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Journal : Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi

Rancang Bangun Media Tes Berbasis Komputer menggunakan Wondershare Quizcreator untuk Mendukung Pembelajaran Daring Imam Mualim; Nuari Anisa Sivi; Najla Asyila; Oriza Panduwinata
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 1 No. 1 (2023): Februari : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v1i1.1215

Abstract

The development of information technology provides opportunities for educators to create more efficient and interactive learning evaluation media. This study aims to design and develop a computer-based test media using Wondershare Quiz Creator as a tool to support online learning. The research method used is Research and Development (R&D) with a waterfall model, which includes the stages of needs analysis, design, development, testing, and implementation. The results show that the developed test media is capable of providing various types of questions, such as multiple choice, short answer, true-false, and matching, and is equipped with features such as automatic feedback, time settings, and exportable test results. User testing indicates that the media is easy to use, responsive, and effective in supporting the learning evaluation process in online learning. In addition, educators can quickly create, manage, and distribute tests through digital platforms without requiring advanced technical skills. Thus, the use of Wondershare Quiz Creator has proven to be an alternative solution for providing practical and interactive computer-based test media that supports improving the quality of online learning. This research is expected to serve as a reference for educators in utilizing technology to enhance the effectiveness of learning evaluation
Penerapan Algoritma Naïve Bayes untuk Analisis Sentimen Ulasan Produk E-Commerce Nuari Anisa Sivi; Imam Mualim; Muhammad Taufik Kussofyan
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 1 No. 1 (2023): Februari : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v1i1.1216

Abstract

The rapid growth of e-commerce in Indonesia has generated a massive and continuous volume of product reviews. This user-generated content is vital for business intelligence, yet its sheer scale makes manual analysis inefficient, subjective, and practically impossible. Automated sentiment analysis is therefore crucial for businesses to efficiently understand customer feedback and market perception. This research addresses this gap by implementing the Naïve Bayes Classifier (NBC) algorithm to automatically classify the sentiment of Indonesian-language e-commerce product reviews. This study utilized a dataset of 2,000 reviews collected from a major e-commerce platform's "Electronics" category. The data underwent critical text preprocessing stages (case folding, tokenizing, stopword removal, and stemming using the Sastrawi library) to handle the complexities of informal Indonesian text. The dataset was split using an 80/20 ratio, resulting in 1,600 training reviews and 400 testing reviews. Model performance was then evaluated using a Confusion Matrix, focusing on the key metrics of Accuracy, Precision, and Recall. The test results showed excellent performance, achieving an Accuracy of 90.00%, Precision of 91.93%, and Recall of 95.00%. These results demonstrate that the Naïve Bayes algorithm, when supported by robust preprocessing, is a highly effective, reliable, and computationally efficient method for this task, providing a valuable tool for e-commerce stakeholders.