9 results on '"Rahman LA"'
Search Results
2. Inhibiting Factors in the Application of Risk Management at Hospital X Jakarta.
- Author
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Hernawati, Lestari, Hariyati, Rr. Tutik Sri, Pujasarit, Hening, Abdul Rahman, La Ode, Mutiasari, Hana, and Harpendewisasmita
- Subjects
NURSE administrators ,HOSPITAL administration ,QUALITATIVE research ,RISK management in business - Abstract
Background: The risk management program will run well with commitment and good management. This study aims to describe the experience of nurse managers in implementing risk management in hospitals. Research methodology: this study used a descriptive qualitative approach. The data collection technique used Focus Group Interviews with 12 nurse managers consisting of 1 Head of Sub Installation, 7 Head nurses, and 4 Team Leaders. Interviews were carried out three times, and each implementation consisted of four participants. Analysis using thematic content and consolidation for reporting qualitative research (COREQ) was used as a guide to research reporting. The research found three inhibiting factors in implementing risk management: 1) Busyness, 2) Lack of knowledge, and 3) Lack of structured monitoring and evaluation. Conclusion: The active participation of nurse managers in implementing risk management is very influential in the successful implementation of risk management in hospitals. Good time management, increasing the level of knowledge, and supported by a systematic risk management monitoring-evaluation system means that risk management will be carried out well. [ABSTRACT FROM AUTHOR]
- Published
- 2024
3. Inhibiting Factors in the Application of Risk Management at Hospital X Jakarta.
- Author
-
Hernawati, Lestari, Hariyati, Rr. Tutik Sri, Pujasari, Hening, Rahman, La Ode Abdul, Mutiasari, Hana, and Harpendewisasmita
- Subjects
OCEAN currents ,SEAWATER ,SALINE waters ,ACOUSTIC Doppler current profiler ,TIDAL currents - Abstract
Background: The risk management program will run well with commitment and good management. This study aims to describe the experience of nurse managers in implementing risk management in hospitals. Research methodology: this study used a descriptive qualitative approach. The data collection technique used Focus Group Interviews with 12 nurse managers consisting of 1 Head of Sub Installation, 7 Head nurses, and 4 Team Leaders. Interviews were carried out three times, and each implementation consisted of four participants. Analysis using thematic content and consolidation for reporting qualitative research (COREQ) was used as a guide to research reporting. The research found three inhibiting factors in implementing risk management: 1) Busyness, 2) Lack of knowledge, and 3) Lack of structured monitoring and evaluation. Conclusion: The active participation of nurse managers in implementing risk management is very influential in the successful implementation of risk management in hospitals. Good time management, increasing the level of knowledge, and supported by a systematic risk management monitoring-evaluation system means that risk management will be carried out well. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
4. Bagging and random forest classification methods for unbalanced data school dropout cases in Lampung province.
- Author
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Setiawan, Dhery, Wijayanto, Hari, Rahman, La Ode Abdul, Afendi, Farit M., and Raharjo, Mulianto
- Subjects
RANDOM forest algorithms ,CLASSIFICATION ,PROVINCES ,MISSING data (Statistics) - Abstract
Classification modeling is currently growing and its use is often found in various fields of work. A lot of researches have been conducted to determine the best classification method in predicting a class of an observation. Most of it says that bagging and random forest methods are the best in predicting a class of observation. However, most of the classification methods will encounter a problem when it is used to modeling an unbalanced data. It is also known that the number of school dropout is relatively less than the number of students who are currently active, so this can be a case study of unbalanced data. The purpose of this research is to compare the performance of bagging and random forest method before handling unbalanced data and the bagging and random forest method after handling unbalanced data with Synthetic Minority Oversampling Technique (SMOTE). The comparison of performance can be seen from the sensitivity score, balanced accuracy, and F1 score of each classification method. The comparison results show that the random forest method has better performance than the bagging method, both before and after handling unbalanced data. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
5. A comparison of fixed effect and mixed effect models in analyzing telecommunication products.
- Author
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Rahmawati, Fardilla, Notodiputro, Khairil Anwar, Rahman, La Ode Abdul, Afendi, Farit M., and Raharjo, Mulianto
- Subjects
TELECOMMUNICATION ,INTERNET sales ,TIME management - Abstract
Mixed model is a model that combines fixed factors and random factors while fixed model is a model that only contains fixed factors. Observations made over time with the same object being observed are called repeated measurement. This research was conducted to determine the determinant factors of internet data quota sales which are influenced by SA (Sales Area), MC (Mutual Check), PC (Product Category), and time factors using a nested linear mixed model with repeated measurement and fixed model with repeated measurement. SA, PC, and time factors as fixed factors while the MC factor nested in SA as a random factor. The results showed that in nested linear mixed model with repeated measurement, the interaction effect between three fixed factors, namely between SA, PC, and time have a significant effect on the sales volume of internet data quota. In fixed model the analysis used the average value of internet data quota sales for each MC, so there is no interaction effect between three fixed factors in the fixed model. This shows that the fixed model is simpler than the mixed model. The nested mixed model with repeated measurement can better explain the effect of MC in SA because it includes random factors, namely the MC factor nested in SA. The fixed model with repeated measurement can better explain the effect of SA because SA is a fixed factor which is the average of MC. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
6. Identifying the Characteristics of Pregnant Women with Inflammation/Infection in Indonesia.
- Author
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Aidi, Muhammad Nur, Efriwati, Efriwati, Suryanty, Santy, Abdul Rahman, La Ode, Nurfadilah, Khalilah, and Ernawati, Fitrah
- Published
- 2022
- Full Text
- View/download PDF
7. Knowledge, perception, and awareness about Sustainable Development Goals (SDGs) among students of a public university in Indonesia.
- Author
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Novieastari, Enie, Pujasari, Hening, Abdul Rahman, La Ode, Ganefianty, Amelia, and Rerung, Meksi Paldo
- Subjects
STATISTICAL power analysis ,STATISTICS ,PSYCHOLOGY of college students ,HEALTH occupations students ,CROSS-sectional method ,WORLD health ,SOCIAL sciences ,CRONBACH'S alpha ,HEALTH attitudes ,UNIVERSITIES & colleges ,PUBLIC sector ,RESEARCH funding ,DESCRIPTIVE statistics ,CHI-squared test ,STUDENT attitudes ,DATA analysis software ,TECHNOLOGY ,HUMANITIES ,GOAL (Psychology) ,SCIENCE - Abstract
The Sustainable Development Goals (SDGs) are a universal action to ensure peace and prosperity by 2030 by rising to meet various challenges. Achieving the SDGs requires every party to take part, including university students. This study aimed to identify knowledge, perceptions, and awareness about the SDGs among students at a public university in Indonesia. An online survey was conducted in 14 faculties and 2 schools at a public university in Indonesia. A total of 138 students from 3 clusters – health, science, and social sciences – participated. Descriptive analysis was used in exploring knowledge, perceptions, and awareness of the SDGs among students from different disciplines. Of the total respondents, 76.8% had good knowledge about the SDGs, and 73.9% had a positive perception towards the SDGs. However, 42.0% of the students were not aware of the SDGs. This study recommends appropriate individual- and population-level educational programs about the SDGs that should be conducted in university settings. Finally, curricular adjustment is essential. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
8. Relationship of Nursing Management Functions with Missed Nursing Care: A Cross-Sectional Study.
- Author
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Nilasari, Putri, Hariyati, Rr. Tutik Sri, and Rahman, La Ode Abdul
- Subjects
OCCUPATIONAL roles ,NURSING ,HOSPITAL patients ,COUNSELING ,CROSS-sectional method ,MOTIVATION (Psychology) ,NURSING services administration ,QUANTITATIVE research ,ACTIVITIES of daily living ,DISEASES ,LABOR supply ,NURSES ,ROOMS ,DESCRIPTIVE statistics - Published
- 2022
- Full Text
- View/download PDF
9. Design of a Clinical Decision Support System for Fracture Prediction Using Imbalanced Dataset.
- Author
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Chen, Yung-Fu, Lin, Chih-Sheng, Wang, Kuo-An, Rahman, La Ode Abdul, Lee, Dah-Jye, Chung, Wei-Sheng, and Lin, Hsuan-Hung
- Subjects
TREATMENT of respiratory diseases ,RESPIRATORY diseases ,ADRENOCORTICAL hormones ,BONE density ,OSTEOPOROSIS treatment ,GENETIC algorithms ,PATIENTS - Abstract
More than 1 billion people suffer from chronic respiratory diseases worldwide, accounting for more than 4 million deaths annually. Inhaled corticosteroid is a popular medication for treating chronic respiratory diseases. Its side effects include decreased bone mineral density and osteoporosis. The aims of this study are to investigate the association of inhaled corticosteroids and fracture and to design a clinical support system for fracture prediction. The data of patients aged 20 years and older, who had visited healthcare centers and been prescribed with inhaled corticosteroids within 2002–2010, were retrieved from the National Health Insurance Research Database (NHIRD). After excluding patients diagnosed with hip fracture or vertebrate fractures before using inhaled corticosteroid, a total of 11645 patients receiving inhaled corticosteroid therapy were included for this study. Among them, 1134 (9.7%) were diagnosed with hip fracture or vertebrate fracture. The statistical results showed that demographic information, chronic respiratory diseases and comorbidities, and corticosteroid-related variables (cumulative dose, mean exposed daily dose, follow-up duration, and exposed duration) were significantly different between fracture and nonfracture patients. The clinical decision support systems (CDSSs) were designed with integrated genetic algorithm (GA) and support vector machine (SVM) by training and validating the models with balanced training sets obtained by random and cluster-based undersampling methods and testing with the imbalanced NHIRD dataset. Two different objective functions were adopted for obtaining optimal models with best predictive performance. The predictive performance of the CDSSs exhibits a sensitivity of 69.84–77.00% and an AUC of 0.7495–0.7590. It was concluded that long-term use of inhaled corticosteroids may induce osteoporosis and exhibit higher incidence of hip or vertebrate fractures. The accumulated dose of ICS and OCS therapies should be continuously monitored, especially for patients with older age and women after menopause, to prevent from exceeding the maximum dosage. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
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