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This research aims to design and build a letter archive information system at the KOFIPINDO Law Office to improve the effectiveness and efficiency of document management. The manual filing system that has been used so far poses various obstacles, such as search delays, the risk of losing documents, and low storage accuracy. To overcome these problems, this study applies the Waterfall System Development Life Cycle (SDLC) model in the process of designing and building the system. Web-based technologies used include PHP, HTML, CSS, Bootstrap, and MySQL. The results of the study show that the developed letter archive information system is able to simplify the process of storing, searching, and managing incoming and outgoing letters in a faster, structured, and safer manner. The implementation of this system not only improves administrative performance, but also strengthens accountability and supports the need for professional legal documentation within the KOFIPINDO Law Office. Thus, this web-based mail archive information system can be a strategic solution in modernizing legal document management.

Information system security faces serious challenges due to increasingly complex cyber attacks. Intrusion Detection Systems (IDS) require efficient approaches to handle high-dimensional data such as the NSL-KDD dataset with 41 features. This study aims to implement the Genetic Algorithm (GA) for feature selection on the NSL-KDD dataset to improve the efficiency and accuracy of network attack detection. The method used is computational experimental research, involving data preprocessing, GA implementation for feature selection, building a classification model using Random Forest, and performance evaluation based on accuracy, precision, recall, F1-score, and computation time. The results show that GA successfully reduced features from 41 to 12 features (70.7% reduction), significantly improving computational efficiency. However, model accuracy slightly decreased from 0.4973 to 0.4951, indicating that while GA is effective for feature selection, the elimination of certain features may reduce classification capability. The implication of this study is that GA can be used as a tool to simplify intrusion detection models, but it should be combined with parameter optimization and data imbalance handling to achieve more optimal performance.  

Chronic kidney disease is an increasingly prevalent health issue that requires more precise clinical data-based early detection methods to enable timely and appropriate treatment. This study focuses on developing a predictive model for chronic kidney disease using the Light Gradient Boosting Machine (LightGBM) algorithm and enhancing its performance through hyperparameter optimization with the Grey Wolf Optimizer (GWO). The dataset used originates from public sources and undergoes several preprocessing steps, including missing value imputation, categorical feature encoding, outlier handling, initial feature selection, and stratified data splitting to maintain model quality. Three modeling approaches were evaluated: LightGBM with default parameters, LightGBM enhanced using Random Search, and LightGBM optimized with GWO. The experimental results indicate that the baseline model already performs well, Random Search improves accuracy and F1-score, and GWO achieves the highest AUC-ROC value despite requiring longer computation time. Significance testing through cross-validation shows that the performance differences among the three models are not statistically significant, suggesting that the observed improvements are not strong enough to determine a definitively superior optimization method. The feature importance analysis highlights that clinical indicators such as creatinine levels, glomerular filtration rate, blood pressure, and urine protein contribute most prominently to the prediction. Overall, the study demonstrates that LightGBM is a reliable model for early detection of chronic kidney disease, and hyperparameter optimization still offers added value that can support the development of AI-based clinical decision-support systems

Accurate wind turbine power curve modeling plays a crucial role in performance evaluation, energy yield estimation, and data-driven control strategies. However, actual power curves often exhibit non-linear behavior influenced by atmospheric variability, measurement noise, and SCADA anomalies, making conventional modeling approaches less effective. This study proposes an optimized logistic power curve model whose parameters are tuned using Particle Swarm Optimization (PSO) to improve predictive accuracy. The analysis uses the Wind Turbine SCADA Dataset from Kaggle, which undergoes extensive preprocessing including physical rule filtering, outlier detection with the Interquartile Range (IQR) method, anomaly removal, and smoothing of the power signal. A three-parameter logistic model is selected due to its ability to capture the typical S-shaped relationship between wind speed and power output. PSO is applied to identify optimal model parameters by minimizing the Mean Squared Error (MSE), utilizing 40 particles over 200 iterations. The optimized model achieves strong predictive performance with RMSE of 404.09, MAE of 179.96, and R² of 0.904 on the test set, indicating that more than 90% of the variability in actual power can be explained by wind speed. Residual analysis reveals heteroscedastic patterns and slight overestimation in mid-range wind speeds, yet overall model consistency remains high. Comparative evaluation against Linear Regression, Random Forest, and logistic modeling using curve_fit shows that the Logistic–PSO approach provides the most accurate and stable predictions. These findings demonstrate that combining logistic modeling with PSO offers an effective and robust method for data-driven wind turbine power curve optimization.

Investments in information technology (IT) often fail to deliver the expected added value due to excessive dependence on external suppliers, inflexible technological systems, or infrastructures that are highly vulnerable to various operational and security risks. This article analyzes organizational strategies to ensure the realization of added value from IT investments through the integration of strategic alignment and comprehensive risk management practices. By implementing strategic alignment, organizations are able to synchronize IT initiatives with core business objectives, organizational processes, and long-term strategic goals. At the same time, effective risk management plays a crucial role in reducing detrimental dependencies, including risks related to data breaches, system failures, cyber threats, and operational disruptions. This approach is supported by an extensive review of literature from credible and relevant academic sources, which demonstrates that systematic risk mitigation can significantly enhance organizational resilience, reliability, and overall value creation from IT investments. As a result, organizations are better positioned to optimize performance, improve decision-making capabilities, and ultimately achieve a sustainable competitive advantage in an increasingly digital business environment.

The exchange of information in the digital era has become a general need for society. However, the information sent often has a public or confidential nature. Therefore, security is needed so that confidential information remains safe. Cryptography is a field of knowledge used to secure information using encryption and decryption processes. One of the cryptographic methods used is the permutation method, which changes the layout, sequence, or structure of data into a form that is difficult to understand without knowledge of the exact key. Implementing cryptography using the permutation method in Android-based applications can increase the security and privacy of user data, as well as protect sensitive information from unauthorized access. This research aims to implement permutation method cryptography in Android-based applications to protect the confidentiality or privacy of user data. By using the permutation method, the sequence of bits or characters in the data is scrambled so that it is difficult for unauthorized parties to understand. The research results show that the implementation of permutation method cryptography in Android applications can provide a higher level of security in maintaining data confidentiality. However, it is worth considering that simple permutation methods may not be secure enough to deal with more sophisticated attacks. Therefore, choosing a stronger cryptographic method needs to be considered to achieve a higher level of security. In conclusion, implementing cryptography using the permutation method in Android-based applications can increase the security and privacy of user data. The permutation method is able to randomize the sequence of bits or characters in the data so that it is difficult for unauthorized parties to understand. However, for a higher level of security, it is necessary to consider stronger cryptographic methods.

Coffe is one of Indonesia’s leading commodities, known for its diverse flavors and aromas. Traditionally, coffee quality assessment is conducted manually through cupping tests performed by expert panelists. However, this method is subjective and requires considerable time and cost. This study aims to implement an Artificial Neural Network (ANN) using the backpropagation algorithm to classify coffee types based on sensory parameters such as flavor, aroma, acidity level, and body. Simulated data were generated from five common Indonesian coffee varieties: Arabica Gayo, Robusta Lampung, Arabica Toraja, Liberica Jambi, and Excelsa. The results show that the ANN-based classification system with a 4-8-1 architecture achieved an accuracy rate of 93% after 500 training epochs, with a final error value of 0.07. The implementation of this method provides an efficient and objective technological alternative to assist the coffee industry in maintaining product quality and automatically identifying coffee types.    

This study aims to determine the accounting treatment for fixed assets at Dr. Adhyatma Regional General Hospital, MPH, Central Java Province, and to determine whether the accounting treatment for fixed assets at Dr. Adhyatma Regional General Hospital, MPH, Central Java Province, complies with PSAP No. 07 concerning Fixed Asset Accounting. This study used a qualitative descriptive research method, using triangulation (a combination of observation, interviews, and documentation) as data collection techniques at Dr. Adhyatma Regional General Hospital, MPH, Central Java Province. The results of this study indicate that the accounting treatment for fixed assets at Dr. Adhyatma Regional General Hospital, MPH, Central Java Province, in terms of classification, recognition, measurement, cost components, post-acquisition expenditures, depreciation, retirement, and disposal, complies with PSAP No. 07 concerning Fixed Asset Accounting. Disclosure of fixed assets regarding the reconciliation of the recorded amount at the beginning and end of the period and depreciation information including the depreciation value, gross recorded value and accumulated depreciation at the beginning and end of the period is in accordance with PSAP Number 07 of 2010 concerning Fixed Asset Accounting. However, for the basic information on the valuation used to determine the recorded value, depreciation information in the form of the depreciation method used and the useful life or depreciation rate used is not in accordance with PSAP Number 07 of 2010 concerning Fixed Asset Accounting.

This study aims to analyze the influence of consumer trust and product price, mediated by e-WOM (electronic word-of-mouth), on purchase decisions on the Shopee platform. A quantitative approach was used, with a sample of 75 undergraduate students living in boarding houses in the Special Region of Yogyakarta who shop on Shopee. Data were collected via questionnaires and analyzed using Structural Equation Modeling (SEM) based on Partial Least Square (PLS) with SmartPLS version 4. The results show that consumer trust and product price have a significant positive influence on purchase decisions, both directly and indirectly through e-WOM. This confirms the vital role of user reviews and recommendations in the decision-making process. The study provides strategic implications for e-commerce platforms and guidance for consumers. In addition, this study also provides guidance for consumers in considering factors that influence purchasing decisions on online platforms and educate them to be more careful in assessing available information before making a purchase. Overall, the results of this study underscore the important role of consumer trust, product price, and e-WOM in shaping purchasing decisions on e-commerce platforms.

This study aims to determine the description of work motivation, workload, and employee performance, as well as to analyze the magnitude of the influence of work motivation and workload on employee performance, both partially and simultaneously. The research method used is descriptive and verification with a quantitative approach. The study population includes all employees of the Bogor City Regional Revenue Agency, namely 83 ASN, who were used as respondents using a non-probability sampling technique through a saturated sampling approach. The results of the study indicate that the description of work motivation, workload, and employee performance are generally included in the sufficient category. Based on the results of the determination test, it is known that work motivation has a 53.5% effect on employee performance, while workload has a 13.9% effect on employee performance. Simultaneously, work motivation and workload have a 61.9% effect on employee performance. Thus, the results of the hypothesis test prove that work motivation and workload have a significant effect on employee performance.

This article discusses the modernity of educational instruments, along with the phenomenon of technological progress, particularly the emergence of artificial intelligence (AI), and its implications for educators in the 21st century. Rapid advances in AI have led to fundamental shifts in teaching strategies and resources, shifting from traditional models to personalized and adaptive learning environments. Through automated assessments, curriculum customization, and the implementation of virtual assistants that enhance accessibility, artificial intelligence (AI) in education aims to improve efficiency and effectiveness. However, this modernity requires educators in the 21st century to change. Teachers now play the role of facilitators, designers of learning experiences, and mentors in ethics, in addition to being providers of knowledge. Teachers need to master AI literacy and focus on teaching students the four Cs of the 21st century: communication, creativity, critical thinking, and teamwork. The integration of AI raises ethical issues related to data privacy, the digital divide, and the dangers of plagiarism, but it also offers significant potential. Therefore, the effective integration of AI technology with irreplaceable human qualities is crucial for the success of contemporary educational technology. AI is an important tool for educators in the 21st century to develop a generation of technologically literate and moral individuals.

Waste management is an urgent environmental issue that requires active community participation. This study aims to analyze the speaking skills of members of the Sapu Lidi Community in Pekalongan during waste management discussions, a community that actively processes organic waste into valuable products such as eco-enzyme. Using a qualitative approach and an ethnographic case study design, this research explores speaking skills within its natural social context. Data were collected through in-depth interviews and non-participatory observation of community discussions, then analyzed using thematic analysis techniques. The findings show that the community members' speaking skills are characterized by fluent delivery, appropriate and credible word choice, and a persuasive, egalitarian, and humorous speaking style. Community members utilize rhetorical strategies such as humor, calls to action, and concrete evidence such as harvest results to build participation and environmental awareness among residents. The application of dialogic communication and the integration of verbal delivery with hands-on practice demonstrations proved effective in achieving the community's goals. Academically, this research contributes to environmental communication studies within grassroots communities. Practically, the findings can serve as a foundation for developing speaking skills training for volunteers in similar communities in other areas.

This study aims to describe the implementation of the Problem Based Learning (PBL) model in teaching personal and official letter writing, and to examine its impact on improving the writing skills of Grade VII B students at SMP Negeri 2 Banjarmasin. The study is motivated by students’ difficulties in distinguishing the structure and language style of personal and official letters, as well as their low engagement in the learning process. This research employed a descriptive quantitative approach using a One Group Pretest-Posttest design. The instruments included writing tests (pre-test and post-test) and observation sheets to assess students’ activities and attitudes. The results indicate that PBL positively influences students' writing abilities. This is evidenced by a significant increase in the average post-test scores compared to the pre-test, along with improvements in critical thinking, collaboration, and independence. Students also demonstrated better understanding of the structural and linguistic features of both types of letters. Thus, the PBL model is recommended as an effective instructional strategy to enhance the quality of writing instruction, particularly within the framework of the Kurikulum Merdeka.

This study provides a comprehensive analysis of the role of the United States in the Cold War rivalry against the Soviet Union, spanning from the end of World War II to the dissolution of the Soviet Union in 1991. The research focuses on the political, military, ideological, and economic strategies employed by the United States to contain the spread of communism through the implementation of the containment doctrine, the establishment of security alliances such as NATO, and economic assistance programs such as the Marshall Plan. The findings reveal that the rivalry between the two superpowers extended beyond military and structural domains, reaching into technological competition through the nuclear arms race and the Space Race, as well as geopolitical confrontations manifested in proxy wars across Asia, the Middle East, Africa, and Latin America. The theoretical framework, which incorporates perspectives from realism, liberalism, and constructivism, demonstrates that U.S. actions were shaped by a combination of power interests, ideological identity, and the pursuit of global leadership. Further analysis indicates that these strategies had a profound impact on the formation of the post–Cold War international order and continue to influence contemporary global politics. The study concludes that the involvement of the United States in the Cold War was a long-term strategic process that not only determined the direction of the conflict itself but also played a crucial role in shaping modern geopolitical structures and international relations.

The 21st century of digitalization is very influential in life such as Education which must adapt to the development of world digitalization technology. Education is carried out by involving innovation, creativity, and also motivation to update more interesting learning methods with interactive media that have been designed. History learning in particular must develop and adapt to the digital era by utilizing technology to make teaching methods the goal of an active learning process. History learning which is considered boring has a great opportunity to be able to adapt to interactive media so that passive students during learning are reduced and become active students and can understand History easily. In this study involved a teacher with 30 high school students who were the objects of the research study. The method used was descriptive qualitative which refers to observation, documents, interviews, questionnaires, and also a social science approach. The results of the study explain the low interest in History learning to many passive students due to learning methods that are not in line with the digital era to attract Gen Z's interest in History Lessons and also show the results of History learning by involving interactive media with digital technology.

Childhood obesity has become an increasingly significant health and education problem in various countries, including Indonesia, influenced by unhealthy eating patterns, lifestyle changes, and low nutritional literacy within families. This article aims to examine the lack of balanced nutrition in obese early childhood from the perspective of family education as part of non-formal education. The research method used is a literature review by reviewing national and international literature related to nutrition, child growth and development, and the increasing trend of obesity. The results show that obesity has physical, cognitive, psychological, and social impacts that can hinder a child's holistic development. Parents play a crucial role in establishing healthy eating habits, monitoring food consumption, and fostering an active lifestyle. Improving nutritional literacy within families, synergizing with early childhood education institutions, and supporting public health policies are considered crucial to preventing the long-term risk of obesity. Therefore, family education about balanced nutrition is a crucial strategy in supporting optimal growth and development and creating a healthy and competitive generation of early childhood children.

Islamic boarding schools (pondok pesantren) are the oldest Islamic educational institutions in Indonesia, playing a significant role in shaping the moral, spiritual, and intellectual character of society. Alongside the growing integration of formal education, pesantren are required to develop more modern and adaptive leadership models without abandoning their traditional values. This study aims to design a pesantren leadership structure that integrates transformational, distributive, and instructional leadership principles rooted in local culture. The analysis conducted at Pondok Pesantren Al-Mukhlisin in Deli Serdang Regency indicates that leadership patterns remain centered on the kiai figure, resulting in suboptimal coordination and delegation of authority. Transformational leadership is needed to foster inspiration and motivation; distributive leadership to strengthen collaboration and participation; and instructional leadership to ensure instructional quality and teachers’ professional development. The integration of these three leadership models is believed to create a pesantren leadership system that is visionary, participatory, and quality-oriented, while remaining aligned with local cultural values such as gotong royong, musyawarah, and familial solidarity. Thus, pesantren can evolve into innovative, adaptive, and sustainable Islamic educational institutions in the modern era.

Leadership in educational organizations, especially in the Darul Hikmah Modern Islamic Boarding School in Medan, faces the challenges of modernity that demand integration between traditional spiritual values ​​and management professionalism. This study aims to analyze the existing leadership structure and design a new structure that integrates the Transformational, Distributive, and Instructional models that are aligned with the local wisdom of North Sumatra, namely the Dalihan Na Tolu philosophy. The method used is qualitative case analysis with observation and interviews. The results of the analysis show that the current leadership is dominated by charismatic and centralistic styles (strong Transformational), but weak in the Distributive dimension (low teacher participation) and Adaptive Technology Instructional. The proposed new leadership structure design emphasizes the formation of a Quality Supervisory Board (DPM) and the Head of Human Resources & Regeneration. This new model places the Kyai/Head of the Islamic Boarding School as the spiritual authority (Hula-hula), Mudir/Executive Director as the managerial change agent (Dongan Tubu), and strengthens the academic/innovation function (Boru). The conclusion suggests that leadership transformation in this Islamic boarding school requires a shift from a figure-based system to a competency-based and collaborative system, making it an adaptive, professional institution firmly rooted in local values.

This study aims to analyze the use of Instagram as a medium for language development in the correct use of the preposition "di" according to the guidelines of Ejaan yang Disempurnakan (EYD) edition V. Although the Indonesian language has clear writing rules, inaccuracies in the use of the preposition "di" are still frequently found in both print and digital media. One of the contributing factors is the low level of public understanding of these rules. Therefore, language development through Instagram is considered an effective way to raise awareness and improve understanding among the public. This research employs a descriptive qualitative approach, collecting data through Instagram’s polling feature, which allows the researcher to measure audience understanding of the correct usage of "di". The results show an increase in audience comprehension after receiving explanations regarding the correct usage, although many respondents still showed inaccuracies in the use of "di". Therefore, a broader and more sustained language development effort via social media is needed to enhance public awareness of correct prepositional writing. This research is expected to serve as a foundation for the development of more interactive and practical language development strategies, especially in the context of social media. Keywords: 

This study aims to determine the implementation and challenges  of the Promblem Based Learning (PBL) learning model and contextual approach to students. So, by knowing the results of the implementation, it is hoped that teachers can improve the way to teach students better. The method used in this study is descriptive qualitative with interviews via chat via whatsapp and provides google from to be filled in by Yuselvin Beo Wesso as a PPG student who teaches at SMP Negeri 6 Banjarmasin grade 8. She was chosen because she was a student of the Teacher Professional Program and also directly taught at school. The results obtained are the advantages and disadvantages of this model and approach. The advantage of this model is that it helps students to hone critical thinking skills through problem solving that can build students' connectivity with learning. The shortcoming faced in its application is that students find it difficult if they are directly asked for problem-solving discussions. In addition, the challenge faced is that teachers must be able to design learning that varies with the context of problem-solving and not all students can construct their experiences into written text. Therefore, efforts are made by applying the jigsaw method. The result of the application of this model and approach is that the students are quite good. Students can work together to complete assignments and be able to bring up topics relevant to daily life.