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All Journal Jurnal Nasional Holistic Science LEBAH Indonesian Journal of Education And Computer Science Jurnal Sains dan Teknologi Informasi
Ritonga, Rama Prameswara
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Increasing cybersecurity awareness among teenagers through digital education and simulation Riandari, Fristi; Tasril, Virdyra; Ritonga, Rama Prameswara
Lebah Vol. 18 No. 1 (2024): September: Pengabdian
Publisher : IHSA Institute

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

Abstract

This community service aims to explore the role of digital education and simulation tools in enhancing cybersecurity awareness among teenagers. The review examines various educational methods, including e-learning platforms, gamification, and phishing simulations, to evaluate their effectiveness in increasing cybersecurity knowledge and skills. The methodology involves analyzing relevant studies from academic databases, combining both qualitative and quantitative research. Key findings suggest that interactive digital education and simulations significantly improve teenagers' ability to recognize and address online threats. However, challenges remain regarding long-term retention and engagement. The review highlights the growing importance of these tools in educating teenagers, emphasizing the need for their integration into educational settings. Trends include the use of gamification and simulations, while gaps in research, such as long-term effectiveness and cultural influences, remain. Recommendations for future initiatives include AI-driven simulations and incorporating cybersecurity education into social media platforms for broader reach.
Development of Marker-Based Augmented Reality Application for Learning Hijaiyah Letters in Tahfiz Schools Nasution, Mutiara Akbar; Ritonga, Rama Prameswara; Ahlun, Zaid; Lubis, Muhammad Rafli Taufiq
Holistic Science Vol. 5 No. 1 (2025): Jurnal Nasional Holistic Sciences
Publisher : Lembaga Riset Mutiara Akbar NOMOR AHU-0003295.AH.01.07 TAHUN 2021

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/hs.v5i1.894

Abstract

Learning Hijaiyah letters is an early stage in Islamic education, but conventional methods are often less interesting for children. Augmented Reality (AR) offers an innovative solution that can increase interactivity in the learning process. This study aims to develop and test a marker-based AR application for learning Hijaiyah letters in Tahfiz Schools. This application allows users to scan markers to display Hijaiyah letters in three dimensions and hear their pronunciation. The research method used is Research and Development (R&D) with a Waterfall model that includes needs analysis, design, implementation, and testing. Evaluation was carried out through Blackbox Testing for functionality and user questionnaires. The test results showed that this application functions well, is easy to use, and is attractive to students. The majority of users stated that the appearance and sound of the application are of good quality. Augmented Reality technology has been proven to improve the learning experience to be more interactive and effective. This study is expected to be a reference for the development of AR applications in Islamic education.
Komparasi Metode Certainty Factor dan Dempster Shafer untuk Mendiagnosa Penyakit Autis Ginting, Ramadhanu; Riandari, Fristi; Afrisawati; Syechu, Weno; Afifa, Rizky Maulidya; Ritonga, Rama Prameswara
Indonesian Journal of Education And Computer Science Vol. 3 No. 1 (2025): INDOTECH - April 2025
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/indotech.v3i1.1212

Abstract

Penelitian ini membahas perancangan sistem yang bertujuan untuk menangani masalah autisme pada anak-anak. Autisme merupakan gangguan yang mempengaruhi kemampuan individu, terutama dalam hal interaksi sosial. Dalam konteks ini, sistem pakar digunakan untuk mentransfer keahlian seorang pakar ke dalam bentuk algoritma yang dapat digunakan untuk diagnosis.Penelitian ini menganalisis dua metode dalam sistem pakar, yaitu Certainty Factor dan Dempster Shafer, yang ditujukan untuk mendiagnosis autisme pada anak. Tujuan utama penelitian ini adalah untuk mengevaluasi dan menentukan metode mana yang paling efektif untuk diimplementasikan dalam aplikasi yang dapat membantu mengklasifikasikan anak-anak dengan autisme.Hasil komparasi menunjukkan bahwanya metode Certainty Factor mencapai tingkat probabilitas di atas 95 %, dibandingkan dengan metode Dempster Shafer dalam komparasi 2 metode yang penulis lakukan. Temuan ini memberikan wawasan yang signifikan mengenai efektivitas kedua metode, serta kontribusi mereka dalam pengembangan sistem pakar untuk diagnosis autisme. Diharapkan penelitian ini dapat menjadi referensi untuk solusi yang lebih baik dalam bidang kesehatan mental anak.
Penerapan Teknik Data Mining dengan Algoritma Regresi Linier Berganda Untuk Estimasi Tingkat Penjualan Cafe Ritonga, Rama Prameswara
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7801

Abstract

This study aims to apply data mining techniques using multiple linear regression methods to estimate sales levels. Efficient sales are a key factor in the success of a cafe business; therefore, this approach is expected to provide accurate predictions to assist management in strategic decision-making. The main problem faced is uncertainty in forecasting sales levels, which can lead to excess or shortages of raw material stocks, operational disruptions, and decreased profits. Therefore, this study focuses on developing a multiple linear regression model that can utilize historical sales data, environmental variables, and other related factors to produce more accurate estimates. This research method involves collecting sales data from previous periods, analyzing statistics, and applying multiple linear regression as the main tool for building a prediction model. In addition, the selection and adjustment of variables that most influence sales levels are also focused in this study. The results show that the multiple linear regression model can provide more accurate sales level predictions compared to conventional methods. This can assist in inventory planning, operational management, and marketing strategy development to improve business performance. The implementation of data mining techniques with this method makes a significant contribution to supporting the sustainability and growth of cafe businesses in an era of increasingly fierce business competition.
Co-Authors Afifa, Rizky Maulidya Afrisawati Ahlun, Zaid Ginting, Ramadhanu Lubis, Muhammad Rafli Taufiq Mutiara Akbar Nasution Riandari, Fristi Syechu, Weno Tasril, Virdyra