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All Journal INDONESIAN JOURNAL OF MEDICAL LABORATORY SCIENCE AND TECHNOLOGY Journal of Indonesian Medical Laboratory and Science (JoIMedLabS) Current Biomedicine Mukhtabar: Journal of Medical Laboratory Technology
Rinaldi, Sonny Feisal
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Biochemistry, Genetics & Molecular Biology Chemistry Health Professions Immunology & microbiology Medicine & Pharmacology Public Health Social Sciences Veterinary

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Penentuan Taksiran Ketidakpastian (Uncertainty) dengan Metode Top-down dan Korelasinya Terhadap Total Error (TE) pada Parameter Hematologi Salvia Maharani, Farah; Ridwanna, Surya; Harianto, Harianto; Rinaldi, Sonny Feisal
Journal of Indonesian Medical Laboratory and Science Vol 5 No 1: April 2024
Publisher : Asosiasi Institusi Pendidikan Tinggi Teknologi Laboratorium Medik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53699/joimedlabs.v5i1.190

Abstract

Background: Uncertainty Measurement (UM) is defined as a parameter associated with a measurement result that characterizes a dispersion of values that can reasonably be associated with a quantity. ISO 15189 clause 5.5.1.4. states that the laboratory shall determine measurement uncertainty for each measurement procedure in the examination phase used to report measured quantity values on patients samples. Objectives: According to Westgard, there is debate about difference between the concepts of Uncertainty and Total Error (TE) so this study was conducted which aims to determine the uncertainty value of hematological parameters and determine the correlation of Uncertainty and TE. Materials and Methods: The material in this research are data of Internal Quality Control (IQC), External Quality Control (EQC), and Uncertainty data from the Sysmex XN-1000 calibrator. Results: Through the results the average uncertainty value of Sysmex XN-1000 2022 for leukocyte with low, medium and high levels, are ±19.05%, ±18.07 %, and ±15.94%, while for erythrocyte are ±4.46%, 4.10%, 4.16%, for hemoglobin are ±5.63, ±5.07, ±5.01, for hematocrit are ±8.99%, ±8.19%, ±8.19%, and for platelet are ±79.23%, ±62.23%, ±58.29%. Conclusions: Based on the uncertainty and TE calculated permonth for each lot number during 2022, the correlation was obtained between the Uncertainty and TE among leukocyte and hematocrit were stated to have a weak correlation, for hemoglobin and platelet it was stated quite correlated and erythrocytes are stated to be strongly correlated.
Comparison of the sigma metrics using the total error allowable algorithm with variation of bias source Rinaldi, Sonny Feisal; Ibadurrahmah, Anisa Agustia; Ridwanna, Surya; Harianto, Harianto
JURNAL INDONESIA DARI ILMU LABORATORIUM MEDIS DAN TEKNOLOGI Vol 6 No 1 (2024): Advancements in Biomedical Research: Insights from Medical Laboratory and Technol
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/ijmlst.v6i1.4930

Abstract

Sigma Metrics, as a quality indicator, have been widely applied in clinical laboratories to assess the performance of analytical methods. Described in the document Clinical and Laboratory Standards Institute (CLSI) EP15- A3, the use of target values can be sourced from certified reference standards, survey materials from the Proficiency Testing (PT)/External Quality Assessment (EQA), materials used in inter-laboratory quality control programs and internal quality control materials with predetermined targets. This research aims to determine whether there is a difference in the sigma metrics between the bias derived from the manufacturer's target value and those from the peer group source in the External Quality Assurance Services (EQAS) program. The research methodology employed is descriptive comparative analysis, utilizing the results of material inspection data for 15 internal quality control parameters of Clinical Chemistry over a span of 2 years at the Pramita Laboratory in Bandung. The calculation of the sigma metrics commences with computing the coefficient of variation (CV), and the appropriate Total Error aalowable (Tea) sources for each parameter are determined beforehand using the TEa algorithm. The research findings indicate a difference between the sigma metrics derived from the manufacturer's target value and those from the EQAS-peer group target value, accounting for 33% or 10 parameters out of the total parameters with 2 levels of inspection are calculated on the sigma scale. However, in 67% or 20 parameters out of the total parameters, no such difference is observed. Bias associated with the target value from the manufacturer and the EQAS peer group shows no significant difference, suggesting that the laboratory can utilize pre-existing target values confidently.
In silico prediction of multi-epitope vaccine candidates against Mycobacterium leprae Shabrina, Almas; Indra, Asep Iin Nur; Rinaldi, Sonny Feisal; Merdekawati, Fusvita
Current Biomedicine Vol. 3 No. 1 (2025): January
Publisher : School of Veterinary Medicine and Biomedical Sciences, IPB University, Bogor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/currbiomed.3.1.22

Abstract

Background Leprosy, also known as Hansen's disease, is an infectious disease caused by Mycobacterium leprae. Despite ongoing efforts to control the disease, leprosy remains a global health concern, with Indonesia ranking third in the world for the highest number of cases. Objective This study aims to identify epitopes that can induce T and B cell immune responses through an in silico approach, to design a multi-epitope vaccine candidate against Mycobacterium leprae. Methods The study used an in silico vaccine design approach utilizing ESAT6, Ag85B, ML2028, ML2380, and ML2055 proteins from Mycobacterium leprae. The process involved sequence alignment, T cell (CTL and HTL) and B cell epitopes identification, and antigenicity, allergenicity, and toxicity assessment. Selected epitopes were constructed into a multi-epitope vaccine candidate using linkers. The tertiary structure of the vaccine was modeled with AlphaFold and evaluated via Prosa-web. The stability and interaction between the vaccine candidate and TLR4 were analyzed using molecular docking. Results The vaccine candidate demonstrated stable interactions with TLR4, with a binding free energy of -13.9 kcal/mol. The vaccine candidate was also predicted to be stable, antigenic, non-allergenic, non-toxic, and hydrophilic. Conclusion This in silico design of a multi-epitope vaccine candidate shows potential for development as a vaccine against leprosy.
Evaluation of Quality Indicators with Lean Six Sigma In Pre and Post Analytical Laboratories Nurhadi, Muhammad Ihsan; Ridwanna, Surya; Rinaldi, Sonny Feisal; Nurhayati, Betty
Mukhtabar Journal of Medical Laboratory Technology Vol 3 No 1 (2025): Mukhtabar: Journal of Medical Laboratory Technology (April 2024)
Publisher : LPPM STIKes Muhammadiyah Ciamis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52221/mjmlt.v3i1.795

Abstract

Background & Objective: Medical laboratories have an important role of 60-70% in diagnosis, patient monitoring, and prevention and treatment of diseases. Therefore, the laboratory must maintain and ensure the quality of service process. This study aims to determine the sigma value and identify waste in pre and post analytical in the laboratory, as well as determine Improvement proposals in order to reduce errors pre and post analytical laboratory. Method: This research design is descriptive study that Analyzes the process and quality indicators at pre and post analytical with the Lean Six Sigma approach, which is a combination of Lean methods that focus on eliminating waste and Six Sigma that focuses on eliminating defects. This research was conducted as a process Improvement effort with five Six Sigma work steps (DMAIC) and identified eight types of waste (DOWNTIME). Result: The results showed that the sigma value at pre and post analytical was 4.6 and 3.5 Sigma, and total sigma value for pre-post analytical was 4.3 Sigma so that both had not met the minimum target achievement of 5 Sigma (Excellent). There are two quality indicators that require improvement and enhancement including suitability of sample and TAT. The results also show that there are 4 wastes, consisting of 1 Defects, 1 Waiting, and 2 Not Utilizing Employees Knowledge. Conclusion: Proposed Improvements are then given so that all waste identified in this study can be minimized so that the achievement of sigma quality indicators can increase.
Analisis Unit Cost Quality Control Kimia Klinik dengan Metode Activity Based Costing di Laboratorium Rumah Sakit Paru dr. H. A. Rotinsulu Suryadi, Arfiah Azzahra Nissa; Kurniawan, Entuy; Rahayu, Ira Gustira; Rinaldi, Sonny Feisal; Hidayatullah, Taufik
Journal of Indonesian Medical Laboratory and Science Vol 6 No 1: April 2025
Publisher : Asosiasi Institusi Pendidikan Tinggi Teknologi Laboratorium Medik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53699/joimedlabs.v6i1.192

Abstract

Hospital laboratories must comply with quality and safety standards as they are responsible for patients' health test results. Laboratory test results must be reliable, so the quality of laboratory services needs to be improved, including implementing quality control measures. Conducting a unit cost analysis for quality control activities is necessary to determine the expenses incurred for each quality control activity. The objective of this writing is to determine the unit cost for Clinical Chemistry Quality Control in the laboratory using the Activity-Based Costing method. Data collection techniques include interviews, observations, and document studies. Various costs are involved in determining the ABC method, including labor costs, depreciation costs for equipment or buildings, and other costs. In addition to cost data, cost drivers are also important in determining them. The equipment used in this research is the Sysmex BX with a total of 14 examination parameters, including glucose, total bilirubin, direct bilirubin, SGOT / AST, SGPT / ALT, total protein, albumin, urea, creatinine, uric acid, cholesterol, triglycerides, HDL, LDL. Based on the research results, the cost of QC for clinical chemistry examinations is Rp. 102,477
Co-Authors Harianto Harianto Ibadurrahmah, Anisa Agustia Indra, Asep Iin Nur Kurniawan, Entuy Merdekawati, Fusvita Nurhadi, Muhammad Ihsan Nurhayati, Betty Rahayu, Ira Gustira Ridwanna, Surya Salvia Maharani, Farah Shabrina, Almas Suryadi, Arfiah Azzahra Nissa Taufik Hidayatullah, Taufik