cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muhammad Khoiruddin Harahap
Contact Email
choir.harahap@yahoo.com
Phone
+6282251583783
Journal Mail Official
publikasi@itscience.org
Editorial Address
Medan
Location
Unknown,
Unknown
INDONESIA
Brilliance: Research of Artificial Intelligence
Published by Information Technology and Science
ISSN : -     EISSN : 28079035     DOI : https://doi.org/10.47709
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Mathematics Other
Brilliance: Research of Artificial Intelligence is The Scientific Journal. Brilliance is published twice in one year, namely in February, May and November. Brilliance aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest information about Artificial Intelligence. Submitted papers will be reviewed by the Journal and Association technical committee. All articles submitted must be original reports, previously published research results, experimental or theoretical, and colleagues will review. Articles sent to the Brilliance may not be published elsewhere. The manuscript must follow the author guidelines provided by Brilliance and must be reviewed and edited. Brilliance is published by Information Technology and Science (ITScience), a Research Institute in Medan, North Sumatra, Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 544 Documents
 8   9   10   11   12 
Wholesale Inventory Management Optimization: Methodological Approach with XGBoost, SVR, and Random Forest Algorithms Carli Apriansyah Hutagalung Hutagalung; Gisela Anastacia Rosalind; Dewi Masito Setyo Tuhu; Ayu Agustianingsih
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3336

Abstract

This research aims to optimize wholesale inventory management at PT Primafood International Pasir Putih 2 by implementing leading algorithms, namely XGBoost, Support Vector Regression (SVR), and Random Forest. In the wholesale industry, effective inventory management plays a crucial role in maintaining smooth production processes and enhancing company profitability. Despite the acknowledged benefits of inventory management, there are aspects that remain not fully disclosed, particularly concerning demand uncertainty and market fluctuations. This study addresses these gaps by exploring the potential of these three algorithms. Experimental methods with a quantitative approach were employed to shape and prepare the dataset. The analysis and predictions' results using XGBoost, SVR, and Random Forest were evaluated using metrics such as Mean Squared Error (MSE), F1-Score, and Accuracy. The evaluation indicates that XGBoost and SVR exhibit optimal performance with low MSE values of 7714.446 and 119.315, high F1-Scores (0.92), and good accuracy levels (0.86 and 0.85), respectively. While Random Forest shows a higher MSE, it still delivers solid performance with an F1-Score of 0.89 and an accuracy rate of 0.81. These findings suggest that all three algorithms can be considered to enhance inventory management performance at PT Primafood International Pasir Putih 2, with significant potential benefits for overall industry development. This research provides valuable insights for decision-making at the business and industrial levels, highlighting the effectiveness of each algorithm in the context of predicting stock level.
Comparison Analysis of K-Means and DBSCAN Algorithms for Improving Budget Absorption Efficiency in EIS Fery Salman; Fauziah
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3373

Abstract

This study aims to analyze the comparison between the K-Means and DBSCAN clustering algorithms in budget absorption within the Executive Information System (EIS). Realized budget achievement data from regional devices serve as the primary dataset for analysis. Before conducting experiments, the data undergo a preprocessing stage to eliminate outliers and apply normalization processes, ensuring the data is ready for further analysis. Subsequently, both algorithms, K-Means and DBSCAN, are applied to the budget achievement data to generate clusters corresponding to their respective characteristics. The research anticipates that the results will unveil significant findings in comparing the performance of K-Means and DBSCAN algorithms in budget absorption within the EIS context, especially within the scope of this study. Therefore, this analysis is expected to provide valuable insights for stakeholders aiming to enhance the efficiency and effectiveness of budget management through the optimal utilization of clustering algorithms within the EIS.
Analysis And Design of Internet Network Infrastructure With Mikrotik Devices At The Penyaring Village Office Using The NDLC Method Yunanri. W.; Yasinta Bella Fitriana; Rizky Andhika Surya
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3377

Abstract

Communication and Internet technology are developing very rapidly, one of which is in the field of telecommunications technology and is directly proportional to the public's need for its use and also with the increasing need for fast and efficient services both in agencies, commercial, academic worlds and in the homes of residents who need internet access. Thus making telecommunications technology an inseparable technology to support human work. The Penyaring Village Office is located in North Moyo District, Sumbawa Regency, which is the center for all activities in the Village, both in the fields of government, empowerment, development, and coaching, all of which are centered at the Penyaring Village office. This research aims to analyze and design the internet network in the Penyaring Village office and prevent slow wifi so that the network stability in the Penyaring Village office becomes more stable/smooth when used, and the work in the Penyaring Village office becomes better and optimal. This research uses Router, Mikrotik, Access Point network devices, Winbox software, and other supporting devices. The network development method uses the NDLC (Network Development Life Cycle) method, which begins with the Analysis, Design, Simulation Prototype, Implemetation, Monitoring and Management. The research method uses qualitative consisting of observation, interviews, and documentation. The results of this research are building network infrastructure, network security, and bandwidth distribution in each sector which can stabilize the process of using WiFi at the Penyaring Village Office.
Utilization of Artificial Intelligence in Chatbot Development for New Student Admission Support at Cokroaminoto University Palopo Muhammad Akram Hamzah; Siaulhak Siaulhak; Iriansa Iriansa; Andi Jumardi; Andryanto Aman
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3389

Abstract

This research aims to develop an artificial intelligence-based chatbot as a support tool for the New Student Admission (PMB) process at Cokroaminoto University Palopo. The system development method applied is the waterfall method, which consists of analysis, design, implementation, testing, and maintenance stages. The main focus of this research is to design and implement a chatbot that is able to provide information and support to prospective new students throughout the admission process. In the analysis stage, user needs and scenarios were identified to guide the development of the chatbot. System design includes the selection of artificial intelligence algorithms and a friendly user interface. Implementation involves developing a chatbot prototype that utilizes artificial intelligence technology. The expected results can improve the efficiency and quality of new student admission services at Universitas Cokroaminoto Palopo.
Towards Integrated Learning and Assistance Systems: A Framework for Technology Selection and Design: Towards Integrated Learning and Assistance Systems: A Framework for Technology Selection and Design Muhannad Ismail Alkhallas; Ahmed Aboubakr Abdulwahid Abraheem; Asma Almkhtar Miftah Alhaj Salem; Ahmed Alnagrat
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3414

Abstract

In the era of Industry 4.0, advanced assistance technologies have permeated manufacturing processes, yet the absence of systematic implementation methods remains a challenge. This research presents a multidimensional framework developed through inductive reasoning, encompassing technological capabilities and instructional considerations. Its primary objective is to guide the development of context-specific assistance solutions, shifting the focus from automated solutions to thoughtful technology selection and implementation. The framework's application has the potential to elevate stakeholder design processes through interactive visualizations and experiential anchoring. Notably, the adoption of cognitive assistance systems within manufacturing is on the rise, driven by the maturation of virtual and augmented reality solutions. However, a notable gap exists in systematic approaches for selecting and designing these technologies. This paper addresses this gap by proposing a comprehensive framework grounded in an inductive approach. This research seeks to enhance awareness among decision-makers in companies regarding essential selection and decision criteria. Furthermore, it offers guidance for a systematic and participatory implementation process. The research results underscore the importance of adopting such a framework in the industry 4.0 landscape, shedding light on the need for strategic technology integration. This study suggests that the proposed framework can serve as a valuable tool to facilitate informed decision-making and drive the successful implementation of assistance technologies in manufacturing processes.
Modeling and Power Quality Enhancement of PV Interfaced with Power Grid System Tareg Elgallai
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3417

Abstract

Recently, photovoltaic (PV) technology has significantly contributed to the utilization of renewable energy sources. It plays a crucial role in addressing the challenges posed by climate change, enhancing energy affordability, ensuring power supply stability, and facilitating energy accessibility. PV technology represents a significant opportunity for addressing the issue of energy access among distant areas that now lack reliable access to electricity. Using a traditional grid is limited due to cost and feasibility constraints. These difficulties are to be addressed in the appropriate timeframe to improve the dependability of the supply. The expansion of the grid into these regions diminishes the overall resilience of the grid system. This leads to a situation where PV systems are integrated into an AC grid with low power quality (PQ) or limited capacity. Nevertheless, the integration of solar power into an AC grid with low capacity. The presence of PQ problems imposes limitations on the levels of penetration. Other factors impose limitations and penetration levels encompass several factors such as non-linear loads, dynamic loads, fluctuating irradiations, and partial shade, among others. This article aims to address the PQ difficulties that arise from a weak electrical infrastructure. The purpose of this compilation is to provide engineers with a readily accessible resource, offering them a distinct advantage in their professional endeavors and scholars engaged in this field of investigation. In this context, the photovoltaic (PV) array is methodically organized into 86 parallel strings. The aforementioned strings are meticulously constructed, consisting of a sequence of seven SunPower SPR-415E solar modules that are intentionally interconnected.
Design and Implementation of the SALUTS System to Support of Improvement of Tourism Transactions and Promotion Juniardi Akhir Putra; Halid Nuryadi; Yuliadi Yuliadi; Erwin Mardinata; Chairul Hudaya; Shinta Esabella; Ardiansyah Putra; Ahmad Juliansyah
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3434

Abstract

This research aims to design and build a tourism system in Sumbawa Regency. In this research is using a qualitative approach that used model of rapid application development (RAD) for system development life circle (SDLC) method. Overall the first stage is system planning, next stage is analyzing tourism data and information that would be presented on web and android technology based. In addition, for users interface display is the attractive database design. The final stage is coding the system and produce a prototype for the implementation which is presenting on the web pages and google play store for android smartphones. The system presented could be used for evaluation, monitoring and facilitating of tourism transaction and promotion processes in Sumbawa Regency.
Application of the Support Vector Machine (SVM) Algorithm for the Diagnosis of Diabetic Retinopathy Yuliadi; Fadhli Dzil Ikram; M. Julkarnain; Fahri Hamdan; Halid Nuryadi
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3436

Abstract

Diabetic Retinopathy (DR) is a disease whose main cause is complications of diabetes mellitus. High levels of sugar in the blood (glucose) are caused by the pancreas' inability to produce insulin. Prevention of diabetic retinopathy and blindness by carrying out examinations at an early stage and doing them regularly. Currently, doctors still carry out examinations manually so they are prone to errors in examinations. This research aims to build an application to diagnose Diabetic Retinopathy in order to facilitate the work of the medical team and doctors at the eye clinic. In the application creation process, MATLAB is used, while feature extraction uses GLCM and for classification, SVM is used. The results of the research are that doctors and medical teams are helped in carrying out manual patient diagnoses and reduce the occurrence of human error.
Evaluating the Efficacy of Traditional Machine Learning Models in Speaker Recognition: A Comparative Study Using the LibriSpeech Dataset Gregorius Airlangga
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3488

Abstract

The efficacy of machine learning models in speaker recognition tasks is critical for advancements in security systems, biometric authentication, and personalized user interfaces. This study provides a comparative analysis of three prominent machine learning models: Naive Bayes, Logistic Regression, and Gradient Boosting, using the LibriSpeech test-clean dataset—a corpus of read English speech from audiobooks designed for training and evaluating speech recognition systems. Mel-Frequency Cepstral Coefficients (MFCCs) were extracted as features from the audio samples to represent the power spectrum of the speakers’ voices. The models were evaluated based on precision, recall, F1-score, and accuracy to determine their performance in correctly identifying speakers. Results indicate that Logistic Regression outperformed the other models, achieving nearly perfect scores across all metrics, suggesting its superior capability for linear classification in high-dimensional spaces. Naive Bayes also demonstrated high efficiency and robustness, despite the inherent assumption of feature independence, while Gradient Boosting showed slightly lower performance, potentially due to model complexity and overfitting. The study underscores the potential of simpler machine learning models to achieve high accuracy in speaker recognition tasks, particularly where computational resources are limited. However, limitations such as the controlled nature of the dataset and the focus on a single feature type were noted, with recommendations for future research to include more diverse environmental conditions and feature sets.
Web-Based Application For Parenting Patterns In Vocational Schools In The Environment Of Politeknik Pelayaran Sorong Muh Idris; Dodik Widarbowo; Yuniar Ayu Hafita; Yudha Herlambang P; Sappewali Sappewali
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3489

Abstract

Digitalization of education is a logical consequence of developments over time, a response to educational services that are experiencing changes in both the learning system and learning culture. Developments in the field of education are closely related to the term innovation. Innovation in the realm of education is an obligation for all educational actors. Moreover, the development of science and technology is growing rapidly. The parenting pattern that has been implemented in most vocational schools within the Ministry of Transportation is still more of a manual system that cannot be connected directly to digitalization. The aim of the process of developing digitalization of parenting patterns is expected to increase efficiency and optimization in many ways, including efficiency and optimization of parenting activities, connectivity between institutions or units involved in parenting, access to data related to parenting patterns, personal data of cadets and caregivers, as well as ease of use. information in accessing rules relating to parenting patterns. The research method used is a mixed type of research. Mixed research is the use of two types of research, namely qualitative and quantitative in one study. The research location is planned to be carried out at a vocational school under the Ministry of Transportation (Poltekpel Sorong). This research then produced an online-based digitalization development desktop software and was then named the see cadet application website. This development and research uses the ADDIE Development Model, namely the analysis stage, design stage, development stage, implementation stage and evaluation stage.

Page 10 of 55 | Total Record : 544

 8   9   10   11   12 

Filter by Year

2021 2026


Reset
Filter By Issues
All Issue Vol. 6 No. 1 (2026): Brilliance: Research of Artificial Intelligence, Article Research May 2026 Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025 Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025 Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024 Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024 Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023 Vol. 3 No. 1 (2023): Brilliance: Research of Artificial Intelligence, Article Research May 2023 Vol. 2 No. 3 (2022): Brilliance: Research of Artificial Intelligence, Article Research November 2022 Vol. 2 No. 2 (2022): Brilliance: Research of Artificial Intelligence, Article Research May 2022 Vol. 2 No. 1 (2022): Brilliance: Research of Artificial Intelligence, Article Research February 2022 Vol. 1 No. 2 (2021): Brilliance: Research of Artificial Intelligence, Article Research November 2021 Vol. 1 No. 1 (2021): Brilliance: Research of Artificial Intelligence, Article Research May 2021 More Issue