The objective of this community service initiative is to enhance the awareness and competencies of village officials in Ngunut Village regarding cyber security threats. Through counseling and mentoring sessions, participants were educated on the principles of cyber security, the categories of cyber attacks, and the preventive measures that can be implemented. Evaluation findings demonstrated a substantial enhancement in participants' knowledge and attitudes towards cybersecurity. It is anticipated that this initiative will serve as a model for other villages, contributing to the development of secure and sustainable communities in the digital era.

Purpose: The main objective of this research is to develop a fall detection system and improve rapid emergency response or early warning systems for falls in the elderly.
Methods: In this research, the waterfall method was used for image analysis to detect falls with high accuracy. We also used Raspberry Pi 3, and OpenCV3 to set up a server to receive fall detection alerts and forward them to email.
Results: This system integrated a camera mounted on a Raspberry Pi 3 to continuously monitor the area captured by the camera. In the fall detection system, the results of testing with data showed that the system accuracy was 72.22%, sensitivity 72.72%, and error 27.77%.
Novelty: The approach this research adopted can be used in a variety of settings, including home healthcare, elderly care facilities, or places that require safety monitoring. With this system, we hope to improve rapid response in emergency situations, thereby protecting and improving the quality of life for people in need.

This study aims to analyze the importance of professional laws and codes of ethics for members of the National Police of the Republic of Indonesia (Polri). The National Police professional code of ethics is a code of conduct that must be followed by every member of the National Police in carrying out their duties and responsibilities. This study examines the legal aspects that govern the code of ethics, as well as evaluating the challenges and its implementation in police practice. Data was collected through literature studies, analysis of laws and regulations, and in-depth interviews with members of the National Police. The results of the study show that effective enforcement of the code of ethics can strengthen integrity, professionalism, and public trust in the National Police. However, several challenges are still faced in the implementation of the code of ethics, such as the lack of socialization and strict supervision. This research provides recommendations to increase awareness and compliance of members of the National Police with the code of ethics, as well as strengthen its enforcement mechanism to strengthen.

Self-directedness is a crucial skill for prospective science teachers, and the Think-Pair-Project-Share (TP2S) model has shown promise in fostering collaboration and critical thinking. This aim study to investigates the effectiveness of TP2S in promoting self-directed learning among these future educators. This research aims to determine the effectiveness of the think-pair-project-share (TP2S) learning model in facilitating the self-directedness of prospective science teachers. This quantitative research uses a nonequivalent control group design. The population in this study were second semester students, while the research sample consisted of 72 students. The self-directedness data collection technique uses an instrument in the form of a scale. Based on the results of the paired sample T test, it can be seen that both experimental classes obtained a Sig value. (2-tailed) 0.000. It can be concluded that the paired sample T test value in the experimental class is 0.000<0.05 so that there is a significant difference in results between the pretest and posttest scores (H0 is rejected). It can be concluded that there is a difference in self-directedness between students who study human and environmental subjects using the think pair project share model and those who use the conventional model. It is known that the application of the TP2S learning model has an effect on the self-directedness of prospective science teachers. The implications of this research support and strengthen the results of theoretical studies that the TP2S learning model is a student-centered learning model that utilizes the ability to manage learning strategies independently.

Pandhalungan Local Wisdom is one of the courses offered by Muhammadiyah Jember University's Indonesian Language and Literature Education Study Program. Learning in this course has various challenges due to its newness, one of which is the lack of textbooks. This study aims to conduct a needs assessment of the textbooks for the course. The goals are to describe the competency criteria, student characteristics, student evaluation against the course, and subject matter suggestions for the course textbook. The results show that the characteristics of students are: 1) the average age of 20–21 years, which is classified as young adults; 2) knowledge of Pandhalungan: high category 50.11%, medium 32.33%, and low 17.56%; 3) perception of the benefits of course learning: very important 32.44%, quite important 52.22%, less important 15.34%; and 4) learning motivation: high 69.13%, medium 21.85%, low 9.02%. It is also concluded that the recommended subject matter for this textbook is eight topics: 1). Pandhalungan Culture and Identity; 2). Pandhalungan Cultural History.) Pandhalungan Art and Cultural Expression; 4) Pandhalungan Traditions and Rituals 5) Pandhalungan Cultural Diversity 6) Changes and Dynamics of Pandhalungan Culture 7) Preservation of Pandhalungan Culture; and 8) Culture and Communication of Pandhalungan Society

Climate change has become a global issue with significant impacts, especially in urban areas, with the Urban Heat Island (UHI) phenomenon being one of its catalysts. This research aims to analyze the effect of the Urban Heat Island phenomenon in Semarang City in 2024, triggered by population growth, urbanization, and land use changes. This research uses spatial analysis methods based on Google Earth Engine (GEE) and Landsat-8 satellite imagery to calculate surface temperature. The sampling technique uses the Purposive Sampling method. The population of this study consists of people residing or staying in the city of Semarang, and the samples are the Garnisun Field area representing South Semarang, the Tugu Muda area representing Central Semarang, and the Old Town area representing North Semarang. The research results show that the highest temperature was recorded in the Tugu Muda area, which was 37.3°C, followed by the Garnisun Field at 36.8°C and the Old Town at 36.4°C. The main factors contributing to the intensity of UHI include the conversion of vegetated land into built-up areas, emissions from motor vehicles, and the lack of green open spaces. The recommended mitigation measures are implementing environmentally friendly technologies such as green roofs, green walls, and high-albedo materials, as well as expanding green spaces in residential and commercial areas.

UPTD Puskesmas Subah adalah salah satu puskesmas yang ada di jajaran Dinas Kesehatan Kabupaten Batang yang selalu berkembang seiring kondisi dan dinamika masyarakat dengan upaya keras untuk menyediakan pelayanan kesehatan yang bermutu, merata dan terjangkau. Seiring perkembangan teknologi yang cepat dan informasi yang dibutuhkan sangat penting, sebab harus dapat diakses dimana saja. Salah satu fasilitas pelayanan kesehatan di UPTD Puskesmas Subah Batang menyelenggarakan pelayanan kesehatan kepada masyarakat, salah satu kegiatannya yaitu pendaftaran pasien yang berfungsi sebagai menerima kunjungan pasien untuk berobat rawat jalan. Selama ini Puskesmas Subah melakukan pelayanan pendaftaran pasien rawat jalan dilakukan bersamaan dengan pendaftaran pasien baru langsung ditempat loket, sehingga terkadang para pasien harus sabar menunggu giliran dan antri untuk mendapat pelayanan masing-masing. Solusi untuk permasalahan tersebut dengan dibuatnya sistem informasi pendaftaran pasien rawat jalan berbasis web dengan menggunakan metode hot-fit. Dengan adanya sistem ini memudahkan pasien dalam proses pendaftaran, memudahkan petugas dalam hal pencatatan dan juga sistem berbasis web memberikan informasi yang cepat dan akurat tanpa mengenal tempat dan waktu.

Kejadian malaria khususnya yang disebabkan oleh plasmodium falciparum pada remaja khususnya di Papua mengalami peningkatan dengan salah satu faktor pengetahuan, sikap dan perilaku dalam mencegah penyakit ini. Penelitian ini menggunakan pendekatan korelasi analitik pada 61 responden yang diperoleh dengan teknik purposive sampling. Pengambilan data menggunakan kuesioner yang hasilnya dianalisis secara bivariat menggunakan Uji Korelasi Spearman. Berdasarkan hasil penelitian diperoleh bahwa ada hubungan antara pengetahuan dengan sikap pencegahan malaria tropika dengan tingkat yang cukup kuat serta berkorelasi secara positif. Hal ini dibuktikan dengan tingkat pengetahuan remaja dalam kategori kurang yang korelasinya sejalan dengan sikap negatif dalam mencegah malaria tropika. Hasil penelitian ini dapat digunakan sebagai lanjutan untuk penelitian selanjutnya, yang menemukan perilaku atau faktor yang berkaitan dengan pencegahan malaria tropika khususnya pada remaja.

Estimating the effort, time, and cost needed to build a software project is an important task in software engineering. Estimating software prior to development can help to reduce risk and improve the project success rate. Researchers have developed numerous traditional and machine learning models to estimate software effort, but it has always been difficult to estimate effort precisely. This paper presents a predictive model based on artificial neural networks namely ANNs to predict the software effort. The NASA dataset is applied to construct the proposed model. The system was trained using 50 data points, and the remaining 10 were used for testing. It was concluded that the ANN approach could estimate the software effort with high accuracy. A comparative study with other published equations was also performed, and it was found that ANN had less error and produced better results than other existing methods.

This research aims to increase efficiency in monitoring student attendance at Madrasah I'dadiyah Salafiyah Syafi'iyah by utilizing the K-Means Clustering analysis method. Monitoring student attendance is still carried out conventionally, so it often takes time and is less effective in identifying overall student attendance patterns. For this reason, in this research, student attendance data collected from the madrasa attendance system was analyzed using K-Means Clustering, a machine learning technique that can group students based on their attendance patterns. This process produces several groups which make it easier for the madrasah to identify students who frequently attend, rarely attend, or frequently do not attend. In this way, madrasas can take more appropriate steps in dealing with attendance problems, such as paying special attention to students who are often absent. The results of this research indicate that the application of K-Means Clustering can increase the efficiency of attendance monitoring and provide a stronger basis for decision making to improve the attendance system at the I'dadiyah Salafiyah Syafi'iyah madrasah.