F. Y. Wattimena, Johan Minggus Loly, Halomoan Edy Manurung
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引用次数: 0
摘要
查亚普拉地区的车辆失窃率相当高,目前还没有任何应用程序可以帮助警方估计或预测下一年将发生的失窃案件数量。2022 年,查亚普拉地区的盗窃案件将开始增加。为了进行这些预测,作者设计并构建了一个可以预测这些案件数量的系统,在构建该应用程序时,作者使用了回归分析方法,这一过程可以帮助警方预测来年的案件数量。使用的开发方法是 SDLC、线性回归分析和 PHP 编程语言,数据库使用 MYSQL 和 Sublime Text。之所以进行这项研究,是因为没有一个系统可以帮助查亚普拉地区度假村警察(Polres)的工作人员。通过这项研究,查亚普拉地区警察局成功建立了一个预测机动车辆易被盗程度的系统,其数据处理包括使用人脸区域的考勤数据、使用条形码的报告数据、使用计数器的排队数据以及帮助警方存储重要文件的数字档案数据。
WEB-BASED INFORMATION SYSTEM PREDICTION OF VEHICLE THEFT VULNERABILITY IN JAYAPURA USING REGRESSION ANALYSIS
Vehicle theft in Jayapura Regency is quite high and there is no application to assist the police in making estimates or predictions of the number of theft cases that will occur in the next year. In 2022, cases of theft in Jayapura district will start to increase. to make these predictions the authors designed and built a system that can predict the number of these cases in building this application the authors use the Regression Analysis method this process can help the police predict the number of cases in the coming year. The development method used is SDLC, linear regression analysis and using the PHP programming language, the database uses MYSQL, Sublime Text. This research was conducted because there was no system that could assist the staff of the Resort Police (Polres) of Jayapura Regency. From this research, a system for predicting the level of vulnerability to motorized vehicle theft has been successfully built at the Jayapura District Police with data processed for attendance data using face region, reporting data using barcodes, queue data using counters and digital archive data helping the police store important documents.