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Mental health among university students has become a critical concern in higher education, particulary as students are required to cope with increasing academic demands, social pressures,and the growing complexity of campus life. At this stage, students are in an early transitional period that requires them to adapt to various changes, both academically and psychosocially. Under thes circumstances, psychological factor play a significant role in helping student maintain mental balance, one of which is emotional intelligence. This study aims to explore and understand the relationship between emotional intelligence and students’ mental health through a literature review approach. The method employed in this study is a qualitative descriptive literature review of 18 national and international scholarly articles published between 2021 and 2025, focusing on topics related to emotional intelligence, academic stress, emotion regulation, and student mental health. The findings indicate that emotional intelligence demonstrates a strong and consistent association with various aspects of students’ mental health, including levels of academic stress, anxiety, depression, academic, burnout, resilience, adjustment abilities, and psychological well being. Students with higher levels of emotional intelligence tend to be more capable of recognizing and understanding their emotions,as well as managing them adaptively when facing academic and social pressures. These abilities contribute to reducing the risk of excessive psychological distress. Furthermore, emotional intelligence functions as a protective factor that support the development of effective coping strategies and healty interpersonal relationship. Therefore, fostering emotional intelligence, through promotive and preventive programs within higher education instituions has the potential to become a strategic effort in enhacing and sustaining students’mental health over the long term.

The study aims to determine: 1) The influence of numerical intelligence and learning motivation together on the mathematical problem solving ability of class XII TKJ students of SMK Negeri 1 Sukaluyu Cianjur. 2) The influence of numerical intelligence on the mathematical problem solving ability of class XII TKJ students of SMK Negeri 1 Sukaluyu Cianjur. 3) The influence of learning motivation on the mathematical problem solving ability of class XII TKJ students of SMK Negeri 1 Sukaluyu Cianjur. The study was conducted using a survey method. The population was class XII TKJ students of SMK Negeri 1 Sukaluyu Cianjur with a sample size of 85 students. The sampling technique used was random sampling. The research instruments used were essay-based mathematical problem solving ability tests, multiple-choice numerical intelligence instruments, and Likert-scale learning motivation instruments. Data analysis using multiple linear regression analysis. The results of the hypothesis testing obtained the following conclusions: 1) There is a significant influence of numerical intelligence and learning motivation together on mathematical problem solving ability, this is evidenced by Sig. 0.000 < 0.05 and Fcount > Ftable, which is 3.57 > 3.12. 2) There is a significant influence of numerical intelligence on mathematical problem solving ability, this is proven by Sig. 0.000 < 0.05 and tcount > ttable, which is 5.7 > 2.00. 3) There is a significant influence of learning motivation on mathematical problem solving ability, this is proven by Sig. 0.000 < 0.05 and tcount > ttable, which is 5.7 > 2.00. The results of this study are useful for improving the quality of learning and improving mathematical problem solving ability at the vocational high school level.

Digital era has brought about the widest and unprecedented generational gap between parents and senior leaders on the one side and the next generation on the other. Raising and, more importantly, multiplying leaders in this era requires contextual intelligence. Seniors must apply this crucial intelligent skill in choosing their content, in the way they communicate and in how they form communities. In post-pandemic era, its urgency only increases, hence needs optimizing.

This study aims to determine the effect of emotional intelligence on student learning outcomes in class X mathematics at Muhammadiyah Maumere Private High School. The population of this study were students of class X IPA I and IPA 2, totaling 39 students. The sample in this study consisted of 39 students. Data collection was carried out by distributing questionnaires related to emotional intelligence on the results of learning mathematics in class X SMA Muhammadiyah Maumere Private High School Based on the results of the analysis with a significant level of 5%, it can be concluded (1) There is a significant effect of emotional intelligence for the experimental class on mathematics learning outcomes (2) There is an insignificant effect of emotional intelligence for the control class on mathematics learning outcomes for Muhammadiyah Maumere Private High School students.

Computer intelligence, particularly Artificial Intelligence (AI), has become a cornerstone in advancing bioinformatics. This study aims to explore the role of AI in addressing the challenges of analyzing complex biological data, especially in genomics, proteomics, and metabolomics. Using machine learning (ML) and deep learning (DL) algorithms, AI efficiently processes large-scale data, accelerates genomic research, predicts protein structures, and identifies disease biomarkers. However, challenges such as data quality, computational limitations, and privacy issues remain barriers to its implementation. The findings of this study highlight the importance of continuous innovation, multidisciplinary collaboration, and strict regulations in AI applications. In conclusion, AI holds great potential to revolutionize bioinformatics, significantly impacting scientific research and the development of global healthcare systems.

In recent decades, artificial intelligence (AI) has significantly advanced and shown great potential across various fields, including bioinformatics. This paper examines current trends in AI applications within bioinformatics, highlighting future potentials and the challenges of integrating these technologies. The research utilizes secondary data collection from scientific literature, books, conference reports, and official documents on AI and bioinformatics, sourced from reputable databases like Scopus, IEEE, PubMed, and Google Scholar. Through comparative analysis, similarities, differences, and technological advancements were identified and discussed. Descriptive narrative interpretation was employed to provide a holistic view of AI trends and potential in bioinformatics. Key findings indicate that AI, particularly machine learning and deep learning, is instrumental in genomic data analysis, protein structure prediction, drug discovery, and clinical bioinformatics. Furthermore, the study underscores the benefits of AI in enhancing data analysis accuracy and efficiency, while addressing ethical and technical challenges. Future prospects emphasize the importance of interdisciplinary collaboration to fully leverage AI's capabilities in bioinformatics.

Di era digital saat ini, kemajuan teknologi informasi mengalami pertumbuhan yang pesat. Salah satu perkembangan yang signifikan terjadi dalam bidang kecerdasan buatan (Artificial Intelligence), yang telah diterapkan luas di berbagai sektor, termasuk analisis data dan pengambilan keputusan. Para peneliti di bidang data mining telah menciptakan beragam algoritma klasifikasi yang meningkatkan proses klasifikasi dengan memanfaatkan atribut numerik dan nominal. Klasifikasi adalah suatu proses analisis data yang menghasilkan model untuk mewakili kelas-kelas dalam data tersebut, seperti yang terjadi pada Decision Tree yang digunakan untuk menganalisis klasifikasi dan pola prediksi data serta menggambarkan hubungan antara variabel atribut  dan variabel target  dalam bentuk struktur pohon. Python, sebagai bahasa pemrograman populer dalam pengembangan kecerdasan buatan, menyediakan pustaka dan framework yang mendukung implementasi algoritma Decision Tree. Dengan menerapkan algoritma Decision Tree untuk klasifikasi data evaluasi mobil menggunakan Python, kita dapat memanfaatkan kekuatan AI untuk memberikan solusi efektif dan efisien dalam pengambilan keputusan terkait evaluasi mobil. Menggunakan dataset Evaluation Car dari UC Irvine Machine Learning Repository, hasil penelitian menunjukkan akurasi sebesar 81%. Confusion Matrix dan laporan klasifikasi menunjukkan performa model yang baik dalam melakukan prediksi.

The aim of this research is to determine the effect of the Chain Whisper Game on the Linguistic Verbal Intelligence Ability of Children Aged 5-6 Years at Pelangi Kasih Siborongborong Kindergarten. The method used in this research is a descriptive quantitative research method. The population was all children aged 5-6 years at Pelangi Kasih Siborongborong Kindergarten, totaling 54 people and a sample of 28 people was determined using a purposive sampling technique. Data was collected using a 25-item positive closed questionnaire. The results of data analysis show that there is a positive and significant influence of the Chain Whisper Game on the Linguistic Verbal Intelligence Ability of Children Aged 5-6 Years at Pelangi Kasih Siborongborong Kindergarten: 1) Test the analysis requirements: a) positive relationship test obtained by the value rxy = 0.532 > rtable (=0.05,n=28) = 0.374, thus it is known that there is a positive relationship between variable n-2=26)= 2.056, thus there is a significant relationship between variable = "18.54"+0.44X. Thus Ha is accepted and H0 is rejected.

Lajunya perkembangan zaman tidak dapat disangkal telah mendorong manusia untuk terus berinovasi dalam mengembangkan beragam teknologi, termasuk kecerdasan buatan atau Artificial Intelegence (AI). Sejauh perkembangannya  AI telah membawa dampak positif yang cukup signifikan dalam memudahkan berbagai aspek kehidupan manusia, mulai dari otomatisasi proses bisnis hingga munculnya alat pengenal wajah (face recognition) yang canggih. Namun, dampak positif ini juga disertai dengan adanya potensi dampak negatif yang harus diperhatikan. Persoalan ini memiliki hubungan yang erat dengan Hukum dan Hak Asasi Manusia (HAM). Sebagaimana eksistensi manusia, terutama dalam hal privasi dan keamanan data, menjadi semakin gampang diakses dan sangat berpotensi untuk disalahgunakan. Munculnya tantangan baru dalam dimensi hukum dan HAM menjadi suatu kebutuhan mendesak dalam menghadapi era teknologi AI yang terus berkembang secara pesat. Penelitian ini bertujuan untuk menganalisis bagaimana teknologi AI mampu memengaruhi berbagai aspek HAM, termasuk privasi, kebebasan individu, dan perlakuan non-diskriminasi. Oleh karena itu, sangat penting untuk memastikan bahwa penggunaan teknologi AI seperti face recognition ini dipandu oleh regulasi hukum yang jelas. Prosedur yang adil, dan kebijakan pemerintah yang sesuai dengan prinsip-prinsip HAM merupakan kunci untuk menjaga keseimbangan antara inovasi teknologi dan perlindungan terhadak hak-hak setiap individu.

This study aims to find out: (1)Effect Of Emotional Intelligence on Organisational Culture On The Nurse Nurse Performance(Study on Emergency on nurse performance (Study on emergency room and Intensive Care nurse of Benyamin Guluh hospital/kolaka SMS Berjaya BLUD). (2) Effect of Organizational Culture on Nurse Performance (Study on Emergency room and  Intensive Care Unit nurses of Benyamin Guluh Hospital/Kolaka SMS Berjaya BLUD). This study uses an approach with quantitative methods.Data collection in this study through observation, literature study and questionnaires. The population of this study ware all emergency room and intensive care unit nurses at Benyamin Guluh Hospital/Kolaka SMS Berjaya BLUD. While the sampel of this study amounted to 30 nurses with the determination of the sample using purpositive sampling with hair formula. Testing of research instruments using validity tests and reliability tests with SPSS 25.0. The data analysis technique used in this research is Structural Equation Modeling (SEM) based on Partial Least Square (PLS) through measurement model test (outer model) and structural model testing (inner model) with Smart PLS 3.0.Based on the results of the study, it is known that the Emotional Intelligence variable has a positive and significant effect on Nurse Performance as indicated by the P-Values value of 0.005.And the Organizational Culture variable also has a positive and significant effect on Nurse Performance, this is indicated by the P-Values value of 0.037.

Background: Jobs related to hospitals or health are often exposed to high work stress, namely nurses. Nurses who experience work stress show negative emotional responses. The negative impact of increased work stress and low emotional intelligence on nurses has an impact on the quality of health services. Therefore, when a nurse is exposed to work stress and low emotional intelligence, her performance in providing nursing services will decrease, which in turn will get complaints from patients. Prolonged job stress can contribute to nurse burnout, increased dropout rates, and decreased job satisfaction. In the long term, this can affect nurse retention and reduce the availability and quality of the nursing workforce. Methods: Quantitative research with a correlational type of research using Cross Sectional. Sampling using the Total Sampling approach totaling 46 nurses. Data analysis using Univariate Analysis and Bivariate Analysis. Results: 1) 56.52% emotional intelligence in nurses at Dr. Hospital. Bratanata Kota Jambi is categorized as low and 43.48% is categorized as high; 2) 54.35% work stress on nurses at Dr. Hospital. Bratanata Kota Jambi is categorized as high and 45.65% is categorized as low; 3) There is a relationship between emotional intelligence and work stress on nurses in the inpatient rooms of Akasia, Cemara and Cendana at Dr. Hospital. Bratanata Jambi City in 2022 with a Spearman correlation value of -0.869. That is, high emotional intelligence, the work stress experienced by nurses will be low. Conclusion: There is a relationship between emotional intelligence and work stress of nurses in the Inpatient Room of Akasia, Cemara and Cendana Dr. Jambi City Bratanata Hospital. It is hoped that the hospital can provide various programs for nurses not to experience high stress, and can increase the emotional intelligence of nurses to reduce work stress with training for nurses such as Gathering which can reduce nurse work stress.

Financial intelligence is an individual's ability to understand, manage, and optimize the management of personal finances. Financial mathematics is becoming an important tool in developing financial intelligence. In this research using literature study method this method involves the search and collection of information from related literature sources. Through financial mathematics, one can calculate the future value of an investment, estimate the return on an investment, calculate annuity payments, understand the concept of time value of money, and analyze investment risk. The application of financial mathematics in financial intelligence provides an advantage in taking better financial decisions and managing finances effectively. By utilizing financial mathematics, one can improve their understanding of Finance, make effective financial planning, and take better financial decisions.

The purpose of this study was to examine the effect of emotional intelligence and learning interest on the level of understanding of accounting. This study uses primary data which includes questions in the form of a questionnaire that is measured using a Likert scale. The research sample is 133 students who had completed introductory accounting courses. The results showed that emotional intelligence had an effect of 64,4% on students understanding of accounting and learning interest had an effect of 72,2% on students understanding of accounting, simultaneously emotional intelligence and student learning interest had a positive and significant impact on the level of accounting of faculty students economics study program of management and accounting at Pasim National University.    

The purpose of this study was to determine the influence of emotional intelligence on consumptive behavior in users of the TikTok Shop application. One psychological factor, namely emotional, also influences financial decisions and financial markets. Someone who has not been able to maximize and control himself is less able to be wise in spending money. The method used in this study is a quantitative method using a non-experimental design. The data collection technique was by distributing questionnaires, namely the emotional intelligence scale consisting of 14 items and the consumer behavior scale consisting of 27 items. The scale is presented using a Likert scale in intervals of 1-5. In this research data analysis technique uses simple regression analysis with the help of SPSS software. The subjects in this study were users of the TikTok Shop application with an age range of 17-40 years. The data obtained from the results of distributing questionnaires to the subjects is that there is no significant influence between the influence of emotional intelligence on consumptive behavior in users of the TikTok Shop application with a sig value. 0.147<0.05. So the results of this study show that there is no influence between emotional intelligence on the consumptive behavior of users of the TikTok Shop application.