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All Journal Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Bigint Computing Journal
Sitorus, Rina Afriani
Unknown Affiliation
Computer Science & IT Engineering

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Improving Image Quality in Hero Photos Using Grayscale Images Using the Histogram Equalization Method Sitorus, Rina Afriani; Aidilia, Yunda; Siregar, Yustria Handika
Bigint Computing Journal Vol 1 No 2 (2023)
Publisher : Ali Institute of Reseach and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/bigint.v1i2.780

Abstract

Photos of heroes are one of the important images in history. Today's hero photos have poor image quality because the camera technology that existed in the past was still simple. Due to technological limitations at that time, the current hero photos are still of low quality with the dominant color being gray. This condition results in the information contained sometimes not being received properly. To overcome this problem, it is necessary to improve the image quality of hero photos which are still of low quality. Image quality improvement is one of the image processing operations which aims to perfect the image by manipulating image parameters. This operation is often applied to images that have poor quality so that the quality can be improved. In this research, we will apply image enhancement operations or improve the image quality of hero photos so that the quality can increase. There are many methods that can be used to enhance images, one of which is histogram equalization which has been widely used to enhance images, especially greyscale images. This method is usually done on images using the Matlab application because of its simple use. This research produces new images with better quality than previous images
Application of the Naïve Bayes Algorithm in Sentiment Analysis of Using the Shopee Application on the Play Store Sitorus, Rina Afriani; Zufria, Ilka
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 15 No. 1 (2024): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v15i1.19828

Abstract

This research aims to find out the opinions of users of the Shopee application on the Play Store using the Naive Bayes Naive Algorithm and to find out the suitability of the correct application of the Naive Bayes algorithm in carrying out sentiment analysis with the classification of three sentiment classes. The dataset used in this study consisted of 2000 customer reviews obtained from the Play Store in 2024 collected by the scraping process using the Python library. The dataset has 1,198 examples of negative attitudes, 583 examples of good sentiment, and 219 examples of neutral sentiment. The results of this study are expected to be used as evaluation material for Shopee Apilkation to improve the performance of Shopee applications. Research findings show that the Bayes naive approach reaches accuracy determined by various aspects, such as the quantity of data collections and positive and negative data distribution. This study shows that the Bayes naive algorithm can function properly as a technique to evaluate user sentiment for applications in the Play Store. However, with the classification of three classes, another algorithm is needed to produce higher accuracy.
Co-Authors Aidilia, Yunda Ilka Zufria Yustria Handika Siregar