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All Journal Jurnal Informatika Polinema (JIP) Science Information System and Technology
Rachmad Saptono
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Library & Information Science

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Implementation of Non-Invasive Detection of Cholesterol Levels, Hypertension Using Android-Based BPW34 and MPX5050GP Sensors Junus, Mochammad; Rachmad Saptono; Nugroho Suharto; Daffa Afrizal Wijaya
Jurnal Informatika Polinema Vol. 11 No. 3 (2025): Vol. 11 No. 3 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v11i3.6963

Abstract

High cholesterol levels and blood pressure are the main indications of body health which can cause heart attacks and strokes. Cholesterol deposits in the blood vessels can cause narrowing which results in hypertension and disorders of the components of the cardiovascular system. In accordance with the function of the cardiovascular system which is responsible for sending blood to various parts of the body, it is necessary to detect cholesterol levels and hypertension as early as possible in order to prevent heart attacks and strokes. The aim of this research is to measure cholesterol and hypertension levels using the BPW34 and MPX5050GP sensors and the addition of the GY-MAX30100 sensor to detect heart rate and oxygen saturation. The three sensors were combined as an experimental analysis test for a prototype medical tool for measuring blood cholesterol levels and hypertension in real-time, non-invasively (does not injure skin tissue). In this research, an application system was created in the form of a dashboard of test results for each sensor, which then sent the medical test data results to the user's smartphone to determine estimated values for cholesterol and hypertension levels for the purpose of initial medical examination.In this research, an application system was created in the form of a dashboard of test results for each sensor, which then sent the medical test data results to the user's smartphone to determine estimated values for cholesterol and hypertension levels for the purpose of initial medical examination. The results of the research show that the prototype created compared to standard medical measuring instruments, has the ability to measure cholesterol levels and blood pressure with an accuracy of 0.675% on the BPW34 sensor and 3.9% on the MPX5050GP sensor and 1.475% accuracy on the GY-MAX30100 sensor. heart rate and 1.305% for oxygen saturation. The measurement data can be connected successfully into an android application enabling remote and live monitoring. This system supports personal health management by enabling people to monitor their health conditions independently and in real time.
Smart Library Management System Using Face Recognition and RFID Based on Flask: Case Study of BBPPMPV BOE Malang Budiarti, Ambar; Farida Arinie Soelistianto; Rachmad Saptono
West Science Information System and Technology Vol. 3 No. 02 (2025): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v3i02.2180

Abstract

This research aims to develop a Flask-based Smart Library system integrated with face recognition technology, RFID, and automated WhatsApp notifications to support library services at BBPPMPV BOE Malang. The face recognition system employs two methods: Local Binary Pattern Histogram (LBPH) and Convolutional Neural Network (CNN) for comparison. Testing results show that the LBPH method achieved a training accuracy of 98.77%, but its real-world recognition accuracy dropped to 39.77%. In contrast, the CNN method achieved a lower training accuracy of 69.11% but demonstrated more stable performance in real conditions with an average accuracy of 76.87%. RFID technology is implemented to automate the book borrowing and returning process through website integration, resulting in a time efficiency improvement of up to 74% compared to manual systems. Additionally, the system features real-time notification via WhatsApp using Venom Bot, which successfully delivers book transaction details accurately and consistently with the database records. The system is built using a Raspberry Pi 4 and the Flask framework and is accessed through a web-based interface. The implementation results show that the system significantly enhances the efficiency, security, and convenience of library services.
Co-Authors Budiarti, Ambar Daffa Afrizal Wijaya Farida Arinie Soelistianto Mochammad Junus Nugroho Suharto