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Penerapan Algoritma Naïve Bayes Dalam Analisis sentiment Masyarakat Terhadap STMIK Widya Cipta Dharma Putri Jelita, Helmelya; Ibnu Sa'ad, Muhammad; Wahyuni
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2029

This study applies the Naïve Bayes algorithm to analyze public sentiment toward STMIK Widya Cipta Dharma using Google Maps reviews as the primary data source. The research aims to classify community perceptions into three categories: positive, neutral, and negative. The methodology follows the CRISP-DM framework, incorporating stages such as data preprocessing (text cleaning, stopword removal, and stemming), TF-IDF for feature extraction, and SMOTE to address class imbalance. Sentiment labels were derived from a combination of review ratings (1–5 stars) and textual content. Results indicate that Naïve Bayes achieved 91% accuracy in classifying the majority (positive) class but struggled with minority classes (neutral and negative), yielding 0% precision and recall for these categories. After applying SMOTE, recall for the negative class improved to 100%, although overall accuracy dropped to 38%, reflecting a trade-off between balanced class recognition and model performance. The study highlights the algorithm's effectiveness in handling large-scale text data but underscores challenges in managing imbalanced datasets. These findings provide actionable insights for STMIK Widya Cipta Dharma to enhance service quality and institutional image by leveraging public feedback. Future research could explore hybrid algorithms or advanced preprocessing techniques to optimize sentiment analysis accuracy across all classes.

Penerapan Algoritma Naïve Bayes Dalam Analisis sentiment Masyarakat Terhadap STMIK Widya Cipta Dharma Putri Jelita, Helmelya; Ibnu Sa'ad, Muhammad; Wahyuni
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2029

This study applies the Naïve Bayes algorithm to analyze public sentiment toward STMIK Widya Cipta Dharma using Google Maps reviews as the primary data source. The research aims to classify community perceptions into three categories: positive, neutral, and negative. The methodology follows the CRISP-DM framework, incorporating stages such as data preprocessing (text cleaning, stopword removal, and stemming), TF-IDF for feature extraction, and SMOTE to address class imbalance. Sentiment labels were derived from a combination of review ratings (1–5 stars) and textual content. Results indicate that Naïve Bayes achieved 91% accuracy in classifying the majority (positive) class but struggled with minority classes (neutral and negative), yielding 0% precision and recall for these categories. After applying SMOTE, recall for the negative class improved to 100%, although overall accuracy dropped to 38%, reflecting a trade-off between balanced class recognition and model performance. The study highlights the algorithm's effectiveness in handling large-scale text data but underscores challenges in managing imbalanced datasets. These findings provide actionable insights for STMIK Widya Cipta Dharma to enhance service quality and institutional image by leveraging public feedback. Future research could explore hybrid algorithms or advanced preprocessing techniques to optimize sentiment analysis accuracy across all classes.

Sosialisasi Perkembangan Bahasa dan Implementasi Budaya Literasi Sejak Dini di SD Cordova Samarinda: Pengabdian Nur, Nurul Hikmah; Eka Selvi Handayani; Gamar Al Haddar; Muhammad Ibnu Sa’ad; Intan Nur Safikah; Nur Yanti
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 1 (Juli 2025 -
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i1.2544

The activity "Socialization of Language Development and Implementation of Early Literacy Culture in Cordova Samarinda" generally aims to find out the Socialization of Language Development and Implementation of Early Literacy Culture for Class Teachers and Students of Grade IV SD Cordova Samarinda. The method of implementing this service is by means of surveys and direct socialization in the field. Introduction to language development and getting used to literacy culture from an early age can be started by communicating with people in the home environment, community environment, school environment, by reading story books or fairy tales to children routinely by parents at home and teachers can also implement reading books and students listening in class. Although it seems like a simple activity, reading books to children is the first stage of introducing children to the world of literacy. Improving literacy culture in the digital era, for example, is very important. Literacy has a big role in training children's basic skills in reading, writing and telling stories.

Pengenalan Tarian Adat Dayak Hudoq Melalui Media Virtual Reality Untuk Pelestarian Budaya Otovianus Oscar; Ibnu Sa’ad, Muhammad; Daud Hasiholan, Jundro
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2338

Abstract- The preservation of the traditional Dayak Hudoq dance faces serious challenges due to globalization and the use of conventional learning media that are less appealing to the digital native generation. These challenges have resulted in a lack of understanding among the younger generation of the philosophical values of dance. There is a research gap in the use of Virtual Reality (VR) technology that focuses on the philosophical values of the dance and can be accessed independently (offline) using low-cost devices. This study aims to (1) develop an offline-based Virtual Reality educational application (VR-Box) using the Multimedia Development Life Cycle (MDLC) method, and (2) test the feasibility of this media as a means of cultural preservation. The MDLC method is applied through six systematic stages: Concept, Design, Material Collecting, Assembly, Testing, and Distribution. The testing process involved Alpha testing for functionality and Beta testing using a Likert scale questionnaire with 10 vocational high school students in Samarinda to measure ease of use and appeal. The results of the study show that the VR-Box application was successfully developed and functions well. The beta test results show a “Very Good” level of user acceptance with an overall average score of 88%. This application is considered very practical to use (96%) and capable of increasing interest in learning about culture (88%). It is concluded that the VR-Box application is feasible and effective to be implemented as a portable and low-cost medium for cultural preservation. However, user evaluation shows that visual quality (74%) is still an aspect that needs to be improved in further research. Keywords: MDLC, Visualization, Dayak, Cultural Preservation, VR

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