• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>2017 15th International Conference on Quality in Research : International Symposium on Electrical and Computer Engineering >Majority vote technique based on multi rough set for multi attributes decision-making system: Case study classifying job competency for civil servants' functional works in ministry of religious affairs of Republic of Indonesia
【24h】

Majority vote technique based on multi rough set for multi attributes decision-making system: Case study classifying job competency for civil servants' functional works in ministry of religious affairs of Republic of Indonesia

机译：基于多粗糙集的多属性决策系统多数投票技术：印度尼西亚共和国宗教事务部公务员职能工作岗位胜任力分类的案例研究

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In the government agencies, civil servants are required to have competence or ability to finish the work effectively and efficiently. In fact, the decision-making system for determining position and assignment of civil servants' functional works is still performed manually, so it takes a longer time. Moreover, the results are not totally accurate in terms of their competency. Rough set, hereinafter called Single Rough Set, is a common method to solve this problem, but the process may be very complex and still has the unclassified result. In this research, Multi Rough Set and Majority Vote technique are proposed to enhance system performance of single rough set with multi attributes of job competency. It obtains accuracy rate with 5-fold cross-validation that is 83.67% better than a Single Rough Set and it has 0.947 Area Under Curve (AUC) derived from Receiver Operator Characteristic (ROC). Thus, it can be said that the system performance of Multi Rough Set can be considered excellent in classifying job competency for civil servants' functional works.
机译：在政府机构中，公务员必须具有有效完成工作的能力。实际上，用于确定公务员职能工作的位置和分配的决策系统仍然是手动执行的，因此需要较长的时间。而且，就其能力而言，结果并不完全准确。粗糙集（以下称为“单一粗糙集”）是解决此问题的常用方法，但过程可能非常复杂，并且仍具有未分类的结果。在这项研究中，提出了多粗糙集和多数表决技术，以提高具有工作能力的多个属性的单个粗糙集的系统性能。它具有5倍交叉验证的准确率，比单一粗糙集高83.67％，并且具有0.947的曲线下面积（AUC）（源自接收者操作员特征（ROC））。因此，可以说，在对公务员职能工作的工作能力进行分类时，可以认为多粗糙集的系统性能是极好的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号