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All Journal IJCIT (Indonesian Journal on Computer and Information Technology) Computer Science and Information Technologies Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian Masyarakat Nauli Journal Collabits
Prihandi, Ifan
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Computer Science & IT Education Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Journal Collabits

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Python Programming Implementation in Food Catalogue Creation Using GUI Danuarta, Brilian; Prihandi, Ifan
Journal Collabits Vol 2, No 2 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v2i2.27266

Abstract

In the modern world of programming, the development of user interface (GUI) applications is very important. A simple GUI application can be implemented using the Python programming language and standard modules such as Tkinter, Pandas, and os, as described in this journal. Using this application, users can view the product catalogue, add products to the shopping cart, and make payments. There will be a record of the transaction in an Excel file after the payment is completed. Readers will learn the basic concepts of GUI application development using Python through this practical approach. They will also learn how to use basic features such as file management, user interaction, and data manipulation. This article can serve as a guide for beginners in developing GUI applications using Python.
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.
Co-Authors Cherid, Ali Hadi Danuarta, Brilian Khabibillah, Khabibillah Miswadi Miswadi Muhammad Rifqi Nazua, Sifania Nurhadi Popy Yuliarty, Popy Prasetyo, Lindo Rahmat Budiarto Sari, Yunita Sartika Saruni Dwiasnati Yasin, Raihan Nur Zaenudin, Imam