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Cloud job-length prediction remains challenging when the target distribution is highly skewed and contains rare extreme values. This study proposes a log-transformed, regime-based machine learning framework for robust prediction of cloud job length, represented in million instructions (MI). The approach integrates sequential feature engineering, logarithmic target transformation, weighted learning, and regime-aware modeling to distinguish between normal and extreme job-length behavior. Using an ordered GoCJ-derived cloud job-length sequence of 1000 jobs, the dataset exhibits a heavy-tailed distribution, with a mean of 129,662 MI, a median of 93,000 MI, a 95th percentile of 525,000 MI, a 99th percentile of 900,000 MI, and a skewness of 3.695. The proposed model is evaluated against sequential baselines and stronger machine learning baselines, including Naive_Last, RollingMean_5, Global_Log_ExtraTrees, RandomForest, GradientBoosting, and MLP_Log. On the main test split, the proposed Regime_Log_ExtraTrees achieved the best RMSE of 206,255.66 and the least negative R² of −0.01062, while Global_Log_ExtraTrees remained competitive in terms of MAE, MedAE, and RMSLE. Additional walk-forward validation confirms that the regime-aware model consistently achieves the best mean RMSE and mean R² across temporal folds. Ablation results further show that regime-aware learning is the primary contributor to robustness, although accurate prediction of extreme jobs remains challenging. These findings indicate that log-transformed, regime-based learning provides a practical and more robust strategy for cloud job-length prediction under heavy-tailed workload conditions.

This study aims to analyze and examine the effect of financial literacy and self-control on financial management behavior, with financial attitude as an intervening variable among accounting students at universities in Lamongan. This research employed a quantitative approach using a survey method through questionnaire distribution via Google Form. The population consisted of accounting students at universities in Lamongan, with a total sample of 232 respondents selected using probability sampling with a simple random sampling technique. Data analysis was conducted using Partial Least Square–Structural Equation Modeling (PLS-SEM) version 4.0. The results indicate that financial literacy does not have a significant effect on financial management behavior, while self-control has a significant effect on financial management behavior. Furthermore, financial literacy and self-control significantly influence financial attitude, and financial attitude significantly affects financial management behavior. Financial attitude is also proven to significantly mediate the relationship between financial literacy and self-control on financial management behavior.

The transformation of revolving funds from the former PNPM Mandiri program into BUM Desa Bersama entities requires accountable financial management aligned with applicable accounting standards. However, inconsistencies between regulations and accounting practices remain. This study analyzes the recognition and measurement of revolving fund assets at BUM Desa Bersama Ajimas Lestari LKD in Ajibarang and assesses their compliance with Ministerial Regulation of Village PDTT No. 136 of 2022 and SAK ETAP. Using a qualitative case study approach, data are collected through interviews, observation, and documentation involving five internal informants. The results show that asset recognition follows regulations, where revolving funds are recorded as receivables upon loan distribution to Women’s Savings and Loan (SPP) groups at nominal value. However, discrepancies persist in asset measurement and presentation, particularly in receivable classification and the placement of allowance for doubtful accounts under equity. These issues stem from limited human resource capacity, lack of a standardized accounting information system, and weak supervision. Strengthening accounting competence and implementing standardized financial reporting systems are essential to improve accountability and transparency in managing community revolving funds.

Childbirth is a series of natural processes that trigger various changes in the mother's body so that she can deliver her baby through the birth canal. Perineal stiffness can actually be anticipated and prevented early in pregnancy, one way is through physical exercises such as pregnancy yoga. Pregnancy yoga has many benefits, especially in alleviating complaints during pregnancy, reducing anxiety, improving sleep quality, and preparing the physical condition before childbirth by strengthening and increasing the elasticity of the pelvic floor muscles, so that the birth process becomes easier. This study aims to analyze the effect of prenatal gentle yoga on the incidence of perineal tears in mothers who will give birth in the work area of ​​the Tiley Health Center on Morotai Island. This study used a quasi-experimental method with a posttest control design. The sample used in the study consisted of mothers giving birth who met certain inclusion criteria, with a total of 36 pregnant women. The instruments used in this study were the Kegel Exercise SOP observation sheet and the assessment of the level of perineal tears. Data were analyzed using the Mann-Whitney statistical test. The results showed a distribution of respondents regarding Kegel exercises: 18 respondents (50%) performed Kegel exercises and 18 respondents (50%) did not. The highest rates of perineal rupture were grade I and grade II, with 13 respondents (36.1%) each. The resulting p-value was 0.0001 (p < 0.05), indicating a significant effect of Kegel exercises on the rate of perineal rupture in primiparous women.

The study aims to analyze in greater depth the influence of work motivation and employee loyalty on employee performance at PT ABC. This research employs a quantitative approach with an explanatory design intended to systematically explain the relationships among variables. Data were collected through the distribution of questionnaires using a Likert scale (1–5) to employees with a minimum of one year of tenure, as they are considered to have an adequate understanding of organizational conditions. Data analysis was conducted using the Structural Equation Modeling–Partial Least Squares (SEM-PLS) method with the assistance of SmartPLS 4 software to obtain more accurate and comprehensive results. The findings indicate that all research indicators have met the established validity and reliability criteria. The structural model test shows that work motivation has a positive and significant effect on employee performance (β = 0.207; p = 0.007), and employee loyalty also has a positive and significant effect (β = 0.718; p = 0.000). The R-square value of 0.753 indicates that both variables are able to explain 75.3% of the variation in employee performance. These findings emphasize that work motivation and employee loyalty play important roles in improving performance, with loyalty being the most dominant factor influencing employee performance.

This study aims to analyze visitors’ Willingness to Pay (WTP) and to estimate the economic value in supporting the development of Gunung Meja Nature Tourism Park (TWA) as a conservation area. This study employed the Contingent Valuation Method (CVM) with a total of 156 respondents. Data were analyzed using descriptive quantitative methods to obtain the average WTP value and its distribution. The results showed that the average WTP of visitors was IDR 19,300 per person, with the highest distribution in the range of IDR 10,000–30,000 and a dominant value of IDR 20,000 (23%). The estimated economic value of the area based on WTP reached IDR 3,939,245,800 per year, which is higher than the actual revenue of IDR 2,755,431,000 per year. The difference of IDR 1,183,814,800 indicates a potential increase in revenue through tariff adjustment. These findings indicate that visitors have a higher willingness to pay compared to the current tariff. Therefore, the WTP value can be used as a basis for determining optimal tariff policies to support sustainable management of conservation areas and to maintain their ecological functions.

This study aims to analyze the in silico profile of the compound orientin derived from the water hyacinth plant (Eichhornia crassipes) as a potential antioxidant candidate. Orientin was selected based on its chemical structure data registered in PubChem, which provides complete information regarding molecular identity, physicochemical properties, and 2D and 3D structural representations. The prediction of biological activity was conducted using PASS Online, which indicated that orientin possesses a promising likelihood of exhibiting antioxidant activity according to relevant probability values. Furthermore, the safety assessment of the compound was carried out through ProTox-II to identify potential toxicity, including toxicity class, possible hepatotoxic effects, and other predicted safety parameters. To determine its pharmacokinetic profile, pkCSM was employed to predict ADMET characteristics such as absorption, distribution, metabolism, excretion, and additional toxicity risks. The results of these analyses show that orientin demonstrates favorable potential as an antioxidant candidate, supported by predicted pharmacological properties and relatively low toxicity levels according to in silico evaluations. Therefore, orientin has promising potential for further development in subsequent in vitro and in vivo studies.

This study aims to analyze the potential of eupatorin found in Cat’s Whiskers (Orthosiphon stamineus) as an anticancer agent using in silico methods. Eupatorin was selected due to its promising biological activity reported in previous literature. The research employed compound structure data registered in PubChem, analyzed through PASS Online for pharmacological activity prediction, ProTox-II for toxicity evaluation, and pkCSM for ADMET parameters. The results indicated that eupatorin has a high probability of inhibiting cancer cell proliferation with significant pharmacological activity values. Toxicity predictions showed a safe profile with an LD50 supporting its potential therapeutic use. ADMET analysis demonstrated that eupatorin possesses good bioavailability, adequate absorption and distribution, and minimal metabolic interactions, supporting its efficacy as an anticancer compound. These findings suggest that eupatorin could be an important candidate for herbalbased drug development, particularly for cancer therapy, and provide opportunities for further research through in vitro and in vivo experiments to validate anticancer activity comprehensively.

This study aims to analyze the phytochemical profile of Sambung Nyawa (Gynura procumbens) leaves as a potential herbal candidate for mild hypertension therapy using in silico methods. Plant samples were examined to identify active compounds documented in the PubChem database. The identified compounds were further analyzed using PASS Online to predict their pharmacological activities, ProTox-II to evaluate toxicity levels, and pkCSM to assess ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) characteristics. The findings reveal that several bioactive compounds present in Sambung Nyawa leaves demonstrate strong predicted anti-hypertensive activity accompanied by minimal toxicological risk. PASS Online analysis indicates potential mechanisms of action, including vascular receptor modulation and mild diuretic properties that may support blood pressure regulation. ProTox-II classification places most compounds in the low-toxicity category, while pkCSM predictions confirm acceptable bioavailability and favorable pharmacokinetic properties. Overall, these results provide a preliminary scientific foundation for the development of Gynura procumbens as an alternative herbal therapy for mild hypertension and support the need for further validation through in vitro and in vivo experimental studies.

Slum upgrading is a strategic step in improving the quality of life of urban communities, where its success is largely determined by the active involvement of local residents. This study aims to analyze the level of community involvement in the implementation of slum upgrading in Mantuil Village, South Banjarmasin District. Using a descriptive quantitative approach, data were collected through a structured questionnaire from 98 respondents selected using a purposive sampling technique. Data analysis was conducted descriptively to measure the level of participation in four stages of the activity. The results show that community involvement is in the good category, but has an uneven distribution. The highest average scores were found in the utilization stage (30.44) and maintenance stages (30.23), indicating that community participation is driven by the principle of direct benefit from the infrastructure being built. Conversely, participation in the planning and implementation stages tends to be lower due to structural barriers such as time constraints and respondents' economic burdens. These findings confirm that sustainable settlement upgrading requires synergy between community social capital and government policies that are adaptive to the geographic characteristics of the region, particularly related to tidal flooding vulnerability in riverbank areas.

The performance of asphalt mixtures is strongly influenced by the composition of their constituent materials, particularly aggregate size and mixing temperature during production. In many tropical and subtropical regions, asphalt pavements frequently experience rutting, reduced stability, and changes in viscoelastic properties due to high environmental temperatures and heavy traffic loads. These conditions can significantly affect pavement durability, making it essential to produce asphalt mixtures that meet established technical standards. This study aims to analyze the effect of variations in aggregate size distribution and mixing temperature on the Marshall characteristics of Asphalt Concrete Wearing Course (AC-WC) mixtures. The research employs the Marshall test method to evaluate the load-bearing capacity and stability of hot asphalt mixtures and to assess their compliance with ASTM/SNI standards. The results indicate that mixtures with standard aggregate gradation achieve stability values of 985 kg at 120°C, 1055 kg at 140°C, and 1107 kg at 160°C. As mixing temperature increases, flow values decrease, while the Marshall Quotient (MQ) increases, indicating improved stiffness. Higher temperatures also enhance compaction, reducing VIM and VMA while increasing VFA. Conversely, non-standard aggregate gradations result in several parameters failing to meet ASTM/SNI requirements, confirming that standard gradation produces superior asphalt performance.

This research examines the influence of the Webtoon platform on the creativits and literary marketing of Gen – Z in Indonesia, with a focus on the increasingly common trasition of digital content to physical books. The research background is grounded in the rapid growth of Webtoon as a platform for illustrated stories accessed by millions of young users via mobile devices, enabling affordable creative expression, but often encountering adaptation challenges to print formats due to differences in distribution and monetization. The primary objective is to analyze how Webtoon shapes the creative processes of young writers and their literary marketing strategies. The research method is qualitative, involving in-depth analysis of 10 popular Webtoons on the Webtoon platform that have been adapted into physical books, with emphasis on narrative elements, visuals, community interactions, and marketing patterns. Findings reveal that Webtoon fosters creativity through collaboration features and instant feedback, resulting in more dynamic original stories, while the transition to physical books enhances market visibility by 20-30% via digital promotion, although hindered by copyright complexities and production costs. The implications of this research underscore the importance of collaboration between traditional publishers and Webtoon to establish a hybrid literary ecosystem that sustainably supports Generation Z talent.

The Fréchet distribution is one of the commonly used Extreme Value Distributions (EVDs) in statistical modeling and heavy-tailed data analysis, where it plays an important role in describing product lifetimes as well as climatic and financial phenomena. The estimation of its two parameters, namely the shape parameter and the scale parameter, is traditionally based on the Maximum Likelihood Estimation (MLE) method. However, maximizing the likelihood function for this distribution involves numerical difficulties, which necessitates the use of numerical optimization methods. In this study, we propose the use of the Aquila Optimizer (AO), a recent metaheuristic algorithm inspired by the hunting behavior of eagles, as an efficient numerical tool for maximizing the likelihood function of the Fréchet distribution. The objective function was formulated as the negative log-likelihood function (-LogL), and the Aquila Optimizer was employed to obtain the optimal estimates of the distribution parameters. Several simulation experiments with different sample sizes were conducted to compare the performance of the proposed method with a conventional approach represented by the Nelder–Mead method, using the Mean Squared Error (MSE) criterion. The simulation results demonstrated that the Aquila Optimizer outperformed the Nelder–Mead algorithm in many cases, although the superiority was slight. The results also showed that both algorithms were consistent, as their MSE values decreased with increasing sample size. In addition, a practical application was carried out using real data, and the results of the survival function estimation indicated a good fit.

Public service is a key indicator in evaluating local government performance; however, various service issues continue to generate increasing public complaints. This study aims to analyze trends in public complaints, identify the most frequently reported institutions, and examine the types of maladministration and the status of complaint resolution through the Ombudsman of the Republic of Indonesia in South Sulawesi Province during 2023–2025. This study offers novelty by providing an integrated analysis of complaint trends, distribution of reported institutions, types of maladministration, and resolution outcomes based on Ombudsman data at the regional level. This research employs a qualitative approach using document analysis, with public complaint reports as the unit of analysis. Data were analyzed through data reduction, data display, and conclusion drawing. The results indicate that local governments are the most frequently reported institutions (55.1%), with dominant maladministration types including procedural deviations and prolonged delays. Several complaints were proven to involve maladministration and were resolved through the Ombudsman’s supervisory mechanism. These findings highlight that public complaints serve as an important instrument in enhancing accountability and transparency in public service delivery. Therefore, local governments need to strengthen service standards, improve the capacity of public officials, and develop more effective complaint management systems.

This study aims to analyze how human development governance is implemented by the Government of South Sulawesi Province in reducing regional disparities, identify institutional factors influencing implementation quality, and examine its implications for human development outcomes. The study employs a qualitative approach using a case study design. Data were collected through interviews with key informants from the Regional Development Planning Agency (Bappeda) and relevant Regional Apparatus Organizations, analysis of regional planning documents such as RPJMD and RKPD, and statistical data from the Central Bureau of Statistics related to the Human Development Index (HDI), poverty, and employment. Data were analyzed thematically using triangulation to ensure validity of findings. The results show that the Human Development Index has been positioned as a key performance indicator in regional development planning documents and prioritized in education and health sector policies. Although overall HDI achievement in South Sulawesi is categorized as high, significant disparities remain across regencies and municipalities, particularly in education and standard of living. A poverty rate of 8.06 percent and the increasing trend of the Gini Ratio indicate that distribution of welfare has not been fully equitable. Furthermore, the dominance of the informal sector in the employment structure reflects challenges related to job quality, income stability, and limited social protection coverage. These findings suggest that the main challenge of human development in South Sulawesi lies not only in improving aggregate indicators but also in strengthening bureaucratic capacity, cross-sectoral coordination, and policy implementation consistency to ensure more inclusive and equitable development across regions.

This study aims to analyze the effect of promotion and price on the purchase decision of IM3 SIM cards among the people of Maumere City. The study uses a quantitative method with a causal associative approach. Data was obtained through the distribution of questionnaires to respondents who use IM3 SIM cards, with a Likert scale instrument. Data analysis was carried out using multiple linear regression. The results of the study indicate that partially, promotion has a significant effect on purchase decisions, as does price, which is also proven to have a significant effect. Simultaneously, promotion and price have a significant effect on purchase decisions, with a coefficient of determination (R²) of 0.986. This means that 98.6% of the variation in purchase decisions is influenced by promotion and price, while the remaining 1.4% is influenced by other factors outside this study. These findings indicate that appropriate promotional strategies and proper pricing play an important role in enhancing consumer purchase decisions. The research results are expected to provide input for companies, particularly telecommunications service providers, to develop more effective marketing strategies.

The Low Voltage Main Distribution Panel (LVMDP) is a critical component in industrial power distribution systems, functioning to regulate, control, and distribute electrical energy to various production equipment. During operation, LVMDP panels often operate under high electrical loads, which may lead to temperature increases in their components. Undetected temperature rise can result in performance degradation, equipment failure, and even fire hazards. Therefore, an effective monitoring method is required to detect the condition of electrical components at an early stage. This study aims to analyze the temperature difference (ΔT) of LVMDP components using the Infrared Thermography method as part of predictive maintenance. The research employs a quantitative descriptive approach with data collected through direct observation from July 1 to July 31 at PT. Dongjin Indonesia. The data consist of hotspot and ambient temperatures measured from several panel components, which are then analyzed to calculate the temperature difference (ΔT) as an indicator of component operating conditions. The results indicate that the highest temperature difference is 26.5 °C in the capacitor bank, while the lowest is 4 °C in other components. All ΔT values are below the threshold limit of 50 °C, indicating that the LVMDP components are in safe operating conditions and do not require corrective actions. Thus, Infrared Thermography is proven to be an effective method for early detection of component conditions and can enhance the reliability and safety of industrial power distribution systems.

This study aims to analyze the employee turnover rate experienced by CV Premium Indonesia employees through the influence of workload and job stress. As a company engaged in the retail and distribution of mobile phone accessories from leading brands, the desire to leave the company often arises due to high workload and feelings of work stress because of the many demands within the company. The methodology used in this study is quantitative, employing SEM model data analysis with the help of SmartPLS software. The sampling technique used is saturated sampling, with a total sample of 127 respondents. The results of this study indicate that high levels of workload can increase employee turnover rates. Meanwhile, high levels of job stress experienced by employees can also increase employee turnover rates. These findings suggest that CV Premium Indonesia should address the issues of workload and job stress in order to retain employees. Effective strategies such as work-life balance, stress management programs, and workload adjustments could help reduce employee turnover and improve overall organizational performance.

The economy of a country, including Indonesia, is a system that encompasses all production, distribution, and consumption activities occurring within the country. In the economy, problems often arise that can affect the welfare of society. The problem formulation in this study is: How is the regulation and supervision of both internal and external banks carried out to prevent customer personal data leakage in credit agreements? And how is the responsibility of BPR Karya Sari Sedana towards the leakage of customer debtor data? The research method used is empirical legal research. The conclusion in the study is the protection of customer data against personal data leakage by understanding the forms of supervision from both internal and external parties conducted by the banking institution and referring to the OJK regulations that have been established, in order to minimize the recurrence of similar incidents and allow the public to conduct transactions safely without worrying about their personal data. Leaked by irresponsible individuals. The responsibility carried out by the banking sector currently, namely the Financial Services Authority Regulation Number 22 of 2023 concerning Consumer and Community Protection in the Financial Services Sector, also regulates consumer protection in the financial services industry. Forms in policies related to regulations in the banking world ensure that the public does not worry about their personal data.

This study analyzes the application of good governance principles in the context of Islamic financial service management at Baitul Maal wat Tamwil (BMT) Islam Berdaya Mandiri Kaitakan. This study uses a qualitative approach with a case study method, collecting data through in-depth interviews, participant observation, and analysis of internal documents. The results of the study show that the five principles of good governance transparency, accountability, responsibility, independence, and fairness have been adequately implemented, albeit with varying degrees of depth. Transparency is realized through routine financial reporting at the Annual Member Meeting, although access to daily information is still limited. Accountability is maintained through internal and external oversight mechanisms from the Cooperative Office, although independent external audits have not been carried out routinely. The institution's responsibility is reflected in its sharia compliance, which is supervised by the Sharia Supervisory Board, and the accuracy of its financial reporting. Independence is realized through a deliberative decision-making process, while fairness is applied in the form of non-discriminatory services and the distribution of financing based on field verification. The findings reveal that the main challenges lie in the digitization of information systems and limited resources for external audits. Overall, the implementation of good governance at BMT has created a governance foundation that is in line with sharia principles and modern public administration values, with room for improvement mainly in the optimization of information technology and institutional capacity building.