In this article, based on data mining technology, machine learning methods and cluster analysis, regularization of task identification is carried out, algorithms for numerically solving the inverse problem for a mathematical model for the spread of the socially significant disease human immunodeficiency virus in Kazakhstan are described. Data mining technology in modeling the situation with the human immunodeficiency virus is especially relevant, since it is on its basis that maps of the short-term incidence forecast in Kazakhstan and the regions of the country are compiled. The article discusses statistical data on the spread of the human immunodeficiency virus in Kazakhstan over the past 10 years (2010–2020). Information technologies, including Data mining technologies, allowed the authors to characterize the morbidity graph, identify risks, and test statistical predictors of morbidity. The main part of the article describes such indicators as an algorithm for numerically solving the inverse problem and building a mathematical model for the epidemiology of the human immunodeficiency virus by classifying regions into homogeneous groups. Data Mining classification methods were used to process the human immunodeficiency virus and analyze their status in the region. The forecast of the incidence of the population of Kazakhstan is carried out using the Statistica software package. An efficient algorithm for the numerical solution of the inverse problem for mathematical modeling will allow testing the developments on real data. 

Using Data Mining Technology in Monitoring and Modeling the Epidemiological Situation of the Human Immunodeficiency Virus in Kazakhstan

The article discusses the effectiveness, methods, and mathematical models of measures to control the spread of the human immunodeficiency virus (HIV) in Kazakhstan. Data were obtained for a 10-year period of the incidence of HIV infection, and a distribution schedule for the morbidity of the population was created and analyzed using the Statistica application software package. A model of HIV spread is considered taking into account the social adaptation of the population, a scheme of a probabilistic model is constructed, and a system of probabilistic differential equations is used. The current direction of the strategy for combating HIV infection is largely determined by a scientifically based system for assessing the epidemiological state of HIV infection using mathematical models that can determine the patterns of the epidemiological process with great confidence and predict the expected level of morbidity. Currently, according to scientists, there are about 150 different forecasting methods, but in practice, 15–20 types of methods are most often used. One of the methods used in the majority is expert assessment, extrapolation, mathematical modeling, and mixed forecasts. To date, the problem of HIV infection is one of the most important Kazakhstan consistently implements steps to curb the spread of HIV infection. The issues of combating HIV infection are included in the state program of healthcare development of the Republic of Kazakhstan for 2020-2025. 

Building a Model and Assessing the Level of Morbidity During the Epidemic

The article considers the effectiveness of methods of mathematical models and control over the spread of human immunodeficiency virus (HIV) in Kazakhstan. Data were obtained for a 10-year period of the incidence of HIV infection, a distribution schedule for the morbidity of the population was created and analyzed using the Statistica application software package. A model of HIV spread is considered taking into account the social adaptation of the population,a scheme of a probabilistic model is constructed and a system of probabilistic differential equations is used. The current direction of the strategy for combating HIV infection is largely determined by a scientifically based system for assessing the epidemiological state of HIV infection using mathematical models that can determine the patterns of the epidemiological process with great confidence and predict the expected level of morbidity. Currently, according to scientists, there are about 150 different forecasting methods, but in practice 15-20 types of these methods are most often used. One of the methods used in the majority are expert assessment, extrapolation, mathematical modeling, mixed forecasts. To date, the problem of HIV infection is one of the most important Kazakhstan consistently implements steps to curb the spread of HIV infection. The problems of combating HIV infection are included in the state program of healthcare development of the Republic of Kazakhstan for 2020-2025.

/pdf/building-a-model-and-assessing-the-level-of-morbidity-during-1e3loc1z.pdf

Building a model and assessing the level of morbidity during the epidemic

The article uses the main directions of development of mathematical modeling of control and spread of human immunodeficiency virus (HIV infection), dynamic and structural classification of the epidemic process. Statistical data on the West Kazakhstan region for the period 2010-2020 were taken from the regional center for the prevention and control of AIDS of the health department of the Akimat of the West Kazakhstan region, with a description of the spread of the virus, depending on the available data and tasks in the world and in the Republic of Kazakhstan, a retrospective, cluster analysis of HIV-infected people was carried out. The characteristics of the morbidity schedule are given, the risk is identified, statistical forecasts of morbidity are checked. In scientific and practical studies, the prevalence of criteria and observations of the epidemic was considered from the information technology side. Examples are given using a forecasting system and existing intelligent mathematical model systems. One of the important directions is the prediction of the consequences of the HIV epidemic, the study of immunological dynamics within one organism, the problem of predicting the development of the epidemic situation at the population level. Data Mining classification methods were used to process HIV-infected people and analyze the situation by age characteristics. The prognosis of the morbidity of the West Kazakhstan region by the age group of HIV-infected people over a 10-year period was carried out using the Statistica application software package.

The technology of intelligent analysis in predicting the epidemiological situation of hiv infection in the west kazakhstan region

Saat ini, komunikasi pemasaran ditandai dengan konsep percakapan multidimensi, dimana produk dapat menemukan suara mereka sendiri di ceruk pasar, bagi konsumen untuk merespons dari alam bawah sadar mereka. Digitalisasi telah secara drastis mengubah skema iklan yang mengarah pada investasi perusahaan yang lebih besar dalam iklan digital. Platform iklan digital menawarkan strategi pemasaran yang dapat menjangkau konsumen dari berbagai tempat sekaligus. Penelitian ini dilakukan untuk memahami pengembangan industri periklanan sebagai bagian dari komunikasi pemasaran di era digital dengan mengeksplorasi strategi periklanan McDonald yang menggunakan teknologi baru untuk mengoptimalkan upaya pemasaran baik secara global maupun dalam konteks lokal Indonesia. Data dalam penelitian ini diperoleh melalui tinjauan literatur artikel ilmiah dan sumber kredibel lainnya yang relevan. Hasil penelitian ini menunjukkan bahwa McDonald's menggunakan teknologi iklan digital terbaru seperti iklan online, AdWords/Adsense, signage digital, endorsement, crowdsourcing dan data mining untuk bertahan di pasar dan memenuhi preferensi konsumen. Praktik iklan multikanal McDonald’s telah terbukti efektif dan sukses. Hal ini ditunjukkan melalui peningkatan pendapatan dari outlet makanan cepat saji nomor satu dunia tersebut. Selain itu, praktik periklanan ini membuat McDonald’s tetap relevan dengan segmentasi konsumen lintas generasi serta meraih peningkatan popularitas.
 

 

Komunikasi pemasaran era digital: literature review terhadap strategi advertising multikanal mcdonald’s

With the rapid development of computer and other information technology and data storage technology, more and more data are stored. Data mining technology can process the data in advertising and marketing in a timely and effective manner to obtain potential and useful knowledge and information. As my country’s market economy system is becoming more and more complete, and science and technology continue to advance, TV advertising has become a major communication tool for economic activities, and the TV advertising industry is booming in our country. Based on the premise of advertising marketing and data mining theory and technology, this article applies data mining technology to all aspects of the advertising marketing process. This article is based on the initial data segmentation of advertising and marketing. First, it analyzes the shortcomings of the commonly used k-means algorithm and fuzzy average algorithm in the clustering effect, and then proposes a fuzzy average algorithm based on the modified membership function and analyzes its effectiveness. And on the basis of this algorithm, analyze its role in advertising and marketing. This thesis takes the basis of advertising marketing and the technology of data mining theory as the premise, and applies data mining technology to all aspects of the advertising marketing process, especially using data mining technology to analyze and study the program ratings and characteristics. The experimental research results show that through the above analysis of data mining technology and data mining advertising and marketing, we clearly realize that advertising and marketing after people’s location services are more than just finding the right people at the right time to push the most correct advertising and marketing services. The role of advertising and marketing based on Web data mining technology strengthens the interaction between users and enterprises.

The Role of Data Mining Technology in Advertising Marketing

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The Role of Data Mining Technology in Advertising Marketing