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Genetic Algorithm Optimization on Nave Bayes for Airline Customer Satisfaction Classification Religia, Yoga; Maulana, Donny
JISA(Jurnal Informatika dan Sains) Vol 4, No 2 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i2.925

Abstract

Airline companies need to provide satisfactory service quality so that people do not switch to using other airlines. The way that can be used to determine customer satisfaction is to use data mining techniques. Currently, the website www.kaggle.com has provided Airline Passenger Satisfaction data consisting of 22 attributes, 1 label and 25976 instances which are included in the supervised learning data category. Based on several previous studies, the Naïve Bayes algorithm can provide better classification performance than other classification algorithms. Several studies also state that the use of Naive Bayes can be optimized using Genetic Algorithm (GA) to obtain better performance. The use of Genetic Algorithm for Nave Bayes optimization in classifying Airline Passenger Satisfaction data requires further research to ensure the performance of the given classification. This study aims to compare the use of the Naive Bayes algorithm for the classification of Airline Passenger Satisfaction with and without GA optimization. The data validation process used in this study is to use split validation to divide the dataset into 95% training data and 5% testing data. The test results show that the use of GA on Naive Bayes can improve the classification performance of Airline Passenger Satisfaction data in terms of accuracy and recall with an accuracy value of 85.99% and a recall of 87.91%.
Seven Tools as Quality Control to Reduce Defective Products in the Honeycomb Board Machine Process Wiji Safitri; Ahmad Sutrimo; Miftakul Huda; Yoga Religia
DEAL: International Journal of Economics and Business Vol. 1 No. 01 (2023): October 2023
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/deal.v1i01.2681

Abstract

Quality is a requirement for a product that will be distributed to consumers. Quality is also a competitive advantage for the company. PT NKR Industri as a company that produces paper still has not met the target to reduce the number of product defects. Product defects set by the company are a maximum of 3%, but currently product defects are up to 5%. Seven tools are tools used to control quality. This research is quantitative research. Data was collected through interviews and direct observation. The population and sample in this research is defect data on honeycomb board machines for the period July to December 2022. The data analysis technique uses seven tools. After mapping with seven tools, one of which is through a fishbone diagram, product defects that occur are caused by environmental factors consisting of room temperature, material factors consisting of damp paper and expired glue, method factors consisting of the dandori method is not suitable, machine factors consisting of less maintenance and the equipment has entered a maintenance period, the measurement factor consists of less carefull measurement process, and finally the man factor consists of lack of knowledge and not carefull.