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All Journal Infotech: Journal of Technology Information
Francka Sakti Lee
Sistem Informasi, Universitas Bunda Mulia, Jakarta
Computer Science & IT

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PENGEMBANGAN APLIKASI REMINDER ONLINE PAYMENT KOST BERBASIS MOBILE Yemima Monica Geasela; Kevin Christianto; Francka Sakti Lee; Fidelia Novena Doa; Angie Wiyani Putri
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.571

Abstract

The advancement of mobile technology provides opportunities for digital transformation in small-scale property businesses, including boarding house (kost) management. This research focuses on developing a Mobile-Based Reminder Online Payment Application for Kost using the Mobile Application Development Life Cycle (MADLC) method. The application is designed to automate payment processes through a virtual account system and provide real-time reminder notifications for both tenants and owners.The development stages included requirement identification, system design using UML diagrams, database structuring with MySQL, and interface implementation. The testing process employed User Acceptance Testing (UAT) to validate system functionality and user satisfaction. The results show that users successfully received automatic payment notifications based on the configured due dates, and all online payment transactions were accurately recorded in the system database without errors. This study concludes that the MADLC approach effectively supports the structured development of mobile applications for digital payment and reminder management in boarding houses. The UAT results confirm that the application meets user expectations in terms of functionality, ease of use, and transaction accuracy.
PENINGKATAN PERFORMA MODEL MACHINE LEARNING UNTUK DETEKSI DINI POLYCYSTIC OVARY SYNDROME MELALUI KOMBINASI METODE PREPROCESSING Ahya Radiatul Kamila; Francka Sakti Lee; Johanes Fernandes Andry
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.448

Abstract

Polycystic Ovary Syndrome (PCOS) is one of the most common hormonal disorders experienced by women of reproductive age and can lead to various health problems, including menstrual irregularities, infertility, and an increased risk of metabolic diseases. Early detection of PCOS is essential to minimize long-term impacts and improve the quality of life for patients. This study aims to identify effective data preprocessing strategies to enhance the performance of classification models for PCOS detection. The dataset used is open source, consisting of 541 participants with 45 clinical and laboratory features. The main challenges encountered include the presence of many missing values, an imbalanced target class distribution, and a large number of independent features. To address these issues, a series of preprocessing steps were applied, including missing value imputation, data balancing using the Synthetic Minority Over-sampling Technique (SMOTE), and dimensionality reduction using Principal Component Analysis (PCA). A classification model was built using the Random Forest algorithm, and its performance was compared before and after applying PCA. The evaluation results show that before PCA, the model achieved an accuracy of 87.5%, precision of 86%, recall of 86%, and an F1-score of 86%. After applying PCA, performance improved to an accuracy of 90%, precision of 89%, recall of 89%, and an F1-score of 89%. These findings indicate that the right combination of preprocessing strategies, particularly SMOTE and PCA, can significantly improve the efficiency and effectiveness of models in detecting PCOS, thereby supporting the development of more reliable medical decision support systems.
RANCANG BANGUN APLIKASI INVENTORI DENGAN METODE PULL INVENTORY PADA PERUSAHAAN PERANGKAT JARINGAN Martinez Nicholas; Francka Sakti Lee
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.564

Abstract

A network equipment company specializing in the provision of switches and servers still faces challenges in stock management because the recording of outgoing goods and inventory withdrawal transactions is still done manually using notebooks and Excel. This condition causes problems such as delays in data updates, difficulties in monitoring stock availability in real time, and the risk of discrepancies between data and conditions in the warehouse. The objective of this research is to design and implement a web-based inventory application using a pull inventory approach, where stock is recorded only upon actual demand from projects or customers. This strategy helps reduce the likelihood of overstocking or understocking. Based on testing results, the developed application can support the recording of outgoing goods, provide real-time availability information, and generate useful reports for management, thereby supporting the efficiency, accuracy, and integration of the company's business processes.
Co-Authors Ahya Radiatul Kamila Angie Wiyani Putri Fidelia Novena Doa Johanes Fernandes Andry Kevin Christianto Martinez Nicholas Yemima Monica Geasela