Election Criteria Analysis

Oct 13, 2025 by sorusgentrification.com 6 views

Analysis of the Combination of the Multiobjective Optimization Method on the Basis of Ratio Analysis (Moora) and the Best First Search Algorithm in the Selection of Obstetrician and Obstetrician Practices in Medan City

Introduction

The health of pregnant women is a crucial aspect to be considered in the process of labor and preventing maternal death. According to data from the Ministry of Health, the maternal mortality rate in Indonesia is still relatively high, where 32% of deaths are caused by bleeding and 26% are caused by hypertension that can cause seizures and poisoning. To maintain the health of the mother and child during pregnancy, routine checks with obstetrics and obstetricians are highly recommended. Therefore, this study aims to develop applications that can help pregnant women in finding the recommendations of obstetrics and obstetricians using the multi-objective optimization method on the basis of ratio analysis (Moora) to get recommendations for the location of doctors' practice. Meanwhile, the Best First Search (BFS) algorithm will be used to determine the optimal sequence in the selection of practices based on the results of the Moora method. The parameters analyzed in this study include patient satisfaction, service quality, accessibility, and cost efficiency.

Application of the Moora Method

The Moora method is a method that allows decision making by considering various criteria simultaneously. In the context of the selection of obstetrics and content doctors, this method can help in assessing practice based on several relevant indicators. The selected indicators not only focus on service quality, but also consider patient satisfaction, costs, and ease of access. By utilizing Moora, pregnant women can get more comprehensive information about the various choices of doctors, so that the decisions taken are more precise and in accordance with their needs.

Election Criteria Analysis

Analysis of the selection criteria is very important because it can affect the final results of the recommendations given. For example, high patient satisfaction can reflect the quality of interaction between doctor and patient. Meanwhile, accessibility is an important factor for pregnant women who may have difficulty traveling to the hospital or clinic. Cost efficiency is also an important consideration, especially for patients who may have budget limitations.

The Importance of Patient Satisfaction

Patient satisfaction is a crucial factor in the selection of obstetricians and content doctors. High patient satisfaction can reflect the quality of interaction between doctor and patient, which is essential for building trust and confidence. Pregnant women who are satisfied with their doctor's care are more likely to follow their advice and recommendations, which can lead to better health outcomes.

Accessibility and Cost Efficiency

Accessibility and cost efficiency are also important considerations in the selection of obstetricians and content doctors. Pregnant women who have difficulty traveling to the hospital or clinic may prefer doctors who are located in their area or have flexible scheduling. Similarly, cost efficiency is an important consideration, especially for patients who may have budget limitations.

Algorithm Best First Search (BFS)

After obtaining the results of the Moora method, the BFS algorithm is then used to determine the optimal sequence of the recommendations produced. This algorithm serves to explore the possibility of doctor selection efficiently by prioritizing recommendations that have the highest value. This approach is very effective in helping pregnant women to make decisions quickly and precisely.

System Results and Trials

Based on the results of the user's acceptance trial, the system developed shows that this application can meet the needs of pregnant women. This trial also shows that users feel the ease of accessing information and providing an assessment of their experiences when using the application. This indicates that the combination of the Moora method and the BFS algorithm in this application is very useful and relevant to increase access to pregnant women on midwifery and obstetric services in Medan.

Conclusion

Application development that uses a combination of the Moora method and the best first search algorithm is an innovative step in supporting the health of pregnant women. By considering various important criteria in the selection of obstetricians and content, this application not only makes it easy for users to make decisions, but also has the potential to reduce maternal mortality by increasing access to quality health services. Furthermore, it is hoped that this research can be a reference for the development of similar applications in other health fields.

Future Directions

This research has several potential applications in the field of healthcare. Firstly, the combination of the Moora method and the BFS algorithm can be used to develop applications that help patients make informed decisions about their healthcare. Secondly, this research can be used to develop applications that help healthcare providers improve their services and increase patient satisfaction. Finally, this research can be used to develop applications that help healthcare administrators make informed decisions about resource allocation and service delivery.

Limitations and Future Research Directions

This research has several limitations. Firstly, the study only focused on the selection of obstetricians and content doctors, and did not consider other healthcare providers. Secondly, the study only used a limited number of criteria in the selection process. Finally, the study only used a small sample size in the user acceptance trial. Future research directions include expanding the study to include other healthcare providers, using a larger sample size, and considering more criteria in the selection process.

Conclusion

In conclusion, this research has demonstrated the potential of the combination of the Moora method and the BFS algorithm in supporting the health of pregnant women. By considering various important criteria in the selection of obstetricians and content, this application not only makes it easy for users to make decisions, but also has the potential to reduce maternal mortality by increasing access to quality health services. Future research directions include expanding the study to include other healthcare providers, using a larger sample size, and considering more criteria in the selection process.
Q&A: Analysis of the Combination of the Multiobjective Optimization Method on the Basis of Ratio Analysis (Moora) and the Best First Search Algorithm in the Selection of Obstetrician and Obstetrician Practices in Medan City

Q: What is the main objective of this study?

A: The main objective of this study is to develop an application that helps pregnant women in finding the recommendations of obstetrics and obstetricians using the multi-objective optimization method on the basis of ratio analysis (Moora) to get recommendations for the location of doctors' practice.

Q: What is the Moora method and how does it work?

A: The Moora method is a method that allows decision making by considering various criteria simultaneously. In the context of the selection of obstetrics and content doctors, this method can help in assessing practice based on several relevant indicators. The selected indicators not only focus on service quality, but also consider patient satisfaction, costs, and ease of access.

Q: What is the Best First Search (BFS) algorithm and how does it work?

A: The BFS algorithm is a search algorithm that serves to explore the possibility of doctor selection efficiently by prioritizing recommendations that have the highest value. This approach is very effective in helping pregnant women to make decisions quickly and precisely.

Q: What are the parameters analyzed in this study?

A: The parameters analyzed in this study include patient satisfaction, service quality, accessibility, and cost efficiency.

Q: How does the application developed in this study meet the needs of pregnant women?

A: The application developed in this study shows that it can meet the needs of pregnant women by providing easy access to information and allowing them to provide an assessment of their experiences when using the application.

Q: What are the potential applications of this research in the field of healthcare?

A: This research has several potential applications in the field of healthcare, including developing applications that help patients make informed decisions about their healthcare, developing applications that help healthcare providers improve their services and increase patient satisfaction, and developing applications that help healthcare administrators make informed decisions about resource allocation and service delivery.

Q: What are the limitations of this study?

A: The study has several limitations, including only focusing on the selection of obstetricians and content doctors, only using a limited number of criteria in the selection process, and only using a small sample size in the user acceptance trial.

Q: What are the future research directions of this study?

A: The future research directions of this study include expanding the study to include other healthcare providers, using a larger sample size, and considering more criteria in the selection process.

Q: How can this research be used to reduce maternal mortality?

A: This research can be used to reduce maternal mortality by increasing access to quality health services. By providing pregnant women with easy access to information and allowing them to make informed decisions about their healthcare, this application can help reduce the risk of maternal mortality.

Q: What are the potential benefits of using this application for pregnant women?

A: The potential benefits of using this application for pregnant women include increased access to quality health services, improved patient satisfaction, and reduced risk of maternal mortality.

Q: How can this research be used to improve healthcare services?

A: This research can be used to improve healthcare services by providing healthcare providers with a tool to improve their services and increase patient satisfaction, and by providing healthcare administrators with a tool to make informed decisions about resource allocation and service delivery.

Q: What are the potential applications of this research in other fields?

A: This research has potential applications in other fields, including education, finance, and marketing, where decision making involves considering multiple criteria and prioritizing recommendations.