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ALGORITMA GREEDY COLORING PADA WEBSITE ENSIKLOPEDIA PETA

Authors: Ibnu Aldi Nugroho; null Fauziah; Nur Hayati;

ALGORITMA GREEDY COLORING PADA WEBSITE ENSIKLOPEDIA PETA

Abstract

Graph coloring is used, because the results of graph coloring can be used in several systems, such as the scheduling and the coloring of map areas in this study. The goal in implementing graph coloring here is to get as few colors as possible in the 44 borders of villages in Jakarta Pusat. The problem of coloring graphs on the Jakarta Pusat’s villages map uses a greedy algorithm that exists on web-based maps and makes encyclopedias to support descriptions of areas that have been colored. The greedy algorithm is a form of algorithm that is currently developing in optimization problems by forming a step-by-step solution. Greedy algorithm can be applied to resolve the problem of graph coloring. The best solution to answer a graph coloring problem is to determine the chromatic number 𝜒(𝐺) using the greedy algorithm. Graph coloring on a map is done using a greedy algorithm to obtain the minimum number of colors possible without adjacent regions using the same color. Based on the research results, the least number of colors used in coloring the village map in Central Jakarta, which consists of 44 areas, is 6 types of colors.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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