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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Sebatik JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Aptisi Transactions on Technopreneurship (ATT) METIK JURNAL TEPIAN Buletin Poltanesa Informatika Wicida Journal of Pedagogy and Education Science TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi BEduManageRs Journal : Borneo Educational Management and Research Journal
Heny Pratiwi
Teknik Informatika, STMIK Widya Cipta Dharma
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

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Sentiment Analysis Using the Naïve Bayes Method to Improve E-Commerce Customer Satisfaction at the PedagangAksesoris Store Bai' Fathur Rayhan; Heny Pratiwi; Muhammad Fahmi
Poltanesa Vol 26 No 2 (2025): December 2025
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid development of the e-commerce sector in Indonesia has made customer feedback a very important source of information in assessing the quality of goods and services. However, with so many reviews available, the manual assessment process often becomes complicated. The purpose of this study is to analyze customer sentiment towards PedagangAksesoris store on the Shopee platform using the Naïve Bayes Classifier method to identify positive and negative opinions that can help improve customer satisfaction. The data for this study was collected through web scraping of Shopee user reviews, followed by a preprocessing stage that included cleaning, filtering, removing affixes, and separating words. The data was then divided into training data and testing data to train and test the model. The Naïve Bayes method was applied by calculating word probabilities using Laplace smoothing, while model performance was evaluated using a Confusion Matrix through the RapidMiner application. The results of this study show that the Naïve Bayes model can classify customer reviews with a high degree of accuracy, with precision reaching 100% for the negative category and 80% for the positive category, as well as recall of 87.5% and 100%. These findings confirm that the Naïve Bayes method is an effective and efficient way to perform text-based sentiment analysis on reviews in e-commerce. The results of this sentiment analysis can be used as a basis for strategic decision-making by businesses to improve product quality, services, and customer satisfaction.  
Integrating Artificial Intelligence in Formative Assessment: Connecting Student Engagement, Learning Styles, and Learning Outcomes Heny Pratiwi; Muhammad Ibnu Sa'ad; Nurul Hikmah; Anggra Prima
Journal of Pedagogy and Education Science Vol 5 No 01 (2026): Article in Press - Journal of Pedagogy and Education Science
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.jpes.001513

Abstract

Formative assessment plays an important role in providing continuous feedback that supports the student learning process. However, formative assessment practices in higher education often remain static and insufficiently responsive to individual learner differences. This study examines the integration of artificial intelligence (AI) into formative assessment by exploring patterns of student engagement, learning styles, and academic achievement within a data-informed learning environment. The findings indicate that student engagement is closely associated with academic performance and dropout risk, suggesting its potential function as an early indicator of academic vulnerability. Differences in learning styles are also reflected in formative performance, highlighting the importance of personalized instructional support. These results illustrate how AI-supported analysis can enhance formative assessment by enabling timely feedback, adaptive learning support, and the early identification of students at risk. Beyond confirming established relationships, this study emphasizes the conceptual role of artificial intelligence in reshaping formative assessment practices. AI is positioned as a formative assessment mediator that integrates learning analytics to support personalization, predictive insight, and adaptive feedback. This conceptualization contributes to formative assessment theory by demonstrating how data-driven intelligence can operationalize continuous, student-centered assessment in higher education. Rather than functioning merely as an analytical tool, artificial intelligence is shown to fundamentally reshape formative assessment by enabling continuous, predictive, and adaptive feedback mechanisms that are not achievable through conventional assessment approaches.
Visualisasi Interaksi Habitat Hewan dalam Lingkungan WebAR sebagai Media Pembelajaran Biologi Loho, Atventitus Etwin; Heny Pratiwi; Jundro Daud Hasiholan
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No2.pp478-485

Abstract

The study aimed to develop an interactive learning medium based on Web-based Augmented Reality (WebAR) markerless to visualize various animal habitats as part of Science education in elementary schools. The research employed the Multimedia Development Life Cycle (MDLC) method, which consists of six stages: concept, design, material collecting, assembly, testing, and distribution. The developed WebAR application allows students to explore 3D dioramas of animal habitats directly through a browser without additional installation. A beta test was conducted with 10 fifth-grade students from SDN 024 Samarinda using a Likert scale questionnaire that covered accessibility, visual display, interactivity, and user satisfaction. The test results showed an average score of 82.8%, indicating that the developed medium is well-received and effective in increasing students' motivation and concept understanding. This markerless WebAR medium provides a more immersive and contextual learning experience compared to conventional two-dimensional media. Future research could expand the number of respondents, test in different learning contexts, and add interactive features such as quizzes or narration to enhance learning engagement.
Implementasi Bot WhatsApp untuk Layanan Informasi Frontline: Studi Kasus: STMIK WICIDA Putra, Muhammad Sadam Saktia; Azahari, Azahari; Heny Pratiwi
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No2.pp320-326

Abstract

This study implemented a WhatsApp bot as a frontline information service at STMIK Widya Cipta Dharma (WICIDA). The main problems were the high burden of repetitive questions, limited service hours, and inconsistent responses. WhatsApp was chosen because of its high adoption rate and support for real-time communication. The study included needs analysis, bot architecture design, Node.js-based development, knowledge base integration, and performance evaluation. The results showed that the bot was able to answer 87.4% of questions correctly, reduce staff workload by 56%, and speed up response time to <3 seconds. These findings demonstrate that the WhatsApp bot is effective as a scalable solution to improve the quality of educational information services.
Co-Authors Ahmad Abul Khair Ahmad Fajri Ahmad Rofiq Hakim Amelia Yusnita Ananta Putra, Resifa Andi Yusika Rangan Anggra Prima Arsita Ashari Ramadani Azahari Azahari, Azahari Bai' Fathur Rayhan Chandra Panca Wibawa Dana Aulia Rahman Daru Caraka Dendy Kurniawan Dessy Purnamasari Ekawati, Hanifah Fadjri Astra Ryan Sinurat Ita Arfyanti Jundro Daud Hasiholan Loho, Atventitus Etwin M Yuditia Arfiyanto T Nassa M. Irwan Ukkas Irwan Ukkas Ukkas Muhammad Fachri Sanjaya Muhammad Fahmi Muhammad Ibnu Saad Saad Muhammad Rega Praduana Nursobah, Nursobah NURUL HIKMAH Pahrudin, Pajar Pitrasacha Adytia Putra, Muhammad Sadam Saktia Putra, Resifa Ananta Putri Wulandari SA'AD, MUHAMMAD IBNU Salmon Salmon Sarifmata Purnomo Shinta Palupi Susi Salviati Syamsuddin Mallala