high volumes of questions simultaneously, reducing the workload of human staff and optimizing the service process. The research method uses a waterfall model by applying the NLP approach. The final result of this study is to produce a virtual assistant (chatbot) application that allows users to get information related to Tasikmalaya tourism destinations in a more flexible way. The application was tested using the black box method and showed that the application ran as expected while the SUS test carried out obtained a final score of 72.30 in the Good category.
Co-Authors Agus Supriatman Aprianis, Epa Arief, Mizar Ismu Arifatun Nasuha Ayu Rahmawati Ayu Rahmawati Cepi Rahmat Hidayat Cepi Rahmat Hidayat Cepy Rahmat Hidayat Chaeruddin, Rofi Dani Rohpandi Edy Setiawan Evi Dewi Sri Mulyani Fadilah, Ai Linda Nurahmah Fadilah, Nizar Gani Adi Alzani Rusandi Gunawan, Anan Hartono, Rudi Heri Purnama Hermayulia, Adzkia Hidayatulloh, Hilmi Hikmatyar, Missi Indah Septianingrum Indradewa, Rhian Indriyanti indriyanti Isyana Rahayu, Isyana Jamal Ma'ruf Kurdiman, Kurdiman M. Akbar Kasyfurrahman Maulana, Akmal N. Nelis Febriani SM Nanang Suciyono, Nanang Nugraha, Muhammad Rizki Nurul Fahmi, Rizki Pramana, Hendri Julian R. Arif Malik Ramadhan Rahmat Hidayat, Cepi Raihan, Razif Raihan Maulana Ramadhan, Teguh Ikhlas Roqhaman, Piqi Rudi Hartono Rudi Hartono Rustin Kania Dewi Ruuhwan Safitri, Mila Meiliani Saputra, Muhammad Randika Sarmidi Sarmidi Sarmidi Seftiawati, Lisma Shafarulloh, M. Hisyam Shinta Siti Sundari Sihab, Rifqi Maulana Sukma, Rexy Khoerul Teuku Mufizar Teuku Mufizar Wakih, Agus Ahmad Yogi _ Yusep Rosmansyah Yusuf Sumaryana