Classification of house buildings based on land size using the K-nearest neighbor algorithm

Novitasari, Melani; Yaddarabullah,; Permana, Silvester Dian Handy; Krishnasari, Erneza Dewi

doi:10.1063/5.0104960

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…Customers of tourist companies belonging to this category can quickly get information about the accessibility of hotels, local attractions, and restaurants, as well as the best routes to them. In addition, artificial intelligence can also be successfully applied to develop virtual tours of tourist attractions accessible to people with limited mobility or sensory impairments [17], [22]. Figure 1 shows the graphical dependence of the change in the dynamics of the volume of foreign tourists visiting the island of Bali for the period 2016-2021.…”

Section: Resultsmentioning

confidence: 99%

The growing use and impact of artificial intelligence technologies in the tourism industry

Indaryanto,

Harijadi,

Sinaga

2023

Sustainable Engineering and Innovation

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The research relevance is determined by the increasing role of artificial intelligence in the tourism business, which was demonstrated during the outbreak of the COVID-19 pandemic in Bali, resulting in a decline in the number of tourists visiting the island. The research aims to investigate the real-life experience of applying artificial intelligence systems in the tourism industry to address the challenges of developing the tourism industry in Bali, Indonesia. The basis of the methodological approach is a combination of theoretical methods of analysis and synthesis of the collected information covering the practical experience of the application of artificial intelligence systems in the tourism industry, as well as a survey of customers of travel agencies that have used such systems in trips to Bali. The research results show that artificial intelligence can significantly help the tourism business in Bali, as the number of tourists visiting the island dropped by 40% during the pandemic, resulting in a reduction in the number of tourism staff. The practical application of systems based on artificial intelligence opens up a wide range of business opportunities, as it allows for optimizing the activities of tourism firms and providing customers with high-quality services with highly technical equipment. The use of neural network mathematical models of tourist firms’ activity based on AI, allows them to achieve high speed of data processing, which allows tourist firms numerous competitive advantages and significantly improves the quality of their services. The practical significance of the results of this scientific research lies in the possibility of their application in the organization of the activities of enterprises in the sphere of tourism business, built on the use of digital technologies and systems based on artificial intelligence.

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Section: Resultsmentioning

confidence: 99%

The growing use and impact of artificial intelligence technologies in the tourism industry

Indaryanto,

Harijadi,

Sinaga

2023

Sustainable Engineering and Innovation

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“…k-NN classification is a well-known non-parametric classification approach that incorporates the simplest algorithm in problem solving and is capable of grouping items in a certain class based on similarities and differences [34]. k-NN classification utilizes the principle of locating the neighbors (k) and categorization based on similarity.…”

Section: Classification Using K-nnmentioning

confidence: 99%

“…The method for determine neighbors (k) using the RMSE. The RMSE calculates the average difference between the anticipated and actual values of a statistical model [34]. This is the standard deviation of the residuals in mathematics.…”

Section: Classification Using K-nnmentioning

confidence: 99%

Improving ventilation classification in under-actuated zones: a k-nearest neighbor and data preprocessing approach

Yaddarabullah,

Rahman,

Saad

2024

IJEECS

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This study investigates the use of k-nearest neighbors (k-NN) for classifying occupant positions in under-actuated zones, aiming to enhance ventilation control. The focus is on evaluating different data preprocessing techniques, particularly cumulative moving average (CMA), Kalman filtering (KF), and their combination, to boost the k-NN model's reliability and accuracy. The research uses received signal strength indicator (RSSI) data in a controlled setting. The methodology involves dividing the dataset into training and testing subsets and using root mean squared error (RMSE) to determine the best k value for model validation. The study performs a comparative analysis of the k-NN model's performance with both original and preprocessed RSSI data, focusing on metrics such as accuracy, precision, recall, F1-score, and RMSE. The findings emphasize the significant impact of the combined CMA-KF preprocessing technique in improving the model's accuracy and reliability. Specifically, this approach achieved an accuracy of 98.58%. The RMSE values are particularly noteworthy, exhibiting a perfect fit (RMSE of 0) for training data and a remarkably low RMSE of 0.119 for testing data, confirming the model's high accuracy and predictive capability.

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Land reform in the Republic of Kazakhstan: Problems of legal regulation of land relations

Ozenbayeva,

Kalymbek,

Yerkinbayeva

et al. 2024

Scientific Herald of Uzhhorod University Series Physics

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Relevance. The relevance of the study is due to the need to resolve problems in the agricultural sector, which consist in violations of current legislation and reducing the level of efficiency of the functioning of the segment under study. Purpose. The purpose of the study is to analyse the regulatory framework for the legislative regulation of land relations in the Republic of Kazakhstan. Methodology. Methods such as dogmatic, legal hermeneutics, logical analysis, deduction, induction were used. Results. In the course of the study, the legal framework and the relevant application practice were examined. In this regard, problematic aspects, shortcomings, and contradictions of the contained norms were identified. The importance of reforming the agrarian economy was noted, which consists in the organisation of cooperatives and joint-stock enterprises without the involvement of the state. It was identified that this necessity lies in the importance of a system of broad cooperation for the effective implementation of activities on combined land plots and individual means of production, increasing the productivity of agriculture, and rational use of land resources. It was noted that it is necessary to ensure the full exercise by agrarian organisations, citizens, and foreign persons of the right to land, establish the terms of transactions that will exclude the possibility of their embezzlement, irrational use, speculation, transfer to other categories. Conclusions. It was identified that it will be influential to create a special law and introduce norms into other acts, which will contain norms on a more detailed procedure for the targeted use of land, regulate monitoring and control, and features of limited turnover. The practical value of the results obtained lies in the development of recommendations, the implementation of which in law enforcement practice will provide an opportunity to increase the level of efficiency and quality of legislative regulation of land relations.

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Classification of house buildings based on land size using the K-nearest neighbor algorithm

Cited by 4 publications

References 9 publications

The growing use and impact of artificial intelligence technologies in the tourism industry

The growing use and impact of artificial intelligence technologies in the tourism industry

Improving ventilation classification in under-actuated zones: a k-nearest neighbor and data preprocessing approach

Land reform in the Republic of Kazakhstan: Problems of legal regulation of land relations

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