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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing Dinasti International Journal of Economics, Finance & Accounting (DIJEFA)
Tiffany
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Computer Science & IT Economics, Econometrics & Finance Education

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Sentiment Analysis On Twitter Posts About The Russia and Ukraine War With Long Short-Term Memory Simarmata, Allwin; Xu, Anthony; Tiffany; Phanie, Matthew Evan
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.12235

Abstract

Sentiment analysis is one method for evaluating public opinion from the received text. In this study, we evaluate the performance of the LSTM model with Sastrawi in sentiment analysis in Indonesian using a Twitter dataset totaling 2537 data collected regarding the Russo-Ukrainian war. The purpose of this study is to determine the reliability of the LSTM model with Sastrawi in sentiment analysis in Indonesian and to evaluate the performance of the model with the collected Twitter dataset regarding the Russian-Ukrainian war. The method used in this study is data pre-processing, training and validation of the LSTM model with Literature, and model evaluation using the metrics of accuracy, precision, recall, and F1 score. In the dataset collected in this study, positive, neutral and negative sentiments were 54.7%, 35% and 10.2%. The results obtained from this study indicate that the LSTM model with Literature can provide good results in sentiment analysis with a prediction accuracy of 82%. The implication of the results of this study is that the LSTM model with Sastrawi can be used for sentiment analysis on Twitter and further research needs to be carried out with a wider and more diverse dataset, especially to produce even better accuracy.
Classification of diseases in snake plants using convolutional neural network Athalia, Kensa; Tiffany; Kevin Adhi Dhamma Setiawan; Bertrand Ferrari; Chairisni Lubis
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3201

Abstract

snake plant has an important role in human life, as well as in increasing the aesthetic value of the environment. Limited knowledge about diseases in snake plants has a crucial result in improper handling and control when the plant is attacked by disease. Advances in deep learning technology and Convolutional Neural Network (CNN) have presented high opportunities with their advantages in recognizing patterns and features from image data. This research will use a CNN model with VGG-19 architecture to classify diseases in the leaves of the snake plant. It is expected that by using the pre-trained VGG-19 model, the model can recognize complex visual patterns in snake plants. Diseases to be classified include several types of diseases that often attack snake plants such as anthracnose, rust, water soaked lesion, and healthy plants for comparison. The highest value of training accuracy reached a value of 98.08%, validation accuracy of 94.02%, and testing accuracy reached 94%.
The Effect of Rating and Lifestyle on the Purchase Decision of Skincare Products of Somethinc Brand on Gen Z in Medan City (Case Study on Shopee Marketplace) Manik, Desma Erica Maryati; Rezeki, Sri; Tiffany
Dinasti International Journal of Economics, Finance & Accounting Vol. 6 No. 4 (2025): Dinasti International Journal of Economics, Finance & Accounting (September - O
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v6i4.5064

Abstract

This study aims to analyze the influence of ratings and lifestyle on purchasing decisions for Somethinc brand skincare products on generation Z in Medan City through the Shopee marketplace. The research method uses a quantitative approach with data collection through questionnaires distributed to 400 Gen Z respondents. The results of the analysis show that ratings have a significant influence on purchasing decisions, indicating that consumer assessments and reviews play an important role in building trust in products. In addition, the respondents' lifestyles are also proven to have a significant influence, where consumer lifestyles and preferences influence the choice of skincare products. Simultaneously, ratings and lifestyle together have a significant influence on purchasing decisions for Somethinc products. This study provides important insights for skincare business actors to improve product quality and marketing strategies that are in accordance with the characteristics and lifestyle of Gen Z, especially on the marketplace platform.
Co-Authors Athalia, Kensa Bertrand Ferrari Chairisni Lubis Kevin Adhi Dhamma Setiawan Manik, Desma Erica Maryati Phanie, Matthew Evan Simarmata, Allwin Sri Rezeki Xu, Anthony