Determining The Senior High School Major Using Agglomerative Hierarchial Clustering Algorithm
Determining the senior high school major is still a dilemma for some junior high school students. The selection of high school majors must be tailored to the interests, talents and academic skills of students so that later students can develop a better competencies, attitudes and academic skills in...
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| Vydáno v: | 2018 International Seminar on Application for Technology of Information and Communication s. 225 - 228 |
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IEEE
01.09.2018
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| Abstract | Determining the senior high school major is still a dilemma for some junior high school students. The selection of high school majors must be tailored to the interests, talents and academic skills of students so that later students can develop a better competencies, attitudes and academic skills in the new environment. The selection of the appropriate high scholl major will influence students' interests and abilities in exploring a field of science so that later it will be easier for students to go to university which is expected and in accordance with their current interests and abilities. This will obviously be very beneficial for the student in preparing for his future. Clustering is one technique known in the data mining process. The core concept of clustering is to group a number of data or objects into a group or several groups where each group contains data that has similarities that are very close to other data. There are two types of grouping methods known as hierarchical clustering and partitioning. The hierarchical clustering method consists of several types, namely complete linkage clustering, single linkage clustering, average linkage clustering and centroid linkage clustering. While the partitioning method itself consists of the following types namely k-means clustering and k-means fuzzy clustering. In this study, the authors have applied and analyzed the Agglomerative Hierarchical Clustering technique in the data of students of SMP Negeri 2 Purwodadi to classify students based on their respective interests and skills to fit the selection of high school majors. In the implementation, the author uses 5 attributes of pre-processing results which are used as experimental data processing variables. The results of this study succeeded in developing a prototype application that has implemented the Agglomerative Hierarchical Clustering algorithm which is used to visualize data processing so that it can help students determine high school majors. From the various experiments that have been carried out, this application has shown good resultsl. |
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| AbstractList | Determining the senior high school major is still a dilemma for some junior high school students. The selection of high school majors must be tailored to the interests, talents and academic skills of students so that later students can develop a better competencies, attitudes and academic skills in the new environment. The selection of the appropriate high scholl major will influence students' interests and abilities in exploring a field of science so that later it will be easier for students to go to university which is expected and in accordance with their current interests and abilities. This will obviously be very beneficial for the student in preparing for his future. Clustering is one technique known in the data mining process. The core concept of clustering is to group a number of data or objects into a group or several groups where each group contains data that has similarities that are very close to other data. There are two types of grouping methods known as hierarchical clustering and partitioning. The hierarchical clustering method consists of several types, namely complete linkage clustering, single linkage clustering, average linkage clustering and centroid linkage clustering. While the partitioning method itself consists of the following types namely k-means clustering and k-means fuzzy clustering. In this study, the authors have applied and analyzed the Agglomerative Hierarchical Clustering technique in the data of students of SMP Negeri 2 Purwodadi to classify students based on their respective interests and skills to fit the selection of high school majors. In the implementation, the author uses 5 attributes of pre-processing results which are used as experimental data processing variables. The results of this study succeeded in developing a prototype application that has implemented the Agglomerative Hierarchical Clustering algorithm which is used to visualize data processing so that it can help students determine high school majors. From the various experiments that have been carried out, this application has shown good resultsl. |
| Author | Arista Harum Perdana, Mahendra Agus Santoso, Heru Luthfiarta, Ardytha Nugraha, Adhitya Pertiwi, Ayu Zeniarja, Junta |
| Author_xml | – sequence: 1 givenname: Adhitya surname: Nugraha fullname: Nugraha, Adhitya organization: Department of Computer Science, Dian Nuswantoro University, Semarang, Indonesia – sequence: 2 givenname: Mahendra surname: Arista Harum Perdana fullname: Arista Harum Perdana, Mahendra organization: Department of Computer Science, Dian Nuswantoro University, Semarang, Indonesia – sequence: 3 givenname: Heru surname: Agus Santoso fullname: Agus Santoso, Heru organization: Department of Computer Science, Dian Nuswantoro University, Semarang, Indonesia – sequence: 4 givenname: Junta surname: Zeniarja fullname: Zeniarja, Junta organization: Department of Computer Science, Dian Nuswantoro University, Semarang, Indonesia – sequence: 5 givenname: Ardytha surname: Luthfiarta fullname: Luthfiarta, Ardytha organization: Department of Computer Science, Dian Nuswantoro University, Semarang, Indonesia – sequence: 6 givenname: Ayu surname: Pertiwi fullname: Pertiwi, Ayu organization: Department of Computer Science, Dian Nuswantoro University, Semarang, Indonesia |
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| Snippet | Determining the senior high school major is still a dilemma for some junior high school students. The selection of high school majors must be tailored to the... |
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| SubjectTerms | Agglomerative Hierarchical Clustering Algorithm Clustering Clustering algorithms Clustering methods Computer science Couplings Data mining Major Determination in Senior High School Seminars Testing |
| Title | Determining The Senior High School Major Using Agglomerative Hierarchial Clustering Algorithm |
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