Publication Search

The development of modern times is marked by the increasing number of companies that facilitate people’s daily activities, one of which is freight forwarding service companies. This condition has led to increasingly intense competition among delivery service companies, requiring each company to implement appropriate strategies in order to maintain its existence and win the competition. One method that can be used to analyze marketing competition strategies is game theory. Game theory is a mathematical concept used to analyze decision-making in competitive situations involving two opposing parties. This study aims to analyze the competition between JNE and J&T using a game theory approach. The method employed is linear programming with the assistance of the POM QM 5.0 application to determine the optimal strategies for each company. The results show that the optimal game value obtained is -1.715. Under these conditions, the optimal strategy for JNE involves a mixed strategy consisting of pricing, delivery estimation, and service security strategies. Meanwhile, the optimal strategy for J&T involves a combination of delivery punctuality, service security, and online application strategies.

The study investigates the impact of governance on firm value, along with the moderating role of institutional ownership, among companies operating in the consumer cyclicals and consumer non-cyclicals sectors listed on the Indonesia Stock Exchange (IDX) over the 2021-2023 period. Drawing on a sample of 42 companies and 126 observations, a quantitative panel data approach was adopted, with data gathered through purposive sampling. The Bloomberg Governance Score was used to measure governance, Tobin's Q served as a proxy for firm value, institutional ownership was the moderating variable, and firm size, leverage, and profitability were included as control variables. Model selection was conducted using the Chow and Hausman Tests in EViews 14, which indicated that the Random Effects Model (REM) was the most suitable estimation approach. The findings reveal that governance does not exert a significant influence on firm value. Furthermore, institutional ownership is unable to strengthen the relationship between governance and firm value. These results suggest that ESG-based governance signals have not yet been optimally absorbed by investors in the Indonesian capital market; hence, reinforcing governance reporting standards and enhancing investor ESG literacy are considered essential steps toward integrating non-financial information into investment decision-making.

This study aims to estimate coal resources using the kriging method at PT. Inti Bara Perdana, Taba Penanjung, Bengkulu. Geostatistical analysis was applied to evaluate spatial variability of coal quality parameters, including total moisture (TM), inherent moisture (IM), ash content (ASH), volatile matter (VM), fixed carbon (FC), and calorific value (CV). The research utilized drilling data with an average spacing of 80 meters. Variogram modeling was conducted using SGeMS software, employing spherical models to determine nugget, sill, and range parameters. The results show a low nugget effect (0%) indicating strong spatial continuity. The obtained ranges vary between 180–1296 meters depending on the parameter. Blo./ck kriging estimation was performed using block dimensions of 25 × 25 × 8 meters and a coal density of 1.3 ton/m³. The total estimated coal resource up to an elevation of 230 m is 253,500 tons. These findings demonstrate that kriging provides reliable resource estimation and supports mine planning optimization. This research contributes to improving coal resource evaluation accuracy and operational decision-making in open-pit mining.

This research try to examine how investment choices in property and real estate sector businesses listed on IDX (2020-2024) are impacted by the cost of debt and equity.For the accuracy of the analysis, this study also uses firm size and profitability as controler. Purposive sampling was used in the sampling process, which produced seven qualifying organizations with a total of 35 observations over a five-year period. Panel data regression was used for data analysis, and the Common Effect Model was shown to be the best estimation model. The findings show that investment decisions are significantly influenced by firm size, profitability, cost of debt, and cost of equity all at the same time. Nonetheless, investment choices are not much impacted by the cost of debt. Similarly, it has been demonstrated that the cost of equity has no appreciable effect on the capital expenditures of the businesses. Firm size has a favorable and substantial impact, making it the main motivator for investment activity in the real estate industry. During the study period, investment decisions were not significantly impacted by profitability. These results show that, especially in the post-pandemic economic recovery era, asset capacity and economies of scale are more important for the viability of real investment projects for property firms on the IDX than yearly variations in capital costs.

This study aims to analyze and design the electrical installation requirements for a prototype residential building with dimensions of 11 × 19 meters. The research applies a technical calculation approach based on lighting standards, air conditioning capacity estimation, load analysis, and electrical protection planning. Lighting requirements were determined using the lumen method by considering room area, illumination standards, coefficient of utilization, and light loss factor. Air conditioning capacity was calculated based on room area and standard cooling load values in BTU/hr. Furthermore, total electrical loads were analyzed to determine installed capacity, nominal current, Miniature Circuit Breaker (MCB) ratings, and appropriate cable cross-sectional areas with safety factors applied. The results indicate that proper load grouping, appropriate MCB selection, and correct cable sizing significantly enhance system safety and reliability. The study provides a systematic planning model for residential electrical installations that meets safety, efficiency, and technical standards, and can serve as a reference for similar residential building designs.

Pneumonia remains a leading cause of morbidity and mortality worldwide, particularly in resource-limited settings and among elderly populations, where timely diagnosis and continuous monitoring are often constrained by limited clinical infrastructure. This study presents an edge–cloud–integrated framework for early pneumonia risk monitoring, leveraging multimodal wearable sensors and deep learning to support continuous short-duration monitoring. The proposed system is designed to operate in near real time under simulated deployment conditions, continuously acquiring and analyzing physiological signals (respiratory rate, heart rate, SpO₂, and body temperature) alongside event-driven acoustic biomarkers (cough sounds) within a distributed architecture. A lightweight edge module performs local signal preprocessing and anomaly triage, selectively transmitting salient information to a cloud-based multimodal deep learning model for refined risk estimation and interpretability analysis. The framework was evaluated using a multi-source dataset comprising public repositories (MIMIC-III and Coswara) and a clinically supervised wearable study conducted in two Nigerian hospitals, resulting in 718  hours of quality-controlled multimodal monitoring data. In a pooled multi-source evaluation, the system achieved an AUC of 0.95, while in a clinically realistic local-only evaluation, the AUC was 0.86, reflecting a consistent but preliminary diagnostic signal. These results highlight the importance of local data adaptation for real-world applicability and suggest that multimodal AI can provide meaningful early risk indicators under resource constraints. Beyond predictive performance, this work demonstrates the feasibility of integrating multimodal learning, edge–cloud computation, and explainable analytics into a deployment-aware, privacy-preserving monitoring framework for low-resource healthcare environments.

Indonesia’s Oil and gas project construction continue face challenges notably delays that lead to underperformance. This study tries to describe the factors that causing delays in EPC oil and gas project in Indonesia from project management view. Started by overall study on cause of delays in construction worldwide, thus phenomenon on neighboring country (Malaysia) where Indonesian workers involved, then study continues with factors in Indonesia as overall, and include specific project which are South Sumatera and Sumbawa. Three main factors are always present in the cause of delays in EPC Project in Indonesia namely; contractor’s financial problem in funding the project, poor project planning and estimation leads to unrealistic determination of the duration, and ineffective change management by owner in project showed in resolving contract dispute, requirement changes, and dispute in understanding in contract articles. These factors are clearly present in EPC projects in Indonesia as main contributor in project delays together with two additional factors namely legal awareness and social community problems.

The foundation of turbine machines in industrial buildings must be able to withstand static and dynamic loads caused by operational vibrations. Generally, reinforced concrete block foundations are used due to their good stability. However, under certain conditions such as limited land, decreased soil bearing capacity, and the need for structural rehabilitation, their application becomes less effective. Therefore, this study aims to analyze the use of Micropile foundations as an alternative for turbine machine foundations at Candi Baru Sugar Factory, Sidoarjo.The research method includes literature studies, soil data collection through Cone Penetration Test (CPT), machine technical data analysis, and the design and analysis of Micropile foundations. The analysis covers bearing capacity, settlement, dynamic response, pile cap design, and cost estimation.The results indicate that Micropiles with a diameter of 0.20 m, a length of 2 m, five piles, and a pile cap size of 2 m × 2 m × 4.5 m are able to safely and stably support the machine load. In addition, this system is considered more efficient in terms of construction time and implementation. Therefore, Micropile foundations are recommended as an effective and economical alternative for turbine machine foundations.

Problems in the transmission box of the Drilling Machine 438-02-814-0925 type (0.75 HP, 230/400V, 1425 rpm, produced in 1988) are the degradation of mechanical components for the pulley, V-belt, and rolling bearing. The purpose of maintenance and repair planning is to obtain maintenance costs, maintenance schedules in the period 2026, and the ratio of maintenance costs to profits. The maintenance and repair planning method includes collecting previous maintenance data; application of the inspection-replace-repair-overhaul (IRRO) method; evaluation of the working conditions of components, especially on the pulley, V-belt, spindle pulley (driven pulley), and rolling bearing; prediction of component service life; prediction of repairman costs; prediction of supporting equipment that will be used in maintenance; prediction of spare part replacement time or reinstallation of components after repair; estimation of maintenance and repair costs in 2026; and calculation of the ratio of maintenance costs to profits. The results of maintenance and repair planning obtained maintenance costs in 2026 amounting to Rp 4,627,000 with an estimated Drilling Machine rental rate of Rp 75,000/hour which has the opportunity to be rented for 400 hours/year, and a maintenance cost to profit ratio of 15.42% which implies that the Drilling Machine still has the opportunity to generate profits and is suitable for use in the coming years.

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.

The study aimed to find out the nature of the budget, know the modern techniques of preparing and implementing the budget, and the consequences of preparing budget based on the modern techniques on performance of government. The descriptive-analytical approach was used to meet the objectives and hypotheses of the research. The data was gathered through a questionnaire whereby 60 questionnaires where distributed to a sample population of accountants working in the Financial Affairs Department at the General Directorate of Education in Wasit Governorate (Iraq), and 57 questionnaires were collected to establish the views of the accountants regarding the effect of preparing and implementing budgets under the modern techniques on the government performance. This paper came up with a number of conclusions. Preparation of the general budget of the state is a technical and political process that involves and is involving different actors in the state. The budget preparation process is a technical process since it involves numerous key calculations that can be used to quantify the anticipated revenues, the cost of activities likely to be obtained in the year and estimation of the planned expenditures. The process of preparing the budget through the traditional ways (line-item budgeting) does not contribute to the optimal planning and budget allocation of the state and, therefore, the fulfillment of the goals laid out by the countries. This paper advises on the need to focus on the current approaches in the budget preparation because they enhance governmental performance, enhance the effectiveness and efficiency of state expenditures, strive to diversify the income, and convert the policies and goals of the state into a definite and actualized reality on the ground, with the help of standards and indicators that modern means of preparing the budget have offered. And to act to modernize the budget system in Iraq, profiteering with the experience of other countries in this domain, and that modernization be a progress, commencing with the budgeting of some ministries or departments within ministries and bodies gradually with the aim of acquiring more experience and expertise, and then meet the impediments which will emerge to proceed to a complete transition.

This study examines the relationship between Corporate Social Responsibility (CSR) disclosure and tax avoidance, with CEO Overconfidence considered as a moderating factor. The research focuses on non-cyclical consumer goods companies listed on the Indonesia Stock Exchange during the 2022-2024 period. Using annual and sustainability reports, the analysis employs multiple linear regression and moderated regression analysis (MRA). Robust standard errors based on the Newey-West method are applied to ensure reliable estimation. The results indicate that CSR disclosure does not have a significant direct effect on tax avoidance. However, CEO Overconfidence significantly moderates the relationship between CSR disclosure and tax avoidance, highlighting the role of executive behavioral characteristics in corporate tax decisions. These findings suggest that CSR disclosure alone is insufficient to explain firms’ tax avoidance behavior without considering managerial traits. The study contributes to the literature by integrating behavioral perspectives into tax avoidance research and emphasizing the importance of executive oversight in aligning CSR practices with responsible tax behavior.

Nickel has become a strategic mineral in the global industrial value chain, particularly for stainless steel production and electric vehicle battery manufacturing. As one of the world’s largest nickel producers, Indonesia has implemented a downstream industrialization policy aimed at increasing value added and strengthening export performance. This study analyzes the effects of international nickel prices, destination countries’ GDP per capita, exchange rates, and the downstreaming policy on the value of Indonesia’s nickel exports (HS 75) over the period 2010–2023. The study employs a quantitative approach using panel data regression with secondary data covering five major export destination countries, namely China, Japan, South Korea, Thailand, and Singapore. Based on the Chow and Hausman tests, the Fixed Effects Model is selected as the most appropriate estimation technique, indicating the presence of country-specific heterogeneity among importing countries. The results show that destination countries’ GDP per capita and international nickel prices have a positive and statistically significant effect on Indonesia’s nickel export value. The downstreaming policy dummy variable also exhibits a positive and significant impact, suggesting that the nickel ore export ban implemented since 2020 has effectively shifted export composition toward higher value-added processed nickel products. In contrast, exchange rates are found to have no significant effect on export performance. Overall, the findings provide empirical evidence supporting the effectiveness of Indonesia’s downstream industrialization policy and highlight the importance of global demand conditions in driving the performance of processed nickel exports.

Unemployment is a socio-economic problem that can threaten the stability of the Indonesian economy. This study analyzes the effect of minimum wages, exports, foreign investment, and the human development index (HDI) on the unemployment raefrom 1990 to 2023. Using the Ordinary Least Square (OLS) multiple linear regression estimation method, to correct bias in the estimation, the Newey-West HAC standard errors approach is used. Minimum wages and foreign investment have a significant negative effect on the open unemployment rate, confirming that wage increases can boost productivity, foreign investment creates direct jobs through the construction of production facilities and economic multiplier effects in supporting sectors. The most surprising finding of the HDI which has a positive effect and exports which are proven to be insignificant on the unemployment rate, this shows that human capital formation is not in line with existing job opportunities due to rapid technological changes, as well as export-increasing policies which focus more on capital intensity. The study provides important implications for policymakers, maintaining and optimizing minimum wage increases and foreign investment in a measurable manner because they have proven effective in reducing unemployment rates. Reorienting export strategies policy from capital-intensive to labor-intensive, increasing the human development index adjusted to technological developments, especially in the business and industrial world.

The implementation of the zoning-based admission policy (PPDB) in Semarang City continues to face challenges related to the accuracy of distance measurement and the transparency of information provided to the public. This study aims to examine the application of Geographic Information Systems (GIS) in defining zoning boundaries for public junior high schools in Semarang City and integrating the results into a web-based information platform. A quantitative descriptive approach was employed, incorporating spatial analysis through a 3-kilometer buffer radius using QGIS software. The results indicate that buffer analysis is effective in delineating priority domicile zones based on school coordinate data. These findings are integrated into a GIS-based website that presents visual information on school locations, enrollment capacity, and final score calculation mechanisms in accordance with current regulations. The proposed system contributes to improving information transparency, enabling the public to better understand admission opportunities while supporting government decision-making in promoting equitable access to education. For future development, the use of road network analysis is recommended to obtain more realistic distance estimations.

Depth perception is a crucial visual ability for humans to judge distance and understand three-dimensional space. However, the brain's distance estimation is not always accurate and is often influenced by external factors such as color. This study aims to examine in depth how orange color influences the acuity of human depth perception. The method applied is a Systematic Literature Review (TLS) by examining 8 research papers from repository data from Google Scholar and ScienceDirect databases ranging from 2007 to 2025. The results show that orange, as part of the warm color spectrum with a long wavelength, significantly creates an advancing color effect that makes objects perceived as closer than cool colors. The main findings reveal that orange provides superior visual acuity in low-light conditions and has a wide stereoscopic disparity range to help the brain map space. In conclusion, the color orange functions as an effective additional visual cue in strengthening spatial perception. The implications of this research are highly relevant for the development of Augmented Reality (AR) technology and visual safety design, where the use of orange can minimize distance estimation errors by users

The development and revitalization of the Sungai Asam drainage system in Jambi City face serious problems in the form of river sedimentation and limited channel capacity, which trigger flooding. These conditions necessitated a design change for bank protection from revetment to a retaining wall (Dinding Penahan Tanah/DPT) in the SA223 to SA228 segment. This study aims to analyze the construction cost and implementation duration of the DPT resulting from the design change. The theoretical framework covers retaining wall concepts, cost estimation (Bill of Quantities), and construction project scheduling. A descriptive-analytical method was applied using secondary data, including design drawings, work volumes, the 2025 Water Resources and Human Settlements Unit Price Analysis (AHSP), the 2025 Jambi Provincial Standard Unit Prices, and time analysis using the S-Curve and Critical Path Method (CPM). The results indicate that the total construction cost of the DPT in the SA223–SA228 segment is IDR 9.524.259.092,02, while the project duration is determined based on the critical path identified through CPM analysis. The discussion confirms that the design change significantly affects work complexity, construction costs, and schedule adjustments. The study concludes that systematic and measurable cost and time analyses are essential as a technical basis for decision-making in river revitalization projects to ensure effectiveness, efficiency, and the sustainability of flood control infrastructure.

This study aims to analyze the operational and marketing strategies of UMKM Bolu Kambu Daeng Rosi in enhancing the competitiveness of traditional food products in Barru Regency, South Sulawesi. The research uses a descriptive qualitative approach with a case study method, through guided observation, semi-structured interviews, and documentation. The findings show that the enterprise's strengths lie in its culturallybased product differentiation and strong customer loyalty. However, the business still faces challenges in managerial aspects, digital promotion, and operational recording. SWOT analysis highlights the importance of strengthening production systems and applying simple marketing strategies to expand market reach. In addition, a daily profit and loss estimation shows a relatively high profit margin, though not yet supported by a documented financial system. The main recommendation is the need for gradual managerial transformation through simple financial record-keeping, basic visual promotion, and technology adaptation aligned with the owner's capacity. This research is expected to contribute to the development of local culinary-based MSMEs rooted in cultural heritage.

The relatively high volatility of Robusta coffee prices creates uncertainty for farmers, business actors, and policymakers in making economic decisions. This study aims to analyze the price movement patterns of Robusta coffee, determine the most appropriate Autoregressive Integrated Moving Average (ARIMA) model, and conduct short- to medium-term price forecasting for Robusta coffee. The data used consist of monthly Robusta coffee price data from January 2023 to September 2025, sourced from the World Bank Commodity Price Data. The analytical method employed is ARIMA using EViews software, beginning with stationarity testing using the Augmented Dickey-Fuller (ADF) test, model identification through ACF and PACF, parameter estimation, and residual diagnostic testing. The results show that Robusta coffee price data are non-stationary at the level but become stationary at the first difference, indicating integration of order one I(1). Based on model identification and diagnostic testing, the ARIMA (0,1,0) model is found to be the most appropriate and satisfies the white noise assumption. Forecasting results indicate that Robusta coffee prices are projected to remain relatively stable with a moderate upward trend through December 2026. These findings are expected to serve as a reference for decision-making by farmers, business actors, and the government in responding to Robusta coffee price dynamics.

The calculation of work volume and construction costs is a fundamental aspect of project management, as errors in the estimation process can directly affect the preparation of the project budget. Many projects still use conventional methods for estimation, which are based on 2D working drawings with the assistance of Microsoft Excel, as seen in the Sungai Raya Religious Court Building project. This method is considered prone to calculation errors and less efficient due to the considerable amount of time required. With the advancement of technology, Building Information Modeling (BIM) has emerged, enabling automatic and integrated calculation of work volumes and construction costs through a three-dimensional digital model. This study aims to examine the implementation of BIM in the Sungai Raya Religious Court Building project and to compare the results of work volume and construction cost calculations between the BIM method using Autodesk Revit and the conventional method based on the project’s Bill of Quantity (BoQ). The research method was conducted by modeling the structural elements of the building, including pile caps, tie beams, columns, beams, floor slabs, and reinforcements. The results of work volume and construction cost calculations obtained from Autodesk Revit were then compared with the project’s BoQ as the conventional method. Based on the analysis, an average difference of 6.3% in work volume and 5.6% in construction cost was found, with the Autodesk Revit calculations showing slightly lower values compared to the project’s BoQ.