2020Journal of Physics Conference SeriesOpen access

Comparative of prim’s and boruvka’s algorithm to solve minimum spanning tree problems

Faridawaty Marpaung, Arnita Arnita

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Abstract

Abstract Optimization is important in an algorithm. It can save the operational costs of an activity. In the Minimum Spanning Tree, the goal is to achieve how all vertices are connected with the smallest weights. Several algorithms can calculate the use of weights in this graph. The purpose of this study is to find out the Primary electricity distribution network graph model and correct algorithm to determine the minimum spanning tree. By comparing two algorithms, Prim’s and Boruvka’s algorithm, it will get an efficient algorithm to solve the minimum spanning tree problem. To get the output it takes several steps: Data collection: Designing Model: calculating the minimum spanning tree of Prim’s algorithm, the Boruvka’s algorithm: Comparing the efficiency of each algorithms. The analysis shows that the Prim’s and Boruvka’s algorithm have different steps even though the final result in the form of weights obtained in achieving the minimum spanning tree is the same. But in the case of electric network optimization, the Prim’s algorithm is more efficient.

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Abstract Optimization is important in an algorithm. It can save the operational costs of an activity. In the Minimum Spanning Tree, the goal is to achieve how all vertices are connected with the smallest weights. Several algorithms can calculate the use of weights in this graph. The purpose of this study is to find out the Primary electricity distribution network graph model and correct algorithm to determine the minimum spanning tree. By comparing two algorithms, Prim’s and Boruvka’s algorithm, it will get an efficient algorithm to solve the minimum spanning tree problem. To get the output it takes several steps: Data collection: Designing Model: calculating the minimum spanning tree of Prim’s algorithm, the Boruvka’s algorithm: Comparing the efficiency of each algorithms. The analysis shows that the Prim’s and Boruvka’s algorithm have different steps even though the final result in the form of weights obtained in achieving the minimum spanning tree is the same. But in the case of electric network optimization, the Prim’s algorithm is more efficient.

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Available abstract

Abstract Optimization is important in an algorithm. It can save the operational costs of an activity. In the Minimum Spanning Tree, the goal is to achieve how all vertices are connected with the smallest weights. Several algorithms can calculate the use of weights in this graph. The purpose of this study is to find out the Primary electricity distribution network graph model and correct algorithm to determine the minimum spanning tree. By comparing two algorithms, Prim’s and Boruvka’s algorithm, it will get an efficient algorithm to solve the minimum spanning tree problem. To get the output it takes several steps: Data collection: Designing Model: calculating the minimum spanning tree of Prim’s algorithm, the Boruvka’s algorithm: Comparing the efficiency of each algorithms. The analysis shows that the Prim’s and Boruvka’s algorithm have different steps even though the final result in the form of weights obtained in achieving the minimum spanning tree is the same. But in the case of electric network optimization, the Prim’s algorithm is more efficient.

Key concepts: Minimum spanning tree, Distributed minimum spanning tree, Kruskal's algorithm, Reverse-delete algorithm, Prim's algorithm, Spanning tree, Algorithm, Computer science

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