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Rancang Bangun Alat Monitoring Suhu Blood Bank Refrigerator Dengan Sistem Database Soeparli, Alian Jerly; Muhtar, Muhtar; Ruhyana, Lili; Gunawan, Gunawan
Jurnal Tika Vol 8 No 3 (2023): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v8i3.2389

Abstract

Blood Bank Refrigerator is a piece of equipment used as a cooler. It is usually used to store blood, and various blood products such as plasma, platelets, and red blood cells. Blood Bank Refrigerator can maintain the quality of blood products even if stored for a long time. Inappropriate temperatures can make blood clot or rupture, making it unsafe to give to patients. The problem with the blood bank referigator is that it cannot be monitored, and currently monitoring the temperature in the blood storage refrigerator is still done independently by taking manual notes.Based on the description above, in this Final Project the author will make a database-based blood bank referigator temperature monitoring tool. This research uses the System Development Life Cycle (SDLC) method, which is the process of making and changing systems as well as models and methodologies used to develop a system. The temperature measurement is done with a value of 4 ° C which is displayed on the LCD and database. Using an average time of 12 minutes and measurements every 2 minutes testing 6 times from 2 blood bank refrgator obtained an average difference of less than 0.2°C. After testing and data collection of the module, it can be concluded that the module and program run well in accordance with the plan.
Design and Construction of a Digital Microscope for Automatically Counting Escherichia Coli Bacteria Using Artificial Intelligence (AI) Ruhyana, Lili; Muhtar; Gunawan; Legowo, Danang Kristioko; Firman, Abdul
Jurnal Kesehatan Masyarakat Perkotaan Vol. 5 No. 2 (2025): Jurnal Kesehatan Masyarakat Perkotaan
Publisher : LPPM Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jkmp.v5i2.3239

Abstract

Detection and counting of Escherichia coli (E. coli) bacteria is an important indicator in assessing water quality and food safety, particularly in the field of environmental health. Conventional methods still require a long time, skilled personnel, and have the potential to cause subjectivity in microscopic observations. This study aims to design and build a digital microscope system equipped with an automatic bacterial counting system based on Artificial Intelligence (AI). The use of this technology is expected to accelerate microbiological analysis, improve detection accuracy, and reduce subjectivity in the manual counting process. The study was conducted using an experimental approach with the System Development Life Cycle (SDLC) method. The dataset consists of 3,011 bacterial images divided into 74% training data, 13% validation data, and 13% test data. The object detection model uses YOLOv11 integrated with Roboflow for annotation and dataset management. Test results show that the model achieved a detection accuracy of 94.1% on the test data, indicating good performance in identifying and counting E. coli colonies. The system is also equipped with a Streamlit-based interface to facilitate users in visualizing detection results in real-time. Thus, the design of this AI-based digital microscope can be an effective and efficient solution to accelerate and improve the accuracy of microbiological analysis, especially in the detection of E. coli bacteria in the fields of environmental health and food safety.