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Journal : Journal Collabits

Use and Application of Virtual Reality (VR) in Learning Optimization and Effectiveness to Increase Student Interest in Learning: A Study Using Systematic Literature Review (SLR) Method Sari, Yunita Sartika; Santoso, Hadi; Rahmah, Nia; Ibrahim, Maulana; Imaman, Rahardian Aulia
Journal Collabits Vol 1, No 2 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i2.27264

Abstract

Adopsi media pembelajaran digital telah merevolusi cara kita belajar dan mengajar. Dalam konteks sistem pendidikan, sering ada kebutuhan untuk media baru. Media inovatif ini diharapkan dapat menyulut motivasi belajar siswa. Selain itu, integrasi mereka ke dalam sistem pendidikan bertujuan untuk meningkatkan prestasi siswa baik secara akademis maupun di luar. Media digital memiliki potensi yang signifikan untuk meningkatkan pengalaman belajar siswa. Penelitian ini berfokus pada kajian pustaka terkait pemanfaatan lingkungan belajar digital dalam pendidikan. Dalam lanskap yang berkembang pesat saat ini, banyak materi pembelajaran telah beralih dari format berbasis cetak ke digital. Meluasnya adopsi media digital dalam pendidikan mencakup teknologi mutakhir seperti virtual reality (VR). VR berfungsi sebagai alat pembelajaran yang kreatif dan mendalam, membawa siswa ke dunia baru yang menantang untuk dijelajahi melalui metode pengajaran tradisional. Penelitian secara konsisten menekankan pentingnya lingkungan belajar berbasis teknologi di abad ke-21. Media ini memfasilitasi keterlibatan siswa, membuat pembelajaran lebih interaktif dan efektif. Pada akhirnya, media pembelajaran mencakup media apa pun yang secara efektif menyampaikan pesan atau informasi antara siswa dan pendidik, menangkap perhatian, minat, pikiran, dan emosi mereka untuk mencapai tujuan pendidikan.Kata kunci: virtual reality (VR), lingkungan belajar digital, optimasi pembelajaran. 
Implementation Analytical Hierarchy Process Method to Improve the Effectiveness of Social Assistance Distribution Sari, Yunita Sartika; Hakim, Lukman
Journal Collabits Vol 1, No 1 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i1.25490

Abstract

Based on the report of the central statistics agency, the number of poor people in Indonesia reached 26.16 million people. The government has made efforts to provide assistance to overcome this problem, one of which is beneficiaries. The distribution of beneficiaries which is being held is still not optimal because of the uneven distribution of aid to underprivileged communities. The purpose of this research is to implement a Decision Support System (DSS) to determine the right community to receive beneficiaries which will be given based on several criteria used, namely: education, employment, and place of residence. In this study, proposes to build a model that has a decision-making concept. The method used in this Decision Support System is the Analytical Hierarchy Process (AHP). The expected results in this study are a decision support system that can assist in determining beneficiaries.
Comparative Analysis of Google Dialogflow and Rule-Based NLTK Chatbots for Application FAQ Yasin, Raihan Nur; Cherid, Ali Hadi; Prihandi, Ifan; Sari, Yunita Sartika
Journal Collabits Vol 2, No 3 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v2i3.27345

Abstract

This study presents a comparative analysis of two chatbot frameworks, Google Dialogflow and rule-based NLTK (Natural Language Toolkit), for the development of chatbots to handle frequently asked questions (FAQ) in applications. The study focuses on Blender, a popular 3D modeling software, as a case study. Ten testing questions were used to evaluate the chatbots' accuracy, precision, recall, and F1-score. The results showed that Dialogflow achieved an accuracy of 80%, precision of 80%, recall of 100%, and an F1-score of 88.9%. In contrast, the rule- based NLTK chatbot achieved an accuracy of 60%, precision of 66.7%, recall of 80%, and an F1-score of 72.8%. The study concluded that Dialogflow is a more effective and reliable chatbot for handling Blender FAQs due to its ability to retrieve relevant information from a large knowledge base and its use of machine learning algorithms to improve its performance over time. However, the rule-based NLTK chatbot may still be useful in certain situations where a more simple and customizable chatbot is required.