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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Atmaja Jalu Narendra Kisma
Universitas Amikom Purwokerto
Computer Science & IT Electrical & Electronics Engineering

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Design Automatic Parking Application of Amikom Purwokerto University Atmaja Jalu Narendra Kisma; Hendra Marcos
Telematika Vol 20, No 1 (2023): Edisi Februari 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i1.8933

Abstract

 Purpose: This study aims to deal with parking problems in the area of Amikom University, Purwokerto. In addition, this research is designed to implement theoretical and practical knowledge that has been obtained in lectures.Design/methodology/approach: In research on parking design applications in the Amikom University area, Purwokerto, library study methods and literature study methods are used. The amount of data can add insight and can make it easier to process data in research.Findings/result: This application will be able to help more Amikom Purwokerto University residents, especially in the Faculty of Computer Science. The use of this application will help find parking areas in FIK areas such as Basement Parking, Front Parking and Field Parking. In addition, security will be helped by this application because if it is implemented, vehicles parked in the reserved area will be tidier and safer. In addition, security does not need to find an empty parking area for users.Originality/value/state of the art: This research focuses on parking system design like previous studies. However, this research focuses more on designing parking applications at Amikom Purwokerto University. 
Analisis aplikasi di Playstore berdasarkan Rating dan Type menggunakan Naive Bayes dan Logistic Regression Atmaja Jalu Narendra Kisma; Chyntia Raras Ajeng Widiawati; Suliswaningsih Suliswaningsih
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 2 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i2.4784

Abstract

The use of mobile applications is increasingly important in daily life in the digital era. However, the abundance of application choices in the Play Store makes it difficult for users to choose the right application according to their needs. Not only that, application developers also have difficulty finding the most liked ratings by users and the type of application that is widely downloaded. This research aims to find a solution to the problems of users and developers by comparing the performance of Naive Bayes and Logistic Regression algorithms in classifying Google Play Store application data based on ratings and the type of application that is most downloaded by users. The results show that both algorithms have a high level of accuracy, but Naive Bayes has a higher level of accuracy than Logistic Regression. Naive Bayes obtains an accuracy rate of 92.63% while Logistic Regression obtains an accuracy rate of 92.60%. This research provides guidance for users to choose the right algorithm in classifying Google Play Store application data. However, these results are based on the data used in a particular study, so they cannot be generalized to all situations and datasets. Other factors such as data quality and proper feature selection can also affect algorithm performance. In addition, this research also shows that the type of application that is most downloaded by users on the Google Play Store is a free application. This can be input for developers to develop types of applications that are favored by users. This research also shows the results of application ratings, where an application named Life Made WI-FI Touchscreen Photo Frame with the photo editing category gets a very high rating. These results can be input or references for application developers to create even better applications in the future..
Co-Authors Chyntia Raras Ajeng Widiawati Hendra Marcos Suliswaningsih