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This research focuses on designing the shortest path to a docking station for the charging system of a robotic coffee delivery system on a cruise ship. With the growing demand for more efficient and innovative services in the maritime industry, autonomous robots are increasingly being used for tasks such as delivering coffee to passengers. However, these robots face unique challenges in the confined and dynamic environment of a ship, particularly in terms of power management and recharging. The goal of this research is to create an efficient charging system using a power bank and Internet of Things (IoT) technology to minimize downtime and ensure continuous robot operation with minimal human intervention. By utilizing sensors such as the MPU 6050 for motion detection and the TCS 3200 for color recognition, the robot can autonomously navigate the shortest path to the docking station for charging, while IoT enables real-time battery capacity monitoring. This helps reduce the time spent on non-operational tasks and improves the overall efficiency of the system. This research not only enhances the robot’s ability to operate autonomously in complex environments but also provides a flexible and scalable solution for the maritime industry to integrate advanced robotics into their service operations. The results of this study contribute to the increased adoption of autonomous systems in the maritime sector, particularly in improving service efficiency on board, reducing the need for human intervention, and ensuring smoother service delivery to passengers.

In the current digital era, SMEs in the culinary sector face challenges in adopting technology to improve operational efficiency. One solution to address this issue is the use of a simple and cost-effective QR Code-based application. This study aims to develop and implement siMenu, an application that provides table, order, and product management solutions without integrating complex digital payment systems. The method used is Project-Based Learning (PBL), which allows the development of technical skills while designing a sustainable business model through Business Model Canvas (BMC). The results show that siMenu successfully improved operational efficiency for SMEs, reduced ordering errors, and provided an easy-to-adopt solution with low implementation costs. However, challenges in application development and building user trust remain obstacles. The conclusion of this study is that simple digital solutions like siMenu can help SMEs in the culinary sector digitally transform and stay competitive in an increasingly evolving market.  

Waste management is increasingly critical due to the rising waste generated by community activities driven by a consumptive lifestyle. A key solution to this issue is the implementation of waste bank programs, though community participation and operational efficiency remain challenges, as seen with the Bangkitku Waste Bank in Jambi City. This study focuses on designing the user interface for the Bangkitku Waste Bank Information System using the design thinking method and evaluating the usability of the prototype. The design process followed the five stages of design thinking: empathize, define, ideate, prototype, and test, with data collected through interviews and observations. The analysis involved tools such as empathy maps, user personas, sitemaps, and user flows, with prototypes created using Figma. Usability testing was conducted with 10 participants, including administrators and customers, resulting in high usability scores—98 for administrators and 97 for customers. The majority of participants found the system easy to use, as indicated by responses on the Single Ease Question (SEQ) survey. The prototype met key usability criteria, improving both operational efficiency and community engagement in waste bank management. The findings demonstrate the system's potential to foster sustainable environmental practices and enhance the effectiveness of waste bank management.

This study aims to analyze the strengths, weaknesses, opportunities, and threats (SWOT) in the development of culinary MSMEs in Central Java Province. A descriptive qualitative approach was used, with data collection conducted through interviews, observations, and secondary document review. Data analysis was performed using the Miles and Huberman interactive model, which allowed for the systematic processing and interpretation of the gathered data. The findings revealed that the key strengths of culinary MSMEs in Central Java include clear market segmentation, strategic locations, and product innovation. These strengths enable the businesses to reach targeted customers effectively and maintain competitiveness in a dynamic market. However, the main weaknesses identified include limited utilization of digital technology and a lack of managerial development, which hinder their ability to scale and improve operational efficiency. The study also highlighted significant opportunities for growth, such as government support for MSMEs and the rapid development of digital technologies that can enhance marketing and operational processes. Despite these opportunities, the threats facing these businesses include intense competition from both local and global players, as well as a low level of interest in entrepreneurship among the younger generation, which limits the growth potential of new businesses. Based on the SWOT analysis, the study proposes a development strategy matrix that MSMEs and policymakers can use to address weaknesses, capitalize on opportunities, and mitigate threats. This strategy emphasizes the need for digital transformation, investment in managerial skills, and fostering an entrepreneurial culture to ensure the sustainable growth of culinary MSMEs in the region. The findings provide valuable insights for both business owners and policymakers to support the development of the culinary sector in Central Java

This research aims to analyze the impact of the merger between PT Indosat Tbk (ISAT) and PT Hutchison 3 Indonesia (H3I) on both companies. Through a merger analysis approach, we identify key factors that influence the success or failure of the integration between these two entities. The research method is literature review to search a financial information and annual reports. Qualitative and quantitative analyses are used to measure the impact of the merger on the financial, operational, and reputational performance of both companies. The research findings indicate that the merger between ISAT and H3I has a positive impact on operational efficiency and economies of scale. However, challenges related to technology integration, corporate culture, and human resource management are also identified as critical factors that need to be addressed. Furthermore, this research discusses the implications of the merger on the telecommunications market in Indonesia and its impact on industry competition. These findings provide valuable insights for business practitioners, regulators, and academics interested in the study of merger impacts in the telecommunications sector.

This study aims to enhance the quality of operational performance by implementing the Holonic Manufacturing System (HMS). The system involves dividing manufacturing processes into autonomous, collaborative, and participatory holons, including the Order Holon, Product Holon, Resource Holon, and Staff Holon. The primary objective is to optimize production efficiency by reducing costs, minimizing processing time, and increasing flexibility while improving overall organizational productivity. The research problem centers on evaluating the impact of holonic manufacturing on operational performance improvement. This study is significant as it addresses a critical issue for firms striving to enhance their efficiency and deliver value to customers. The adoption of HMS is not only a practical approach but also a widely recognized business strategy that has garnered interest from researchers and industry professionals alike.To achieve the study’s objectives, a structured questionnaire comprising 36 items was developed and distributed to participants. Two primary hypotheses were formulated to examine the relationship between HMS implementation and operational performance quality. Various statistical analyses were conducted using SPSS (version 24) and AMOS (version 24) to test the hypotheses and validate the findings. The results indicate a significant correlation and causal relationship between the Holonic Manufacturing System and operational performance quality. The findings suggest that implementing HMS effectively enhances organizational performance by improving production processes, increasing efficiency, and reducing operational constraints. Therefore, adopting this system can lead to a more agile, cost-effective, and productive manufacturing environment, making it a valuable strategy for modern organizations.

This study aims to analyze the efficiency of raw material inventory control for bread products at Rejeki Bakery in Mijen, Semarang, and to examine the application of the Material Requirement Planning (MRP) method in optimizing raw material inventory costs. The research employs a quantitative approach using secondary data as the main source. The data analysis technique utilized in this study is the Material Requirement Planning (MRP) method, which includes three inventory control techniques: Lot For Lot (LFL), Economic Order Quantity (EOQ), and Period Order Quantity (POQ). Each method was analyzed to determine the most efficient inventory cost. The results show that the raw material inventory cost using the Lot For Lot (LFL) method is Rp 2,400,000.00, the Economic Order Quantity (EOQ) method results in an inventory cost of Rp 2,992,600.00, while the Period Order Quantity (POQ) method incurs a cost of Rp 6,924,800.00. Additionally, the current raw material inventory cost under Rejeki Bakery’s management policy is Rp 2,681,600.00. Based on these findings, the implementation of the Material Requirement Planning (MRP) method at Rejeki Bakery in Mijen, Semarang, has demonstrated its effectiveness in improving the efficiency of inventory management. Among the three techniques analyzed, the Lot For Lot (LFL) method proves to be the most cost-effective, as it minimizes excess inventory while ensuring that production needs are met. This study highlights the importance of selecting an appropriate inventory control method to optimize costs and enhance operational efficiency in bakery production.

Supplier selection is a strategic element in supply chain management to ensure operational efficiency and business sustainability. This study aims to determine the best urea supplier for PT DSSA 1, a textile company specializing in dyeing and finishing processes, using the Analytic Network Process (ANP) method. This method was chosen for its ability to systematically analyze interdependencies among criteria, leading to more accurate and comprehensive decision-making. Data were collected through direct observation, in-depth interviews with internal company sources, and relevant literature reviews. The analysis was based on five main criteria: quality, price, service, delivery, and flexibility, each further broken down into sub-criteria. The results indicate that quality is the most critical criterion, with the highest weight of 23.19%, followed by price, service, and delivery, each with relatively balanced weights of 19.93%. Flexibility, although ranked last with a weight of 17.01%, remains relevant, especially for urgent orders. Based on the analysis, Supplier A was identified as the best choice with the highest overall weight, followed by Supplier B and Supplier C. This study provides practical contributions by offering strategic recommendations for PT DSSA 1 in selecting suppliers that support production efficiency and business sustainability. The study is limited in the scope of criteria and the number of suppliers analyzed. Future research is recommended to explore more variables, expand the sample size, and consider the implementation of digital technologies to optimize the supply chain.

This study aims to determine the optimal queue system configuration for online motorcycle taxi driver partner registration services at the PT XYZ Bali Branch Office using a quantitative approach. Data on arrival time, service time, and operational costs were analyzed through queuing theory using the POM-QM software. The analysis results show that although phases 1, 2, and 4 meet efficiency criteria (utilization below 70%), reducing the number of servers in phases 1 and 2 can lower operational costs, as the queuing cost is lower than the service cost. Meanwhile, phase 3 shows a high utilization rate (80%), but adding a server increases the total cost. Therefore, the study recommends implementing an interchange schedule to dynamically allocate servers during peak hours to maintain a balance between cost efficiency and service capacity. Additionally, the implementation of self-service in phase 2 is proposed to enhance efficiency without reducing service capacity, with experimental results showing an increase in service rates from 2 to 7 registrants per hour. These findings contribute to the development of a more efficient and applicable queuing model and serve as a reference for companies in improving service quality and registrant satisfaction.

MSMEs play a key role in the national economy, especially in increasing economic growth and creating new jobs. However, in the digital era, MSMEs face major problems, such as low levels of digital literacy, limited access to the internet, and fierce competition with large companies that have used technology before. This study examines the variables that influence the sustainability of MSMEs amidst digital challenges and finds methods that can be used so that MSMEs can survive and grow. The research method was carried out through surveys and direct interviews with MSME actors at Pasar Pagi Setia Budi, Medan, North Sumatra. The results of the study showed that most MSME actors did not utilize digital platforms for marketing and transactions, which resulted in decreased income. To increase competitiveness, MSMEs need to improve their digital knowledge, adopt online marketing strategies, and optimize the use of e-commerce and social media. Support from the government, financial institutions, and technology companies is also very important. In the increasingly competitive digital era, by implementing the right digitalization strategy, MSMEs can improve operational efficiency, expand market reach, and maintain the sustainability of their business.

Along with the development of the industrial sector, companies are competing to create quality and affordable products. To support production, automation tools have emerged that help the production process so that it is faster. One of the machines that is widely used by large factories is a 3-phase induction motor. 3-phase induction motors are often used in driving equipment in industry because they have a simple construction, are relatively cheap, lightweight, have high efficiency, and are easy to maintain. This study utilizes the A3114 hall effect sensor device, PZEM-PP4T Sensor, 20x4 LCD, ESP32 module, Relay, Mitsubishi D700, MCP 4725 Sensor. The tests carried out showed that the performance of the sensor for measuring speed, voltage, and current on 3-phase motors has a high level of accuracy. Testing of motor speed shows a difference in speed value (Rpm) between the hall effect sensor and the tachometer, with an average accuracy percentage of 4,12%, indicating that the hall effect sensor has a fairly good level of accuracy. For voltage measurement, the Pzem sensor compared to the Multitester produces an average accuracy percentage of 0,90%, indicating that the pzem sensor is very reliable. Meanwhile, current testing shows a difference in value between the pzem sensor and the multitester with an average accuracy percentage of 0,98%, indicating a fairly high level of accuracy. Overall, this system can be relied on for measuring operational parameters of 3-phase motors because it has consistent and good accuracy. With this research, the 3-phase induction motor monitoring system which was originally done manually has changed to automatic and has a fairly high level of work efficiency.

The digital transformation of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia is crucial for enhancing competitiveness and sustainability in the digital economy era. However, MSMEs face significant challenges, including low digital literacy, limited financial resources, uneven digital infrastructure, and insufficient regulatory support. This study aims to analyze these challenges and propose adaptation strategies through a qualitative literature review approach. Data were collected from credible sources, including academic journals, government reports, and reputable articles, focusing on the period from 2019 to 2024. The findings highlight the importance of external support, such as training, mentoring, and government policies, in facilitating digital transformation. Key strategies include improving digital literacy, collaborating with digital platforms, and fostering product innovation. The study also emphasizes the need for government intervention in infrastructure development and policy reform to create a conducive ecosystem for MSMEs. While digital transformation offers significant benefits, such as operational efficiency, market expansion, and increased competitiveness, the digital divide between urban and rural MSMEs remains a critical issue. This research provides recommendations for stakeholders to ensure inclusive and sustainable digital transformation for all MSMEs in Indonesia.

Harvesting is a crucial stage in the palm oil production process that impacts the efficiency and productivity of the plantation. Choosing the right harvesting method can increase the effectiveness of time and labor. This study compares harvesting efficiency using manual and mechanized methods by measuring the duration of fruit harvest and transportation time to the collection point (TPH). This study was conducted in November–December 2024 at PT. Kencana Sawit Indonesia, located in Talao Sungai Kunyit, South Solok, West Sumatra. The equipment used included stationery, a stopwatch, and data related to working time and harvest results. Data were collected through direct observation. The analysis was carried out using the t-student statistical test to evaluate the difference in working time between the manual and mechanized methods. The results showed that harvesting with mechanization was more efficient than the manual method. The difference in harvest time reached 12 seconds per bunch with a P value of 0.0002, while the transportation time to the TPH was 23.48 minutes faster per ton with a P value <0.0001. Monthly production with mechanization averaged 48.69 tons, while the manual method only produced 38.13 tons per month. Thus, the use of mechanized harvesting methods has proven to be faster in the harvesting process, fruit transportation, and increasing monthly production results. The implementation of mechanization can be a strategic step to increase operational efficiency and productivity of oil palm plantations.

The supply chain is crucial to company operations, especially in the poultry farming industry, to ensure the availability of quality feed. PT X, located in Kintamani, faces challenges in its supply chain due to the long distance from its main supplier, PT Sreeya Sewu. This has led to high logistics costs and risks of delivery delays, which impact the company’s operational efficiency. This study aims to assist PT X in selecting the best supplier using the Analytical Hierarchy Process (AHP) method and the Super Decision application. With five criteria and 15 sub-criteria, the results show that UD Tunas Harapan is the best supplier, excelling in nine sub-criteria.  

This study discusses the importance of developing soft skills and hard skills for vocational high school students in preparing themselves to enter the workforce. Soft skills, such as communication, teamwork, and leadership, are considered key factors in creating a productive and harmonious work environment. Meanwhile, hard skills, which include specific technical abilities, are the main foundation in carrying out operational tasks. The combination of these two types of skills not only improves work efficiency but also allows the workforce to adapt quickly to changes and challenges in various industrial sectors. This study emphasizes that although hard skills are often the main focus, soft skills have an equally important role in supporting long-term career success. This study also identifies various effective strategies for developing both types of skills, including practice-based training, mentoring, and the use of technology in learning. The results of the study indicate that the integrated development of soft skills and hard skills can increase the productivity and competitiveness of the workforce in the era of globalization and digital transformation.

This study aims to analyze the effectiveness of implementing Accurate accounting software in financial report management at PT. XYZ). Accurate is utilized to enhance operational efficiency, recording accuracy, and real-time financial reporting. The findings reveal that the use of Accurate reduces recording errors and accelerates the financial reporting process. Integration features across modules such as purchasing, sales, and inventory improve interdepartmental data consistency. Additionally, Accurate helps the company comply with Indonesian Financial Accounting Standards (PSAK) and tax regulations through automated reporting. Key success factors include adequate employee training and feature customization tailored to the needs of manufacturing companies. This study concludes that technology-based accounting software not only improves financial data accuracy but also supports better strategic decision-making for management.

In supporting the progress of an airport, there needs to be infrastructure development and expansion, such as airside expansion. Sultan Muhammad Kaharuddin III Airport has expanded its airside such as runway, taxiway, and apron. The expansion of the airside aims to increase flight capacity, improve flight operational safety, improve flight operational efficiency, and support tourism in Sumbawa Besar. This study uses a qualitative research method with primary data collection through interviews and observations, as well as secondary data through documents related to airside expansion. Data analysis techniques use data collection, data reduction, data presentation, and drawing conclusions. This study was conducted at Sultan Muhammad Kaharuddin III Airport. The results of the study show that there is an expansion of the airside at Sultan Muhammad Kaharuddin III Airport, such as the runway, taxiway, and apron which has been carried out in several years. This airside expansion has a positive impact on flight operations. Where the impact is an increase in the number of passengers, increasing flight capacity and adding flight routes, as well as increasing flight security and safety at Sultan Muhammad Kaharuddin III Airport..

This research was designed using Unified Modeling Language (UML) as a tool for visualizing system requirements. The system designed is expected to improve efficiency, accuracy and speed of service, thereby providing a better experience for customers and making it easier for Bank Sumut officers to manage registration data. The system development method used is waterfall. The research results show that the designed information system can automate various manual processes such as collecting prospective customer data, document validation, and managing account data. It is hoped that this management information system can be used to provide an overview of the applications that will be created to increase the Bank's operational productivity and minimize the potential for administrative errors, as well as supporting the digital transformation of Bank North Sumatra in facing competition in the banking sector.

Travel insurance provides financial protection for individuals during their trips, both domestically and internationally. With the increasing demand for travel insurance, insurance companies face challenges in efficiently managing claims. This study aims to develop a predictive model to classify whether an insurance policy will be claimed based on historical customer and transaction data. This research utilizes a dataset containing various features related to travel and policyholders, such as agent type, distribution channel, insurance product, travel duration, and premium amount. The methods used include data exploration, feature processing, and the application of machine learning algorithms such as Logistic Regression, Random Forest, and XGBoost. Experimental results indicate that the XGBoost model performs the best, achieving the highest accuracy compared to other models. With this predictive model, insurance companies can optimize claim evaluation processes, reduce fraud risks, and improve operational efficiency in handling travel insurance claims.

Hotel booking cancellations pose significant challenges to the hospitality industry, affecting revenue management, demand forecasting, and operational efficiency. This study explores the application of machine learning techniques to predict hotel booking cancellations, leveraging structured data derived from hotel management systems. Various classification algorithms, including Random Forest, XGBoost, and LightGBM were evaluated to identify the most effective predictive model. The findings reveal that XGBoost model outperforms other models, achieving F2-score of 0.7897. Key influencing factors include deposit type, total number of special requests, and marketing segment. The results underscore the potential of predictive modeling in optimizing hotel revenue strategies by enabling proactive measures such as dynamic pricing, targeted customer engagement, and improved overbooking policies. This study contributes to the ongoing advancements in data-driven decision-making within the hospitality industry, offering insights into how machine learning can mitigate financial risks associated with booking cancellations.