World epidemiological data states that primary dysmenorrhea occurs most frequently in women aged 17-24 years. Multinomial Logistic Regression (MLR) modeling is suitable to produce predictive models with the dependent variable (menstrual pain) consisting of four categories. The study aimed to analyze the predictive model of risk factors for menstrual pain among adolescent girls in Pekalongan City. The research design was an analytic survey with a cross sectional design. Samples totaled 100 with multistage random sampling at four school sites. The questionnaires used included NRS, PSS-10 and anthropometric measurements. Of the fourteen variables studied, three variables, namely female relatives who have a history of menstrual pain, the amount of sleep time and exercise habits, proved to significantly affect the incidence of menstrual pain in adolescent girls (p value <0.05). The Multinomial Logistic Regression model produced three logit equations. The Nagelkerke model showed that all risk factors studied (14 variables) simultaneously influenced the incidence of menstrual pain by 61.2% while the other 39.8% was influenced by variables not studied. The accuracy of the classification table with a prediction truth rate of 80.9% explained that female relatives who have a history of menstrual pain are 98.319 times more likely to have moderate menstrual pain compared to not having female relatives who have a history of menstrual pain. The predictive modeling has good accuracy.
The use of Artificial Intelligence (AI) and digital resources in developing sustainable English language teaching (ELT) materials is increasingly relevant in developing countries. Although various studies have discussed the integration of technology in education, there is still a gap in the use of AI and digital resources to create contextual and sustainable ELT materials. This research aims to examine the extent to which AI and digital resources assist English teachers in developing adaptive and sustainable ELT materials. This research employed a descriptive qualitative approach, employing in-depth interviews and field observations with 25 teachers across various regions in Indonesia. Data were analyzed thematically using NVivo 15 software to identify key patterns in material development practices. Research findings showed that AI and digital resources could accelerate the material creation process, adapt the level of difficulty to students’ abilities, and incorporate local cultural context into learning content. Teachers can also utilize AI to develop various materials for classroom practice. The research results also indicated that teachers had inadequate facilities and were incompetent in using the latest technology. Nevertheless, teachers are confident that they can maximally use AI to develop sustainable ELT materials. Therefore, the support from relevant stakeholders is needed through various constructive policies and training in using AI and digital resources for ELT materials development. Despite the obstacles faced, teachers are advised to optimally use AI and digital resources to develop quality ELT materials that meet the needs of the twenty-first century.
Penelitian ini bertujuan untuk mendeskripsikan bentuk kesalahan kontruksi sintaksis tataran kalimat pada caption Instagram batang.update. Sumber data penelitian ini adalah keslahan kontruksi sintaksis dalam caption Instagram batang.update yang mengandung tataran kalimat. Metode penelitian yang digunakan adalah metode deskriptif kualitatif, yaitu mendeskripsikan kesalahan kontruksi sintaksis pada caption Instagram batang.update. Teknik yang digunakan untuk mengumpulkan data kesalahan kontruksi sintaksi yaitu menggunakan Teknik baca dan catat. Kesalahan kontruksi sintaksis tataran kalimat meliputi lima kesalahan, yaitu: (1) Kalimat tidak bersubjek, (2) Kalimat tidak berpredikat, (3) Kalimat Ambiguitas,(4) Penggunaan konjungsi yang berlebihan, dan (5) Penggunaan istilah asing.
Globalization has accelerated regional integration and digital connectivity across ASEAN while simultaneously creating new opportunities for transnational criminal activities. As criminal networks increasingly operate through interconnected physical and digital infrastructures, conventional criminal justice systems face growing challenges in responding effectively across jurisdictions. This study aims to examine how globalization influences the evolution of transnational crime in ASEAN, how member states respond through legal and criminal justice mechanisms, and how institutional fragmentation affects the effectiveness of regional responses. The study employs a qualitative approach using document-based research and comparative criminological analysis of scholarly publications and international institutional reports. The findings reveal that globalization has transformed transnational crime into increasingly networked, adaptive, and technologically facilitated forms of criminality that transcend national boundaries. Although ASEAN member states have expanded criminalization frameworks, strengthened law enforcement capacities, and developed regional cooperation mechanisms, their effectiveness remains constrained by legal fragmentation, institutional disparities, technological asymmetries, and governance limitations. The originality of this study lies in its integrated analytical framework linking crime transformation, criminal justice responses, and regional governance within ASEAN. The study contributes to contemporary criminological scholarship by demonstrating how networked criminality and governance fragmentation collectively shape the challenges of combating transnational crime in an increasingly interconnected regional environment.
Penelitian ini bertujuan untuk mendeskripsikan rancangan inovasi media pembelajaran interaktif berupa storycard dalam pembelajaran menulis cerpen yang berorientasi pada pendekatan deep learning. Menulis cerpen merupakan keterampilan berbahasa yang kompleks karena melibatkan aspek kognitif, afektif, dan psikomotorik secara terpadu. Dalam konteks deep learning, menulis tidak sekadar memproduksi teks fiksi, tetapi juga menjadi sarana pengembangan imajinasi, pemaknaan personal, serta penciptaan karya yang reflektif dan mendalam. Media storycard dirancang sebagai kartu pembelajaran yang memuat unsur-unsur cerita seperti tokoh, latar, konflik, dan pesan moral yang dapat digunakan baik secara terstruktur maupun acak. Penelitian ini menggunakan metode kualitatif dengan pendekatan konseptual, di mana data diperoleh melalui studi literatur terhadap penelitian-penelitian terdahulu yang relevan. Hasil kajian menunjukkan bahwa storycard memiliki potensi dalam meningkatkan imajinasi serta keterampilan menulis cerpen siswa secara kreatif dan menyenangkan. Selain itu, media ini juga mampu menumbuhkan motivasi belajar, mengakomodasi perbedaan gaya belajar, serta mendukung proses pembelajaran yang aktif, reflektif, dan bermakna. Dengan demikian, storycard layak dipertimbangkan sebagai alternatif media inovatif dalam pembelajaran menulis cerpen berbasis deep learning.
