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Journal of Education Technology and Information System
Published by Universitas Negeri Surabaya
ISSN : -     EISSN : 30898706     DOI : https://doi.org/10.26740/jetis
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Library & Information Science
JETIS published twice a year, double blind peer-reviewed publication that concentrates on various aspects of Educational Technology, Information System in Education, Pedagogical Innovation, Student Engagement and Outcomes, Information Science and Digital Libraries, Policy and Management, Emerging Technologies and Information System. JETIS mission is to be the leading journal in the field of information systems (IS) education. To achieve this, JETIS prioritizes high-quality and relevant papers. The journal also acknowledges the global influences on IS education and actively seeks international contributions in all areas, including authorship, reviewing, and membership on the Editorial Board. Educational Technology: Topics such as IT integration in the classroom, e-learning platforms, mobile learning applications, and gamification in education. Information Systems in Education: Areas including the development of learning management systems (LMS), educational data mining, cybersecurity, and cloud computing in educational contexts. Pedagogical Innovations: Contributions exploring innovative teaching methods, blended learning models, collaborative learning, and professional development for educators in IT. Student Engagement and Outcomes: Research on the impact of IT on student engagement, motivation, personalized learning environments, and educational outcomes. Information Science and Digital Libraries: Insights into digital libraries, metadata standards, digital preservation, and knowledge management in education. Policy and Management: Topics covering IT policy development, ethical considerations, governance, and management of educational technologies. Emerging Technologies: We invite cutting-edge research in areas like AI, virtual and augmented reality, blockchain, and IoT in education. Information System: Research in enterprise systems, IT governance, software development, AI applications, and IT management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 21 Documents
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Design of an Android Application for Leaf Disease Detection in Plants Muhammad Nizam Setiawan; Ardhini Warih Utami
Journal of Education Technology and Information System Vol. 2 No. 01 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

Agriculture plays a strategic role in Indonesia's economy, with approximately 29,342,202 individual agricultural enterprises recorded in 2023, according to Statistics Indonesia (BPS). Golokan Village, located in Sidayu District, Gresik Regency, is one of the agrarian areas where 23.22% of the population works as farmers, and it has a total agricultural land area of 385 hectares. However, between 2019 and 2023, there was a significant decline in the production of three main commodities: corn decreased from 302.5tons to 275.6tons, tomatoes from 810tons to 585 tons, and cassava from 1,000tons to 832tons. One of the contributing factors is the difficulty in early detection of plant diseases. To address this challenge, this study designed and developed an Android application called AgroAI utilizing deep learning technology, specifically a Convolutional Neural Network (CNN) model based on the MobileNet architecture optimized with TensorFlow Lite for mobile devices. The development was carried out using the Scrum methodology in two sprints. The first sprint included needs analysis, dataset collection, interface design, and model training. The second sprint implemented the core features such as leaf disease detection via camera or gallery, classification results with recommended solutions, analysis history management, educational articles, and user authentication via Firebase. Black box testing confirmed that all features functioned as intended, while model validation achieved an accuracy of 94.74%. This application is expected to enhance farmers' efficiency in crop management and support the sustainability of both local and national agricultural sectors.
Information System Design for Local Tax Revenue Planning in Surabaya City Ramadhan Jatmiko, Muhammad Ammarul; Utami, Ardhini Warih
Journal of Education Technology and Information System Vol. 3 No. 01 (2027): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

Surabaya has great potential for regional tax revenue, but the planning process remains manual, resulting in inaccurate data, delays, and lack of system integration. This study aims to design and develop an information system to support more accurate and efficient regional tax revenue planning. The method used is Rapid Application Development (RAD), an iterative approach based on user feedback. Data were collected through interviews, observations, and literature review. The system is web-based, developed using C# and ASP.NET Core. Key features include tax account management, revenue component input, and component-based planning evaluation. Implementation results show the system improves data accuracy, planning efficiency, and administrative transparency. It also helps Surabaya's Regional Revenue Agency monitor real-time revenue planning. This research contributes to strengthening local tax management and supports digital transformation in public services.
Design and Construction of An Omnichannel Application at Dispendukcapil Surabaya Fikko Muharavid Yoga Mardhany; Utami, Ardhini Warih
Journal of Education Technology and Information System Vol. 3 No. 01 (2027): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

The customer service at Dispendukcapil Surabaya faces challenges in managing incoming messages from the public through various communication channels such as WhatsApp and Instagram. Unmonitored messages and a limited number of staff lead to delays in responding to complaints. Therefore, this study aims to develop an Omnichannel application that integrates WhatsApp and Instagram into a centralized platform, equipped with a keyword-based auto-reply feature to accelerate response time. The development method used is Rapid Application Development (RAD) with an iterative and fast-paced approach. Testing results show that the application successfully improves chat handling efficiency, accelerates response times, and provides a more integrated communication experience for the public. This study is expected to offer a solution to improve complaint and information service systems in government institutions.
Evaluation of Service Quality And User Experience on Livin' By Mandiri Using E-Servqual and Usability Testing Methods Zulvia Arifatul Fadzilah; Suyatno, Dwi Fatrianto
Journal of Education Technology and Information System Vol. 2 No. 02 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

Livin’ by Mandiri is application from Bank Mandiri which can accessed and used by customers or candidate Bank Mandiri customers. The number of complaints submitted​ user become challenges that must be faced by the parties Livin’ by Mandiri. Parties Livin’ by Mandiri need to know how expected service​ users and services what needs to be improved and how experience user during use application. To find out matter the done study this is by using method E-Servqual and Usability Testing. Research data taken from user application Livin’ by Mandiri through questionnaires and testing. Data analysis techniques in study this includes, analysis ­gap between perception and expectation users, analysis importance performance analysis, and analysis usability testing using use system usability scale. The results in study this show that all dimensions of E-Servqual is in a negative gap. The SYS1 dimension in importance performance analysis is in quadrant 1, which means it is priority improvements. The results of usability testing show that application easy used however Still there were 0.35 errors during testing. In addition, the time user completing the task is 0.0796 goal/sec. Satisfaction level user is at grade C which means it is still can accepted but needs to be improved.
Implementation of Time Series Method in Drug Sales Forecasting at XYZ Pharmacy Using a Dashboard on the "Riycast" Website Shahab, Ali Zainal Abidin; Palupi, Ghea Sekar
Journal of Education Technology and Information System Vol. 2 No. 02 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

Apotek XYZ faces significant challenges in drug stock management due to unpredictable seasonal demand fluctuations, particularly during flu season, which risks stock shortages or excess inventory. This study implements a Long Short-Term Memory (LSTM) method for time-series-based drug sales forecasting and develops the "Riycast" web dashboard as an interactive stock management solution. Historical daily sales data (January 2021–December 2024) for 10 key drugs (e.g., multivitamins, flu medications) were processed through CRISP-DM stages including data cleansing, normalization, seasonal decomposition, and hyperparameter tuning via grid search. The LSTM model captured seasonal patterns and trends with variable accuracy (RMSE 0.11279–0.31552), peaking for Ultraflu and Vitalong Z Sinc. The Riycast dashboard built with Flask(backend), React.js (frontend), and MySQL features real-time sales data input, interactive prediction visualizations, historical trend analysis, and automatic surge alerts (>100 units). Implementation boosted stock management efficiency by 30% in trials, reduced stockout risk by 25%, and enabled data-driven decisionmaking at Apotek XYZ.
Public Complaint Text Classification in the Wargaku Application Using Natural Language Processing Alfina Dian Febyani; I Kadek Dwi Nuryana
Journal of Education Technology and Information System Vol. 2 No. 02 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

The Wargaku application is utilized by Surabaya residents to submit complaints concerning population administration services. With the increasing number of complaints, manual categorization becomes inefficient and susceptible to errors. This research aims to create an automatic classification system utilizing Natural Language Processing (NLP) and machine learning techniques. The dataset comprises 2,303 complaints divided into 18 categories. During preprocessing, text data was converted into numerical form using the Term Frequency–Inverse Document Frequency (TF-IDF) approach. Three machine learning models were tested: Support Vector Machine (SVM), Random Forest (RF), and Neural Network (NN), with evaluations based on accuracy and F1-score. Hyperparameter tuning was applied to enhance model performance. The SVM model yielded the best outcome with a training-to-testing data ratio of 85:15, resulting in a training accuracy of 93.96%, an F1-score of 96.08%, and a testing F1-score of 94.15%. This model was deployed in a web-based application via Streamlit to automatically categorize public complaints. The findings confirm the effectiveness of combining NLP and SVM in improving the efficiency of digital public service systems.
Implementation of SVM and GLDA for Gap Analysis on Mobile JKN Balqis Nur Aura Shaviradilla; I Kadek Dwi Nuryana
Journal of Education Technology and Information System Vol. 2 No. 02 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

This study aims to analyze user perceptions of the Mobile JKN application developed by BPJS Kesehatan through sentiment analysis, topic modeling, and service quality gap analysis (SERVQUAL). Sentiment analysis was conducted using the Support Vector Machine (SVM) algorithm with linear and RBF kernels. The classification results, based on an 80:20 data split, indicate that the majority of user reviews express negative sentiment—2,784 reviews using the linear kernel and 2,847 using the RBF kernel—followed by positive and neutral sentiments. These findings suggest a general dissatisfaction among users regarding the application’s performance. Topic modeling was performed using the Guided Latent Dirichlet Allocation (GLDA) method, successfully grouping reviews into five main topics aligned with the SERVQUAL dimensions: tangibles, assurance, empathy, reliability, and responsiveness. The empathy topic appeared most frequently, while responsiveness was the least represented. The GLDA model achieved a coherence score of 0.64 and a UMass score of -1.99, indicating the model’s interpretability and consistency. Finally, the dimension-by-dimension gap analysis revealed that the assurance dimension had the smallest gap (-0.06), while the reliability dimension had the largest gap (-0.74). The overall SERVQUAL gap score was 0.11, highlighting a notable disparity between user expectations and their actual experiences. These results underline the need for targeted improvements in several service aspects of the Mobile JKN application.
Recommendations For Improving Application Services Using Root Cause Analysis Based On User Review Sentiment Analysis (Case Study: Digital Korlantas Polri) Mawarni, Lintang Iqhtiar Dwi; I Kadek Dwi Nuryana
Journal of Education Technology and Information System Vol. 2 No. 02 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

Abstract. Amid the wave of digital transformation, the Digital Korlantas Polri application emerged as a solution and breakthrough in the digital-based SIM (driver's license) issuance process. However, concerns regarding the application’s performance quality remain, one of which can be assessed through user comments on the Google Play Store. A disparity was found between the app’s rating and the content of user reviews, raising questions about the actual quality of the application. This study aims to identify the root causes of user issues with the Digital Korlantas Polri application and generate improvement recommendations based on the identified problems. The research utilizes the pre-trained IndoBERT model for sentiment classification, followed by semi-supervised topic modeling using Guided LDA to uncover hidden patterns in the review data. Furthermore, the pre-trained GPT-2 model is employed as a text generator to produce application improvement recommendations based on the identified issues. Evaluation results show that the sentiment model achieved a confidence score of 0.99, the Guided LDA model reached a coherence score of 0.51, and the GPT-2 model yielded a perplexity value of 1.3. Overall, the models successfully fulfilled their respective roles, enabling more effective and efficient analysis, and generating realistic and timely recommendations for addressing the identified issues
Customer Profiling and Purchase Patterns Using K-Means and Apriori Algorithms Muhammad Risalah Naufal; Yustanti, Wiyli
Journal of Education Technology and Information System Vol. 3 No. 01 (2027): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

This study aims to analyze customer segmentation and purchasing patterns at PT. Benteng Api Technic (BAT) using the K-Means and Apriori algorithms. Customer segmentation is based on the RFM (Recency, Frequency, Monetary) approach, which reflects customer purchasing behavior. The K-Means algorithm is applied to group customers into clusters with similar characteristics, while the Apriori algorithm is used to identify frequent product purchasing patterns within each cluster. The dataset used consists of sales transaction data from June 1, 2023, to June 30, 2024. The results show clear customer segmentation based on purchasing characteristics, and several associations between products frequently purchased together by customers in specific clusters were found. These findings are expected to help the company develop more targeted marketing strategies and improve inventory management efficiency.
Article Reviewer Recommendation System Using Euclidean Distance Similarity with Content-Based Collaborative Filtering (Case Study: ICVEE) wilda; I Kadek Dwi Nuryana
Journal of Education Technology and Information System Vol. 3 No. 01 (2027): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

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Abstract

The growth of research publications in academic environments has resulted in large volumes of unstructured data, particularly in the form of article titles and abstracts. However, the majority of educational institutions still manage these resources manually, without optimizing them for academic decision-making. This study proposes an article reviewer recommendation system using a content-based filtering method with TF-IDF for text representation and Euclidean Distance as the similarity measure. Reviewer profiles are constructed based on previously reviewed articles. A new article is represented as a vector and compared against reviewer profiles to determine relevance. The system was evaluated using 20 articles as ground truth. Results show that the Euclidean Distance approach outperformed Cosine Similarity, achieving an accuracy of 55%, precision of 0.2333, recall of 0.2121, and F1-score of 0.222. This study demonstrates the potential of content-based filtering in enhancing reviewer assignment efficiency for academic conferences such as ICVEE.

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