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All Journal Jurnal Teknologi dan Manajemen Informatika Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aiti: Jurnal Teknologi Informasi Journal of Applied Computer Science and Technology (JACOST) Eduvest - Journal of Universal Studies
Baisa, Lorna Yertas
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Aerospace Engineering Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Health Professions Neuroscience Social Sciences

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Evaluasi kualitas website e-learning UNIPA menggunakan metode Webqual 4.0 Yang, Ester Deborah; Baisa, Lorna Yertas; Sanglise, Marlinda
AITI Vol 21 No 2 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i2.285-297

Abstract

Computer and internet technology advancement has prompted higher education institutions to utilize online services such as e-learning in teaching and learning activities. This research aims to measure the quality of the University of Papua (UNIPA) e-learning website from the user's perspective by employing the WebQual 4.0 approach, which encompasses the dimensions of usability, information quality, service interaction, design appearance, and user satisfaction. This study is expected to obtain specific insights to enhance the effectiveness and convenience of website usage, supporting UNIPA's progress in digital education. Based on 200 student respondents, it was found that UNIPA's e-learning website excels in information quality with an average score of 4.2 and significantly influences user satisfaction. Ease of use and design appearance are also strengths, with scores of 3.9 and 3.7, respectively, and have a significant impact. However, service interaction still needs improvement, with a score of 3.4, although it has a significant influence. Overall, user satisfaction is reasonably good, with a score of 3.8, but improving service interaction needs to be addressed by UNIPA's management. These findings illustrate user needs and serve as a basis for development to enhance the efficiency and effectiveness of online learning.  
Development and Evaluation of Android-based Infrastructure Rental Application: A Design Science Research Approach Kandami, Joshua Hans; Inan, Dedi Iskandar; Juita, Ratna; Baisa, Lorna Yertas; Sanglise, Marlinda; Indra, Muhamad
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.13004

Abstract

This study developed and evaluated a mobile application for infrastructure rental at the Quality Assurance Agency for Education (BPMP) in West Papua using the Design Science Research (DSR) approach in the field of Information Systems (IS). This application, the first designed specifically for the needs of BPMP West Papua and integrated with the existing system, was assessed based on usability and user acceptance through interviews, black box testing, and effectiveness testing using Structural Equation Modeling (SEM) with the Technology Acceptance Model (TAM) approach. The black box testing results indicated successful application development. Evaluation with 64 respondents through hypothesis testing showed that social influence and technological anxiety significantly affect attitudes toward accepting the use of the application. This highlights the importance of considering these factors for the successful implementation of the mobile application at BPMP West Papua, potentially enhancing the efficiency of infrastructure rental.
Evaluation of User Satisfaction on the Indonesian National Police Recruitment Website Using the EUCS Method Dwi Pratiwi, Dinda Malika; Sanglise, Marlinda; Baisa, Lorna Yertas
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.10284

Abstract

The digitalization of public services encourages government institutions to provide efficient and responsive information systems, including in the recruitment process of the Indonesian National Police (Polri). The Polri recruitment website was developed as an online registration platform to improve transparency, accessibility, and service effectiveness. However, systematic evaluations of user satisfaction with this website are still limited. This study aims to measure user satisfaction using the End User Computing Satisfaction (EUCS) model. A quantitative approach was applied, with data collected through questionnaires from 144 prospective applicants in the West Papua Regional Police area. Data were analyzed using the Partial Least Squares - Structural Equation Modelling (PLS-SEM) method. The findings reveal that ease of use and timeliness significantly influence user satisfaction, while content, accuracy, and format do not. This indicates that usability and information timeliness play a more critical role. The study encourages system developers to focus on enhancing functional and responsive features to improve digital public services.
Effect of Bluebox E-commerce Service Quality on User Satisfaction Using Webqual 4.0 and End User Computing Saticfaction (EUCS) methods Febriyanti, Irna Awalia; Marini, Lion Ferdinand; Baisa, Lorna Yertas
Eduvest - Journal of Universal Studies Vol. 4 No. 12 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i12.50037

Abstract

Bluebox is the first online shopping platform in Manokwari that provides a wide range of daily and monthly shopping products not only that but also food and snacks, which can help the shopping process from home. Bluebox comes with delivery services in various areas in Manokwari and offers various payment options, including COD, transfer, and QRIS. The purpose of this study is to investigate in depth how the Bluebox application can improve their service quality from various aspects based on user satisfaction and experience with the ultimate goal of increasing user satisfaction and the success of MSMEs in Manokwari. The data is processed using the Webqual 4.0 method which includes Usability, Information Quality, service Interaction variables and the End User Computing Satisfaction (EUCS) method, especially the Timeliness variable. The data analysis method in this study uses the PLS-SEM approach with SmartPLS version 4.1.0.2 as a tool to help test research data. From the test results obtained in this study, each of the four hypotheses proposed that the average measurement of user satisfaction with the Bluebox application gets a value of 4.095 with the Satisfied category. Factors that affect user satisfaction with 4 hypotheses and 1 acceptable hypothesis, namely the Timeliness variable which has a significant effect of P Values <0.05 on User Stisfaction, while the Usability, Information Quality and Service Interaction variables do not show a significant effect on User Satisfaction with a significance level of P Values> 0.05 in the Bluebox application.
Evaluasi Pengaruh Kualitas Website Kampung Kopo terhadap Kepuasan Pengguna Menggunakan Model WebQual 4.0 Ahoren, Anan Ansi; Suhendra, Christian Dwi; Baisa, Lorna Yertas
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/tftzct83

Abstract

This study evaluates the quality of the Kampung Kopo website using the WebQual 4.0 model, which comprises three dimensions: usability, information quality, and interaction quality. A quantitative survey was conducted with 109 purposively selected respondents, and data were analyzed using multiple linear regression. Descriptive results showed that usability (4.03) and information quality (4.03) received high scores, while user satisfaction was moderate (3.41). Regression analysis revealed that all three dimensions significantly influenced satisfaction: interaction quality (β = 0.401; p < 0.001), information quality (β = 0.345; p < 0.001), and usability (β = 0.306; p < 0.001). The model was significant (F = 308.281; p < 0.001) and explained 89.8% of satisfaction variance (R² = 0.898). These findings confirm that while interaction quality has the strongest effect, all three dimensions play essential roles in determining user satisfaction. Village websites should adopt a comprehensive approach to improve usability, information quality, and interaction quality simultaneously to strengthen digital transformation at the village level.
Pengembangan Sistem Inventori Dan Monitoring Stok Wedrink Dengan Pendekatan Machine Learning Dan Notifikasi Real-Time Melalui Whatsapp Bot Hardito, Franciscus Xaverius Andika; Suhendra, Christian Dwi; Baisa, Lorna Yertas
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7704

Abstract

Pengelolaan inventori yang masih manual di Wedrink Manokwari menimbulkan berbagai permasalahan operasional seperti ketidakakuratan data stok, keterlambatan pembaruan informasi, dan kesulitan dalam melakukan tracking barang secara real-time. Penelitian menunjukkan bahwa 67% perusahaan yang masih menggunakan sistem inventori manual mengalami kerugian rata-rata 15-20% dari total pendapatan tahunan. Penelitian ini bertujuan untuk mengembangkan sistem monitoring stok berbasis web dengan framework Laravel yang mengintegrasikan teknologi QR Code untuk otomatisasi pencatatan, machine learning untuk prediksi ketersediaan stok, dan notifikasi real-time melalui WhatsApp Bot. Metode penelitian menggunakan pendekatan System Development Life Cycle (SDLC) dengan model Waterfall yang terdiri dari lima tahap: analisis kebutuhan, perancangan sistem, pengembangan, pengujian, dan implementasi. Hasil penelitian menunjukkan bahwa sistem berhasil meningkatkan efisiensi operasional dengan pencapaian system uptime 99.9%, response time kurang dari 2 detik, dan akurasi prediksi machine learning di atas 95%. User Acceptance Testing (UAT) mencapai tingkat penerimaan 100% dari manager operasional dan staf dengan skor kepuasan pengguna 4.8/5, serta menunjukkan peningkatan efisiensi waktu hingga 75% dibandingkan sistem manual. Dapat disimpulkan bahwa implementasi sistem monitoring stok dengan integrasi QR Code, machine learning, dan WhatsApp Bot berhasil mengotomatisasi proses pencatatan stok, memberikan notifikasi real-time, menghasilkan laporan akurat, dan menyediakan prediksi ketersediaan stok yang tepat. Pengembangan lebih lanjut disarankan untuk menambahkan fitur analisis prediktif yang lebih kompleks, meningkatkan keamanan sistem, dan mengoptimalkan model machine learning.
Analysis of Students’ Perceptions of the Free Nutritious Food Program (MBG) Based on K-Means Clustering Rahmi, Nur; Baisa, Lorna Yertas; Sumendap, Andreas Leonardo
Indonesian Journal of Artificial Intelligence and Data Mining Vol 9, No 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v9i1.39240

Abstract

The Free Nutritious Food Program is a strategic policy to support students’ nutritional resilience and readiness to learn. This study examined students’ perceptions of the program and identified respondent profiles using the K-Means clustering algorithm. Data from 501 students were collected through a Likert-scale questionnaire and analyzed to determine distinct perception patterns. The results revealed five clusters with strong validity, indicated by a silhouette value of 0.917. Overall, 74.6% of respondents expressed positive perceptions, suggesting that the program has been well received and supports school nutrition. However, some groups reported concerns regarding menu variety and cleanliness at distribution points. These findings underscore the need for routine quality monitoring, standardized implementation procedures, and greater attention to service consistency. Future studies should also include objective indicators such as body mass index and school attendance to provide a more comprehensive evaluation of program impact
Comparative Study of Machine Learning Methods for Sentiment Analysis of TikTok Comments Related to Cyberbullying Mariwy, Celestina Florecita; Baisa, Lorna Yertas; Sumendap, Andreas Leonardo
Indonesian Journal of Artificial Intelligence and Data Mining Vol 9, No 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v9i1.39183

Abstract

The rapid growth of internet use in Indonesia has contributed to the rise of cyberbullying on TikTok, increasing the importance of automated sentiment analysis for digital safety. This study compares the performance of Support Vector Machine, K-Nearest Neighbors, and Naive Bayes in classifying sentiments in TikTok comments related to cyberbullying. The dataset was collected via web scraping and processed through several preprocessing stages, yielding 7,900 unique comments. Sentiment labeling used a lexicon-based approach, and the data were split into training and testing sets with an 80:20 ratio. Results show that 34.18% of comments were negative, indicating a notable level of harmful content. Among the three models, Support Vector Machine performed best with an accuracy of 91.5%, followed by Naive Bayes at 82.8% and K-Nearest Neighbors at 80.8%. These findings suggest Support Vector Machine is the most effective method for sentiment classification in this context and offer a useful reference for developing more accurate content moderation systems on social media.
Public Sentiment Analysis of the Affan Kurniawan Social Issue: A Comparison of Naïve Bayes and SVM Algorithms Mamusung, Marsella Iriana; Baisa, Lorna Yertas; Sumendap, Andreas Leonardo
Indonesian Journal of Artificial Intelligence and Data Mining Vol 9, No 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v9i1.39258

Abstract

Social media X is a dynamic public space where opinions on social issues, including the Affan Kurniawan case, spread rapidly. This study aims to analyze sentiment distribution, compare the performance of Multinomial Naïve Bayes and Linear Support Vector Machine (LinearSVC), and evaluate classification consistency under a unified evaluation framework. Indonesian-language posts were collected using keyword-based crawling and cleaned from 10,624 to 7,431 valid records (28 August–2 September 2025). The data were preprocessed through normalization, tokenization, stopword removal, and stemming, and labeled into negative, neutral, and positive sentiments using a lexicon-based approach. The results show a dominance of negative sentiment (50.26%), followed by neutral (30.96%) and positive (18.77%). Using Bag-of-Words features and an 80:20 train–test split, LinearSVC outperformed Naïve Bayes with higher accuracy (0.826 vs 0.745) and macro F1-score (0.759 vs 0.579). This study highlights the effectiveness of SVM as a stronger baseline model for Indonesian sentiment classification on social media data.
Co-Authors Ahoren, Anan Ansi Barrang, Herlina Christian Dwi Suhendra, Christian Dwi Dwi Pratiwi, Dinda Malika Febriyanti, Irna Awalia Hardito, Franciscus Xaverius Andika Inan, Dedi Iskandar Indra, Muhamad Kandami, Joshua Hans Mamusung, Marsella Iriana Marini, Lion Ferdinand Mariwy, Celestina Florecita Nur Rahmi Ratna Juita Sanglise, Marlinda Sumendap, Andreas Leonardo Yang, Ester Deborah