Prediction of State Civil Apparatus Performance Allowances Using the Neural Network Backpropagation Method

Puan Maharani Kurniawan, Agung Teguh Wibowo Almais, M. Amin Hariyadi, M. Ainul Yaqin, Suhartono Suhartono
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Abstract

Performance allowance is a form of appreciation given by an agency to its human resources. The Office of the Ministry of Religion of Batu City provides performance allowances to civil servants who work in the agency. Several things that affect the provision of performance allowances, such as grade, deduction, taxable income, income tax, and total tax, are used in this study to produce the total gross performance allowances and total performance allowances received. Based on the data obtained, there are some missing data from the parameters of taxable income, income tax, and total tax. This study aims to predict performance allowance when there is missing data. The method used is Neural Network Backpropagation. This study uses 480 data with split data ratios of 50:50, 60:40, 70:30, and 80:20, with epochs 40,000 and a learning rate 0,9. Four types of models used in this study are distinguished based on the number of hidden layers and epochs used. Model A uses two hidden layers to produce the highest accuracy with a 50:50 data split ratio of 65,16%. Model B uses four hidden layers to produce the highest accuracy with a 50:50 data split ratio of 69,34%. Model C uses six hidden layers to produce the highest accuracy with a 50:50 data split ratio of 68,18%. Model D uses eight hidden layers to produce the highest accuracy with a 50:50 data split ratio of 70,90%.
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基于神经网络反向传播方法的国家民用设备性能津贴预测
绩效津贴是机构对其人力资源给予的一种奖励形式。巴图市宗教部办公室向在该机构工作的公务员提供绩效津贴。影响绩效津贴发放的几个因素,如职级、扣除、应纳税所得额、所得税和总税额,在本研究中被用于产生总绩效津贴和总绩效津贴。根据所得数据,应纳税所得额、所得税额、总税额等参数存在数据缺失。本研究的目的是在数据缺失的情况下预测性能容许值。使用的方法是神经网络反向传播。本研究使用480个数据,分割数据比分别为50:50、60:40、70:30、80:20,epoch为40000,学习率为0,9。根据隐层的数量和所使用的时代,将本研究中使用的四种模型区分开来。模型A使用两个隐藏层产生最高的精度,50:50的数据分割比为65,16%。模型B使用四个隐藏层来产生最高的精度,50:50的数据分割比例为69,34%。模型C使用六个隐藏层来产生最高的精度,50:50的数据分割比例为68.18%。模型D使用8个隐藏层产生最高的精度,50:50的数据分割比为70,90%。
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来源期刊
JOIV International Journal on Informatics Visualization
JOIV International Journal on Informatics Visualization Decision Sciences-Information Systems and Management
CiteScore
1.40
自引率
0.00%
发文量
100
审稿时长
16 weeks
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