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Item Open Access ҚАЗІРГІ ЗАМАНДАҒЫ ЖАСӨСТПІРІМДЕРДІҢ ДЕВИАНТТЫ МІНЕЗ-ҚҰЛҚЫНЫҢ ҚАЛЫПТАСУЫ МЕН ҚЫЛМЫСТЫЛЫҒЫНА ИНТЕРНЕТТІҢ ӘСЕРІ(СДУ хабаршысы - 2020, 2020) Нұрқұс Б. ; Жұмағали А.Аңдатпа. Жасөспірімдердің қылмыстылық проблемасы әрдайым криминология үшін өзекті. Жасөспірімдердің қолымен жүзеге асып жатқан құқық бұзушылықтардың өз көрінісін табуы олардың әлеуметтік-құқықтық сипатын және себептерін кешенді криминологиялық зерттеуді талап етіп отыр. Сол себепті бұл мақалада кәмелетке толмағандардың қылмыстылығы, оның себептері, атап айтқанда интернеттің әсері, девиантты мінез-құлықтың қалыптасуына интернеттің әсері мәселелері қарастырылған.Item Open Access ИНФОГРАФИКА ПЕДАГОГИКАЛЫҚ ПРОЦЕСТЕ ҚОЛДАНЫЛАТЫН АҚПАРАТТЫ ВИЗУАЛИЗАЦИЯЛАУ ҚҰРАЛЫ РЕТІНДЕ(СДУ хабаршысы - 2021, 2021) А.Қ. Жакупова; М.C. ЖолшаеваАңдатпа. Қазіргі уақытта байланыс құралдары ақпаратты ауызша беруден көрнекі түрде көрсетуге ауысады, бұл жанама көрнекілікті жаңа жолмен қалыптастыруға және жеткізуге және оқу ортасын ұйымдастыруға мүмкіндік беретін визуализапияяның жаңа бағыттары мен технологияларының пайда болуына әкеледі. Оқу пропесінде компьютерлік және телекоммуникациялық технологияларды қолдану ақпаратты визуализациялау құралы ретінде инфографиканың дамуына жаңа серпін берді. Инфографикалық тапсырмалар студенттерді мұғалімнің қосымша қолдауынсыз қарым-қатынас дағдыларының барлық түрлерін қолдануға шабыттандырады. Мақалада қазіргі оқу үдерісіндегі инфографиканың қолданылу аясы, ақпаратты визуализациялаудағы әсері жайлы жан-жақты ашып көрсетуге тырыстық.Item Open Access USING THE GINI COEFFICIENT TO BUILD A CREDIT SCORING MODEL(СДУ хабаршысы - 2021, 2021) Sultanova N. ; Tulegenova A. ; Suleimen B.Abstract. The credit scoring model is widely used to predict the likelihood of a customer default. To measure the quality of such scoring models, you can use quantitative indicators such as the GINI index, KolmogorovSmirnov (KS) statistics, Lift, Mahalanobis distance, information statistics. This article discusses and illustrates the practical use of the GINI index.Item Open Access ARTIFICIAL AI IN TEST AUTOMATION: SOFTWARE TESTING OPPORTUNITIES WITH OPENAI TECHNOLOGY - CHATGPT(СДУ хабаршысы - 2023, 2023) Talasbek A.Abstract. One of the most important and significant stages of the software development life cycle is software testing. Automated testing reduces testing costs and increases productivity, resulting in a high-quality and stable end product. To ensure that software is bug-free and delivers the desired user experience, test automation is critical. As technology advances, test automation becomes more complex. However, advanced Al technologies will soon become commonplace thanks to powerful tools like ChatGPT that, among countless other things, can chat with you and teach you how to read and write code like a human. In this article, we will try to consider the possibilities of automation with chatgpt. Starting with writing test plans, and test scripts by using Python and Selenium WebDriver. How ChatGPT can improve our tasks and make them more feasible. By leveraging the capabilities of ChatGPT, software testing engineers can enhance their skills, improve testing capabilities, and achieve better quality and accuracy of test results. The opportunities presented by ChatGPT can lead to improved efficiency, productivity, and overall performance in the field of software testing engineering.Item Open Access ОБЗОР УГРОЗ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ В ПРЕДПРИЯТИИ(СДУ хабаршысы - 2020, 2020) Атымтаева Л. ; Баймуратов О. ; Хашимова Д.А.Аннотация. В данной статье представлены результаты анализа по выявлению групп угроз, специфичных для инфраструктуры и систем предприятии которое является одним из основных этапов в прогнозировании. Рассмотрены состояние информационной безопасности на предприятиях, проанализированы квалификации угроз безопасности и методов классификации, основанные на методах атак и на воздействии угроз. Оценены угрозы по безопасному использованию Интернета и взламыванию сайтов, краж данных, атакам фишинга и социальной инженерии; выявление угроз безопасности облачных вычислений, которые встречаются в интернет сетях предприятии. Изучены преимущества и недостатки Файрвол веб-приложений (WAF), который применяются для защиты атак, такие как DDoS-атаки, SQL-инъекции, межсайтовый скриптинг (XSS), и др. Представлены работы для обеспечения защиты с применением искусственного интеллекта и машинного обучения.Item Open Access COMPARATIVE ANALYSIS OF SORTING ALGORITHMS USED IN COMPETITIVE PROGRAMMING(СДУ хабаршысы - 2021, 2021) Mamatnabiyev Zh. ; Zhaparov M.Abstract. Sorting is one of the most used and fundamental operation in computer science since the first time it had been tried to arrange list of items in some sequence. A large number of sorting algorithms were designed in order to have best performance in terms of computational complexity, memory usage, stability, and methods. In addition, in algorithmic problem solving, not all algorithms have same efficiency. This paper makes comparison research and discusses four different types of sorting algorithms: bubble sort, quick sort, insertion sort, and merge sort. The algorithms are tested and compared for data usage and time spent for sorting given amount of data.Item Embargo The Art of Personalized Student-Supervisor Matchings(ADAL Kitap, 2025) Serek A.G.; Berlikozha B.A.The process of student-supervisor matching is a critical yet complex task in higher education institutions, directly influencing research productivity, student satisfaction, and workload distribution. The ability to assign students to the most suitable supervisors is essential for fostering strong academic relationships, optimizing institutional resources, and improving research outcomes. However, traditional manual assignment methods often lead to inefficiencies, subjective biases, and an imbalance in workload distribution. As a result, automated recommendation systems have emerged as a promising solution to enhance the efficiency and fairness of student-supervisor pairings. This study evaluates three recommendation algorithms—Singular Value Decomposition (SVD)-based collaborative filtering, graph-based matching using the Hungarian Algorithm, and machine learning via Random Forest Regression—to determine their effectiveness in optimizing student-supervisor assignments. A rigorous empirical analysis is conducted across five key performance metrics: accuracy, fairness, stability, scalability, and computational efficiency. The findings reveal that while collaborative filtering performs well with established datasets, it struggles with novel cases due to its dependence on prior interactions. The Hungarian Algorithm guarantees optimal matching but faces scalability challenges, particularly in large academic institutions with thousands of students and supervisors. Meanwhile, Random Forest Regression effectively captures complex compatibility patterns but requires extensive labeled data, limiting its applicability in cases where historical matching data is sparse or unavailable. To overcome these limitations, the study proposes an adaptive hybrid framework that integrates the strengths of all three approaches. The hybrid model leverages collaborative filtering’s ability to recognize patterns in existing data, the Hungarian Algorithm’s precision in optimal pairings, and the predictive power of machine learning. By combining these methodologies, the proposed system enhances match accuracy, ensures fair workload distribution, and remains computationally efficient for large-scale institutional implementation. Additionally, the framework introduces dynamic adaptation mechanisms that allow the system to update recommendations based on real-time changes in student preferences and supervisor availability, making it more practical for real-world applications. The research contribution is a comprehensive, empirically validated hybrid framework that improves student-supervisor matching by balancing accuracy, fairness, and efficiency. This study provides educational institutions with actionable guidelines for scalable and equitable assignment processes, ultimately contributing to more effective mentorship experiences, improved research collaborations, and enhanced academic outcomes.Item Open Access IMPLEMENTING COURSE SCHEDULE GENERATION APPLICATION FOR UNIVERSITY(СДУ хабаршысы - 2021, 2021) Zhuniskhanov M. ; Suliyev R.Abstract. This work is about researching and implementing Course Schedule Generation Application for university. She compares other similar applications in this area and explores important points. Through UML diagrams, important concepts and development progress are explained. Screenshots of using the application will also be provided. Dataset, configuration and rules explained. In the end, we will talk about the importance of such an application and facilitate planning for the university.Item Open Access HANDWRITTEN OPTICAL CHARACTER RECOGNITION: IMPLEMENTATION FOR KAZAKH LANGUAGE(СДУ хабаршысы - 2021, 2021) Kalken M.Abstract. Many documents, including as invoices, taxes, memoranda, and surveys, historical data, and test replies, still require handwriting with the transformation to digital information interchange. Handwritten text recognition (HTR), which is an automatic approach to decode records using a computer, is required in this aspect. For this proposal, I present a study of the implementation of optical recognition algorithms for handwritten text in the Kazakh language, using a recently collected database. The database, called the Kazakh Autonomous Handwritten Text Dataset (KOHTD), contains more than 140,335 segmented images of handwritten exam papers. As an algorithm, I used the proposed model by Harald Scheidl, which consists of several layers of neural networks and an CTC decoder. The trained model by putting an interval of Ir = 0.01 and a batch size of 60 showed effective results with indicators of about 85% accuracy.Item Open Access ФРАКТАЛЬНЫЙ МЕТОД ПРОЕКТИРОВАНИЯ ИНТЕЛЛЕКТУАЛЬНЫХ ИНФОРМАЦИОННЫХ CHCTEM(СДУ хабаршысы - 2021, 2021) Абдрахманов Р.Б. ; Рустамов Е.Н.В работе рассматривается — решение — задачи проектирования интеллектуальных информационных систем (ИИС). На концептуальном уровне предлагается техническая и алгоритмическая структура ИИС и логическая цепочка интеллектуализация связывающих ее частей. При этом констатируется, что главную часть ИИС составляет фрактальная база знаний (БЗ) и система ее управления. Формализируя понятия «данные» и ‹«информация» приводится аналитический вид понятие ‹знание». На основе продукционного знание первые вводится понятие «фрактальное знание». С целью создания фрактального базы знаний приводится алгоритм управления этими базами знаний. Процедура принятие решений строится на базе алгоритма вычисления оценок (АВО). На основе трех алгоритмических фракталов предлагается концепция проектирования ИИС с фрактальной базы знаний. Предполагается, что такой подход проектирование ИИС дает ей в определенном смысле универсальность. Целью обеспечения универсальности предлагаемого метода появляется — возможность инженерам проектировать ИИС без особых затруднений.