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Journal : DISTANCE: Journal of Data Science, Technology, and Computer Science

The Best Nurse Selection Decision Support System At Dr. Hospital. Hadrianus Sinaga Using the Analytical Hierarchy Process (AHP) Method Lamtiar Purba; Agustina Simangunsong
DISTANCE: Journal of Data Science, Technology, and Computer Science Vol 1 No 1 (2021): December : 2021
Publisher : Putaka Timur Publisher

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Abstract

In this study, the authors conducted a study to apply the Analytic Hierarchy Process (AHP) method in the Selection of the Best Nurses and build applications in the application of the method. A nurse is a person who cares for and cares for other people who have health problems. But in its development, the understanding of nurses is getting wider. At this time, the notion of nurses refers to their position as part of health workers who provide services to the community in a professional manner. Decision Support System (DSS) is part of an interactive computer-based information system that is useful for supporting decision-making. The results of this study are the results of the final calculation or ranking, the best nurse chosen is A01 - Lenny M. Simbolon with a value of 0.342. so that the researcher concludes to apply the analytic hierarchy process (AHP) method in the decision support system for selecting the best nurse at RSUD Dr. Hadrianus Sinaga must follow the AHP work steps by comparing the values of each criterion to produce a criteria comparison matrix, Criteria Priority Weight Matrix, Criteria Consistency Matrix and then determine the location comparison scale value based on each criterion. After finding the weight of each criterion against the predetermined alternative, the next step is to multiply the weight of each criterion by the weight of each alternative, then the results of the multiplication are added up by the line. So that the total global priority is obtained. To build a decision support system for selecting the best nurse using the Analytical Hierarchy Process (AHP) method, the authors first analyze system requirements, perform calculations using the AHP method, design systems with UML.
The Application of the Naive Bayes Method for Determining Food Aid Recipients in Bandar Selamat Subdistrict, Kec. Medan Tembung Muhammad Bayu Habi Yasa; Agustina Simangunsong
DISTANCE: Journal of Data Science, Technology, and Computer Science Vol 1 No 1 (2021): December : 2021
Publisher : Putaka Timur Publisher

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Abstract

The method of selecting candidates for basic foodstuff recipients who still uses conventional methods is that in terms of data storage it is still in paper form, this will certainly have an impact on processing, storing, and searching for stored data if it is matched with newly obtained information or guidelines. This study conducted data processing using data mining to classify the eligibility of recipients and non-recipients of basic food assistance with the classification method using the Naïve Bayes Algorithm. It is hoped that the data generated from the data mining process can be used as evaluation material for the government. In addition, to prevent beneficiaries who often do not refer to the criteria of poor families and cheating by certain parties, a system is needed that can predict the appropriateness of food receipts that can provide alternative decisions and reduce the level of cheating in the selection of basic food recipients.
Application of the Naive Bayes Algorithm to Predict New Student Admissions at Mulia Pratama Vocational School in the Digital Age Andre Edlin Siahaan; Agustina Simangunsong
DISTANCE: Journal of Data Science, Technology, and Computer Science Vol 1 No 1 (2021): December : 2021
Publisher : Putaka Timur Publisher

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Abstract

The development in the era of globalization and the rapid progress in the field of information technology has had a considerable influence both in the field of education. Several problems can be explained related to the achievement of results in predicting the results of new student admissions at SMK Mulia Pratama in the digital era. The promotion is quite complicated because there is no target for the results of new student admissions so the promotion does not know the achievement of new student admissions who are registered for each promotion. To solve this problem, the naive Bayes method is used. Naïve Bayes is an algorithm that can be used to predict the results of new student admissions that can be categorized as achieved or not achieved. The data was used in this study from January to December 2018. From the results of the application of the nave Bayes method, the highest probability value is in class P(X). Receipt of acceptance prediction = No so that it can be concluded that the results of acceptance are included in the classification of "No" meaning that every new acceptance improves.
Expert System to Diagnose Disease Mushroom Plants Using Backward Chaining Method Dinda Vionica Zahro; Agustina Simangunsong
DISTANCE: Journal of Data Science, Technology, and Computer Science Vol 1 No 1 (2021): December : 2021
Publisher : Putaka Timur Publisher

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Abstract

Mushrooms are one of the plants that have high nutritional content that other types of vegetables do not have. This plant is easy to cultivate because it easily adapts to the environment. The risk of loss in the oyster mushroom business cannot be avoided because it is not careful or diligent in maintaining oyster mushrooms. As a tool, an expert system is used to identify the type of oyster mushroom disease using several methods including the backward chaining method. The backward chaining method is a method that starts from the conclusion of several existing facts to refute or support the hypothesis. The results of the research and discussion that have been carried out have concluded that an expert system designed to be able to diagnose fungal plant diseases, the method used can be used as an alternative in calculating the diagnosis of fungal diseases and an expert system designed to make it easier for farmers to diagnose diseases that occur in fungal.
The Application Of The Weighted Product (WP) Method To Determine The 1st General Champion In SMT TD Pardede Foundation Misael F Siahaan; Agustina Simangunsong
DISTANCE: Journal of Data Science, Technology, and Computer Science Vol 1 No 1 (2021): December : 2021
Publisher : Putaka Timur Publisher

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Abstract

SMK T.D. Pardede Foundation selects students from each class to get 1st place overall, to increase students' enthusiasm for learning, and students who get 1st place overall will get scholarships for the next 1 semester. The general 1st place selection system at SMK TD Pardede Foundation involves every class. The selection is based on the highest Knowledge Score, with several important values ​​such as Skill Average Score, Extracurricular Value, Attendance Value, and Character Value. So far, determining the overall 1st place winner has not been optimal and is still done manually, in which the selection of the general 1st place winner is still subjective. If viewed from these problems, it is necessary to make a decision support system as a tool to evaluate the potential of students. In this case, 5 criteria are determined, namely Total Knowledge Value, Number of Skills, Extracurricular Value, Attendance Value, and Character Value. and based on the 5 criteria above, the author uses the Weighted Product (WP) method. Using the Weighted Product (WP) method is more efficient because the time used in the calculation is shorter. This method was chosen because it can determine the weight of each attribute. The results of this study have resulted in a Decision Support System to Determine the Web-Based General Champion using the Weighted Product method using 5 variable criteria to determine the overall 1st place winner.