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Diesel engines are widely used in the transportation and industrial sectors due to their high thermal efficiency and good operational durability. However, increased fuel consumption due to inefficiency of the injection system remains a common problem. Injector characteristics, particularly nozzle diameter and injection pressure, are important factors that affect the quality of fuel atomization, air-fuel mixing, and combustion efficiency. An inappropriate combination of parameters can cause suboptimal combustion and increase fuel consumption. This study aims to analyze the effect of variations in nozzle diameter and injection pressure on fuel consumption efficiency in diesel engines. The method used is an experiment with variations in nozzle diameter of 0.150 mm, 0.152 mm, and 0.154 mm and injection pressures of 400 bar, 420 bar, and 440 bar. Tests were conducted at engine speeds of 500 rpm, 1000 rpm, and 1500 rpm with a fuel consumption measurement time of one minute for each parameter combination. Fuel consumption was measured using the volumetric method and analyzed through the fuel volumetric flow rate, fuel mass flow rate, Brake Power (BP), and Brake Specific Fuel Consumption (BSFC). The results showed that the combination of a nozzle diameter of 0.150 mm and an injection pressure of 400 bar produced the lowest BSFC value, thus providing the best fuel consumption efficiency. Meanwhile, the combination of a nozzle diameter of 0.152 mm and an injection pressure of 420 bar showed the closest condition to optimal because it was able to provide a balance between atomization quality and the amount of fuel injected, resulting in efficient and stable combustion. Thus, the efficiency of a diesel engine is influenced by the balance of nozzle size and injection pressure, not solely by the lowest fuel consumption.

Malware represents an evolving cybersecurity threat that demands more effective detection methods. Conventional signature-based detection systems have limitations in identifying new variants, driving the development of deep learning-based approaches. This research implements and evaluates four variants of the YOLOv11 algorithm (n, s, m, l) for malware classification based on visual image representation. The dataset consists of 22,056 malware and benign images, divided into 70% training, 15% validation, and 15% testing across 8 classes (adware, backdoor, benign, downloader, spyware, trojan, virus, worm). Each model was trained for 100 epochs with batch size 32 using Google Colab with GPU support. Results demonstrate that all variants achieve high accuracy (97.8%-98.1%) with YOLOv11m as the best performer (98.1%). YOLOv11n offers optimal balance between accuracy (97.9%) and efficiency (1.5M parameters, 0.3 ms/img inference) ideal for real-time applications. This research surpasses previous methods such as K-NN (97.18%) and hybrid CNN (96.55%) with superior inference speed (0.3-0.9 ms/img vs tens to hundreds of ms/img), proving the effectiveness of YOLOv11 for fast, accurate, and scalable malware detection.

The thesis supervision process in higher education institutions is still frequently conducted manually, which may lead to inefficiencies in recording supervision data. This study focuses on the development and implementation of a web-based thesis supervision attendance application designed to facilitate attendance documentation, supervision session administration, and systematic monitoring of thesis supervision history. The methodology applied in this study is the Waterfall model, which includes the phases of requirements analysis, system design, implementation, and testing. The application was developed using the Laravel framework and a MySQL database. The system design was modeled using Unified Modeling Language (UML), while the validation process was conducted through Black Box Testing techniques. The research findings indicate that the developed application is capable of performing real-time supervision attendance recording, managing supervision information, and generating attendance reports effectively and efficiently. It can be concluded that the web-based thesis supervision attendance application improves the efficiency and accuracy of supervision record management and supports a more effective thesis supervision monitoring process..

This study examines the transformation of financial management through the implementation of digital accounting in PPOB (Payment Point Online Bank) businesses, which still face manual recording problems such as input errors, delayed reconciliations, and data discrepancies. The research used a descriptive qualitative method with a case study approach involving PPOB agents in Sidoarjo. Data were collected through observation, interviews, and documentation. The findings show that digital accounting significantly improves operational efficiency through automated transaction recording, real-time data integration, and faster as well as more accurate reconciliation processes. In addition, features such as automatic validation, API integration, and audit trails help minimize recording errors and maintain data consistency. The implementation of digital accounting also supports transparency and improves the quality of financial information used in decision-making. Although challenges remain regarding agents’ technological understanding and infrastructure readiness, overall implementation has provided positive impacts on financial management effectiveness and business operations in PPOB services, making processes more efficient, accurate, and reliable.

Construction project control requires careful planning to avoid delays and cost overruns. This study aims to evaluate the performance of the CBT Laboratory Building construction project at the Faculty of Medicine, Wahid Hasyim University, Semarang, in terms of cost and time using the Earned Value Analysis (EVA) method, and to analyze acceleration alternatives using the crashing method. The method used is a quantitative approach with a case study, based on project data such as the Budget Plan (RAB), S-curve, and work progress reports. The analysis was carried out using the Earned Value Analysis (EVA) method to assess project performance in terms of cost and time through indicators such as CV, SV, CPI, and SPI. Furthermore, an acceleration analysis was conducted using the crashing method to determine the optimal alternative for overcoming project delays by considering time and cost efficiency. The results of the Earned Value Analysis indicate that the project experienced delays and cost overruns, as shown by SPI < 1 and CPI < 1. The estimated project completion time increased to 227 days, longer than the initial plan of 217 days, while the estimated final cost reached RP 5,451,241,064.85, exceeding the initial budget. Acceleration efforts using the crashing method show that adding adding labor is more efficient than working hours (overtime), resulting in a project duration of 212 days with lower costs of RP 5,658,221,364.08. Thus, the Earned Value Analysis method is effective for evaluating project performance, while crashing can be a solution for acceleration by considering time and cost efficiency.

Coal hauling activities are an important part of mining operation because they affect production continuity, cycle time efficiency, and operational safety. This study aims to analyze the requirements of road support equipment on the coal hauling road from Sector 4 to the new Coal Processing Plant (CPP) at PT. Asmin Bara Bronang, Central Kalimantan. Based on road geometry, traffic density, California Bearing Ratio (CBR), and Unsurfaced Road Condition Index (URCI). The research method used was applied research with a quantitative approach. Primary data ware collected through field measurements consisting of road geometri observations, traffic density observations, Dynamic Cone Penetrometer (DCP) testing to obtain CBR values, and road surface condition assessment using the URCI method. Secondary data were obtained from the company records. The results showed that the hauling road has a total length of 9.1 km with an average width of 16 m, and grade values ranging from -7.68% to 10.52%, which are still below the maximum standard of 12%. Traffic density reached 184 dump trucks/day, for coal hauling and 62 units/day for construction material transportation, indicating high traffic intensity. CBR values ranged from 7% to 100%, showing variations in subgrade bearing capacity. The URCI value ranged from 72,50 to 91.00, indicating fair to good road conditions. Based on the analysis of road conditions and maintenance area requirements, the recommended support equipment for maintaining the hauling road consists of 1 motor grader unit, 1 compactor unit, 1 bulldozer unit, and 1 water truck unit.

The International Community Service Seminar on the Application of Artificial Intelligence (AI) for students of SMA Muhammadiyah Program Khusus Kotabarat Surakarta was conducted to enhance digital literacy and provide practical understanding of AI utilization in daily life and learning activities. The program aimed to introduce basic concepts of artificial intelligence, its functions, benefits, and challenges in modern education. Through presentations, interactive discussions, and quizzes, participants were exposed to real-life applications of AI such as digital assistants, personalized learning systems, and time management tools. The seminar involved participants from Indonesia and Malaysia, creating a cross-cultural learning environment that enriched the discussion. Both students and teachers gained improved understanding of how AI can support adaptive and effective learning processes. The activity highlighted the importance of responsible technology use in education. Integrating AI into learning environments was found to improve creativity, efficiency, and engagement among participants while also supporting teachers in administrative and instructional tasks.

This study aims to evaluate how petty cash management practices contribute to improving operational efficiency at PT Anugerah Langgeng Berkat Abadi. This research focuses on examining the implementation of the petty cash management system, applied procedures, and its impact on the smooth execution of daily operational activities. The study employs a descriptive qualitative approach, with data collected through interviews, direct observation, and documentation during the internship period. The collected data were analyzed systematically to describe the actual condition of petty cash management within the company. The results indicate that PT Anugerah Langgeng Berkat Abadi implements a fluctuating fund system in managing petty cash. Expenditures are initially recorded manually and then re-entered into the company’s internal digital system to maintain control and accountability. Petty cash is used to finance routine and urgent operational needs, such as office stationery, transportation costs, and other short-term expenditures. The company has established standard operating procedures governing the use, recording, and accountability of petty cash. Several challenges were identified, including delays in the disbursement and reimbursement process, which may affect time efficiency. However, overall, the petty cash management system is considered effective in supporting short-term operational needs without disrupting the stability of the company’s main cash. This study concludes that systematic and well-controlled petty cash management plays an important role in the company’s cost efficiency strategy and supports daily operational activities. These findings align with strategic management principles, where appropriate financial decision-making contributes to the achievement of long-term organizational objectives.

The optimal therapeutic impact of local vaginal drug delivery systems is strongly influenced by the physical characteristics balance of Solid Vaginal Suppositories. A comprehensive review regarding the comparison of mechanical profiles, specifically melting time and crushing strength parameters, from various base classifications constitutes the primary objective of this literature research. The implementation of a Literature Review study design was executed through the extraction of empirical data from twelve experimental journals published within the last ten years. Excessively rapid phase transformation characteristics at physiological basal temperatures and low compression resistance were consistently demonstrated by lipophilic bases such as Oleum Cacao. The risk of structural deformation during the distribution process is highly susceptible to unmodified lipid preparations. High surface elasticity accompanied by a delay in molecular hydration duration reaching 120 minutes was recorded in the utilization of Glycerinated Gelatin Base. Structural rigidity exceeding 4 kgF and disintegration time efficiency under 60 minutes were optimally demonstrated by Polyethylene Glycol (PEG) Base. An enhancement in mechanical resistance against external shocks during the storage period is offered by the thorough modification of the synthetic polymer ratios. Therefore, the determination of the PEG base as the most optimal material is recommended to maintain the quality stability of pharmaceutical products. Compendial regulation standards regarding the physical strength testing of pharmaceutical preparations must be obeyed by every institution to ensure long-term treatment effectiveness. Thus, the alignment between active substance release duration and physical preparation endurance can be realized for absolute patient comfort.

This research investigates the effect of the amount of MSMEs, the number of buildings, and GRDP on regional tax revenue in selected cities and regencies in South Sulawesi, driven by the inconsistency between the growth of economic potential and the realization of tax revenue, where increases in MSMEs, buildings, and GRDP are not always followed by higher tax receipts. The study aims to analyze the effect of these variables and identify the most significant factors contributing to regional fiscal capacity. A quantitative approach is employed using panel data that combine time series and cross-sectional data from 2015-2024, analyzed through panel data regression with model selection based on Chow, Hausman, and Lagrange Multiplier test. The results show that partially, MSMEs and the number of buildings do not have a significant effect on tax revenue, while GRDP has a positive significant impact; however, simultaneously, all variables significantly influence tax revenue, as indicated by a high Adjusted R-squared value. These findings suggest that economic growth, as proxied by GRDP, plays a more dominant role in increasing tax revenue compared to the mere increase in the number of MSMEs and buildings, implying that optimizing tax revenue requires not only expanding economic potential but also enhancing tax compliance, administrative efficiency, and the quality of economic growth.

This study aims to analyze the effect of renewable energy, energy consumption, and Gross Domestic Product (GDP) per capita on carbon dioxide (CO2) emissions in Indonesia for the period 1995-2024. This study uses secondary data over time (time series) with the Ordinary Least Square (OLS) multiple linear regression analysis method corrected using the Newey-West Heteroskedasticity and Autocorrelation Consistent (HAC) approach. The results show that renewable energy does not have a significant effect on CO2 emissions, which is caused by the still low share of renewable energy in the national energy mix which only reaches 10.95% in 2024. Energy consumption has a positive and significant effect on CO2 emissions, where every 1% increase in energy consumption increases CO2 emissions by 84.23%. Gross Domestic Product (GDP) per capita has a positive and significant effect on CO2 emissions. Every 1% increase in GDP per capita increases CO2 emissions by 35.03%, indicating that Indonesia remains on the EKC curve. Simultaneously, all three variables have a significant effect, with an adjusted R-squared value of 53.63%. This finding confirms that Indonesia's energy mix, still dominated by fossil fuels, is a major factor in high carbon emissions. Comprehensive energy efficiency policies, accelerated renewable energy transitions, and greener and more sustainable economic growth strategies are needed.

PT. X is a textile company that produces greige fabric. One of the crucial stages in the greige fabric production process is inspection. Currently, the facility layout of the inspection area at PT X is still suboptimal. This results in longer fabric movement distances and increased time, leading to delivery delays and higher material handling costs. This study aims to design an optimal facility layout in the inspection area using the Activity Relationship Chart (ARC) method and to determine the distances, times, and costs for the proposed layout. In the initial production layout, the fabric movement distance reached 26,130 meters in one working day, and the fabric movement time was 936 minutes. Furthermore, the initial production layout generated a relatively high OMH of Rp 13,742,980 per month. After designing the facility layout using the Activity Relationship Chart (ARC) and Blockplan methods, the proposed layout was arranged according to the production process sequence, resulting in a smoother material flow. The proposed layout yields 16,830 meters of fabric movement per workday, 660 minutes of required time, and a monthly OMH of Rp 7,945,622, with an efficiency of 39.32%.

This study aims to analyze public concerns regarding fast food consumption from the perspective of risk society, particularly among university students. The increasing consumption of fast food reflects shifts in consumption patterns influenced by globalization, practicality, and time efficiency. This research employs a qualitative approach through a literature review supported by interview data to strengthen the analysis. The findings reveal that fast food consumption is not solely driven by biological needs but also by practical, emotional, and social factors. Although students demonstrate a relatively high awareness of health risks associated with fast food, their consumption behavior persists as an adaptive response to structural conditions such as time constraints, accessibility, and academic pressures. From the perspective of risk society, this phenomenon illustrates a contradiction between risk awareness and everyday consumption practices. Risks produced by modernity are not entirely avoided but are negotiated and normalized in daily life. Therefore, fast food consumption cannot be understood merely as an individual choice but as a result of the interaction between structural factors, consumer culture, and social construction within modern society.

This study aims to examine the application of artificial intelligence (AI) in learning to write scientific papers and its impact on the level of originality of students in the Indonesian Language and Literature Education Study Program (PBSI) Semester VI at Bina Bangsa University. This study uses a qualitative method with a descriptive approach, which was conducted through reference searches and interviews with 30 of the total 35 students. The results of the study indicate that AI is utilized functionally as an aid in the writing process, such as compiling outlines, paraphrasing, developing ideas, and reviewing writing. Based on the interview results, the use of AI platforms is dominated by Chat GPT at 50%, followed by Perplexity at 27%, and Gemini.ai at 23%. These findings indicate that students do not rely on a single platform, but rather utilize various technologies adaptively according to their needs. In terms of discussion, the use of AI has a positive impact in the form of improved writing quality, time efficiency, development of creative ideas, increased digital literacy, and the provision of instant feedback. However, there are also challenges that arise, such as the potential for decreased originality, dependence on AI, the risk of violating academic ethics, information bias, and data privacy issues. Therefore, AI should be used as a tool, not a substitute for students' critical thinking skills. This research emphasizes the importance of using AI wisely, critically, and responsibly so that students can produce original, high-quality, and integrated scientific work in the digital age.

The development of digital technology has transformed trading patterns through the emergence of live shopping, a phenomenon that enables real-time interaction between sellers and consumers. Although it offers marketing efficiency, this model poses significant legal risks, including misleading information, promotional manipulation, and product non-conformity. This study aims to analyze legal certainty in consumer protection within live shopping transactions, examine the forms of business actors’ liability for consumer losses, and identify obstacles to regulatory implementation along with efforts to strengthen supervision.The research method employed is normative legal research using both a statute approach and a conceptual approach. The results indicate that legal certainty in consumer protection within this ecosystem is grounded in the integration of Law No. 8 of 1999 (Consumer Protection Law) as the lex generalis and Government Regulation No. 80 of 2019 (Electronic Commerce/PMSE) as the lex specialis, which recognizes the validity of real-time electronic contracts. The legal liability of business actors is strict liability in nature, in accordance with Article 19 of the Consumer Protection Law, and may also be construed as a tort (Article 1365 of the Civil Code) in cases involving distortion of visual information.However, the effectiveness of these regulations is hindered by the ephemeral nature of transactions and low levels of digital literacy. This study recommends the implementation of technology-based supervisory systems (suptech), strengthening the oversight function of platforms (PPMSE), and policy synchronization between the Ministry of Trade and the Ministry of Communication and Informatics in standardizing business actor verification to ensure the security of the digital commerce ecosystem.

This study analyzes the implementation of public service innovation through the E-TTSP application at the Investment and One-Stop Integrated Services Agency (DPMPTSP) of Banten Province. Using a descriptive qualitative method, data were collected through interviews, observation, and document analysis. The results show that this digital system has significantly improved service quality and efficiency. Processing time was reduced from 7–14 days to only 2–5 days, while bureaucratic procedures were simplified. The system also enhances transparency, accountability, and accessibility, allowing users to apply online without visiting the office. Consequently, the investment climate improved, marked by a 28% increase in permit applications and a 35% rise in investment value within two years. However, challenges remain, including uneven network infrastructure, low digital literacy, and limited human resource capacity. It is recommended to improve infrastructure, provide continuous training, and intensify socialization. In conclusion, E-TTSP has delivered tangible benefits, yet sustainable development is necessary to ensure equal and optimal services for all.

This research is motivated by the increasing role of Artificial Intelligence (AI) in organizational transformation and the crucial function of leadership in ensuring its successful implementation. The primary objective of this study is to analyze the relationship between leadership, AI integration, and organizational performance, as well as to identify various challenges and supporting factors in the process. This study employs a systematic literature review (SLR) method by examining 30 relevant, reputable scientific articles from the Scopus and Google Scholar databases within the 2020–2026 timeframe through selection, evaluation, and thematic synthesis processes. The results indicate that AI integration significantly contributes to improving operational efficiency, data-driven decision-making quality, and organizational innovation. However, this success heavily depends on the role of adaptive, transformational, and digitally-oriented leadership capable of steering the technological vision. Conversely, major challenges were identified, such as employee resistance, limited digital competencies, and ethical issues surrounding data privacy. This study contributes to strengthening the conceptual understanding of leadership's role as a bridge between technology and organizational performance, while offering practical implications for management in designing effective, inclusive, and sustainable digital transformation strategies.

The search and booking of boarding houses (kost) remain a significant challenge for newcomers in campus areas, particularly in Kelurahan Samata, home to UIN Alauddin Makassar, which admits approximately 15,000 new students annually. Many of these students come from outside the region and require temporary accommodation near the campus. This issue is primarily caused by limited access to information and the lack of an optimal system to support the search and booking process. Therefore, it is necessary to evaluate the level of user acceptance of the developed system. This study aims to analyze user acceptance of a boarding house search and booking information system in the case of Kelurahan Samata using the User Acceptance Testing (UAT) method. UAT is a testing approach used to determine whether a system meets user requirements, is accepted according to expected standards, and to identify the need for further improvements to ensure its feasibility for use. The UAT was conducted by end users, namely boarding house seekers and property owners/managers, by responding to 10 evaluation indicators: (1) ease of search, (2) time efficiency, (3) booking process, (4) geospatial search features, (5) completeness of information, (6) availability of suitable boarding houses, (7) accuracy of information, (8) ease of payment process, (9) check-in scheduling, and (10) navigation features for directions. The results of the User Acceptance Testing (UAT) indicate that the system achieved an average score of 87.77, suggesting that the system is highly acceptable and significantly facilitates users. These findings demonstrate that the system is well received by users, confirming that it functions effectively and is capable of accommodating all required functionalities.

This study aims to design and develop a web-based sales information system for a goat farming business at Herman Farm using the Rapid Application Development (RAD) method. The identified problems include manual transaction recording, stock management, and sales reporting processes, which are inefficient, prone to errors, and unable to provide real-time data access. The RAD method is selected due to its ability to accelerate system development through an iterative approach and active user involvement in each stage, including requirements planning, system design, construction, and implementation. Data collection techniques include observation, interviews, and literature studies. The developed system provides features for managing goat data, sales transactions, customer management, and integrated sales reporting within a web-based platform. The results show that the system improves efficiency in data management and transaction processes, while producing more accurate, structured, and accessible reports. Therefore, this system can assist Herman Farm in optimizing its sales operations and expanding its online marketing reach.

This study examines the determinants of the Jakarta Composite Index (JCI) based on three main macroeconomic factors namely inflation, the USD/IDR exchange rate, and the SBI interest rate (BI Rate) covering the period January 2020 to December 2025, in the context of post-COVID-19 pandemic recovery and global economic turmoil. A quantitative approach was employed using the Ordinary Least Squares (OLS) method, with 72 monthly observations derived from secondary data sourced from official institutions including Bank Indonesia (BI), the Central Statistics Agency (BPS), the Indonesia Stock Exchange (IDX), and the Financial Services Authority (OJK). Classical assumption tests were applied comprising the Jarque-Bera normality test, Variance Inflation Factor (VIF) for multicollinearity, Breusch-Godfrey for autocorrelation, White Test for heteroscedasticity, and Ramsey RESET for model specification. Partially, inflation, exchange rate, and BI Rate each demonstrate a positive and significant effect on the JCI (p < 0.05). Simultaneously, all three variables exert a significant combined influence on the JCI, with a coefficient of determination R² = 0.4414, indicating that the model explains 44.14% of the variation in the JCI. The remaining 55.86% is attributed to other variables outside the model. Classical assumption test results reveal violations of normality, autocorrelation, and heteroscedasticity assumptions, although the model is free from multicollinearity. These findings confirm that Bank Indonesia's monetary policy has a significant and measurable impact on capital market performance. Further research is recommended using more advanced time series models such as GARCH or VECM to address violations of classical assumptions and improve estimation efficiency.