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In the rapidly evolving digital economy, the ability to anticipate transaction surges is a strategic asset for marketplace platforms to maintain operational efficiency. This research aims to build an accurate daily transaction volume forecasting system thru the implementation of an Extract, Transform, and Load (ETL) pipeline and Autoregressive Integrated Moving Average (ARIMA) predictive modeling. The dataset used is sourced from dataset_olshop.csv, which includes transaction history for the entire year of 2025. The ETL stage focused on data cleaning and handling missing values, while time series analysis began with the Augmented Dickey-Fuller (ADF) stationarity test, which yielded a significant p-value of 0.000006. The parameter model was optimized using the auto_arima algorithm, which determined the ARIMA(2,0,0) configuration as the best model. The evaluation results of the model show fairly stable performance with a Root Mean Squared Error (RMSE) value of 2.002 and a Mean Absolute Error (MAE) of 1.704 on the test data. Research findings reveal a consistently higher purchasing pattern during the mid-month and end-of-month periods, with an average of 5.52 daily transactions, compared to the beginning of the month, which saw 5.48 transactions. The 30-day forecast results provide valuable insights for online store managers to proactively adjust inventory and logistics workforce allocation strategies. This research concludes that integrating data engineering techniques and statistical analysis can provide predictive solutions for the dynamics of the digital market.

Indonesia, as a country with the highest seismicity in the world, requires an accurate earthquake prediction system through the use of the BMKG earthquake catalogue. This research aims to implement ETL-based data pipeline engineering to process 92,887 earthquake catalog entries for the 2008-2023 period into ready-to-use daily time series for the LSTM seismicity forecasting model. The ETL process includes raw data extraction, cleaning of 97% missing values columns on focal mechanism parameters, datetime conversion, daily resampling producing 5,200 entries with earthquake count, total magnitude, and average magnitude features, as well as Min-Max Scaler normalization for LSTM compatibility. The dataset was processed using Google Colab with a stacked LSTM architecture of two layers of 50 and 25 units, dropout 0.2, Adam optimizer, and a sequence window of 30 days to predict the daily earthquake count. The model trained for 100 epochs shows the ability to capture stable seismic activity trends with a consistent decrease in MSE loss, although it shows deviations in extreme spikes due to aftershock sequences. The ETL pipeline proved crucial in ensuring temporal consistency, 100% data completeness, and relevant physics representation, resulting in a reproducible end-to-end framework for disaster mitigation.

This study aimed to analyze efforts to optimize official residence rental retribution as one of the sources of Local Own-Source Revenue (PAD) in Sikka Regency. The main problem identified was the accumulation of official residence rental arrears due to the low awareness of Civil Servants (ASN) in fulfilling their payment obligations. The method used was qualitative, with data collection techniques conducted through observations and interviews during the internship program. The results of the study showed that the Regional Financial and Asset Management Agency (BPKAD) had implemented various strategic measures, such as mapping priority areas in six sub-districts, standardizing rental values through an appraisal team, and implementing a non-cash payment system through Bank NTT based on Sikka Regent Regulation No. 22 of 2024. However, strengthening law enforcement and the digitalization of asset management still need to be improved to minimize arrears

Hospitals often face difficulties in determining patient treatment priorities due to limited medical resources and the uncertainty of patient conditions. Conventional prioritization methods tend to rely on subjective judgment, which can lead to inconsistent decisions and delays in treatment. This study aims to apply fuzzy logic in a decision support system to determine patient priority levels more objectively and systematically. The proposed method utilizes a fuzzy inference system that processes several criteria, including the severity of symptoms, vital signs, patient age, and waiting time. These criteria are represented as fuzzy sets and evaluated using a set of inference rules to generate priority classifications. The results indicate that the fuzzy logic–based system is able to classify patient priorities more consistently and transparently compared to manual assessment. The system provides clear priority categories that can support medical staff in making faster and more accurate decisions. The findings imply that the implementation of fuzzy logic in hospital decision support systems can improve the quality of healthcare services, enhance fairness in patient handling, and optimize the allocation of medical resources, particularly in emergency and high-demand situations.

Stock price prediction remains a complex challenge due to the dynamic and non-linear nature of financial markets, especially for banking stocks like PT Bank Negara Indonesia (Persero) Tbk (BBNI). This study aims to optimize BBNI stock price forecasting by integrating an automated Extract, Transform, Load (ETL) pipeline with the Long Short-Term Memory (LSTM) algorithm within a data engineering framework. Historical data from 2019 to 2025 were processed through a structured ETL sequence—including data cleaning, feature engineering, and MinMaxScaler normalization—to ensure high data quality. The dataset was partitioned into 80% for model training and 20% for testing to ensure rigorous evaluation. The results demonstrate that the systematic ETL approach significantly enhances model stability and predictive accuracy compared to conventional methods. The LSTM model effectively captured long-term temporal dependencies, providing reliable trend forecasts with an impressive test accuracy, achieving a Root Mean Squared Error (RMSE) of 0.0354. This research underscores that integrating robust data engineering practices with deep learning is essential for building resilient financial decision-support systems.

Land and Building Tax for Rural and Urban Areas (PBB-P2) is one of the sources of Regional Original Revenue that has a strategic role in supporting regional development financing. However, the optimization of PBB-P2 revenue still faced various problems, especially related to the inaccuracy of tax object and subject data. This study aimed to analyze the optimization of PBB-P2 revenue through the implementation of verification and validation in increasing PAD at the regional Revenue Agency (BAPENDA) of Sikka Regency. The research method used was a qualitative approach with data collection techniques through interviews, observations, and documentation.                 The results showed that the implementation of verification and validation of PBB-P2 data was able to improve the accuracy of the tax database, refine the determination of the Tax Object Sales Value, and reduce data discrepancies between the system and field conditions. These efforts had a positive impact on increasing the realization of PBB-P2 revenue and its contribution to PAD of Sikka Regency. Nevertheless, the implementation of verification and validation still faced several obstacles, such as limited human resources, suboptimal utilization of information technology, and low awareness among some taxpayers. Therefore, strengthening the data collection system, increasing the capacity of apparatus, and enhancing inter-agency synergy were required to optimize PBB-P2 revenue sustainably.

Focusing on Yuli Bakery, this study aims to examine in depth how production planning budgets and cost effectiveness influence business profitability, particularly in the food and bakery industry sector. This research is based on the assumption that effective production planning can optimize the utilization of available resources, minimize raw material waste, and establish more efficient and structured business operational performance. The study explores the implementation of labor management, raw material management, and production process control oriented toward cost efficiency without reducing product quality, thereby enabling sustainable profitability improvement. The results of the analysis show that Yuli Bakery successfully reduced its cost of goods sold (COGS) by IDR 12,800,000, which directly contributed to an increase in operating profit and gross profit. This cost reduction did not affect overall production volume nor generate additional expenses in other cost components. These findings indicate that even in the absence of significant revenue growth, cost optimization through proper production planning can make a substantial contribution to improving Yuli Bakery’s profitability.

This research is based on the problem of declining morals of third-grade students at SD IT Baitul Muslim, which has implications for daily behavior, particularly in Pancasila Education learning. Students tend to exhibit attitudes that are inconsistent with positive character values, such as a lack of tolerance and a low sense of love for the homeland. The purpose of this study is to identify the significant influence of educators' roles in shaping the character of third-grade elementary school students in Pancasila Education subjects. The method used is an ex post facto method with a quantitative approach and a purposive sampling design. The study population consisted of 10 educators and 95 students, with a sample of 10 educators and 40 students from two selected classes. Data collection techniques were carried out through questionnaires and documentation that had been tested for validity using Aiken's V and reliability with Cronbach Alpha. Hypothesis testing using simple linear regression analysis showed a significance value of 0.044 which is smaller than 0.05 and a calculated F value of 5.692 which is greater than the F table of 2.27. Thus, the null hypothesis is rejected and the alternative hypothesis is accepted. The research findings confirm the significant influence of educators, particularly as demonstrators, classroom managers, facilitators, and evaluators, in shaping students' character in Pancasila Education. The implication of these findings is that educators need to optimize role models to improve students' character development.

Lifting activities are an essential part of manual material handling across various industrial sectors and constitute a primary source of ergonomic risk exposure when performed with inappropriate work postures. The use of hands-off tools such as push-pull sticks is often implemented to maintain a safe distance between workers and loads and to reduce exposure to line-of-fire hazards. However, the implementation of work aids does not automatically ensure neutral work postures, as push-pull techniques, reach distances, and environmental conditions can still lead to awkward postures. This study aims to evaluate the work posture risk in lifting activities using a fiber-composite push-pull stick based on the Rapid Entire Body Assessment (REBA) method. The research was conducted as an observational analytic field study involving nine workers in tubular pushing and pulling activities. Work postures were documented through direct observation and visual recordings, then assessed using REBA to obtain risk scores, risk categories, and required corrective actions. The results indicate that work postures fall into the medium to high-risk categories, with trunk and shoulder components being the dominant contributors. These findings confirm the need for improvements in work methods, ergonomic training, and strengthening of lifting SOPs to optimize the safety and ergonomic benefits of work aids.

Public service quality plays a crucial role in ensuring that social assistance is delivered effectively to vulnerable communities. This study aims to analyze the quality of public services in the distribution of social assistance by the Social Service Office of Kerinci Regency and to identify improvement efforts undertaken by the institution. This research employed a descriptive qualitative approach using observation, interviews, and documentation techniques. Informants consisted of Social Service officials, social facilitators, and beneficiary communities. Service quality analysis was conducted using the SERVQUAL dimensions: tangible, reliability, responsiveness, assurance, and empathy. The findings indicate that the social assistance distribution service in Kerinci Regency is generally adequate, particularly in the assurance and empathy dimensions. Beneficiaries feel that services are delivered fairly, transparently, and without discrimination. However, obstacles remain in the tangible, reliability, and responsiveness aspects, including limited service facilities, inaccurate beneficiary data due to incomplete DTKS updates, and delays in assistance distribution in remote areas caused by geographical constraints. To address these challenges, the Social Service Office has implemented periodic data validation, strengthened coordination with village administrations, and optimized digital-based social service information systems. This study provides empirical evidence that can serve as an evaluation reference for local governments in improving transparent, effective, and equitable social assistance services.

Tax Management refers to a company’s efforts to manage its tax obligations efficiently and legally in order to optimize net income. This study aims to examine the effect of Fixed Asset Intensity and Leverage on Tax Management, with Profitability as a moderating variable, in mining companies listed on the Indonesia Stock Exchange (IDX) for the 2021–2024 period. This research is conducted because tax management practices are considered to potentially influence corporate profitability and financial performance. The study is grounded in Agency Theory and employs a quantitative approach. The sample was selected using purposive sampling, resulting in 28 companies observed over four years, with a total of 112 secondary data observations obtained from annual reports or financial statements. Data analysis was performed using EViews 13 with a Moderated Regression Analysis (MRA) approach. The findings indicate that: (1) Fixed Asset Intensity has no significant effect on Tax Management; (2) Leverage has a significant negative effect on Tax Management; (3) Profitability does not moderate the relationship between Fixed Asset Intensity and Tax Management; and (4) Profitability strengthens the effect of Leverage on Tax Management.

The rapid development of the digital era requires human resources to not only master software, but also understand hardware infrastructure. This community service program aims to improve the technical competence and digital literacy of the people of Pati Regency through a PC assembly and optimization workshop. The method used is the Participatory Action Learning Sistem (PALS), in collaboration with "Pati Tech" as an industry partner, and utilizing the campus computer laboratory as a training center. Activities consisted of orientation, planning, and hands-on practice in PC assembly. The results of the community service program showed a significant increase in the technical skills of participants, as reflected in the average pre-test score of 52.5 which increased to 86.4 in the post-test. Participants are now able to assemble and optimize sistem independently. The implication of this activity is the formation of independent digital talents who can manage digital infrastructure, which is expected to support the development of the local creative economy in Pati Regency. This program contributes to improving technological skills relevant to the needs of the digital market.

This research aims to analyze the strategies for increasing Local Own-Source Revenue (Pendapatan Asli Daerah/PAD) implemented by the Regional Revenue Agency (Badan Pendapatan Daerah/Bapenda) of Surabaya City. As the second largest city in Indonesia and the capital of East Java Province, Surabaya has significant potential for local revenue that needs to be optimized to support regional development. Using SWOT analysis framework and strategic management theory from David, this study examines the strengths, weaknesses, opportunities, and threats in PAD management, as well as the strategies formulated and implemented to increase revenue. This qualitative research employs a descriptive approach with data collection through in-depth interviews, observation, and documentation study at Bapenda Surabaya City during June-August 2025. Informants include agency leaders, division heads, tax and retribution collectors, and taxpayers. The results indicate that Surabaya City has successfully increased its PAD from Rp 5.2 trillion in 2022 to Rp 6.8 trillion in 2024, representing a 31% growth. Key strategies implemented include digital transformation of tax services through e-tax system, intensification of existing tax sources, extensification through identification of new taxpayers, improvement of taxpayer compliance through education and enforcement, and inter-agency collaboration for data integration. The study identifies several challenges including tax evasion, outdated property valuations, and limited human resources. This research recommends strengthening digital infrastructure, updating tax object databases, enhancing taxpayer awareness programs, improving coordination with central government, and developing performance-based incentive systems for revenue collectors.

This community service initiative provides a comprehensive business analysis to evaluate financial feasibility, aiming to mitigate potential losses and ensure operational viability. By offering concrete data on business prospects and challenges, this analysis serves as a strategic guide for resource allocation and market targeting, while simultaneously enhancing attractiveness to potential investors. The program was conducted in the South Nunukan District, Nunukan Regency, North Kalimantan. As Indonesia's 34th province and a strategic border region, North Kalimantan faces significant challenges in food security due to limited supply chains. A central component of this study is the Break-Even Point (BEP) analysis—the threshold at which a business incurs neither profit nor loss. The BEP analysis provides critical insights into the relationship between pricing, operational costs, sales volume, and production levels. Consequently, it serves as a vital decision-making tool for business owners to optimize profitability. The results of this study demonstrate that, despite the continued use of traditional methods, the polyculture system remains highly profitable and sustainable for the local community.

Urban waste management remains a major challenge in achieving a clean and sustainable environment, including in Bontoduri Sub-district, Makassar City. Waste banks, as a community-based waste management model, have significant potential to reduce waste generation while creating economic value. However, in practice, the role of waste banks has not been fully optimized due to limitations in institutional capacity, community participation, and managerial practices. This community service activity aimed to strengthen the role of waste banks in promoting a clean and economically valuable environment through participatory and community empowerment approaches. The methods employed included preparation, environmental education and socialization, waste bank management training, institutional mentoring, and activity evaluation. The program involved approximately 30 participants consisting of waste bank managers, local government representatives, and community members. The results indicated an increase in community awareness and understanding of waste segregation, improved managerial and administrative capacities of waste bank operators, and enhanced community participation in waste-saving activities. In addition, waste banks contributed to generating added economic value from household waste and reducing the volume of waste disposed of into the environment and landfills. This activity concludes that strengthening the role of waste banks through education, training, and continuous mentoring can serve as an effective strategy to support sustainable urban waste management based on circular economy principles.

The increasingly rapid digital transformation demands that MSMEs optimize technology not only in business processes but also in human resource management. Although HR digitalization is believed to improve organizational effectiveness, research on the psychological mechanisms and role of leadership in the context of e-commerce MSMEs is still limited. This study used a quantitative approach with an explanatory survey method and involved 366 respondents from e-commerce MSMEs in various regions of Indonesia. Data analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) techniques to test direct relationships, mediation, and moderation. The results showed that digital HR practices have a positive and significant effect on employee performance. The digitalization of HR functions, such as e-recruitment, e-learning, HRIS, and digital performance management, can improve work effectiveness and the quality of work output. Furthermore, work engagement was shown to mediate this relationship, meaning that employees perform better when they feel more passionate, dedicated, and involved in their work. This mediating role emphasizes the importance of psychological aspects in the successful implementation of digital HR. Leaders who possess a digital vision, provide technological support, and encourage innovation have been shown to increase employee motivation and comfort in working using digital systems. Overall, this study confirms that the success of digital transformation in e-commerce MSMEs is determined not only by the technology used, but also by leadership support and employee engagement. These findings provide important contributions to the digital HR management literature and offer practical implications for MSME owners in increasing competitiveness in the digital era.

Punctuality is a crucial factor in ship repair projects because it directly affects operational efficiency, project costs, and the utilization rate of shipyard facilities. Delays in work completion can lead to increased costs, disruption of ship operational schedules, and decreased shipyard productivity. Therefore, this study aims to analyze and optimize the repair scheduling of Ship X at PT XYZ using the Critical Path Method (CPM). The research data were obtained from the actual project schedule compiled using Microsoft Project software, including the duration of each activity and the dependency relationships between tasks. The analysis results show that the project has one main critical path with a total duration of 74 hours. Most activities are on the critical path with a float value of 0 hours, while the Non-Destructive Test Penetrant Testing activity has a time slack of 1 hour. The application of the CPM method has proven effective in identifying critical activities, improving schedule control, and supporting managerial decision-making in optimizing ship repair projects.  

The E-Kinerja Program is a policy innovation developed by the Madiun City Government to support the digitalization of civil servant performance management as part of bureaucratic reform and the implementation of the Electronic-Based Government System (SPBE). This study aims to evaluate the implementation of the E-Kinerja Program in Madiun City using six policy evaluation criteria proposed by William N. Dunn, namely effectiveness, efficiency, adequacy, equity, responsiveness, and appropriateness. This research employs a qualitative descriptive approach, with data collected through interviews, direct observation of the E-Kinerja application usage, and documentation review of related policies. The findings indicate that the E-Kinerja Program is relatively effective and efficient in supporting the monitoring of civil servant attendance and daily activities through features such as QR Code-based attendance, photo documentation, and daily activity reporting. However, several challenges remain, including unstable GPS accuracy, limited internet connectivity, and the practice of non real time input of daily activities. In addition, differences in digital literacy levels and device compatibility among civil servants affect the equitable utilization of the application. Overall, the implementation of the E-Kinerja Program is considered appropriate as part of bureaucratic digital transformation in Madiun City, although further improvements in technical aspects and human resource capacity are required to optimize its implementation.

The commercial sector, especially the hospitality industry, is one of the largest consumers of electrical energy, with energy costs often ranking as the second highest operational expense. This study aims to conduct a specific Electrical Energy Audit in the Office Engineering unit of Aston Denpasar Hotel & Convention Center to optimize electricity usage and improve energy efficiency. The research applies a detailed audit approach with a focus on lighting systems and air conditioning (AC), which are major contributors to energy consumption. The initial stage involves calculating the actual Energy Consumption Intensity (IKE) in kWh/m²/month and comparing the results with ASEAN and SNI standards to determine the efficiency classification of the building. Data collection is carried out through direct field measurements as primary data, using instruments such as a Clamp Meter and Lux Meter. The expected outcome of this study is the identification of detailed Energy Saving Opportunities (ESO), along with the estimation of potential monthly energy cost savings and the calculation of the investment Payback Period.

This study is motivated by the importance of financial and asset management strategies in supporting the operational effectiveness of the Regional Disaster Management Agency (BPBD) of Central Sulawesi, which plays a strategic role in disaster mitigation, preparedness, emergency response, and post-disaster recovery. The main problems addressed are how financial and asset management strategies are implemented, to what extent they affect operational effectiveness. The objectives of this research are to analyze the applied strategies, assess their influence on operational effectiveness, and identify challenges as well as relevant solutions.The literature review refers to public financial management theories, regional asset management, and previous studies highlighting the relationship between financial governance, accountability, and public sector performance. This study employs a quantitative approach with a descriptive design. Data were collected through literature study, observation, interviews, and questionnaires distributed to BPBD staff in finance and asset divisions. The analysis included validity and reliability tests, along with multiple linear regression to examine the effect of independent variables on operational effectiveness. The findings show that BPBD Central Sulawesi’s financial management strategy in 2024 achieved a realization rate of 89–100% in most programs, although imbalances were found in certain activities such as the disaster management system arrangement, which only reached 38%. In terms of asset management, fixed assets dominate with a book value of IDR 19.6 billion, with significant growth in equipment and machinery. Regression analysis results indicate an R² value of 0.817, meaning that 81.7% of operational effectiveness is influenced by financial and asset management strategies, while the remaining 18.3% is explained by other factors.The study concludes that financial and asset management strategies significantly affect BPBD’s operational effectiveness. Nevertheless, challenges such as limited human resources, inadequate information systems, and discrepancies in budget realization require solutions through capacity building, technology utilization, and improved planning mechanisms to optimize disaster management effectiveness.