Satya Wacana Christian University

This study addresses anomaly detection in high dimensional time series data within the context of Artificial Intelligence (AI) driven software development, where modern systems generate large temporal data streams and reliable monitoring remains difficult due to noise, complexity, and limited labeled anomalies. The objective of this research is to develop an effective and scalable anomaly detection framework based on self supervised transformer models that can learn meaningful temporal representations without heavy reliance on manual annotation. The proposed method applies self supervised pretraining through masked sequence reconstruction and contrastive temporal learning on large scale, unlabeled multivariate time series datasets, followed by transformer based attention mechanisms to capture long range dependencies and compute anomaly scores. Experiments are conducted using benchmark datasets and real world system log data implemented with Python based deep learning tools and transformer architectures to evaluate detection performance. The results indicate that the proposed approach improves detection accuracy and reduces false positive rates compared to traditional statistical techniques and supervised deep learning models, particularly in high dimensional and low label settings. In conclusion, integrating self supervised learning with transformer architectures provides a robust and generalizable solution for time series anomaly detection, contributing to software analytics and monitoring systems by lowering labeling costs and improving adaptability across application domains.

The background of this study is based on the growing reliance of businesses on digital data driven by digital transformation, which demands higher standards of data security and transparency. The IoT and Blockchain are recognized as key technologies that can address these issues, yet empirical research exploring their combined roles remains limited. The objective of this research is to examine the role of the IoT in strengthening business data security, the role of Blockchain in enhancing data transparency, and the effect of integrating both technologies on business data management. This study adopts a quantitative approach, with data gathered through questionnaires distributed to business practitioners who have implemented digital technologies. The data were analyzed using descriptive statistical methods and simple inferential analysis to identify relationships among the research variables. The results show that the IoT positively influences business data security through real time monitoring, while Blockchain improves data transparency and integrity through its immutable recording mechanism. Moreover, the integration of the Internet of Things and Blockchain produces a stronger impact on data security and transparency compared to their individual use. The study concludes that the adoption and integration of the Internet of Things and Blockchain provide effective strategies for organizations to enhance business data security and transparency, while also fostering stakeholder trust and supporting business sustainability in the digital era.

Pertussis (whooping cough), a vaccine-preventable disease that affects people of any age, has resurged globally after the COVID-19 pandemic. Key reasons for recent pertussis outbreaks include suboptimal pertussis vaccination coverage (particularly for vaccination during pregnancy) and growing vaccination hesitancy. During the 2023–2024 pertussis outbreaks in Europe, adolescents aged 10–14 years and 15–19 years had the first and third highest incidence rates, respectively. To reduce pertussis burden, it is essential to strengthen vaccination programs in the indicated target groups. This requires increased awareness among healthcare professionals about the local epidemiology of pertussis and its clinical presentation, alongside reinforcement of the benefits of vaccination for disease prevention. In parallel, robust surveillance systems and strong public health capacity for early disease detection and response are crucial to effectively manage outbreaks and build resilience against future outbreaks. Infants remain at high risk for pertussis, with complications, hospitalisation, and death being more common than in other age groups. Immunisation programmes combining vaccination during pregnancy, to protect newborn infants until their primary immunisation series has induced immunity, and infant immunisation are key to reducing morbidity and mortality. Strategies to improve pertussis vaccination uptake among adolescents and adults, especially those with high-risk medical conditions, are also essential. Strengthening global collaborations to invest in and build surveillance systems capable of identifying and responding to future outbreaks, to align national policies, to scale up immunisation during pregnancy, and to adopt a life-long immunisation approach are needed to better control endemic pertussis and manage future outbreaks.

Developmental crisis episodes are common during emerging adulthood. Evidence from existing research suggests that existential concerns about life’s meaning are prominent during crisis episodes in emerging adulthood, but little quantitative research exists on this topic. The current cross-cultural study investigated the relationships between components of developmental crisis (measured using the 3-factor Developmental Crisis Questionnaire), and meaning in life (measured using the Meaning in Life Questionnaire, which has two factors: search for and presence of meaning in life). The sample comprised 1967 emerging adults across eight countries (Brazil, Czechia, Greece, India, Indonesia, Pakistan, Turkey and the United Kingdom). Two components of developmental crisis – being in transition/turning point and feeling disconnected/distressed – were positively associated with a search for meaning in life. Feeling disconnected/distress and lacking clarity/control were negatively associated with a presence of meaning in life. The findings emphasize the need for organizations and services that focus on supporting young adults in crisis, and that these should provide help with the often-hidden existential sense that life may be lacking meaning, and the corresponding endeavour to search for meaning.

Ibu tunggal yang hamil di luar nikah, seringkali mendapat tekanan emosional dan label yang buruk, serta mendapat diskriminasi dari masyarakat sehingga memengaruhi resiliensi diri. Penelitian ini bertujuan untuk mengetahui pengaruh pemaafan, kebermaknaan hidup dan resiliensi pada ibu tunggal yang hamil di luar nikah. Metode penelitian menggunakan pendekatan kuantitatif dengan desain analisis regresi berganda. Partisipan merupakan ibu tunggal yang hamil di luar nikah dengan rentang usia 18-30 tahun. Berjumlah 107 partisipan dengan menggunakan teknik insidental sampling. Pengukuran menggunakan Transgression-Related Interpersonal Motivation (TRIM-18) (α = 0,920), Meaning in Life Questionnaire (MLQ) (α = 0,856), Connor-Davidson Resilience Scale (CD RISC) (α = 0,925). Hasil dari penelitian membuktikan bahwa pemaafan dan kebermaknaan hidup berpengaruh terhadap resiliensi pada ibu tunggal yang hamil di luar nikah (F = 43,300 dan sig. = 0,000; p)