Brilliance: Research of Artificial Intelligence最新文献

IoT-Based Rainfall Monitoring System for Chili Farming Land 基于物联网的辣椒耕地降雨监测系统

Brilliance: Research of Artificial Intelligence Pub Date : 2024-03-08 DOI: 10.47709/brilliance.v3i2.3649

Rahmadani Putri, Ratna Dewi, Silfia Rifka, Sri Nita, Andi Ahmad Dahlan

{"title":"IoT-Based Rainfall Monitoring System for Chili Farming Land","authors":"Rahmadani Putri, Ratna Dewi, Silfia Rifka, Sri Nita, Andi Ahmad Dahlan","doi":"10.47709/brilliance.v3i2.3649","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3649","url":null,"abstract":"This research focuses on the design and implementation of a rainfall monitoring system for chili pepper farms using Internet of Things (IoT) technology. The rainfall monitoring system consists of a transmitter system, a receiver system, the Thingspeak platform as a database, and a weather station application that can be accessed via a mobile device. The weather station application is built using the MIT App Inventor platform. In the testing phase, the system successfully collected data from two sensors used, namely the rainfall intensity sensor and the raindrop sensor. The test results showed that the data obtained from the rainfall intensity sensor was 0.25 inches and the raindrop sensor was 1. This result shows that there was no rain during the test. This rain intensity and raindrop data can provide farmers with an overview of the weather conditions in the chili pepper farm. So, with this rainfall monitoring system, farmers can monitor the condition of their agricultural land in real-time. The collected data can help farmers to care for chili pepper plants more effectively and adapt to environmental changes. In addition, this system is expected to increase the productivity of chili pepper farming because it uses a more precise and responsive approach to changes in environmental conditions on the chili pepper farm.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"23 25","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140258144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Marketing Efforts to Improve Products of Micro Small and Medium Enterprises (UMKM) in Tegal 改善 Tegal 地区中小微型企业 (UMKM) 产品的数字营销工作

Brilliance: Research of Artificial Intelligence Pub Date : 2024-02-29 DOI: 10.47709/brilliance.v3i2.3646

Nugroho Adhi Santoso, Bangkit Indarmawan Nugroho, Aang Alim Murtopo, Sarif Surorejo, Gunawan Gunawan

{"title":"Digital Marketing Efforts to Improve Products of Micro Small and Medium Enterprises (UMKM) in Tegal","authors":"Nugroho Adhi Santoso, Bangkit Indarmawan Nugroho, Aang Alim Murtopo, Sarif Surorejo, Gunawan Gunawan","doi":"10.47709/brilliance.v3i2.3646","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3646","url":null,"abstract":"Digital marketing is promotional activities and market search through the media\u0000digitally online by utilizing various means such as social networks. The aim of this research is to increase knowledge and skills about digital marketing, especially social media, for Small and Medium Enterprises (SME) business people to increase their sales and profits. Digital marketing is the use of social media networks to carry out promotional activities and map digital markets. By using computers or other electronic equipment, digital marketing ideas can bring together geographically diverse parties. The aim of this research is to identify the most effective digital marketing tactics for the growth of MSMEs in Tegal City and Tegal Regency. The method used in this research is descriptive qualitative. With Data collection through observation, interviews, and secondary sources, such as books, journals, and articles, were used to collect information for this research. The results of this research show that the productivity growth of MSMEs in Tegal City and Tegal Regency has not been positive. Even when a website for an online business has been created, not everyone has implemented a digital marketing plan. It can be seen that digital marketing strategies have not received much attention from MSMEs in Tegal City and Tegal Regency. So it is hoped that MSMEs in Tegal City and Tegal Regency can adapt to changing times, namely selling online using digital marketing strategies.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"96 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140408710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating the Efficacy of Traditional Machine Learning Models in Speaker Recognition: A Comparative Study Using the LibriSpeech Dataset 评估传统机器学习模型在说话人识别中的功效：使用 LibriSpeech 数据集的比较研究

Brilliance: Research of Artificial Intelligence Pub Date : 2024-01-31 DOI: 10.47709/brilliance.v3i2.3488

Gregorius Airlangga

{"title":"Evaluating the Efficacy of Traditional Machine Learning Models in Speaker Recognition: A Comparative Study Using the LibriSpeech Dataset","authors":"Gregorius Airlangga","doi":"10.47709/brilliance.v3i2.3488","DOIUrl":"https://doi.org/10.47709/brilliance.v3i2.3488","url":null,"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.","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"81 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140478739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Utilization of Artificial Intelligence in Chatbot Development for New Student Admission Support at Cokroaminoto University Palopo 利用人工智能开发聊天机器人，为科克罗米诺托大学帕洛波分校新生入学提供支持

Brilliance: Research of Artificial Intelligence Pub Date : 2024-01-22 DOI: 10.47709/brilliance.v3i2.3389

Muhammad Akram Hamzah, Siaulhak Siaulhak, Iriansa Iriansa, Andi Jumardi, Andryanto Aman

引用次数: 0

Application of the Support Vector Machine (SVM) Algorithm for the Diagnosis of Diabetic Retinopathy 支持向量机 (SVM) 算法在糖尿病视网膜病变诊断中的应用

Brilliance: Research of Artificial Intelligence Pub Date : 2024-01-18 DOI: 10.47709/brilliance.v3i2.3436

Yuliadi Yuliadi, Fadhli Dzil Ikram, M. Julkarnain, Fahri Hamdan, Halid Nuryadi

引用次数: 0

Design and Implementation of the SALUTS System to Support of Improvement of Tourism Transactions and Promotion 设计和实施 SALUTS 系统，以支持改善旅游交易和促进工作

Brilliance: Research of Artificial Intelligence Pub Date : 2024-01-18 DOI: 10.47709/brilliance.v3i2.3434

Juniardi Akhir Putra, Halid Nuryadi, Yuliadi Yuliadi, Erwin Mardinata, C. Hudaya, Shinta Esabella, Ardiansyah Putra, Ahmad Juliansyah

引用次数: 0

Intelligent Control Techniques for Microgrid Systems 微电网系统智能控制技术

Brilliance: Research of Artificial Intelligence Pub Date : 2023-03-23 DOI: 10.47709/brilliance.v3i1.2192

M. Khaleel

引用次数: 7

Role of AI in Business Management 人工智能在企业管理中的作用

Brilliance: Research of Artificial Intelligence Pub Date : 2023-03-20 DOI: 10.47709/brilliance.v3i1.2191

Bimalendu Pendy

引用次数: 0

Early Warning System on Motorcycle Rider Helmets Using Gyrescope Sensors 基于陀螺仪传感器的摩托车头盔预警系统

Brilliance: Research of Artificial Intelligence Pub Date : 2023-03-13 DOI: 10.47709/brilliance.v3i1.2189

Khusnul Azima, Arifah Adani, H. Setiawan

引用次数: 0

Artificial Intelligence in Engineering 工程中的人工智能

Brilliance: Research of Artificial Intelligence Pub Date : 2023-03-13 DOI: 10.47709/brilliance.v3i1.2170

M. Khaleel, A. Ahmed, Abdulgader Alsharif

{"title":"Artificial Intelligence in Engineering","authors":"M. Khaleel, A. Ahmed, Abdulgader Alsharif","doi":"10.47709/brilliance.v3i1.2170","DOIUrl":"https://doi.org/10.47709/brilliance.v3i1.2170","url":null,"abstract":"Artificial intelligence (AI) has moved past its primitive stages and is now poised to revolutionize various fields, making it a disruptive technology. This technology is expected to completely transform traditional engineering in design, electrical, communication, and renewable energy approaches that have been human-centred. Despite being in its early stages, AI-powered engineering applications can work with vague design parameters and resolve intricate engineering problems that cannot be tackled using traditional design, electrical, communication, and renewable energy methods. This article aims to shed light on the current progress and future research trends in AI applications in engineering concepts, focusing on the ramp-up period of the last 5 years. Various methods such as machine learning, genetic algorithm, and fuzzy logic have been carefully evaluated from an engineering standpoint. AI-powered design studies have been reviewed and categorized for different design stages such as inspiration, idea and concept generation, evaluation, optimization, decision-making, and modeling. The review shows that there has been an increased interest in data-based design methods and explainable artificial intelligence in recent years. The use of AI methods in engineering applications has proven to be efficient, fast, accurate, and comprehensive, particularly with the use of deep learning methods and combinations that address situations where human capacity is inadequate. However, it is crucial to choose the appropriate AI method for an engineering problem to achieve successful results. \u0000 ","PeriodicalId":440433,"journal":{"name":"Brilliance: Research of Artificial Intelligence","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115893209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2