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All Journal Jurnal Pendidikan Vokasi Jurnal Teknologi Informasi dan Ilmu Komputer Konvergensi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Research In Management and Accounting (RIMA) Journal of Information System,Graphics, Hospitality and Technology Buletin Ilmiah Sarjana Teknik Elektro Jurnal Informatika dan Sistem Informasi (JUISI) Jurnal Teknik Informatika (JUTIF) Teknika Jurnal AbdiMas Nusa Mandiri Insyst : Journal of Intelligent System and Computation JUSTIN (Jurnal Sistem dan Teknologi Informasi) Joutica : Journal of Informatic Unisla Jurnal Nasional Teknik Elektro dan Teknologi Informasi Reflection Journal Jurnal Sistem Cerdas dan Rekayasa Jurnal Sistem Informasi Research In Management and Accounting (RIMA)
Devi Dwi Purwanto
Department Of Informatics, Widya Mandala Surabaya Catholic University, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Physics Social Sciences Other

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Empirical Evaluation of IndoBERT and LSTM for Sentiment Analysis of Tourism Reviews: A Data-Driven Study on Kenjeran Park Purwanto, Devi Dwi
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.4901

Abstract

Tourism plays a pivotal role in Indonesia’s economic and cultural landscape, contributing significantly to job creation, regional development, and international recognition. This study evaluates the performance of IndoBERT, a state-of-the-art Indonesian language model, and Long Short-Term Memory (LSTM) networks for sentiment classification of 2,560 Google reviews of Kenjeran Park in Surabaya, consisting of 54% positive, 28% neutral, and 18% negative sentiments. Preprocessing steps included slang replacement, stemming, stopword removal, and tokenization, with class imbalance addressed through weighted loss adjustments. IndoBERT was fine-tuned using contextual embeddings with a learning rate of 0.00005, while the LSTM model employed a 128-unit architecture trained over 150 epochs with the Adam optimizer. Experimental results show that IndoBERT achieved 87.50% accuracy, 0.7697 precision, 0.7643 recall, and 0.7643 F1-score, outperforming LSTM’s 77.93% accuracy, 0.6826 precision, 0.6812 recall, and 0.6826 F1-score. This research establishes a comparative benchmark of transformer-based and RNN-based architectures for Indonesian tourism review sentiment analysis, introduces a domain-specific preprocessing pipeline with imbalance handling, and provides actionable insights for digital tourism analytics. Beyond its technical contributions, the study highlights the urgency of advancing robust natural language processing approaches for low-resource languages, thereby strengthening the field of informatics and supporting data-driven decision-making in the tourism sector.
A Development and evaluation of a 3D electromagnetic field simulation tool for aviation communication engineering education Fatmawati Sabur; Heru Prasetyo; Mulyadi Nur; Kurniaty Atmia; Supriyadi Supriyadi; Devi Dwi Purwanto; Slamet Winardi; Arsyen Pratama Parrangan; Che Zalina Zulkifli
Jurnal Pendidikan Vokasi Vol. 16 No. 2 (2026)
Publisher : ADGVI & Graduate School of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpv.v16i2.91450

Abstract

This study addresses a learning gap in Aviation Communication Engineering education, where electromagnetic field concepts are highly abstract and difficult to understand through conventional teaching methods. Existing instructional media provide limited interactive and contextualized visualizations of electric and magnetic field phenomena, resulting in low levels of students’ conceptual understanding. The study employed a Research and Development (R&D) methodology based on the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) instructional design model. Subject matter experts and media experts evaluated the application in terms of content validity, interface design, and interactivity. The primary outcome was the development of a web-based three-dimensional (3D) electromagnetic field simulation to support learning in aviation communication engineering. Its effectiveness was subsequently evaluated using a quasi-experimental pre-test–post-test control-group design involving 30 students assigned to experimental and control groups. The experimental group used the web-based 3D simulation developed with Python and Three.js, whereas the control group received conventional instruction. Data were analyzed using paired-samples t-tests, Cohen’s d effect size, and 95% confidence intervals. The results revealed significant improvements in both groups (p < 0.05), with the experimental group demonstrating greater learning gains (M = 23.3; from 63.2 to 86.5; t = −73.06) than the control group (M = 11.3; from 62.8 to 74.1; t = −48.79). Effect size analysis indicated a very large educational impact (Cohen’s d ≈ 5.85), while the confidence intervals showed no overlap between groups, supporting the robustness of the observed differences. The findings suggest that 3D simulation-based learning is more effective than conventional instruction in enhancing students’ conceptual understanding of electromagnetic field concepts. The study also provides empirical support for the Cognitive Theory of Multimedia Learning and Cognitive Load Theory in the context of vocational aviation education.
PEMBUATAN APLIKASI KOPERASI SIMPAN PINJAM DI DESA BAMBE, DRIYOREJO Devi Dwi Purwanto; Slamet Winardi; Philipus Suryo Subandoro; Shierly Kartika Salim; Robertus Geraldyn Alexandro Gabeler; Berliana Az Zahra Tristianti; Agustinus Bimo Gumelar
Jurnal AbdiMas Nusa Mandiri Vol. 8 No. 1 (2026): Periode Januari 2026
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v8i1.7390

Abstract

This community service activity aims to support the Savings and Loan Cooperative in Bambe Village, Driyorejo District, in addressing problems of inefficient manual recording, potential errors, and suboptimal transparency of financial information for members. The proposed solution is the development of a web-based application that includes membership management, recording of savings and loan transactions, interest calculation, real-time financial reporting, transaction notifications, and automatic calculation of Operating Surplus (SHU). The implementation method consists of six stages: problem analysis, collaborative solution design with partners, system implementation, training and assistance, monitoring and evaluation, and report preparation and publication. The results show that the application is able to improve cooperative administrative efficiency, accelerate the reporting process, and increase the openness of information access for members. Based on questionnaire results from 30 respondents, the level of user satisfaction falls into the very good category with an average score of 4.5 out of 5. Further evaluation indicates the need to improve members’ understanding of application usage, leading to additional training and system improvements based on user feedback. Future development is directed toward the integration of digital payment systems.
Optimizing Stock Prediction in Supermarket: A Comparative Analysis of LightGBM and XGBoost for Enhanced Inventory Management Devi Dwi Purwanto; Philipus Suryo Subandoro; Agustinus Bimo Gumelar
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 14 No. 3 (2025)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v14i3.94433

Abstract

Stock management in supermarkets is a critical challenge due to unpredictable demand fluctuations and seasonal purchasing patterns. Inaccurate forecasting often leads to understocking or overstocking, which in turn reduces customer satisfaction and causes financial losses. To overcome this problem, machine learning approaches have gained attention for their ability to model complex patterns in sales data more effectively than traditional methods. This study compares two widely used algorithms, XGBoost and LightGBM, in forecasting daily supermarket sales. A dataset of 23,873 transactions from January 2023 to December 2024 was used, processed into daily sales per product, and enriched with seasonal and lag features. Hyperparameter tuning was conducted using GridSearchCV and RandomizedSearchCV, and model evaluation applied multiple metrics including MAE, MAPE, RMSE, and MSE. The results indicate that XGBoost outperformed LightGBM, achieving the lowest MAE of 2.413×10⁻⁵ after optimization. While LightGBM demonstrated computational efficiency, its accuracy was less optimal for this dataset. These findings highlight the superiority of XGBoost for small- to medium-scale retail time series forecasting and provide practical insights for supermarkets to enhance inventory management and supplier coordination.
Co-Authors . Gunawan . Gunawan . Gunawan . Gunawan Aditya Dwi Aryanto Agustinus Bimo Gumelar Agustinus Bimo Gumelar Aji Prasetya Wibawa Arsyen Pratama Parrangan Berliana Az Zahra Tristianti Budianto, Herman Che Zalina Zulkifli Endang Setyati Eric Sugiharto Honggara Fatmawati Sabur Hadikusuma, Jeremiah Irawan Hakkun Elmunsyah Hartarto Junaedi Herman Budianto Herman Thuan To Saurik Heru Prasetyo Hongary, Kevin - Ikhsan, Teguh Pribadi Indra Maryati Jimmy Tegarianto Joan Santoso Kevin - Hongary Kristian, Yosi Kurniaty Atmia Limantoro, Stephen Ekaputra Mazarina Devi Mochammad Faid Mulyadi Nur Nathaniel Tjoa Novi Duwi Setyorini Philipus Suryo Subandoro Philipus Suryo Subandoro Robertus Geraldyn Alexandro Gabeler Setya Ardhi Shierly Kartika Salim Sitepu, Rasional Siti Sendari Slamet Winardi Slamet Winardi Stefanie Angelina Gunarto Stephen Ekaputra Limantoro Suhatati Tjandra Supriyadi Supriyadi Yosi Kristian Yunan Kholilul Fatah