Data Mining Method to Determine a Fisherman's Sailing Schedule Using Website

Dwi Ayu Mutiara, Alung Susli, Didit Suhartono, Dani Arifudin, Imam Tahyudin
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引用次数: 0

Abstract

Some of Cilacap people live in coastal areas as fishermen who utilize the seafood to meet the needs of life. One of the fishermen supporters in the cruise is the information of Meteorological, Climatological, and Geophysical Agency (BMKG). This information is important for safety such as wind speed and wave height. For addressing the problem, research is conducted to determine the sailing schedule of fishermen using data mining method with the website based. The proposed method is using Support Vector Machine (SVM) classification algorithm. This research uses data from BMKG Cilacap from 2015 until 2017. Test data is part of data that is 30% randomly fetched from the overall data used. From model testing, get value with performance results from datasets that generate accuracy of 88%, 87% precision and 89% recall. This solution is followed by constructing the website in order to easy to access of sailing information. Therefore, the researcher created a website of fisherman sailing scheduling system based on SVM algorithm.
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基于网站的数据挖掘方法确定渔民的航行计划
一些Cilacap人生活在沿海地区,作为渔民,他们利用海鲜来满足生活的需要。渔民的支持者之一是气象、气候和地球物理局(BMKG)的信息。这些信息对安全很重要,比如风速和浪高。针对这一问题,采用基于网站的数据挖掘方法对渔民的航行日程进行了确定研究。该方法采用支持向量机(SVM)分类算法。本研究使用BMKG Cilacap从2015年到2017年的数据。测试数据是从所使用的总体数据中随机提取的30%的数据的一部分。从模型测试中,从数据集获得具有性能结果的值,生成88%的准确性,87%的精度和89%的召回率。在此解决方案的基础上,建立了航海信息网站,方便用户获取航海信息。因此,研究人员创建了一个基于SVM算法的网站渔民航行调度系统。
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0.00%
发文量
7
审稿时长
24 weeks
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