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All Journal International Journal of Education, Science, Technology, and Engineering (IJESTE) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Wahyuni, Ulfia
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Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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Utilization of Technology in Development Business Management in the Post-Pandemic Era Akbar, Rizky Aulia; Wahyuni, Ulfia; Rina
International Journal of Education, Science, Technology, and Engineering (IJESTE) Vol 6 No 1: June 2023
Publisher : Lamintang Education and Training Centre, in collaboration with the International Association of Educators, Scientists, Technologists, and Engineers (IA-ESTE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36079/lamintang.ijeste-0601.481

Abstract

So far in 2019, the COVID-19 pandemic has claimed many lives. Due to the pandemic, many people have lost their jobs due to massive layoffs, and many businesses have failed. This journal examines the application of technology to business development in the post-COVID-19 era. Consequently, the purpose of this study is to develop businesses following the pandemic by utilizing the transformation of digital marketing technology and the difficulties in an era in which many individuals have used technology and social media to develop their businesses. Plans to utilize technology via websites or social media as well as e-commerce applications circulating on multiple platforms include: (a) determining sales goals or target markets; (b) preparing captions that attract buyers' interest in the goods we will market; and (c) planning sales goals to be achieved and managing expenses and income. The methods of digital marketing that we wish to describe are: a) promoting through product videos that pamper buyers; and b) creating their own website with an aesthetically pleasing design so that many interested individuals desire to purchase.As anticipated for research purposes, the results of this study indicate that digital marketing can be utilized as a means of business development in the post-pandemic era.Through the use of technology, businesses are able to develop rapidly, and the information that can be accessed is accurate and quick, thereby expanding the scope of sales.
EduMood: Sistem Deteksi Sentimen Berbasis Web Menggunakan Metode Machine Learning untuk Identifikasi Awal Gejala Stres Mahasiswa Prasetya, Riko Anshori; Rahman, Subhannur; Priyatno, Arif Mudi; Mera, Mera; Wahyuni, Ulfia
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.8042

Abstract

Students' mental health is an important issue that needs serious attention, especially in the era of social media which is full of psychological pressure. This research aims to develop EduMood, a web-based sentiment analysis system to monitor college students' mental health issues by analyzing tweets on Twitter. The tweet data is collected using relevant keywords and goes through preprocessing stages such as text cleaning, bilingual lexicon-based initial labeling, and balancing the amount of data between sentiment classes. The system uses two machine learning algorithms, Support Vector Machine (SVM) and Naive Bayes with Term Frequency-Inverse Document Frequency (TF-IDF) feature representation. The evaluation results show that SVM has a higher accuracy of 99.3% compared to Naive Bayes which reaches 96.5% with f1 scores for all classes above 0.99 for SVM. EduMood is implemented as a web-based application using Flask and Bootstrap 5, which presents the analysis results through an interactive dashboard. The dashboard displays the aggregate sentiment distribution in the form of diagrams, wordclouds, monitoring tables, and text manual predictions. The results of this study show that EduMood not only provides excellent model performance, but also offers a practical solution for the campus to monitor the psychological condition of students in a fast, real data-based, and easily accessible manner. This system is expected to support efforts to improve student mental health in a sustainable manner.
Co-Authors Akbar, Rizky Aulia Arif Mudi Priyatno Mera, Mera Prasetya, Riko Anshori Rina Subhannur Rahman, Subhannur