Publication Search

Changes in labor regulations through the Job Creation Law have brought significant changes to the employment system in Indonesia, particularly in terms of labor flexibility. This study aims to analyze labor flexibility after the implementation of the Job Creation Law from the perspective of Human Resource Management (HRM). The research method used is a qualitative approach through a literature study with thematic analysis of 16 scientific journals, books, and regulations related to labor flexibility and strategic Human Resource Management (HRM) practices. The results show that labor flexibility has positive impacts on companies in improving operational efficiency, productivity, and adaptability to market changes. However, on the other hand, such flexibility also creates several challenges, including job uncertainty, decreased job security, and reduced protection for contract and outsourced workers. From the HRM perspective, companies are required to create a balance between business interests and labor protection in order to maintain harmonious industrial relations. This study is expected to provide a more comprehensive understanding of labor flexibility as part of human resource management strategies in the post-labor deregulation era in Indonesia.

This research was conducted to examine the implementation of the Accurate system in recording cement purchase transactions at PT. XYZ and to evaluate its effectiveness in supporting the company's operational activities. A qualitative approach was employed, emphasizing the analysis of descriptive data in the form of words and documents. The study was carried out using a case study method to obtain an in-depth understanding of the phenomenon being investigated. During the internship period, data were collected through interviews, observations, and documentation techniques. Research shows that the Accurate system helps companies record purchases in a more organised, faster and more accurate way than the manual method using Microsoft Excel. The Accurate system can automatically record purchase invoices, business debts, suppliers and the inventory of goods. This makes the accounting department more efficient. Accurate helps to reduce the risk of recording errors and makes it easier to find transaction data. However, when it is being used, there are still several problems, such as delays in entering transaction data, mistakes when entering names or account numbers, and being unable to change invoices after a certain amount of time. To get around these problems, the company checks the transaction data again and makes sure that the recording process is more consistent. Research results show that the Accurate system is effective in PT. XYZ can help make sure that the process of recording cement purchases is effective and efficient. It can also help make sure that financial information is more accurate and joined up.

The development of Artificial Intelligence (AI) has driven significant transformation in hospital management, particularly in operational efficiency, service quality, and patient safety. This study aims to analyze the implementation of AI in hospital management based on recent scientific evidence from 2020 to 2026. The method used was a systematic review guided by the PRISMA 2020 framework. Literature was retrieved from PubMed, ScienceDirect, SpringerLink, Google Scholar, and ProQuest. From 360 identified articles, a stepwise selection process was conducted, resulting in 15 articles that met the inclusion criteria. The findings indicate that AI contributes to improved operational efficiency through patient flow optimization, operating room management, workforce scheduling, and electronic medical record management. AI also enhances service quality through predictive data analytics and supports patient safety through risk detection and early warning systems. In conclusion, AI has strong strategic potential to support modern hospital management. However, its implementation still faces several challenges, including human resource readiness, data security, algorithmic bias, system interoperability, and investment requirements. Therefore, AI implementation should be carried out in a planned, ethical manner and evaluated from a health economics perspective.

The rapid development of information and communication technology has encouraged military organizations to adopt modern systems capable of supporting operational effectiveness. One of the challenges faced by the Indonesian Marine Corps is the limitation of conventional monitoring methods that still rely on voice reports through tactical radios and manual communication systems. This condition often causes delays in information delivery, inaccuracies in troop positioning data, and difficulties in controlling personnel and logistics in dynamic operational environments. This study aims to formulate a conceptual model for the utilization of a GPS Tracking System integrated with Marine Corps communication equipment to improve troop and material movement monitoring. The study employed a Research and Development (R&D) method with a descriptive qualitative approach. Data were collected through literature review, observation, interviews, questionnaires, and documentation involving operational personnel and military communication experts. The results indicate that integrating GPS Tracking Systems with communication equipment can provide real-time location information, improve command and control effectiveness, accelerate reporting processes, enhance logistics supervision, and support operational evaluations through recorded movement data. The proposed concept is expected to strengthen situational awareness, increase operational efficiency, and support mission success in future Marine Corps operations.

This study investigates the integration of digital twin technology and machine learning for predictive analysis in smart mechanical systems. The research emphasizes the role of intelligent computational frameworks in improving industrial monitoring, predictive maintenance, and operational efficiency within Industry 4.0 environments. A qualitative content analysis approach was employed by reviewing scientific literature, industrial reports, and previous studies related to digital twins, artificial intelligence, and predictive analytics. The findings indicate that digital twin architectures supported by machine learning algorithms can significantly enhance real-time monitoring, fault prediction accuracy, and maintenance optimization. The integration of IoT devices, cloud computing, and intelligent analytics also improves industrial sustainability, reduces operational downtime, and supports data-driven decision-making processes. Furthermore, the study identifies several technological challenges, including cybersecurity risks, data integration complexity, and computational limitations. Overall, the proposed intelligent digital twin framework provides a promising approach for future industrial innovation and sustainable smart mechanical system management

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.

The growth of the nickel mining industry in Indonesia, particularly in Southeast Sulawesi Province, has made this sector one of the main contributors to the Regional Gross Domestic Product (RGDP). However, the development of supporting infrastructure—especially mining haulage roads—still faces various risks that could potentially cause project delays and disrupt operational efficiency. Therefore, a systematic risk identification process is necessary to ensure that project implementation proceeds in accordance with established time, cost, and quality targets. This study aims to identify and assess risks in mining infrastructure development projects using a stakeholder-based approach. This approach is employed to gain an understanding of the risks that arise from the perspectives of the parties involved in the project. The results of this study describe the dominant risks that could potentially occur in nickel mining projects, namely opposition from the local community surrounding the project, conflicts with community organizations, denial of access to project roads, and disruption of project security due to inadequate security measures by authorities. It is hoped that these dominant risks can serve as a basis for developing effective risk mitigation strategies to support the successful and sustainable development of mining infrastructure.

The development of technology in the digital era has significantly altered consumer behavior, particularly for Generation Z, who are known as digital natives. This group possesses unique characteristics, highly relying on social media to seek product information before making purchasing decisions. This study aims to analyze digital marketing management strategies through social media in enhancing brand engagement and loyalty among Generation Z consumers, as well as to identify the key determinants of its success. The research method employed is descriptive qualitative, utilizing literature review as the data collection technique across prior scientific sources. The analysis reveals that the implementation of digital marketing strategies based on visual content and short-form videos on platforms such as TikTok and Instagram is proven to be highly effective in capturing the audience's attention rapidly. In addition to content format, collaboration with highly credible influencers and the application of authentic, responsive two-way communication serve as the main pillars in building emotional proximity and trust among young consumers. Operationally, this strategy offers cost efficiency and a broader market reach. The conclusion of this study emphasizes that the optimal integration between management information systems and interactive, adaptive communication approaches toward digital trends is the main key to winning the market and sustaining the long-term loyalty of Generation Z.

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.

Magelang City faces the challenge of limited land availability, with a total area of only 18.58 km2 and a high population density. Consequently, telecommunications infrastructure development requires a precise strategy. This study aims to analyze the business model and investment feasibility of Pole and Greenfield type telecommunication towers in Magelang City. Using a descriptive quantitative approach, this research processes secondary data from PT Dayamitra Telekomunikasi Indonesia by applying feasibility analysis based on Life Cycle Costing (LCC), Net Present Value (NPV), Internal Rate of Return (IRR), Break-Even Point (BEP), Payback Period (PP), and Benefit-Cost Ratio (BCR). The results indicate significant differences in cost structures; Pole towers proved to be more efficient, requiring an initial capital outlay of only 28.8% of the total capital required for Greenfield towers. Greenfield towers generated an NPV of Rp13.07 billion with an IRR of 20%, while Pole towers generated an NPV of Rp2.46 billion with a higher IRR of 23%. Pole towers have proven to offer a faster return on investment and better operational cost efficiency, making them the most strategic option to support network densification and the implementation of 5G technology in urban areas with spatial constraints like Magelang City.

PT. Bukit Baiduri Energi (BBE) is a coal mining company that utilizes hauling roads as the main infrastructure for material transportation. This study focuses on a 1.7 km road segment selected as the object of technical evaluation. The objective of this research is to analyze the effect of road geometry improvements on hauling time efficiency and equipment productivity. The method employed includes direct field measurements and calculations of operational parameters such as travel time, cycle time, and productivity. The results indicate that improvements in road grade reduced travel time from 10.13 minutes to 9.86 minutes. This reduction was followed by a decrease in cycle time from 16.29 minutes to 16.22 minutes. In addition, productivity increased from 65.4 bcm/hour to 66.69 bcm/hour. Also, improvements in curve radius and superelevation were implemented on the hauling road. These improvements resulted in a further decrease in travel time from 9.86 minutes to 8.6 minutes. Consequently, the cycle time also decreased from 16.22 minutes to 16.18 minutes. The productivity of hauling equipment increased from 66.69 bcm/hour to 67.02 bcm/hour. Overall, the evaluation of road geometry provided a positive contribution to operational performance. The productivity of overburden removal increased from 65.4 bcm/hour to 67.02 bcm/hour, representing an improvement of 2.48%.

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 rapid growth of digital commerce has encouraged companies to integrate digital and physical marketing channels to create seamless and consistent customer experiences. This study aims to analyze the role of integrated marketing channels through omnichannel strategies, the utilization of Artificial intelligence (AI), and their impact on customer experience in the context of digital commerce. The study employs a Systematic literature review (SLR) approach by examining relevant scholarly articles related to omnichannel marketing, AI technologies, and customer experience. The findings indicate that integrated marketing channels supported by AI enhance service personalization, customer engagement, operational efficiency, and the quality of interactions between companies and customers. Furthermore, the implementation of omnichannel strategies contributes to higher customer satisfaction and loyalty by providing a more connected experience across multiple customer touchpoints. However, the implementation of integrated marketing channels still faces several challenges, including fragmented channel integration, technological complexity, high investment requirements, and concerns regarding customer data privacy and security. Therefore, effective management of integrated marketing channels is essential for improving customer experience while creating sustainable competitive advantages for companies in an increasingly dynamic digital era.

This study was conducted based on the crucial role of diesel generator engines as the primary source of electrical power on board ships, making their operational reliability essential. One of the factors influencing generator engine performance is lubricating oil temperature. Excessive lubricating oil temperature may reduce lubrication effectiveness, increase friction between moving components, and lower engine efficiency. Therefore, this research aimed to identify the causes of high lubricating oil temperature in diesel generator engines and determine appropriate corrective actions. The study employed a descriptive quantitative approach. Data were collected through direct observation, interviews, and documentation during sea practice aboard MV. CL FLANDERS from 4 July 2024 to 5 July 2025. The data were analyzed using simple linear regression to examine the relationship between generator load and lubricating oil temperature. The findings revealed that generator load had a significant effect on the increase in lubricating oil temperature. Under normal operating conditions, the lubricating oil temperature ranged from 60°C to 72°C, while under abnormal conditions it increased to between 68°C and 81°C. The abnormal rise in temperature was mainly caused by cooling system problems, particularly a dirty LO cooler, scale deposits on the sea water pump impeller, and blockage in the cooling capillary pipes. The regression equation under normal conditions was Y = 45 + 0.30X, whereas under abnormal conditions it was Y = 53.5 + 0.30X. Elevated lubricating oil temperature resulted in lower oil viscosity, higher fuel consumption, and reduced diesel generator engine performance. Therefore, regular maintenance of the LO cooler, sea water pump, and continuous temperature monitoring are necessary to maintain optimum engine performance.

The Food & Beverage industry relies heavily on the availability and quality of fresh raw materials, making inventory management crucial. This study aims to analyze the implementation of the First-In, First-Out (FIFO) method in inventory management at PT K Hospitality Investment. The research design used a case study. Data were collected through interviews, observation, and documentation, then analyzed descriptively and qualitatively to assess the implementation of the FIFO inventory method in inventory management. The results show that PT K Hospitality Investment adopts a strict chronological inventory system and issuance of goods based on the order of entry. The use of FIFO inventory is often supported by the FEFO (First-Expired, First-Out) technique. Integrated inventory control has contributed to the financial stability of PT K Hospitality Investment. When properly implemented, the FIFO method not only helps reduce waste and increase efficiency, but also supports the company's operational sustainability. Although the implementation has been successful, the company still faces challenges such as limited infrastructure, a manual recording system, sudden changes in trends or guest order volumes, and delays in supplier deliveries.

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.

This study examines the effect of working capital on firm performance and sustained growth among consumer non-cyclicals manufacturing companies listed on the Indonesia Stock Exchange (IDX) over the period 2019–2023. Working capital is operationalized through three distinct proxies derived from Akgün and Memiş Karatəs (2021): the Cash Holding Level (CHL), which measures the proportion of cash and cash equivalents relative to total assets; the Cash Interactive Effect (CIE), which captures the efficiency of converting revenue into operating cash flow; and the Gross Working Capital Ratio (GWCR), which reflects the share of current assets within total assets. Firm performance is assessed through Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q, while sustained growth is measured using the model proposed by Gerson et al. (2025), expressed as SG = b × ROE, where b denotes the earnings retention ratio. Panel data regression analysis is applied to 225 firm-year observations drawn from 45 companies. The study employs the Fixed Effect Model (FEM) for ROA and ROE, and the Random Effect Model (REM) for Tobin’s Q, as determined by the Hausman specification test. The findings reveal that CHL and CIE exert significant positive effects on ROA and ROE, while CIE is the only proxy to produce a statistically significant positive effect on Tobin’s Q. With respect to sustained growth, CHL and GWCR demonstrate significant negative effects, whereas CIE shows a significant positive effect, indicating that operational efficiency dimensions of working capital actively support long-term growth sustainability. These results reinforce the liquidity management theory and contribute empirical evidence that the structure and efficiency of working capital are strategic determinants of both short-term financial performance and long-term growth sustainability in Indonesia’s consumer goods manufacturing sector.

This study conducts a systematic review of literature concerning the role of Management Information Systems (MIS) in managing Umrah pilgrim data across Indonesia. Employing a Systematic Literature Review (SLR) guided by the PRISMA protocol, the study examined and synthesized 24 peer-reviewed articles published between 2019 and 2026, drawn from Google Scholar, SINTA, and nationally accredited journal portals. Findings indicate that MIS adoption has yielded notable improvements in operational efficiency, data reliability, service transparency, and the overall quality of managerial decision-making within Umrah travel organizations. Web-based MIS remains the predominant technological approach, offering integrated modules for pilgrim registration, document handling, financial tracking, and departure scheduling. At the national level, government-initiated platforms such as SISKOHAT and SISKOPATUH have demonstrated tangible contributions to the administration of Hajj and Umrah services. Nevertheless, persistent obstacles continue to hinder full-scale adoption, including inadequate digital infrastructure in certain regions, inconsistent internet connectivity, and gaps in human resource competencies for operating digital systems. The study argues that embracing MIS is no longer optional for Umrah travel operators; rather, it constitutes a strategic necessity. Future research is encouraged to investigate long-term implementation outcomes, cross-system comparisons, and data security considerations within the broader digital landscape of pilgrimage service management.

The rapid advancement of artificial intelligence (AI) has significantly altered the landscape of business decision-making, particularly for Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. Despite their critical role in economic growth and employment generation, MSMEs frequently encounter substantial barriers related to technological adoption, digital literacy, and resource allocation. This research systematically investigates the utilization of artificial intelligence as a responsive innovation mechanism designed to optimize decision-making processes within the MSME sector. By employing a comprehensive systematic literature review methodology, analyzing peer-reviewed publications from globally recognized academic databases between 2018 and 2024, this study delineates the multifaceted benefits, complex challenges, and contextualized adoption strategies associated with AI integration. The findings reveal that artificial intelligence holds transformative potential for enhancing operational efficiency, refining predictive analytics, and sustaining long-term competitiveness. Conversely, critical challenges, including inadequate digital infrastructure, financial constraints, and organizational resistance, remain pervasive obstacles. Consequently, the study advocates for a gradual, responsive innovation approach that aligns technological adoption with specific business needs and environmental pressures. The insights derived from this research offer substantial theoretical and practical implications, providing a strategic framework for policymakers and MSME owners to accelerate digital transformation inclusively.

.This study aims to analyse the role of Financial Information Systems (FIS) in supporting risk management, decision-making, and organisational performance in the digital transformation era. This study employs the Systematic Literature Review (SLR) method to examine articles indexed in Scopus from 2016 to 2026. The PRISMA framework is used to ensure a systematic, transparent article selection process, resulting in the selection of 37 relevant articles for further analysis. The results of the study show that Financial Information Systems make a major contribution to improving financial transparency, operational efficiency, the quality of strategic decision-making, and organisational risk mitigation. In addition, the integration of emerging technologies such as Artificial Intelligence (AI), FinTech, big data analytics, and cloud computing further strengthens the effectiveness of financial information systems in modern organisations. This study contributes theoretically by mapping research trends and identifying research gaps, while providing practical benefits for organisations seeking to increase competitiveness through digital financial systems. For future research, it is recommended to develop a more predictive and intelligent Financial Information Systems model to address future business dynamics.