Universitas Semarang

This study examines Indonesia's national defense legal politics in the post-reform era in safeguarding national sovereignty amidst the dynamics of globalization and strategic environmental changes. Utilizing a normative political law research method with a legislative and historical approach, the study analyzes the direction and nature of defense policy through the review of the 1945 Constitution of the Republic of Indonesia (after the amendments), Law No. 3 of 2002 on National Defense, and various related regulations, including policies on budgeting, military force management, and defense sector reform. The findings show that post-reform defense legal politics seeks to assert civilian supremacy over the military, return the Indonesian National Armed Forces (TNI) to its primary defense function, and build a democratic, professional, and accountable defense system. However, policy implementation still faces various challenges, including weak synchronization of legislation, budget limitations and modernization of defense equipment, suboptimal parliamentary roles in legislation and oversight, and high corruption risks in the defense sector. This study recommends strengthening the defense regulatory framework, enhancing the capacity and integrity of the legislative and executive institutions, strengthening the national defense industry, and improving budget governance and transparency as prerequisites for realizing defense legal politics that can ensure national sovereignty and security in a sustainable manner.

This study aims to identify the most effective social media platforms for digital marketing. The use of social media for promotion continues to grow, yet many businesses still struggle to determine which platforms have the greatest impact. Therefore, this study compares the performance of various machine learning platforms to predict the best platform. The algorithms used are Gradient Boosting Regressor, XGBoost Regressor, Convolutional Neural Network (CNN), and Support Vector Regression (SVR) to estimate digital conversion potential based on user reviews, ad reach, and content trend patterns. A Knowledge Discovery in Databases (KDD) workflow is used to identify the most important key factors. This process includes data preprocessing, TF-IDF feature extraction, sentiment analysis, feature engineering, and feature elimination (RFE). The results showed that the CNN algorithm excelled in prediction, with the highest R² score of 0.74 and the lowest RMSE of 14.78. CNN predictions showed YouTube topping the list in terms of conversion potential, followed by Facebook and TikTok. These results highlight the higher promotional effectiveness of video-based platforms and the importance of machine learning in digital marketing decision-making. However, this study is limited by its reliance on static user review and ad reach data, which may not fully capture the dynamic changes of social media platforms.

Penelitian ini bertujuan menganalisis pengaruh kompetensi, kepuasan kerja, dan beban kerja terhadap kinerja pegawai dengan motivasi kerja sebagai variabel intervening pada Pengadilan Agama Semarang. Penelitian menggunakan pendekatan kuantitatif dengan desain eksplanatif dan teknik sensus terhadap 51 pegawai. Data dikumpulkan melalui kuesioner skala Likert lima poin dan dianalisis menggunakan Partial Least Squares–Structural Equation Modeling (PLS-SEM). Hasil penelitian menunjukkan bahwa kompetensi berpengaruh positif dan signifikan terhadap kinerja pegawai, sedangkan kepuasan kerja dan beban kerja tidak berpengaruh langsung. Motivasi kerja berpengaruh positif dan signifikan terhadap kinerja serta memediasi pengaruh kompetensi dan kepuasan kerja terhadap kinerja pegawai. Namun, motivasi kerja tidak memediasi pengaruh beban kerja terhadap kinerja. Model mampu menjelaskan 45,5% variasi kinerja pegawai. Temuan ini menegaskan bahwa peningkatan kinerja sektor publik lebih efektif dilakukan melalui penguatan kompetensi dan pengelolaan motivasi kerja dibandingkan hanya berfokus pada kepuasan atau beban kerja

This study aims to analyze unfair business competition practices and their resolution mechanisms in government procurement of goods and services in Indonesia using Lawrence M. Friedman's legal system theoretical framework. The study method used is normative legal research with a legislative, conceptual, and case study approach, which is analyzed qualitatively through a review of legislation, decisions of the Business Competition Supervisory Commission (KPPU), and relevant legal literature. Case studies were conducted by analyzing three KPPU decisions that represent patterns of tender collusion in procurement, namely the Revitalization of Taman Ismail Marzuki (TIM) Phase III case, the provision of clean water in North Lombok, and the construction of the Prabumulih Mall. The novelty of this research lies in the simultaneous integration of weaknesses in legal structure, legal substance, and legal culture to assess the effectiveness of antitrust law enforcement in the procurement sector. The results of the study show that the main obstacles to the enforcement of business competition law not only stem from regulatory loopholes and definitions of norms that are not yet operational, but are also influenced by institutional capacity constraints, weak inter-agency coordination, and a permissive culture towards collusion in procurement practices. This study emphasizes that strengthening the effectiveness of law enforcement requires practical measures such as refining the norms prohibiting collusion, integrating sanctions and a database of violations into the national e-procurement system, and strengthening the synergy between KPPU and LKPP through a post-decision monitoring mechanism to prevent repeat violations. The conclusion of the study states that regulatory reformulation, strengthening of supervisory institutions, and renewal of the culture of compliance are key prerequisites for the realization of transparent, fair, and accountable procurement governance.

The transformation of information technology in the modern era provides significant opportunities to improve the effectiveness of educational administration, particularly in the new student admission process. One form of implementation is a web-based registration system that can automate the online registration flow and minimize data recording errors. Pertiwi 14 Kindergarten currently still uses the conventional registration method through paper forms that require parents to be present in person at the school, potentially causing verification delays, information duplication, and data input errors. This study aims to design and build a web-based new student registration system using the Laravel framework with Laravel Filament support to display a dynamic interface and structured data management. The system development uses the Waterfall model through the stages of needs analysis, design, implementation, testing, and maintenance. Testing results using Black Box Testing show that all system functions run according to specifications without any errors and are able to reduce input errors by up to 100% compared to manual methods. In addition, the registration data verification process is faster with an increase in time efficiency of 70%. The implementation of this system makes a real contribution to improving ease of access, data accuracy, management transparency, and administrative efficiency in the new student admission process at Pertiwi 14 Kindergarten.