Claim Missing Document
Check
Articles

Found 5 Documents
Search
Journal : journal collabits

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.
Python Programming Implementation in Food Catalogue Creation Using GUI Brilian Danuarta; Ifan Prihandi
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 Raihan Nur Yasin; Ali Hadi Cherid; Ifan Prihandi; Yunita Sartika Sari
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.
Design and Implementation of a Python-Based Cinema Ticket Ordering Prototype Using Linear Search Ramando Girsang; Hisyam Fadhila; Yunita Sartika sari; Nia Rahmah Kurnianda; Ifan Prihandi
Journal Collabits Vol. 3 No. 2 (2026)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v3i2.27260

Abstract

The increasing adoption of digital services has encouraged the development of ticketing systems that simplify access to movie information and transaction processes. This study aims to design and implement a Python-based cinema ticket ordering prototype and to examine the suitability of the Linear Search algorithm for movie-title lookup in a small and unsorted dataset. The development process consists of requirements analysis, system design, implementation, functional verification, and algorithmic complexity analysis. The prototype supports customer input, movie selection, ticket quantity calculation, optional food and beverage ordering, and transaction calculation. Linear Search is selected because it can operate directly on a small unsorted list without preprocessing or an additional indexing structure. Theoretical comparison shows that Linear Search has O(n) average and worst-case time complexity, while Binary Search offers O(log n) complexity for sorted data and hash-based lookup offers O(1) average lookup time with additional storage requirements. The study therefore does not claim Linear Search as a new or universally efficient algorithm. Its contribution lies in presenting a transparent small-scale ticket-ordering architecture and an academically justified algorithm selection. Future development should incorporate persistent database storage, a graphical or web/mobile interface, authentication, secure payment integration, usability evaluation, and empirical performance benchmarking.