Hospitalized patients are very susceptible to various food-borne diseases. Food management in the hospital needs more careful attention. Hazard Analysis Critical Control Point (HACCP) is a preventive control system based on identification of critical points in the management and production of food as a way to ensure food safety. The objective of this study is to identify the implementation of HACCP principles in nutritional and dietetic service of RSUD Toto Kabila, Bone Bolango. This qualitative study employed descriptive survey method with HACCP as the study focus. The informants consist of eight people; three people as key informants and five people as triangulation informants obtained by purposive sampling. Data were analyzed using Miles and Huberman method, in which the collected data was written as matrix and then as checklist. The result revealed that nutrition and dietetics of RSUD Toto Kabila Bone Bolango was yet to implement HACCP according to the national standard (without documentation). This issue attributed lack of facilities and human resources at the department. It is suggested that the hospital implements HACCP according to the Indonesian National Standard as well as provides supporting facilities.
The airline business is one of the businesses determined by the quality of its services. Every airline creates its best service so that customers feel satisfied and loyal to using their services. Therefore, customer satisfaction is an essential metric to measure features and services provided. By having a database on customer satisfaction, the company can utilize the data for machine learning modelling. The model generated can predict customer satisfaction by looking at the existing feature criteria and becoming a decision support system for management. This article compares machine learning between Split Point and Attribute Reduced Classifier (SPAARC), Multilayer Perceptron (MLP), and Random Fores (RF) in predicting customer satisfaction. Based on the data testing, the Random Forest algorithm provides better results with the lowest training time compared to SPAARC and MLP. It has an accuracy of 95.827%, an F-score of 0.958, and a training time of 84.53 seconds.
Phenols are the oldest antimetabolites that are often used as disinfectants or microbiosides. Phenols are aromatic compounds that have a distinctive odor and include derivatives of benzene (C6H6). Phenol has a germicidal effect that causes protein denaturation and has active substances on the surface (surfactants) so that it can damage cell membrans and control the growth of microbes that can prevent nosocomial infections in hospitals. Pseudomonas aeruginosa is a Gram-negative bacteria that can live on medical equipment and other parts of the hospital that can cause post-surgical infections.The aims of research to determine the inhibition of phenol antimetabolites against Pseudomonas aeruginosa.Through a literature study of several research results that have been published in scientific journals, it is known that the method and concentration used are very influential in testing the inhibition of phenol antimetabolites on the growth of Pseudomonas aeruginosa bacteria. The results of several literature searches state that phenol antimetabolites are only able to inhibit the growth of Pseudomonas aeruginosa with a weak strength of 4±0,5 - 11 mm. In Lysol which is a phenol antimetabolite that reacts with halogens, there is a large difference in the zone of strong (sensitive) inhibition, which is influenced by a large concentration with the greatest inhibitory strength at concentrations of 75% and 100%, with a diameter of 26 mm. From the results of research that has been done it can be concluded that, phenol antimetabolites can inhibit Pseudomonas aeruginosa.
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