Village Government as a government entity at the local level has an important role in community development and empowerment. This research aims to conduct an in-depth analysis of the village government system in Indonesia with a focus on the organizational structure, policies and challenges faced. This study uses a qualitative descriptive research method by collecting data through interviews, observation and study of related documents. The results of the analysis show that the Village government system in Indonesia has various components, including the Village head, Village Consultative Body (BPD), and other Village officials. However, there are still several challenges that affect the effectiveness and efficiency of Village government. Factors such as limited resources, lack of access to information, and regulatory complexity are the main obstacles in carrying out the duties of the Village government. In addition, community involvement and the role of women in village decision making still need to be improved to ensure fair representation. This research also highlights the importance of improving central government policies related to Village funds and increasing human resource capacity at the Village level. Recommendations for improvement involve a holistic approach involving relevant parties, including the central government, regional government and local communities.

This legal research aims to investigate how absentee land regulations are implemented in relation to agricultural land ownership in Temanggung Regency. The main objective is, first, to understand how absentee land regulations are implemented in relation to agricultural land ownership in Temanggung Regency. Second, to identify the factors that cause absentee ownership and control of land in Temanggung Regency. This research is a type of empirical juridical legal research that is descriptive in nature. This research method uses primary data obtained through direct interviews with the Temanggung Land Office and people who own absentee land. The research results show that absentee ownership and control of land still occurs in Temanggung Regency due to less than optimal implementation of the authority of the Temanggung Land Office. This condition occurs because there are buying and selling transactions outside official mechanisms and a lack of clear records by the Temanggung Regency Land Office regarding land inheritance. Several factors that cause the emergence of absentee land control and ownership in Temanggung Regency include legal aspects, law enforcement, community participation, infrastructure and culture.

This research aims to explore the role of technology in developing the reading skills of class VIII students at SMPN 2 Bone. With rapid technological advances, education is experiencing a significant transformation, including in teaching and learning methods for reading. This study uses a qualitative approach with a case study method to understand the impact of using technology such as educational software, e-books, and interactive reading applications on students' reading abilities. Data was collected through classroom observations, interviews with teachers and students, and document analysis. The results showed that the use of technology significantly increased students' motivation and interest in reading, as well as improving their reading comprehension. Technology allows access to a variety of more interesting and interactive reading materials, which not only improve reading skills but also broaden students' horizons and knowledge. However, this research also found several challenges, such as limited technological infrastructure and the need for training for teachers to utilize technology effectively. In conclusion, technology has great potential in developing students' reading skills, as long as it is implemented with the right strategies and adequate support.

This research discusses the role of teachers in developing the spoken and written language of early childhood at RA Labschool IAIS Sambas.  Early childhood is an important period in language development. In this phase, children learn not only to speak verbally but also begin to recognize letters and numbers. The role of teachers in developing spoken and written language in early childhood is very vital. Teachers have the responsibility to create an environment that supports children's language development, both verbally and in writing. As a result of this research, researchers found that the role of teachers is very important in developing oral and written language skills in early childhood, including developing fine motor skills, understanding letter concepts, and the ability to compose words or sentences.

Islamic religious education is education that teaches the values of goodness which then its implementation is applied in life. Islamic education itself has an important role in the history of the development of the Indonesian nation, especially in terms of the historical dimension where Islamic education has been a formal education for centuries known as pesantren. The purpose of this study is to determine the relationship, the role of Islamic education in the national education system because to make a person who is balanced from an intellectual perspective, religious education is needed, namely Islamic education in order to achieve the goals of national education. The method used in this research uses qualitative research methods with the type of library research. Based on the research results, it can be concluded that Islamic education in the national education system is Islamic education occupying a position as a formal, non-formal, informal, and religious institution.
 
 

The aim of this research is to analyze and test the influence of CAR, NPL, BOPO on LDR PT. Bank Tabungan Negara Indonesia Tbk. This type of research is explanatory research. The sample used in this research was PT. Bank Mandiri (Persero) Tbk published its financial reports for the 2006-2013 period. Data collection techniques are library research and field research techniques. This research uses descriptive analysis, classical assumption tests and multiple linear regression for data analysis with the help of the Eviews 8 program. From the analysis test results it is known that the CAR, BOPO and NPL ratios have no influence on the LDR ratio during the 2006-2013 period.

Analysis of digital marketing in increasing brand awareness has been carried out very often. However, there has not been much analysis that specifically carries out marketing content analysis to increase brand awareness. This research aims to conduct content marketing analysis to increase brand awareness of skincare products. The research was conducted using a qualitative descriptive approach. Research data comes from the results of reviews of official publications and data searches in various digital databases. The research results show that there are several main content marketing strategies carried out by brands by paying attention to several factors, namely collaborating with influencer marketing through creative marketing campaigns, providing attractive discounts and promotions on certain dates in the form of flash sales, and giveaways to get audience engagement which ultimately resulting in increased sales. This is related to design factors, current events, reading experience, time and also the tone of the content marketing strategy carried out by skintific. Apart from that, Skintific also provides platforms on various social media as a reference source of information and increases marketing sales in various marketplaces such as Shopee, TikTok and Lazada. In this research, general strategies are explained so that for further research it is recommended to be more specific, for example a strategy by utilizing influencer marketing to produce a deeper understanding and be easier to understand

The increase in connected IoT devices causes increased vulnerability to cyber attacks. This research develops a hybrid machine learning model to detect real-time anomalies in IoT networks. This model combines the K-Nearest Neighbors (KNN) and Random Forest (RF) algorithms to increase accuracy and efficiency. Evaluation was carried out using the UNSW-NB15 dataset to test model performance. The results show that this hybrid approach is able to detect anomalies with high accuracy and a low false positive rate.

Hemoglobin (Hb) is an erythrocyte tetrameric protein that binds to non-protein molecules, namely the iron porphyrin compound called heme. Hb is one of the laboratory tests on pregnant women which can support the diagnosis or occurrence of complications in pregnant women, these complications can be detected through danger signs of pregnancy. Danger signs of pregnancy are signs that indicate dangers that can occur during pregnancy (antenatal), which if not detected can cause death. The aim of this community service is to facilitate Hb checks and to increase knowledge of pregnant women through education about the danger signs of pregnancy. The method of this activity is carried out by checking hemoglobin levels using the Sahli method and providing counseling using the discussion method to pregnant women about the danger signs of pregnancy and using the KIA book as the medium. This counseling was carried out at the Batursari Village Posyandu which was attended by 10 pregnant women. The results of the counseling showed that 8 pregnant women had normal Hb, 1 pregnant woman was in the mild anemia category, and 1 pregnant woman was in the severe anemia category. and after education regarding the danger signs of pregnancy, all pregnant women have good knowledge.

Data centers are major contributors to global energy consumption, with significant implications for operational costs and environmental sustainability. As energy demand increases, optimizing energy usage within these facilities has become essential. This study investigates the application of machine learning-based predictive analytics to enhance energy efficiency in data centers. By leveraging models such as Random Forest, Neural Networks, and Deep Learning, predictive analytics forecasts energy demands based on variables like temperature, workload, and time of day. Results from multiple case studies reveal that machine learning models can reduce energy consumption by up to 20%, offering a sustainable solution without compromising data center performance.