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Andirwana
Medical Laboratory Technology Study Program, Health Science College Of Papua, Southwest Papua, Indonesia.
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An AI-Powered Diagnostic Tool for Plasmodium Malaria: A Case Study on Microscopic Image Analysis Junaiddin Junaiddin; Andirwana Andirwana; Muhamad Faizal Arianto; Astuti R Astuti R; Andi Sulfikar; Muhammad Rivaldi; Khusnul Sari Wahyuni
Indonesian Journal of Global Health Research Vol. 7 No. 6 (2025): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v7i6.501

Abstract

Malaria is still become disease the infection that has the biggest impact to health humans all over the world. When parasites Plasmodium enter into blood can influence physiology general body host, so that can cause disruption of hematological parameters which can cause a number of manifestation clinical such as anemia and thrombocytopenia so that can make things worse Health conditions. Identification in a way accurate infection parasite plasmodium is very important for determine therapy that will given with right. Technology intelligence artificial intelligence (AI) offers solution innovative For identify parasite Plasmodium Malaria with more efficient and accurate. AI, especially that based on deep learning and computer vision, can analyze picture microscopic with high speed and accuracy so that help speed up diagnosis and treatment in Medical decision. For develop and test system based intelligence artificial that can in a way automatic classify type parasite Plasmodium Malaria based on picture microscopic. Type study This covering image data set collection parasite Plasmodium malaria from laboratory medical, data labeling, and training of deep learning models based on convolutional neural networks (CNN). This model will evaluated based on accuracy, sensitivity, and specificity in differentiate various type Plasmodium. Type study is combination between experimental, quantitative and developmental AI technology in microbiology medical. Malaria Level (Mild, Moderate, Severe) and Duration of AI Use (Sig = 0.004). While Malaria Level and Duration Inspection Microscopic Conventional show significant and relevant results, which strengthen urgency innovation AI-based. With mark significance (Sig) 0.006, AI (Artificial Intelligence) is effectively superior in the diagnosis of Severe Malaria in endemic areas.
Comparison Of Urine Leukocyte Examination In Patients With Urinary Tract Infections (Utis) Using The Dipstick And Microscopic Methods In The Working Area Of Klasaman Health Center Junaiddin Junaiddin; Sahrul Gunawan; Evi Hudriyah Hukom; Muhamad Faisal Arianto; Andirwana; Sakinah Sarnia Iriani Lihawa; Sabila
Indonesian Journal of Nursing and Health Care Vol. 2 No. 1: February (2025)
Publisher : Ammar Dharma Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64914/g6tr4e86

Abstract

Background: Urinary tract infection (UTI) is a common type of infection caused by the growth of microorganisms in the human urinary tract. Leukocytes are a component of the immune system that fight infection and inflammation. The methods commonly used for urine leukocyte examination are the dipstick and microscopic methods.Objective: This study aims to compare the results of urine leukocyte examination between the dipstick and microscopic methods in UTI patients.Methods: This research is descriptive comparative with a cross-sectional design. The study was conducted at Puskesmas Klasaman and the TLM Laboratory of STIKES Papua from June 28 to August 21, 2024. The study population includes all UTI patients at Puskesmas Klasaman, Sorong City, totaling 16 patients, with a sample of 16 urine samples from patients confirmed positive for UTI, selected using a total sampling technique. The data collected were entered into a master table and analyzed statistically.Results: The results of the urine leukocyte examination using the dipstick method showed that the majority of respondents had results of approximately 70 leukocytes/µl (+1), while the results from the microscopic method indicated that the majority had 5-9 cells/HPF (+2). This study found a significant difference between the results of urine leukocyte examination using the dipstick and microscopic methods (p-value < 0.05) using the nonparametric Wilcoxon Signed Rank Test (WSRT).Conclusion: There is a significant difference in the results of urine leukocyte examination between the dipstick and microscopic methods, where the dipstick method is more practical but less accurate compared to the more detailed and accurate microscopic method. It is recommended to explore other urine examination methods and compare the results with a larger sample to understand the advantages and disadvantages of each method.
Co-Authors Agung, Angelich Windy R AMIR, NURHIDAYAH Andi Sulfikar Astuti R Astuti R Astuti R Cindy H. May Diva Dallas Soulisa Emray, Joan Etnis, Baktianita Ratna Etnis, Baktianti Ratna Evi Hudriyah Hukom Evi Hudriyah Hukom Evi Hudriyah Hukom Fatimah Fenti A Tupanwael Fenti A Tupanwael Fenti A. Tupanwael Fitriani Fitriani Grecia Felicia Lopulalan Gunawan, Sahrul Hukom, Evi Hudriyah Junaiddin, Junaiddin Khusnul Sari Wahyuni Lerebulan, Exaudian Flourens Marasabessy, Hadija Muhamad Faisal Arianto Muhamad Faizal Arianto Muhammad Rivaldi Mulyati Mulyati Nurfatimah, Lia Sabila Sakinah Sarnia Iriani Lihawa Sulfikar, Andi Taborat, Miranda Tupanwael, Fenti A Tyas, Lusia Wahyunig Untari