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All Journal Indonesian Journal of Halal Research International Journal of Disaster Management
Khamidinal Khamidinal
chemistry department UIN Sunan Kalijaga Yogyakarta
Religion Humanities Biochemistry, Genetics & Molecular Biology Decision Sciences, Operations Research & Management Earth & Planetary Sciences Environmental Science Medicine & Pharmacology Social Sciences Other

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Detection of Animal Fat Mixtures in Meatballs Using Fourier Transform Infrared Spectroscopy (FTIR Spectroscopy) Fajriati, Imelda; Rosadi, Yusi; Rosadi, Nisrina Nabila; Khamidinal, Khamidinal
Indonesian Journal of Halal Research Vol. 3 No. 1 (2021): February
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ijhar.v3i1.11166

Abstract

Detection of animal mixtures in meatballs by using Fourier Transform Infrared Spectroscopy (FTIR spectroscopy) has been studied. This research aims to study the different markers of fat characters in meatballs containing the mixture of chicken fat, lard and rat fat. Sample preparation used Soxhlet extraction with n-hexane solvent and distillation of fat from the solvent. The extraction temperature is 70°C with solvent volume 200 mL. Fat samples were prepared by varying the ratio of 100% chicken fat concentration which corresponds to 1%, 10%, and 20% lard, and 1%, 10%, and 20% rat fat. The meatballs were made with a composition of 0%, 5% and 90% rat meat. The result of FTIR interpretation shows that the increasing concentration of the mixture of lard and rat fat have increased the absorption at wave numbers of 3371 cm-1, 3332 cm-1, 2337 cm-1, and 1743 cm-1. The FTIR spectrum is interpreted based on the uptake of typical functional groups of animal fats. The characteristics of animal fat properties can be distinguished by consistent results using infrared spectroscopy.
Workload Analysis of Rapid Response Team Regional Disaster Management Agency at the Support Command Post of the COVID-19 Task Force Special Region of Yogyakarta Indonesia Farihah, Tutik; Krisdiyanto, Didik; Murtono, Murtono; Khamidinal, Khamidinal
International Journal of Disaster Management Vol 7, No 1 (2024)
Publisher : TDMRC, Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/ijdm.v7i1.36714

Abstract

This Study evaluated mental workload of Rapid Response Team ((RRT) Regional Disaster Management Agency in Special Region of Yogyakarta as funeral team along COVID-19 pandemic. Mental workload is formed due to differences between individual abilities and performance demands of a task within a certain time. NASA TLX is the most widely used mental workload measurement, capable of being used in several levels of workload and sensitive to low workloads. The Rapid Response Team is a team to ensure that the disaster management process carried out quickly, accurately, skilled personnel to back up the medical team who continue to work hard so that the handling of the pandemic virus is better, and the virus does not spread. In this study, the subject of research is the funeral team of Rapid Response Team ((RRT) Regional Disaster Management Agency in Special Region of Yogyakarta Indonesia. Sampling data was collected online and offline using the Goggle Form in the range March-April 2021. There are 28 team members of the RRT who filled out the questionnaire. Workload assessment using the NASA-TLX and OWL methods falls within the range of medium (45.58458; 0.610535), high (74.73789; 0.739889), and very high (87.7969; 0.879976), with an average workload value of high (75.9935; 0.748672). Based on statistical tests using paired t-tests and one-way ANOVA, both methods are declared to be equivalent. The dimension that predominantly contributes to workload according to the NASA TLX method is Effort, followed by Mental Demands. Meanwhile, the factor that predominantly forms the workload according to the OWL method is S2 (Environmental Workloads, sub-factors: improper temperature, chemical exposure), followed by S3 (Body Motion and Postural Workloads, sub-factors: stooping, standing). The research findings offer manual guidance for workload identification, particularly utilizing OWL, serving as the foundation for workload assessment for teams involved in COVID-19, particularly in Indonesia. Additionally, this study also demonstrates that the OWL method possesses the same level of reliability as the NASA-TLX method.
Co-Authors Didik Krisdiyanto Imelda Fajriati Murtono Murtono Rosadi, Nisrina Nabila Rosadi, Yusi Tutik Farihah, Tutik