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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 Articles sent to the Brilliance may not be published elsewhere.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
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Advancing Voice Anti-Spoofing Systems: Self-Supervised Learning and Indonesian Dataset Integration for Enhanced Generalization Prihasto, Bima; Nur Farid, Mifta; Al Khairy, Rafid
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5182

Abstract

This study examines how self-supervised learning and a novel Indonesian language dataset enhance anti-spoofing systems. Results show improved model performance, with a lower Equal Error Rate (EER) during training, indicating effective learning from diverse audio samples. Using weighted cross-entropy analysis highlights the model's robustness in minimizing training errors. Comparisons with baseline models using English data reveal the proposed approach's superiority, achieving a significantly lower EER due to the incorporation of language-specific data. The unique phonetic features of Indonesian languages provide valuable training material, boosting the system's defence against spoofing attacks. The dataset improves generalization across dialects and recording conditions by including diverse speech samples. This integration enhances the anti-spoofing systems' adaptability, which is vital for real-world applications where recording variability affects performance. The experimental setup used a balanced dataset of genuine and spoofed utterances from male and female speakers, ensuring high-quality input. The training configuration splits the dataset into training, development, and testing sets on a high-performance computing setup. Results showed the proposed model achieved an EER of 0.33, compared to 7.65 for the traditional sinc-layer model and 0.82 for the wav2vec 2.0 model with English data. Overall, this research advances anti-spoofing solutions and emphasizes the need for diverse datasets and advanced learning approaches to improve automatic speaker verification systems in practical applications. The incorporation of the Indonesian dataset is vital for addressing linguistic diversity challenges in biometric security, paving the way for future advancements in this area.
Improving Multiclass Rainfall Prediction with Multilayer Perceptron and SMOTE: Addressing Class Imbalance Challenges Cahyani, Nita; Putri, Wardiana Adinda; Irsyada, Rahmat
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5203

Abstract

Rainfall is a key climate element that affects weather patterns and human activities, especially in agriculture and daily life. Therefore, accurately classifying rainfall is crucial for predicting future rainfall amounts. This study uses the Multilayer Perceptron (MLP) classification method, a neural network algorithm, to classify rainfall. The dataset, sourced from the BMKG website, has a class imbalance, requiring using the SMOTE (Synthetic Minority Over-sampling Technique) technique. The research compares the performance of MLP with and without SMOTE. The results show that the best model was achieved with SMOTE. MLP without SMOTE achieved an accuracy of 75%, sensitivity of 40.34%, specificity of 86.15%, and an AUC of 63.25%. In comparison, MLP with SMOTE achieved an accuracy of 71.27%, sensitivity of 71.14%, specificity of 90.30%, and an AUC of 80.72%. Although accuracy decreased, the overall evaluation, particularly the AUC, improved significantly. Therefore, the SMOTE technique effectively addresses the class imbalance issue in rainfall classification.
Innovation of an Expert System for Diagnosing Allergic Diseases in Children using the Web-based Certainty Factor Method Irsyada, Rahmat; Cahyani, Nita; Badriyah, Lailatul
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5204

Abstract

In this modern era, the development of computer technology has increased so rapidly. Currently the computer is a tool in helping to overcome all the problems encountered by humans, including in the field of health. With the existence of technology, of course, it will greatly facilitate the community to get health services and consultations. One of the technological developments is an expert system. An expert system is a branch of artificial intelligence (Artificial Intelligence), which is an application designed to use a computer that tries to imitate the reasoning process of an expert or expert in solving specific problems and making decisions or conclusions because to solve a problem and save it. in the knowledge base for processing. This expert system was created to assist experts in deciding diseases based on existing symptoms. The Certainty Factor method is a theory that can be used to solve uncertainty problems. Certainty Factor (CF) is a value to measure expert confidence. Certainty Factor was introduced by Shortliffe Buchanan in making the MYCIN expert system to show the amount of trust. This method can work well when there are problems that start from gathering and then gathering information and then being able to find conclusions that can be drawn from that information. The Certainty Factor method will be applied to accurately determine allergic health in children. If this method is applied, it can minimize the presence of allergic diseases suffered by dangerous children. And when you have an allergy, it can be treated immediately.
Optimizing Public Services through Industrial Work Practice Management Applications Using Extreme Programming Methods Azis, Muh Nur Luthfi; Hapsari, Ayunda Nur
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5213

Abstract

Industrial work practice or industrial Internship is applying knowledge and skills to solve real problems. It becomes one of the efforts to improve the quality of human resources in an agency or company. Managing the industrial Internship at PT Artha Abadi is still being carried out using physical documents. This allows errors to occur in recording Industrial Internship data and documents. This study aimed to overcome existing problems so that the management of Industrial Internship activities at PT Artha Abadi is more systematic, organized and efficient. The method used in creating this system is the Extreme Programming method which aims to increase effectiveness and efficiency in the software development process. The Industrial Internship Management Application is built using the Laravel framework and MySQL as its database. The tools used to create this system are XAMPP as a database server and Visual Studio Code for a text editor, in system testing using Black Box Testing to test the software's functionality. Testing shows that the Industrial Internship Management Application does not experience system errors or bugs. The results of this study show that the application is built according to the main objectives and is ready to be implemented so that the Industrial Internship at PT Artha Abadi runs more systematically, organized, and efficiently.
Implementation Of Weighted Aggregated Sum Product Assessment (Waspas) Method In Determining English Language Learning Levels At Vanka Speaking Course Sumbawa Andini, Virna Febri; Julkarnain, M.; Yuliadi, Yuliadi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4207

Abstract

English is an international language that plays a crucial role in global communication. English is very influential in aspects of life, ranging from the work sector to the education sector. Vanka Speaking Course Sumbawa is one of the course institutions in Sumbawa Regency that accepts participants from various levels, namely elementary to junior high school, with multiple levels and six levels of learning. Currently, Vanka Speaking Course Sumbawa has seven tutors with 142 students divided into 13 regular classes (117 people) and 12 private classes (25 people). In a language course like this, determining the student's learning level is a critical initial stage. This allows teachers to design learning programs with suitable modules and materials to meet the needs of each student. The course party still needs help determining the initial stage and learning level that suits the student's abilities. This study aims to apply the Weighted Aggregated Sum Product Assessment (WASPAS) Method in determining the level of English learning by selecting alternatives based on specific criteria. The development method designs the system using Rapid Application Development (RAD), PHP programming language, Laravel framework, MySQL database, and Unified Modeling Language (UML). After being built and tested using black box testing, this application can be run properly and help Vanka Speaking Course Sumbawa make decisions related to determining the level of English learning. The results of this study can improve the accuracy of assessment in determining the level of English learning in students and ultimately further improve the quality of learning at the Vanka Speaking Course.
Analysis of Red Brick Product Quality Improvement at UD. Batu Bata Bulan Using CRISP-DM and C4.5 Algorithm Septiana, Widya; Tsani, Farhan; Utami, Silvia Firda; Andani, Rina Meri
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4208

Abstract

UD Batu Bata Bulan is a home industry in Batu Bulan Village that produces red bricks. The industry has been operating for 20 years and has been producing bricks every day. The home industry is facing problems related to the quality of red bricks that require appropriate action to improve to meet the desired quality. In addition, the home industry is still experiencing difficulties in conducting product quality inspections due to the lack of inspection technology to help the process. The problems faced can be detrimental to UD. Batu Bata Bulan. Therefore, it is necessary to analyze the causes of defective products in the process of producing red bricks and improve the quality of red brick products. Therefore, the researcher conducted an analysis to address the problems that occurred in the company related to product quality. The solution that can be given is to classify the type of defective product using the role of data mining. In this study, the standard Cross Industry Standard Process For Data Mining (CRISP-DM) procedure and C.45 Algorithm were used in data processing.The result of this research indicate significant knowledge in classifying black color defect in data this could facilitate the quality inspection department in making accurate decisions.
Design and Construction of Traditional Tribal Musical Instruments in Sumbawa With Augmented Reality Technology Android-Based Ismiyarti, Wilia; Irawati, Irawati; Ismail, Ismail
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4210

Abstract

Areas of various tribes have distinctive characteristics, such as those of the Sumbawa tribe. Dance arts and traditional tools are elements of the Sumbawa tribal culture. Apart from dance and traditional instruments, the Sumbawa tribe has unique arts, which we generally know as fairy tales (Sakeco), accompanied by the conventional Rebana musical instrument. The culture of the Sumbawa tribe is preserved by building an art studio as a place for its preservation. Sumbawa Regency, especially in Alas District, has a studio called Kemban Alas Art Studio. We can see cultural preservation using modern technology through social media, such as Facebook, Instagram, and TikTok. However, there is still very little preservation through social media regarding Sumbawa culture, such as the content in the press itself due to the influence of new cultures, which has caused the culture of various tribes, especially the Sumbawa tribe, to be little known by most people. The method used in this research is developing the Waterfall model of LifeL Cycle (SDLC) Software and qualitative data collection. This research aims to build an Android-based Augmented Reality application at the Kemban Alas Art Studio and assist the Art Studio in educating Sumbawa tribal culture using the Augmented Reality application. The result of this research is that researchers have completed the design and development of an application that uses Android-based Aulgmelnteld Reality technology as a medium for introducing the traditional music tool Sulkul Sulmbawa.
Decision Support System For Determining Prospective Students' Department At Vocational School 1 Buer Using Simple Additive Weighting Yuliadi, Yuliadi; Romero, Reynaldo; Rodianto, Rodianto
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4211

Abstract

Choosing a major is essential for students, especially junior high school students, who must choose the appropriate field. Vocational High School (SMK) is a formal education unit that organizes vocational education at the secondary education level as a continuation of junior high school. At SMK Negeri 1 Buer, the central determination system is carried out with a ranking system where the ranking system is carried out based on the order in which prospective students register for the primary major so that it cannot be determined according to the interests and talents of the students. The purpose of this major is so that students can be directed to receive lessons based on their abilities and skills. SMK Negeri 1 Buer has eight majors: Building Modeling and Information Design, Motorcycle Engineering and Business, Visual Communication Design, Light Vehicle Engineering, Welding Engineering, Industrial Electronics Engineering, Animation, and Graphic Engineering. Therefore, this decision support system can make it easier for schools to determine majors according to students' interests and talents. This study uses the Extreme Programming method as a system development method and Simple Additive Weighting for calculating the Decision Support System, using PHP as a programming language with the Codeigniter framework and MySQL database. With this SPK, SMKN 1 Buer can distribute students according to their interests and make it easier for students to choose majors according to their interests
College Department Recommendation Expert System Web-Based Using Certainty Factor Method Hasannah, Kholifatun; Agustin, Ninik; Aziz Zein, Mochamad Taufiqurrochman Abdul
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4212

Abstract

The choice of college major is an important decision that each prospective student must take. In the decision-making process, a genuinely accurate source of information is usually needed to avoid mistakes for prospective students when determining the college major they will take. This study implemented the certainty factor method in a website-based college central recommendation expert system to minimize and avoid these mistakes. This study uses the certainty factor method to calculate the level of confidence and uncertainty of each recommendation result given by the expert system. This system will use predetermined rules to connect input and output to provide results that match the input from the user. Based on this process, prospective students will then obtain the appropriate college major recommendation results; in this study, the recommendations are based on the types of intelligence. This study aims to help solve existing problems by building an expert system to provide colleges with significant recommendations and by implementing the certainty factor method to determine the output results of recommendations from the system. This study produces a "College Major Recommendation Expert System (SIPAREK)" to help determine college majors that suit each interest to minimize the risk of mistakes in choosing a college major. In this study, the accuracy value of the recommendation results by applying the certainty factor method was 80%; from this value, it can be concluded that the certainty factor method can work well to provide recommendations for college majors in the system created.
Real Time Chicken Egg Size Classification Using Yolov4 Algorithm Sandy, Cut Lika Mestika; Husna, Asmaul; Rizal, Reyhan Achmad
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4496

Abstract

The common problem currently faced by MSMEs producing chicken eggs is experiencing difficulties in grouping egg sizes every day. Currently, grouping egg sizes is still done manually, this is less than optimal and prone to errors so that many business owners often experience losses. Grouping egg sizes before being sold is very important to note because each size affects the selling price of eggs. The use of technology on a MSME scale in laying hen farmers has not been widely adopted, this is due to limited access and understanding of technology so that to improve and strengthen productivity, management, and marketing in this business, technological innovation is needed. One alternative solution to deal with this problem is to build a real-time computerized system that can group eggs according to their size. This study aims to evaluate the performance of the Yolov4 algorithm in grouping egg sizes based on their size in real time. Based on the results of the tests carried out, the Yolov4 algorithm is able to group chicken eggs in real time with an F1-Score value: 0.89 where the F1-Score value approaching 1 indicates that the system performance has been running well. The results of this classification can be used to create a real-time egg size grouping application that can help MSMEs to monitor the productivity of chicken eggs every day.

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