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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Manajemen Terapan dan Keuangan JURNAL SISTEM INFORMASI BISNIS Jurnal Pendidikan dan Pengajaran Elkom: Jurnal Elektronika dan Komputer Indonesian Journal of Artificial Intelligence and Data Mining JSiI (Jurnal Sistem Informasi) Jurnal Ilmiah Media Sisfo Jurnal Nasional Komputasi dan Teknologi Informasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Journal of Information System,Graphics, Hospitality and Technology Jurnal Kridatama Sains dan Teknologi Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Nasional Ilmu Komputer Information System Journal (INFOS) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Sains Teknologi dan Sistem Informasi JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Brilliance: Research of Artificial Intelligence MATHunesa: Jurnal Ilmiah Matematika Algoritme Jurnal Mahasiswa Teknik Informatika Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pustaka Aktiva : Pusat Akses Kajian Akuntansi, Manajemen, Investasi, dan Valuta Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Karya Abdi Masyarakat Journal of Business Studies and Management Review Journal of Fish Health MIMBAR INTEGRITAS J-Icon : Jurnal Komputer dan Informatika Journal of Software Engineering and Information System (SEIS) Jurnal Pengabdian Masyarakat Pinang Masak Jurnal Sistem Informasi dan Ilmu Komputer Journal of Management and Innovation Entrepreneurship (JMIE) JUPEMA Jurnal Indonesia : Manajemen Informatika dan Komunikasi International Journal of Computer Technology and Science Akademika Jurnal Ilmu Komputer dan Teknologi Informasi Tesseract: International Journal of Geometry and Applied Mathematics EdLib Journal (Education and Library Journal) Indonesian Journal on Learning and Advanced Education (IJOLAE)

Utomo, Pradita Eko Prasetyo

Univeristas Jambi

Author-ID : 3863561

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Physics Public Health Social Sciences Transportation Other

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Business Intelligence Roadmap for Tableau Dashboard Development in Higher Education Fatoni, Yuda; Utomo, Pradita Eko Prasetyo; Bintana, Rizqa Raaiqa
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.

Ichthyofauna Biodiversity in Lake Kelari Within the Muaro Jambi National Cultural Heritage Area as a Basis for Establishing a Lubuk Larangan Wulanda, Yoppie; Sukmono, Tedjo; Yunita, Lauura Hermala; Magwa, Rizky Janatul; Putra, Tri Syukria; Utomo, Pradita Eko Prasetyo
Journal of Fish Health Vol. 5 No. 2 (2025): Journal of Fish Health
Publisher : Aquaculture Department, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jfh.v5i2.6451

Lake Kelari is located in the Muaro Jambi National Cultural Heritage Area (KCBN) and has ecological and economic value as a habitat for various species of fish. This study aims to identify the biodiversity of the lake, conservation status, global distribution, and fish biodiversity index in the lake, which can be the scientific basis for the establishment of the proclamation pit as an in-situ conservation effort. The method used is a survey method including the collection of primary data through fishing using nets, bubu, and fishing rods in the 2023 rainy season and the 2024 dry season, as well as measuring water quality and habitat character. The results of the study show that the biodiversity of ikhtiofauna in Lake Kelari includes; 13 species, 13 genera and 7 families. The biodiversity index shows medium criteria. Lake Kelari has the potential as an insitu conservation area with the discovery of a species of senggiringan fish (Hemibagrus planicep) which has the status of Data Vulnerable in the IUCN Red List. Most of the species found are consumption fish, and some others are ornamental fish. The riparian vegetation found varied, the water quality was relatively maintained, and the absence of introduced fish showed the natural environment of Lake Kelari. In conclusion, Lake Kelari has medium fish biodiversity index with important conservation and economic value. The implementation of the ban can be a strategic step in maintaining fish populations and supporting the sustainability of the ecosystem and local economy.

CLUSTERING WILAYAH DI INDONESIA BERDASARKAN KUALITAS PENDIDIKAN MENGGUNAKAN ALGORITMA FUZZY C-MEANS Anwar, Gema Fitria; Khaira, Ulfa; Utomo, Pradita Eko Prasetyo
Information System Journal Vol. 8 No. 02 (2025): Information System Journal (INFOS)
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/infosjournal.2025v8i02.2442

Pendidikan merupakan kebutuhan mendasar yang berperan penting dalam membentuk kualitas sumber daya manusia serta menentukan masa depan bangsa. Hasil PISA (Program for International Student Assessment) 2018 menunjukkan kualitas pendidikan Indonesia masih memprihatinkan dengan peringkat 74 dan skor 1.146. Meskipun pada PISA 2022 posisi Indonesia meningkat lima peringkat, skor turun menjadi 1.108 dan tetap berada di bawah rata-rata negara peserta. Upaya peningkatan kualitas pendidikan salah satunya dapat dilakukan melalui pemerataan kualitas di setiap provinsi. Penelitian ini bertujuan untuk mengidentifikasi pengelompokan provinsi di Indonesia berdasarkan kualitas pendidikan menggunakan algoritma Fuzzy C-Means. Data yang digunakan mencakup enam indikator Pendidikan APK, APM, APS, AMH, RLS, dan HLS pada 34 provinsi selama periode 2022–2024 yang diperoleh dari Badan Pusat Statistik (BPS). Hasil analisis menunjukkan bahwa jumlah Cluster optimal setiap tahun adalah dua Cluster berdasarkan nilai Partition Coefficient Index, yaitu 0.8905128 (2022), 0.8822183 (2023), dan 0.8602231 (2024). Tahun 2022 dan 2023 menunjukkan pola pengelompokan yang konsisten dengan 15 provinsi pada Cluster 1 dan 19 provinsi pada Cluster 2. Pada tahun 2024 terjadi perubahan komposisi, di mana Cluster 1 berkurang menjadi 14 provinsi dan Cluster 2 meningkat menjadi 20 provinsi.

Peramalan Indeks Harga Prulink Rupiah Equity Fund Dengan Metode Exponential Moving Average Mahadewa, Agung; Aryawan, Made Gitra; Prasetyo Utomo, Pradita Eko
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 1 No 2 (2018): December
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Company that has the added investment products with protection products, from a variety of investment products offered, product PRUlink Rupiah Equity Fund is the most desirable, the product has a high volatility compared to other products. Because it is a customer who is also an investor in this case, often feel disadvantaged by the insurer at the time of withdrawal own funds, it is caused by a lack of knowledge to know the price index next period Alleged right is the main information needed by investors to determine the next strategy in investing, One is the method of Exponential Moving Average. This method is a method of time series are used to predict the future by using historical data. Assigning weights to involve periods, so the longer the period that we use, the smaller the final value weighting we use With the abundance of available data, the construction of a system that utilizes past data, in other words, try using a time series model time series of the past to predict, the system will be useful to assist investors in predicting the allegations of the value of equity funds in the future so as to determine the appropriate strategy for investment.

Application of You Only Look Once (YOLO) Method for Sign Language Identification Reni Triyaningsih; Pradita Eko Prasetyo Utomo; Benedika Ferdian Hutabarat
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.21931

Limited understanding of sign language has widened the social gap for deaf people, creating barriers in communication and social interaction. To address this challenge, technology-based solutions are required to facilitate inclusive communication. Deep learning-based detection methods, particularly the You Only Look Once (YOLO) algorithm, have gained attention for their speed and accuracy in real-time object detection. This research aims to develop and evaluate a YOLO training model for the identification of Indonesian sign language system (sistem isyarat bahasa Indonesia, SIBI). The dataset was obtained from resource person at the State Special School Prof. Dr. Sri Soedewi Masjchun Sofwan, SH. Jambi, and enriched with additional images collected from external subjects. Augmentation techniques with Roboflow were applied to expand the dataset, and several training schemes were implemented. Model performance was assessed using confusion matrix while considering accuracy and indications of overfitting. The results showed that the quality and quantity of training data, as well as the epoch values, strongly influenced the accuracy of the trained model. The best performance was achieved with 40 primary images per label class, augmented to 60 images, and trained over 24 epochs, resulting in a confusion matrix accuracy of 99.9%. The implemented model was able to recognize SIBI gestures in real-time using a webcam with fast processing. Overall, the proposed YOLO-based model successfully identifies sign language in real-time and demonstrates strong potential for reducing communication barriers among deaf people. However, further refinement and expansion of the dataset are recommended to improve effectiveness and enable broader real-world applications.

Perancangan UI/UX Website Point of Sale (POS) Menggunakan Metode Design Thinking di PT Hayaa Investama Group Azzahra, Naesya; Utomo, Pradita Eko Prasetyo; A., Muhammad Razi
Jurnal Kridatama Sains dan Teknologi Vol 8 No 01 (2026): Jurnal Kridatama Sains dan Teknologi (In Progress)
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v8i01.1981

The process of managing sales transactions, inventory, and financial records at PT Hayaa Investama Group is still done manually. This causes the work process to be less efficient and risks causing recording errors. This condition indicates the need for the implementation of a web-based Point of Sale (POS) system that can support the company's operational activities more effectively, especially in terms of ease of use. This study aims to design the interface and user experience of the web-based Point of Sale system at PT Hayaa Investama Group using the Design Thinking method. This method is implemented through five stages, namely Empathy, Definition, Ideation, Prototype, and Testing. Data collection was carried out through observation and interviews with employees and company owners to obtain an overview of user needs. The result of this study is a High-Fidelity prototype equipped with features for managing transactions, inventory, suppliers, purchases, sales, and reports. Prototype testing was conducted using Maze Usability Testing and resulted in a score of 80% from 9 respondents with 7 block missions. The test results indicate that the developed system design is quite easy to use and can be understood by users

Back-End Geographic Information System Development for Linguistic and Literary Mapping in Jambi Province Hutabarat, Cagivamito Tadashi; Utomo, Pradita Eko Prasetyo; Khaira, Ulfa
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 Putra, Aldi Sukma; Utomo, Pradita Eko Prasetyo; Khaira, Ulfa
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 Yolanda, Ketri genes; Utomo, Pradita Eko Prasetyo; Abidin, Zainil
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 Rhamadani, Hana Silvanov; Utomo, Pradita Eko Prasetyo; Putri, Mutia Fadhila
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.

Co-Authors Abidin, Zainil Afifa, Afifa Lutfia Fakhira Akhiyar Waladi Amanda Iza Sofiani Anwar, Gema Fitria Arsa, Daniel Aryani, Reni Aryawan, Made Gitra Aulia Dwiza Puteri Ayu Indryani Azhari SN Azzahra, Naesya Benedika Ferdian Hutabarat Bisma Aulia Cepi Ramdan Cepi Ramdan Chika Efansa Chit, Suwannit Chareen Dawam Suprayogi Dedy Setiawan Desi Musfiroh Dewa, Raldi Fitra Dewi Lestari Dinda Fatimah Sarah Dwi Agus Kurniawan Dwi Kurniawan Edi Saputra Edi Saputra Efansa, Chika Elisa, Edi Fachrul Sukmadinata Fatoni, Yuda Fitri Dwi Lestari Fitri, Lucky Enggraini Ghaitsa Althafah Wandira Ghaitsa Althafah Wandira Hadaya, M. Syahan Afdhal Haloho, Ica Yunarti Haloho Hasanatul Iftitah Hasby Kuswanto Holis, Rahul Marcellino Hutabarat, Cagivamito Tadashi Iftita, Hasanatul Ilhami, Mohamad Imelda Raudati Imelda Raudati Indra Weni Jaya, Asirman Jefri Marzal Jefri Marzal Jodion Siburian Khaira, Ulfa Lucky Enggraini Fitri Lutvianita, Febby M. Rizky Ardiansyah Putra M. Taufik Hidayat Mahadewa, Agung Mahmudin, Riyan Malik, Raihan Mauladi Mauladi Mh. Khathamy Fhadlullah Haq Syahlevy Mochammad Farisi Muhammad Iqbal Muhammad Nabil Muhammad Razi A Muksin Alfalah Mutia Fadhila Putri mutia fadhila putri, mutia fadhila Nasution, Mukhtada Billah Nazwa Eka Hervy Novita Sari Novita Sari Nuraini, Rts Putra, Aldi Sukma Putra, Tri Syukria Putra, Yahya Nugraha Putri Hazmawati Putri, Anastasya Alya Ragil Johanda Rahayu Rahayu Rayandra Asyhar Reni Triyaningsih Repaldi Handi Saputra Reza Safitri Rhamadani, Hana Silvanov Rivaldi, Ikvi Akmal Rizka Octavia Sandra Rizky Janatul Magwa Rizqa Raaiqa Bintana Sahrial Salmah Nur Zahra Salman Jumaili Salsabila, Adinda Desiska SAUDAGAR, FERDIAZ Sigit Indrawijaya Simanjuntak, Januar SRI RAHAYU Suhartini, Sugih Sukma, Silvia Antana Sulfiyandi Sulfiyandi Suwannit Chareen Chit Sylvia Kartika Wulan Bhayangkari Tasia Maidi Saputri Tasia Maidi Saputri Tedjo Sukmono Teguh Sumarsono Tia Wulandari Tri Suratno Ulfa Khaira, Ulfa Wahyu, Ofel Idhan Yenny Yuniarti Yolanda, Ketri genes Yoppie Wulanda Yosika Dian Saputri Yovita, Kristian Yuhana Yuhana Yusnita, Erli

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