Article Per Year (5 Year)
p-Index From 2021 - 2026
2.908
P-Index
This Author published in this journals
All Journal Telematika : Jurnal Informatika dan Teknologi Informasi JUITA : Jurnal Informatika JOIV : International Journal on Informatics Visualization IJCIT (Indonesian Journal on Computer and Information Technology) Martabe : Jurnal Pengabdian Kepada Masyarakat JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Linguistik Komputasional Jurnal Ilmu Teknik dan Komputer Jurnal Abdidas JUSTIN (Jurnal Sistem dan Teknologi Informasi) Universal Raharja Community (URNITY Journal) Jurnal Indonesia Sosial Teknologi Eduvest - Journal of Universal Studies Jurnal Pengabdian Masyarakat Nasional Engagement: Jurnal Pengabdian Kepada Masyarakat Journal Collabits
Afiyati, Afiyati
Universitas Mercu Buana
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Neuroscience Public Health Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Journal Collabits

 1 
Linear Regression Algorithm in Pulse Purchase System Simple Using Python Afiyati, Afiyati; Ayu, Kurnia Gusti; Roza, Yuni; Sakhrassalam, Haytsam; Syafiq, Nur Muhammad Zihni
Journal Collabits Vol 1, No 2 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i2.27256

Abstract

In today's digital era, the online credit purchase system has become an integral part of everyday life. The use of linear regression algorithms in this context is becoming increasingly relevant, as it provides a powerful approach to analyzing and predicting pulse buying patterns. This research proposes a simple pulse purchase system that implements a linear regression algorithm, using the Python programming language. The purpose of this study is to develop a predictive model that can estimate the amount of credit to be purchased based on certain variables, such as the time of purchase, the number of previous transactions, and the value of prior purchases. By analyzing historical transaction data, the system can take into account possible purchase patterns and estimate future credit needs with an adequate level of accuracy. The implementation of linear regression algorithms in Python allows users to easily access and use this pulse purchase system. Through a simple but intuitive interface, users can enter their transaction parameters and the system will predict the required number of pulses. Experiments were conducted to test the performance of this system in producing accurate predictions. The results of the experiment show that this system can provide estimates close to the real value, with a high degree of accuracy. This indicates that the use of linear regression algorithms in pulse purchase systems has great potential to improve efficiency and reliability in online transactions. In addition, the implementation of this algorithm also has a positive impact on transaction security. By analyzing purchasing patterns, the system can detect anomalies or suspicious activities that may occur, thereby increasing the level of security in the process of buying credit online. Overall, this study shows that the use of linear regression algorithms in pulse purchase systems has significant benefits in improving the efficiency, reliability, and security of online transactions. The practical implementation of this algorithm in the Python programming language opens the door for further development in the analysis and optimization of future pulse purchase system.
Web-based Application Design "UMB Eats" With Laravel Framework Afiyati, Afiyati; Fahrezi, Zidane; Rizky, Muhammad; Ardi, Liandy Hayanto; Ahmad, Ersa
Journal Collabits Vol 2, No 1 (2025)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v2i1.31239

Abstract

The ‘UMB Eats’ application was developed to improve the efficiency of Mercu Buana University canteen services by providing online ordering and payment features. This application makes it easier for users to access menu information, prices, and food stocks, while reducing long queues at the canteen. This research aims to design a web-based system that is practical and helps the management of orders and stock by sellers. As a result, ‘UMB Eats’ proved to provide a faster and more convenient experience for users, as well as supporting a more organised canteen operation.
Toothpaste Brand Prediction Based on Analysis of Teeth Condition and Price Preferences Using the Random Forest Algorithm Afiyati, Afiyati; Ningrum, Rahma Farah; Naima, Faaza
Journal Collabits Vol 1, No 1 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i1.25560

Abstract

This study aimed to predict toothpaste brands based on an analysis of dental conditions and price preferences using the Random Forest algorithm and the CRISP-DM approach. The research results indicated that the variables of tooth color range and frequency of toothache had the highest influence, suggesting that consumers were more likely to choose a brand based on tooth color and sensitivity. Evaluation using the Confusion Matrix and Classification Report models demonstrated good performance with an accuracy of 91.3%. Based on the result, the model could serve as a robust foundation for developing a GUI-based Toothpaste Brand Prediction Application using the tkinter library, assisting users in making more informed decisions.
Co-Authors Abdul Karim Ahmad, Ersa Alief Rama, Alief Ramadhan Dwi Putra Anis Cherid Anny Kartika Sari Ardi, Liandy Hayanto Arrachman, Abdul Kholiq Ayu, Kurnia Gusti Azhari Azhari Bambang Jokonowo Fahrezi, Zidane Gian Maulana Hadi Santoso Hadi Santoso Hanif, Ilham Hilyah Magdalena Karisma Riskinanti Kurnia, Rizki Ade Lestari, Mulyati Lukman Hakim Maun Harahap, Rachmita Mira Zulia Suriastuti Mohamad Yusuf Muchtar, Irfan Rasyid muhammad rizky, muhammad Naima, Faaza Ningrum, Rahma Farah Novrizal, Kevin Riando, Dhafin Roza, Yuni Sabar Rudiarto Saddam Wahib Rozaqi Sakhrassalam, Haytsam Siti Maesaroh Sukur, Daan Surya Aji Prasetio Syaban, Zulfikar Syafiq, Nur Muhammad Zihni Yuli yuli Astari Zelina, Nur