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Analysis Of Tokopedia Product Clustering Using The K-Means And K-Medoids Algorithms Raihan Malik; Pradita Eko Prasetyo Utomo; Benedika Ferdian Hutabarat
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6992

The Indonesian e-commerce market has experienced extraordinary growth, driven by increasing internet penetration and smartphone adoption, which necessitates advanced data analysis for competitive advantage. Clustering is a crucial data mining technique used to group products based on similar characteristics, providing in-depth insights into product performance. Previous studies often focused on single performance metrics, overlooking the nuances of combining multiple variables. This study aims to address this gap by implementing and comparing the K-Means and K-Medoids clustering algorithms on Tokopedia product data using a combination of numerical attributes: Price, Customer Rating, Number Sold, and Total Review. The methodology involved data preprocessing, Min-Max Scaling for normalization, and using the Elbow Method to determine the optimal number of clusters, which was found to be K=2. The clustering quality was rigorously evaluated using the Davies-Bouldin Index (DBI) and Silhouette Score. The results demonstrate that K-Means exhibits superior performance, achieving a lower DBI of 0.5717 and a higher Silhouette Score of 0.6012, compared to K-Medoids (DBI: 0.5870; Silhouette Score: 0.5857). Furthermore, K-Means proved significantly more efficient computationally, with an execution time of 0.0947 seconds versus 0.1622 seconds for K-Medoids. The main conclusion is that K-Means is more effective in creating compact and clearly separated clusters. This research contributes a valuable analytical framework for e-commerce managers to comprehensively understand product profiles, guiding more effective marketing and recommendation strategies.

Semantic FAQ Chatbot Using SBERT (Sentence-BERT) and Cosine Similarity for Academic Services Rahul Marcellino Holis; Pradita Eko Prasetyo Utomo; Benedika Ferdian Hutabarat
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7027

Handling repetitive inquiries in academic environments requires significant time and human resources, potentially delaying service delivery. This study developed a semantic FAQ chatbot using Sentence-BERT (SBERT) and Cosine Similarity to improve efficiency and consistency of academic information services at Universitas Jambi. The system encodes user queries into dense vector embeddings and compares them with FAQ entries using cosine similarity. A dataset of 65 frequently asked questions was collected through interviews and direct observation with students, lecturers, staff, and helpdesk officers. To evaluate semantic understanding, these entries were expanded into 130 question variations using paraphrasing. Model performance was measured with a confusion matrix and standard metrics. At a similarity threshold of 0.5, the system achieved 79.2% accuracy, 81.7% precision, 96.3% recall, and an F1-score of 88.4%. The results show that SBERT effectively identifies semantically similar questions with different wordings, handling both formal and informal Indonesian queries. High recall demonstrates that most relevant questions were successfully retrieved, while precision remains sufficient to ensure reliable responses. This study demonstrates that SBERT-based semantic matching can successfully handle Indonesian academic FAQ with diverse linguistic variations, enabling 24/7 accessibility and consistent service delivery independent of staff availability. Future work should expand the dataset to include emerging queries and conduct pilot deployment to validate operational effectiveness and user satisfaction

Business Intelligence Roadmap for Tableau Dashboard Development in Higher Education Yuda Fatoni; Pradita Eko Prasetyo Utomo; Rizqa Raaiqa Bintana
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7094

Universities are increasingly required to make data-driven decisions, yet many are still hindered by static and non-interactive reports. This study addresses these challenges at the Jambi University with the aim of designing and developing a series of interactive dashboards using Tableau, applying an adaptive framework based on the Business Intelligence Roadmap. The research methodology includes three main stages: pre-development, development, and post-development. The technical process involves Extract, Transform, Load (ETL) of data from different datasets into a MySQL database that serves as a centralized data source before visualization. The main results of this study are seven functional dashboard prototypes that were successfully developed, covering data analysis of lecturers, graduates, and other strategic areas. This dashboard is capable of presenting key insights, such as the lecturer-to-student ratio and lecturer qualification profiles (29.8% holding a PhD), in a visual and interactive manner. Furthermore, the prototype was successfully integrated into a web interface, demonstrating the technical feasibility of its implementation. This study concludes that the application of an adapted BI Roadmap is an effective approach for dashboard development in an academic environment. The results not only provide a decision-support tool for the Jambi University but also offer a methodological framework that can be replicated.

Back-End Geographic Information System Development for Linguistic and Literary Mapping in Jambi Province Cagivamito Tadashi Hutabarat; Pradita Eko Prasetyo Utomo; Ulfa Khaira
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7384

Indonesia possesses a rich diversity of regional languages and literature, including 718 recorded languages and 965 literary works nationally. Jambi Province, with its seven local languages and abundant oral traditions, requires more effective preservation efforts. Currently, available information is limited to static physical maps that are difficult to access. This study aims to develop a web-based Geographic Information System to digitally, interactively, and flexibly map the distribution of languages, literature, and scripts in Jambi. The system was developed using the System Development Life Cycle (SDLC) approach with an Incremental model, allowing for gradual development and continuous adjustments. The primary focus was on back-end development, including the database, business logic, and server. Functional testing was conducted using black-box testing, while non-functional performance evaluation was carried out through load testing using k6 on the main features, simulating 50 Virtual Users (VUs). Test results indicated that the system was stable and responsive, with a 0.00% failure rate, average response times of 59.08–68.74 ms, and a P95 not exceeding 106 ms. The system was developed in two increments: a general user interface and an administrator dashboard, enabling efficient management of language, literature, script, announcement, and feedback data. The implementation of this digital platform enhances information accessibility, supports the Language Office of Jambi Province in data dissemination, and contributes to the preservation of regional cultural heritage for the public and researchers.

Front-End Development of a Geographic Information System for Language and Literature Mapping in Jambi Aldi Sukma Putra; Pradita Eko Prasetyo Utomo; Ulfa Khaira
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7388

This study addresses the need for an interactive digital platform to support the preservation of linguistic and literary data in Jambi Province. Existing platforms developed by Balai Bahasa Provinsi Jambi provide textual information only and lack spatial visualization, limiting users’ ability to explore linguistic distributions. Geographic Information Systems (GIS) are suitable for linguistic documentation because dialect boundaries and speech communities are strongly related to geographic regions. This study aims to design and develop a front-end GIS interface for mapping linguistic and literary data using the Incremental Model and to evaluate its functional performance through Black-Box Testing. The system was built using HTML, CSS, JavaScript, the Laravel Blade templating engine, and the Leaflet library for interactive map visualization. The Incremental Model supported iterative development, allowing core features map visualization, search and filter functions, and detailed information pages to be refined based on continuous feedback. Data from Balai Bahasa Provinsi Jambi, including language names, literary descriptions, documentation files, and geographic coordinates, were used as input. The results show that the system meets all functional requirements, achieving a 100% success rate across 11 Black-Box test scenarios, and providing real-time response capabilities for search and filter functions. These technical outcomes demonstrate that incremental front-end development is effective for building modular and interactive GIS interfaces. This study contributes to digital cultural preservation efforts and provides a foundation for future GIS-based linguistic mapping initiatives, while further research is needed to enhance backend integration, expand datasets, and evaluate system performance at scale.

Application of Visual Data Mining for Visualization of UKBI Achievement Data Ketri genes Yolanda; Pradita Eko Prasetyo Utomo; Zainil Abidin
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7409

The current visualization of Adaptive Indonesian Language Proficiency Test (UKBI Adaptif) results in Jambi Province is suboptimal, often relying on static, basic charts, which hinders transparency and the effective formulation of evidence-based language policies. This research aims to address this critical gap by developing an interactive, data-driven system to analyze the language proficiency profile of UKBI participants in Jambi from 2021 to 2024. The research objective is to accurately map regional competence, identify hidden patterns, and provide actionable intelligence to the Jambi Language Center. The study adopts the Visual Data Mining (VDM) methodology, integrating interactive visualization with the K-Means clustering algorithm. This method allowed for the normalization and grouping of over 10,000 participant data points, with the optimal number of clusters determined by the Silhouette Score. The research results successfully established three distinct proficiency clusters, including a "Listening Struggler Group" dominated by non-education professions, exhibiting significantly low scores in the Listening section. Furthermore, geographical analysis revealed a disparity where Jambi City—the region with the highest participation—maintained an average proficiency at the lower boundary of the Intermediate category, while smaller regions like Muaro Jambi showed higher rates of Superior and Exceptional achievement. The conclusion is that the VDM-based interactive dashboard is a validated and effective tool that successfully provides micro-level insights, supporting the strategic allocation of resources and the design of targeted intervention programs to address specific skill weaknesses, such as listening comprehension.

Operational Data Integration with Pureshare Dashboard for Unified Service Unit Hana Silvanov Rhamadani; Pradita Eko Prasetyo Utomo; Mutia Fadhila Putri
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7412

Public institutions in digital era increasingly require integrated data to support decision-making and performance monitoring. The development of the Electronic Unified Service Units (ULT-E) at the Jambi Language Office responds to this need by establishing a mechanism capable of consolidating operational data. The objective of this research is to design and develop a service dashboard using Pureshare as a guiding framework for identifying requirements, planning visual structures, and organizing information elements. The key performance indicators are presented as operational indicators across operational service data, including service requests, complaints, and public satisfaction. The development process includes requirement user, operational indicators, visual design, data integration through ETL procedures. The results show that the dashboards produced in this research present key performance indicators as operational indicators across three main areas, service requests, complaints, and public satisfaction surveys. The visual components consist of drill-down and time-range features for data exploration. The integration of these dashboards into the operational web interface indicates that the system is ready to support the institution’s digital service environment. The average System Usability Scale (SUS) score of 72.50 represents that users were able to follow the interaction flow and understand the visual components provided. The conclusion is that dashboard development can enhance service management efficiency, even when data conditions differ across modules, making operational information more accessible.

Evaluating BISMA Application Success at Jambi University Using the D&M Information Success Model Rts Nuraini; Pradita Eko Prasetyo Utomo; Dewi Lestari
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7455

The BISMA application is a web-based information system adopted by Jambi University to manage the submission, review, and reporting processes for research and community service activities. As a mandatory system implemented since 2024, it is essential to evaluate its level of success and user acceptance to ensure that the system effectively supports academic and administrative needs. This study aims to assess the success of BISMA using the DeLone and McLean IS Success Model, which comprises six key constructs: System Quality, Information Quality, Service Quality, Use, User Satisfaction, and Net Benefit. This model was selected because it provides a comprehensive framework for examining system performance, information effectiveness, and the resulting impact on user satisfaction and organizational benefits. A quantitative approach was employed by distributing questionnaires to 100 respondents consisting of lecturers and internal BISMA users. The collected data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) to test the relationships among the model’s constructs. The findings indicate that Information Quality and User Satisfaction significantly influence system use and perceived net benefits, suggesting that accurate, relevant, and timely information plays a crucial role in enhancing the value of the system. Conversely, System Quality and Service Quality were found to have no significant effect on user satisfaction, indicating the need for improvements in system reliability, responsiveness, and technical support. Overall, BISMA is considered to provide satisfactory benefits in supporting research and community service management; however, enhancements in service quality and system stability are still required to optimize user experience and strengthen system effectiveness in the future.

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