Articles

Application of the Analytical Hierarchy Process (AHP) for Innovative Technological Projects Evaluation and Prioritization in an FMCG Company

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The FMCG industry is known for its dynamic and competitive nature. To thrive in this business sector, companies must possess the ability to swiftly adapt to the market demand changes, continuously enhance operational efficiency and drive innovation. Those abilities are crucial for maintaining competitiveness and ensuring long term viability of the company. Over the past few decades, technology along with its advancement has emerged as a factor that disrupts the ecosystem of various industries by reshaping the way businesses operate and interact with the customers. In Indonesia, many organizations including FMCG companies have continuously embraced and adopted emerging and innovative technologies within their business operations. Although it offers various benefits for the companies, the execution process has usually encountered various challenges which causing the implementation projects to experiencing delays, especially during the decision-making process. This was also the case in one of the largest FMCG companies in Indonesia due to varying interpretations of project importance, as well as the absence of clear prioritization criteria and an unorganized decision-making process. In order to address the issues, the organization plans to develop a decision-making framework that harmonizes diverse stakeholder perspectives related to project importance based on a number of key criteria while also analyze the benefit and impact provided by the implemented technologies through the application of the Multi Criteria Decision Making (MCDM) approach using the Analytical Hierarchy Process (AHP) framework. There are three technology innovation projects to be analyzed and assessed in this research: AGV Implementation, and Digital Warehouse Management System, and Universal QR for Traceability. In order to evaluate the projects, eighteen criterion which are divided into eighteen sub criteria that has been established through Secondary Data Collection and Focus Group Discussion (FGD) process. The data were processed by leveraging the systematic decision-making structure provided by the AHP framework. The research yields two primary outcomes: a structured decision-making framework and a project prioritization scheme intended for application at the organization. The findings of the research highlight the critical role of structured decision-making in navigating the complexities of evaluating and prioritizing innovative technological projects, while also proposing a scalable model that can be repeatedly utilized by the company in the project evaluation and prioritization contexts.

Decision Making to Choose Communication Network System for Teleremote Dozer Operation Using Analytic Hierarchy Process

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One type of heavy equipment is a mining material pushing tool called a dozer. Dozers generally work in areas near cliffs that are prone to landslides, where these areas can be classified as dangerous areas. New technology is needed to increase the safety of dozer operators from the threat of danger when operating a dozer. Teleremote dozers are one method that can reduce the risk of accidents that can happen to dozer operators. Instead of operating the dozer from inside the cabin, the operator operates the dozer via a remote control device.

There is an important aspect in operating a teleremote dozer, namely the need for a signal that will transmit data and commands from the remote control to the dozer unit operating in the field. Good and uninterrupted signal quality is the main key to good teleremote dozer operations with minimal risk.

The wireless signal network system currently used by companies will enter its obsolete period. However, the old system was tough and not easily damaged. There are strategic options for supporting the signal network for teleremote dozer operations: maintaining the old network system, replacing it with a new one, or using the old and new systems in a hybrid manner. Because there will only be one strategy chosen, a decision must be made. The SWOT AHP method is used for decision making regarding the strategy to be taken. The results of the AHP SWOT will produce a strategy, which will become a benchmark for making subsequent alternatives. Determining alternative types of network systems to support teleremote dozer operations will use the AHP method.

Predictive Analysis for Personalized Machine: Leveraging Patient Data for Enhanced Healthcare

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This research explores predictive analysis for personalized machine: leveraging patient data for enhanced healthcare. By leveraging the power of information and analytics, the healthcare industry can be driven towards a more patient-centric, proactive model that enhances outcomes and improve the overall quality of care. The objectives of the study are to: determine the significance and challenges of predictive analytics in healthcare, ascertain the data analytics techniques used in healthcare to enhance patient care, find out how predictive analytics can be applied for enhanced healthcare, and determine the ethical considerations associated with healthcare predictive analytics. This study employs the case study approach and experimental design. The study analyzes case studies of real-time deployment of predictive analytics models in healthcare centers, examines how these models enhance the healthcare delivery in those centers. Experiments were also conducted to understand how predictive analytics works. The C4.5 learning algorithm was employed to predict the presence of chronic kidney disease (CKD) in patients and differentiate between those not affected by the condition. The C4.5 classifier shows reasonable strength, evident in the large number of rightly classified occurrences (396) and a low misclassification of only 4 occurrences. This is further demonstrated by a low error rate of 0.37, as shown in table 5. The prevalence of this algorithm is emphasized by the large value of KS (0.97), indicating the classifier’s ground-breaking accuracy and performance. The performance of C4.5, featured by its minimal execution time and accuracy, puts it as a decent classifier. This characteristic makes it specifically well-suited for application in the healthcare sector, particularly for tasks involving prediction and classification. The application of data analytics methods for predictive analysis holds significant benefits in the health sector, as it gives us the power to predict and address potential threats to human health, covering different age groups, from the young ones to the elderly. This proactive method enables early disease detection, helping in timely interventions and contributing to better decision-making.

 

Enhancing Community Participation in Corporate Social Responsibility Activities at PT. Prima Bara Nusantara through Improved Decision-Making Process

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Corporate Social Responsibility (CSR) is crucial for companies that have a substantial ecological footprint, such as coal mining in Indonesia. PT. PBN strives to achieve a harmonious combination of responsible behaviors and economic viability. However, attaining this equilibrium necessitates strong community engagement to alleviate negative effects and provide beneficial contributions at the local level. This study focuses on the underexplored issue of poor community participation in CSR initiatives within Indonesia’s coal mining sector. Although PT. PBN has made substantial investments in environmental and community activities, recent evaluations indicate a substantial disparity between stakeholder expectations and the level of actual participation in activities. Gaining insight into the factors contributing to this disparity is vital for the effectiveness of CSR endeavors, as the support of stakeholders and active involvement of the community are crucial for ensuring social sustainability and enduring stability. The study utilizes analyzed data from interviews conducted with both internal and external respondents. It uses problem tree analysis in order to uncover the root causes of low community participation. Focus group discussions are used to delve deeper into the objectives of Value-focused Thinking (VFT) and help determine which alternative solutions should be chosen. The integration of VFT with Analytical Hierarchy Process (AHP) aids decision-making by recognizing the criteria and sub-criteria used to evaluate solutions based on their values. The findings emphasize identifying skill gaps and providing formal acknowledgment to improve the sense of responsibility and involvement of the community in CSR initiatives. This is in line with PT. PBN’s commitment to its stakeholders and the sustainable development of the community in the long run. In the end, decision-makers give the utmost significance to the strategy of licensing and training, considering its long-term impact, effectiveness, resource availability, and ease of control.

Corporate Renewable Energy Procurement Prioritization Using Analytic Hierarchy Process (AHP) by Energy Service Company Perspective in Response to COP26

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To be able to participate in the COP26 commitment to work together to make clean and sustainable solutions, making clean power is the most affordable and reliable option for Indonesia to meet its power needs efficiently by 2030. The purpose of this research is to create a prioritization of prospective renewable energy projects from the point of view of a service company as an oil and gas company’s contractor. These include Indonesia’s prospective projects, which are geothermal or carbon capture and utilization, and decarbonization or reduction emission from existing services. This research also decides criteria that important for service company in providing renewable energy. A literature study, interviews with key decisionmakers in the company, questionnaires to company experts, and a questionnaire to practitioners in the industry were done to determine the criteria and prioritization technique. Four criteria of governance, marketing and sales, financial and project management were found to support the prioritization process using the Analytical Hierarchy Process (AHP). Among the nine sub-criteria, the sub-criteria with the highest global weights are profitability, cashflow, and service quality assurance.