基于层次分析法(AHP)的艺术家音乐节选择的韦伯模型修正权准则

Gede Iwan Sudipa, P. Sugiartawan, I. A. Wiguna
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引用次数: 2

摘要

从许多标准的替代方案中进行选择的过程是一个经常在决策过程中确定的决定。决策者在进行选择时使用的标准可以由许多属性组成,这些标准被称为多标准决策(MADM)。在一个活动中确定艺术家音乐节是一个相当复杂的困难,因为对标准的评估是异质的。蜘蛛网整合标准的方法导致了最受关注和公众兴趣的艺术家形式的选择。模型AHP使用多属性来选择在音乐节上表演的艺术家,使用标准来选择艺术家,即追随者数量(C1)、邮票C2、平均流行曲目(C3)、平均Youtube观众(C4)和艺术家的价格(C5)。使用Spotify和YouTube API获得了关注者数量、受欢迎程度、平均流行曲目和YouTube平均观看人数的数据。采用的解决方法是层次分析法(AHP)和评分量表算法,另一种方法是使用五个印尼艺术家样本。该研究结果有望为音乐节上的表演者提供建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modification Weight Criteria With Webbed Model For Selection Artist Music Festival Using Analytical Hierarchy Process (AHP)
The process of selecting from many alternatives to the criteria is a decision that is often determined in decision making. The criteria for which criteria can consist of many attributes are used by decision-makers in making the selection or are called multi-criteria decision making (MADM ). Determining the Artist Music Festival at an event has quite a complicated difficulty, because the assessment of the criteria is heterogeneous. The spider web's approach to integrating criteria results in the selection of the artist form that attracts the most attention, and public interest. Model AHP use of multi-attributes is used in selecting artists to perform at music festivals, selecting artists using criteria, namely Number of Followers (C1), stamp C2, Average Popular Tracks (C3), Average Youtube Viewers (C4), and the price of the artist (C5). Data on the number of followers, popularity, average popular tracks, and average YouTube viewers were obtained using the Spotify and Youtube APIs. The settlement method applied is the Analytical Hierarchy Process (AHP) and the Rating Scale algorithm, with an alternative using five samples of Indonesian artists. The research results are expected to provide recommendations for artists as performers in the music festival.
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