Decision Uncertainty Research Articles

A hybrid BWM–CRITIC–VIKOR approach for assessing oil and gas risk scenarios in probabilistic linguistic term set

The oil and gas industry plays a crucial role in supporting energy supply and economic development. Mitigating risks in oil and gas projects is essential for reducing decision-making uncertainties, optimizing resource allocation, and fostering the competitiveness and sustainable growth of enterprises. Therefore, evaluating decision-making risks in the oil and gas sector is of significant practical importance. This paper proposes a comprehensive approach based on the BWM–CRITIC–VIKOR multi-criteria decision-making (MCDM) evaluation model. An evaluation index system encompassing six critical dimensions—technology, economics, environment, security, societal impact, and political factors—is established. To enhance assessment precision, the AHP interval estimation method is employed to identify and eliminate indicators with low contributions. Subsequently, the probabilistic linguistic term set (PLTS) is introduced into the best–worst method (BWM) and CRITIC methods to calculate the weights for each index. This approach helps to circumvent the subjectivity inherent in single subjective weighting methods. To evaluate and rank alternatives, the PLTS is used as an evaluation linguistic tool within the VIKOR framework. Finally, this methodology is applied to decision-making in the oil and gas industry, and its effectiveness and superiority are compared with the AHP–TOPSIS method and the BWM–CRITIC method.

Penerapan IoT dengan Algoritma Fuzzy dan Mikrokontroler ESP32 dalam Monitoring Penyiraman

Smart farming has become a major focus in the development of modern agricultural technology. In this context, the Internet of Things (IoT) offers innovative solutions to increase productivity and efficiency in crop management. This research introduces an IoT-based plant watering monitoring system that uses a fuzzy algorithm and an ESP32 microcontroller. This system is designed to automatically regulate plant watering based on environmental conditions and plant needs. The ESP32 microcontroller acts as the brain of the system, collecting environmental data such as soil moisture, air temperature, and relative humidity. This data is analyzed using a fuzzy algorithm to determine plant watering needs in real-time. Based on the output of the fuzzy algorithm, the system automatically controls the water pump to water the plants according to the specified needs. The application of fuzzy algorithms allows the system to overcome uncertainty in plant watering decisions, especially in the face of complex variations in environmental conditions. With the adoption of IoT technology, farmers can monitor and control crop watering efficiently through web interfaces or mobile applications, even remotely. This research shows that the integration of IoT with fuzzy algorithms and ESP32 microcontrollers can be an effective solution in managing crop watering, increasing overall agricultural productivity, while reducing water and energy consumption.

The Influence of Interpersonal Communication on Relational Commitment in Young Married Couples in Indonesia

This study explores the impact of interpersonal communication on relational commitment among young married couples in Indonesia, employing Structural Equation Modeling (SEM) to analyze the relationships between key variables. Specifically, the research investigates how openness, empathy, support, and positive attitudes influence several critical relational outcomes, namely acquiescence, cooperation, functional conflict, and decision-making uncertainty. The study's findings reveal significant connections between the communication variables and various aspects of relational commitment. Openness and empathy emerged as particularly influential, suggesting that these dimensions of communication play crucial roles in fostering relational stability and satisfaction. Openness, characterized by transparent and honest interactions, was found to enhance acquiescence, cooperation, and reduce decision-making uncertainty and functional conflict. Similarly, empathy, involving the ability to understand and share the feelings of one’s partner, significantly impacted acquiescence and cooperation, though its effect on other relational outcomes was less pronounced. In contrast, support and positive attitudes showed varying degrees of influence across different relational aspects, highlighting their specific but nuanced roles in shaping marital dynamics. These results underscore the importance of tailored communication strategies in strengthening marital relationships. The study provides valuable insights for both researchers and practitioners focused on improving marital satisfaction among young couples. By emphasizing the role of effective communication, the research contributes to the development of interventions aimed at enhancing relational commitment and overall marital stability.

Multiple and subject-specific roles of uncertainty in reward-guided decision-making.

Decision-making in noisy, changing, and partially observable environments entails a basic tradeoff between immediate reward and longer-term information gain, known as the exploration-exploitation dilemma. Computationally, an effective way to balance this tradeoff is by leveraging uncertainty to guide exploration. Yet, in humans, empirical findings are mixed, from suggesting uncertainty-seeking to indifference and avoidance. In a novel bandit task that better captures uncertainty-driven behavior, we find multiple roles for uncertainty in human choices. First, stable and psychologically meaningful individual differences in uncertainty preferences actually range from seeking to avoidance, which can manifest as null group-level effects. Second, uncertainty modulates the use of basic decision heuristics that imperfectly exploit immediate rewards: a repetition bias and win-stay-lose-shift heuristic. These heuristics interact with uncertainty, favoring heuristic choices under higher uncertainty. These results, highlighting the rich and varied structure of reward-based choice, are a step to understanding its functional basis and dysfunction in psychopathology.

Evaluation and Ranking of Energy Alternatives for Implementation in Different Geographic Scenarios using Decision Methods: Case Study of Colombia

In this research, several crucial aspects have been explored in the evaluation and ranking of energy alternatives in Colombia using advanced decision methods such as TOPSIS and Diffuse TOPSIS. The study analyzed how these techniques allow to effectively compare different renewable energy sources in various regions of the country, highlighting the importance of considering multiple approaches due to the unique geographical and energy characteristics of each region. Specifically, five regions were evaluated: Caribbean 1 and 2, Pacific 1 and 2, Andean, Amazonian and Orinoquia, observing significant differences in the evaluation of technologies between the models. In the evaluation of energy sources for each region, the potential of photovoltaic solar energy in the Caribbean and Orinoquia regions was emphasized due to the high solar radiation, wind energy in the Caribbean and Pacific regions due to its strong winds, and biomass in the Amazon and Andean regions thanks to the abundance of organic resources. These technologies not only contribute to the reduction of carbon emissions and the diversification of the energy matrix, but also promote a just energy transition by generating employment and improving the quality of life in local communities. The TOPSIS method and its diffuse variant make it possible to weigh criteria with different degrees of importance and manage uncertainty in decision-making, resulting in more precise evaluations adapted to specific contexts. This type of research is vital for decision-making in the Colombian electricity sector, as it provides a solid and replicable methodology for evaluating energy alternatives in an integral way. The results not only contribute to environmental sustainability, but also boost the socio-economic development of the regions, fostering an equitable and fair energy transition.

Modeling First-Line Daratumumab Use for Newly Diagnosed, Transplant-Ineligible, Multiple Myeloma: A Cost-Effectiveness and Risk Analysis for Healthcare Payers.

This study aimed to assess the cost-effectiveness of two regimens regarded as the standard of care for the treatment of newly diagnosed, transplant-ineligible multiple myeloma in Singapore: (1) daratumumab, lenalidomide, and dexamethasone and (2) bortezomib, lenalidomide, and dexamethasone. Additionally, it aimed to explore potential strategies to manage decision uncertainty and mitigate financial risk. A cost-effectiveness analysis from the healthcare system perspective was conducted using a partitioned survival model to estimate lifetime costs and quality-adjusted life years (QALYs) associated with daratumumab-based treatment and the bortezomib-based regimen. The analysis used data from the MAIA and SWOG S0777 trials and incorporated local real-world data where available. Sensitivity analyses were performed to evaluate the robustness of the findings, and a risk analysis was conducted to analyze various payer strategies in terms of their payer strategy and uncertainty burden (P-SUB), which account for the decision uncertainty and the additional cost of choosing a suboptimal intervention. The incremental cost-effectiveness ratio (ICER) for daratumumab, lenalidomide, and dexamethasone (DRd) compared with bortezomib, lenalidomide, and dexamethasone (VRd) was US $90,364 per QALY gained. The results were sensitive to variations in survival for DRd, postprogression treatment costs, cost of hospice care, and hazard ratio for progression-free survival. The scenarios explored indicated that structural assumptions, such as the time horizon of the analysis, significantly influenced the results due to uncertainties arising from immature trial data and treatment efficacy over time. Among the various payer strategies compared, an upfront price discount for daratumumab emerged as the best approach with the lowest P-SUB at US $14,708. In conclusion, this study finds that daratumumab as a first-line treatment for myeloma exceeds the cost-effectiveness threshold considered in this evaluation. An upfront price reduction is the recommended strategy to manage uncertainties and mitigate financial risks. These findings highlight the importance of targeted payer strategies to address specific types and sources of uncertainty.

Robust ordering, production, and replenishment in a supply chain for innovative products: A two-echelon newsvendor problem with partial information in yield and demand

With partial yield and demand information, we investigate a two-echelon newsvendor problem in a supply chain for innovative product, in which the retailer and the supplier make sequential decisions in ordering, production, and replenishment, respectively. We adopt the minimax-regret criterion to assume the risk-averse nature and deduce the minimax-regret inventory decisions. We explore replenishment (emergency) production strategies for the supplier. Then we propose shortage penalty strategies as well as subsidized replenishment strategies for the retailer so that the supplier can maintain the required supply even under higher replenishment production costs. We further reveal the role of information uncertainty in the minimax-regret decisions and the bullwhip effect. Interestingly, the results show that the penalty strategies do not always lead to less regret for the retailer, and the information uncertainty does not necessarily lead to greater regret for the supplier. Moreover, some schemes to reduce the bullwhip effect are proposed, such as improving the accuracy of uncertain yield, increasing shortage penalty or replenishment subsidy, and decreasing replenishment cost. It is verified that the replenishment strategies can increase profits for both the retailer and the supplier under some conditions. In extensions, we reveal the supplier’s preference for emergency production and external procurement, as well as preferences for information sharing and confidentiality. Meanwhile, we find that decentralized decision-making may even outperform centralized decision-making in some situations when the minimax-regret criterion is adopted to deal with the information deficiency. Finally, the robustness of the replenishment strategies in reducing both enterprises’ regrets is checked.

Portfolio Optimization Strategies: New Approaches Based on Machine Learning Forecasting

This study provides an in-depth discussion and comprehensive review of the latest applications of machine learning techniques in the field of portfolio optimization. The article begins with an overview of traditional portfolio optimization theory and its limitations, and then focuses on how machine learning predictive models, which have flourished in recent years, can provide new perspectives and tools for solving the problems of non-linearity, dynamics and uncertainty in investment decision-making. This paper provides a detailed overview of the application practices of various machine learning algorithms (e.g., deep learning, reinforcement learning, integrated learning, etc.) in the areas of asset return prediction, risk assessment, and optimal weight allocation, and analyses their advantages and challenges compared to traditional methods. The analysis of relevant research cases reveals the significant effect of machine learning predictions in increasing expected portfolio returns, reducing risk exposure, and achieving effective diversification. The study also explores possible future trends and potential research directions for machine learning in portfolio optimization, highlighting the importance of combining domain knowledge with big data-driven intelligent investment decisions. This review aims to provide financial scholars and practitioners with a new way of thinking about portfolio optimization, and to promote the combination of theoretical research and practical operation in the fields of financial engineering and investment management, so as to achieve more accurate and efficient investment decisions.

Peran Tokoh Masyarakat dalam Pelestarian Kearifan Lokal Pasca Ketiadaan Kepala Adat di Desa Adat Cireundeu Cimahi

Establishing a cultural community becomes a valuable asset capable of supporting the dissemination of cultural values. The community in Kampung Adat Cireundeu Village, Cimahi City has long upheld traditional values. This research aims to explain how the Cireundeu community can preserve and maintain its culture despite the absence of an official adat leader. Using a qualitative method with a case study approach, data collection techniques were derived from interviews, observations, and documentation studies. This research found that the Cireundeu community successfully overcame this challenge through collective leadership mechanisms and the use of modern technology. Community figures, including elders and the deputy adat leader, play a crucial role in preserving customs and traditions through the effective distribution of responsibilities and active involvement in various customary activities. Despite facing some obstacles, such as uncertainty in decision-making and suboptimal coordination, the Cireundeu community has adopted adaptive strategies that allow them to maintain cultural preservation and ensure their social continuity. This research demonstrates that even without an Indigenous leader, community strength, local figures, and local innovation can support cultural preservation in sustaining the Indigenous community.

Advanced Fuzzy-Based Decision-Making: The Linear Diophantine Fuzzy CODAS Method for Logistic Specialist Selection

This study addresses the inherent uncertainty in human decision-making by leveraging fuzzy sets, which were introduced to better capture the imprecision associated with human thoughts and judgments. As an extension to traditional fuzzy sets, the Linear Diophantine Fuzzy Set (LDFS) was developed, offering a more flexible approach by relaxing existing limitations on grade values. The LDFS has found applications across various fields, demonstrating its versatility and effectiveness. In this study, we explore the application of the Linear Diophantine Fuzzy Set within the framework of the Combinative Distance-based Assessment (CODAS) method. The CODAS method stands out because it incorporates Euclidean and Taxicab distances. Decision-making should consider not only the direct distances between ideal solutions and alternatives but also the indirect distances. The foremost objective of this research is to propose a novel approach by integrating the CODAS method with the LDFS to address complex decision-making problems characterized by uncertainty and imprecision. To illustrate the practical utility of the proposed method, we apply it to a numerical example involving the selection of a logistics specialist, a critical decision in emergency logistics optimization. The research also includes a case study on a logistics specialist, highlighting the practical application of the methods discussed. Furthermore, this study provides a comprehensive sensitivity analysis of the parameters' weights to evaluate the robustness and reliability of the proposed method. The results highlight the effectiveness of the LDF CODAS method in making informed and reliable decisions under conditions of uncertainty, paving the way for future applications in other decision-making scenarios.

Navigating ambiguity: A novel neutrosophic cubic shapley normalized weighted Bonferroni Mean aggregation operator with application in the investment environment

The Neutrosophic Cubic Shapley Normalized Bonferroni (NC-SNWBM) method represents a cutting-edge approach to decision making theory, combining three distinct mathematical frameworks the neutrosophic cubic sets (NCS), Shapley values, and the Bonferroni aggregation operator. This innovative method addresses the challenges posed by uncertainty, vagueness, and imprecision in decision-making (DM) processes, offering a comprehensive and versatile tool for handling complex and dynamic scenarios. Neutrosophic cubic sets offers a strong platform to handle ambiguous and vague data due to three components Membership Grade (MG), Non-Membership Grade (NMG) and Indeterminancy Grade (IG) in data. By adding Shapley Fuzzy Measures (SFM), which come from cooperative game theory, distribute values among cooperative agents equally and to account for each agent's contributions to all potential coalitions. The Bonferroni aggregation operator—a statistical aggregative tool that regulates the likelihood of many types in error in statistical tests and the interdependence of the input arguments by allowing different values to parameters involved. These values are further improved by normalization in the framework of the NC-SNWBM approach in order to consider the various degrees of impact that agents exert in various circumstances. This operator is smoothly combined with normalized Shapley values and neutrosophic cubic sets in the NC-SNWBM approach to enable the aggregation of data with different levels of imprecision and uncertainty from various sources using NCS. The MG, NMG and IG connected to NCS are important elements of the NC-SNWBM approach. To evaluate each element's contribution to the overall value distribution SFM are used, and the Bonferroni aggregation operator maintains a careful balance between conservatism and significance. Together, these components provide a thorough framework that successfully tackles the problems caused by ambiguity, imprecision, and uncertainty in scenarios involving decision-making. The NC-SNWBM operator is applied to a numerical problem as an application in investment environment and sensitive and comparative analysis are conducted. The recommendation based on sensitive and comparative analysis proposed.

A Study on AG-Groups in Spherical Fuzzy Environment

An AG-group is an algebraic structure that satisfies the left invertive law and includes its left identity and inverse elements. This framework is naturally suited for representing and manipulating various real-life applications in civil engineering, information engineering, artificial intelligence, and more. In this paper, we present the structural application of AG-groups in data encryption and in the rotational transformation of water molecules. Additionally, numerous authors have explored fuzzy set theory over AG-group systems, yielding many valuable results. Spherical fuzzy set theory, an extension of fuzzy set theory, allows for the representation of uncertainty in decision-making, where there may be multiple possible choices or uncertainty about the degree of membership of an element in a set. However, no prior work has combined spherical fuzzy set theory with AG-groups, which motivates our study. In this paper, we apply spherical fuzzy set theory to AG-groups and introduce the concept of spherical fuzzy AG-subgroupoids. We provide the characterization of spherical fuzzy AG-subgroupoids over AG-groupoids and examine their related properties. As an application of spherical fuzzy sets over AG-groups, we develop the concept of normal spherical fuzzy groups over AG-groups and investigate their various properties.

Beyond Risk: A Measure of Distribution Uncertainty

This paper addresses the critical yet often overlooked concept of distribution uncertainty (ambiguity) in decision making, emphasizing its importance alongside traditional outcome uncertainty (risk). It introduces a novel quantitative measure of ambiguity that accurately captures distribution uncertainty. This measure enhances empirical models, yielding more reliable parameter estimates and improving decision-making processes. The study demonstrates the practical value of this ambiguity measure using financial market decision making as an example. The measure helps identify and adjust for uncertainties in underlying distributions, supporting more robust financial models and better risk management. The findings advocate for integrating ambiguity considerations into data analytics models and developing more reliable methodologies for empirical research and practical applications. This study promotes a nuanced understanding of uncertainty, offering significant implications for research methodologies and practical risk management across various fields.

Application of the Affinities Theory to the environmental sustainability of tourist destinations: The case of Ljubljana

Sustainability has become a critical concern for many destinations seeking to revitalize their tourism industry while also dealing with issues stemming from climate change. To address these challenges, practical strategies to manage the harmful effects of the environmental crisis are necessary. Despite the critical role of sustainability, there still needs to be more practical solutions for implementing it in practice. The article aims to (i) broaden the discussion on sustainable tourism and solutions to reduce the impacts of climate change, and (ii) to understand the relationships of affinities between pro-environmental initiatives and the characteristics of the destination based on the perceptions of tourists who visit the city of Ljubljana. This study analyses tourist perception in an urban destination focusing on reducing carbon footprint and promoting sustainable development. Through a case study and the application of Affinities Theory, a specific algorithm to recognise affinity connections, a database with 372 international tourists who visited Ljubljana is utilised. This study has an explanatory goal and uses a comprehensive method (quantitative-qualitative). The findings confirmed that the characteristics of the destination most relevant to the tourist are Sustainable, Environmentally Friendly, and Safe. The research acknowledged practical approaches to improve the competitiveness and sustainability of tourism. The results could assist managers and policymakers in formulating sustainability-based strategies and reducing decision-making uncertainty. Also, it deepens the theoretical understanding of sustainable tourism and climate change mitigation strategies using a modelling and simulation method that other researchers can replicate in different contexts. This innovative research employs the Affinities Theory to assess Ljubljana's urban sustainability, examining how environmental practices can help reduce climate change's impact and how tourists perceive these practices.

Uncertainty of fiscal policy and corporate leverage decisions

We explore the impact of fiscal policy uncertainty (FPU) on corporate leverage in the context of Chinese firms. The analysis reveals a significant negative association between FPU and leverage, consistent across various leverage measures. Additionally, trade credit, financial distress risk, state ownership, and nonlinear dynamics significantly influence this relationship. These findings offer new insights into the effects of fiscal uncertainty on corporate leverage, highlighting the broader implications for corporate financial strategies.

Uncertainty in Postpartum Permanent Contraception Decision-Making: Physician and Patient Perspectives

PurposeWe sought to understand how patients and physicians conceptualize uncertainty in the permanent contraception decision-making process. Basic ProceduresIn 2022–2023, we interviewed postpartum patients with a documented desire for permanent contraception (n = 81) and their delivering physicians (n = 67). Eligible patients gave birth at one of our four study hospitals in California, Ohio, Illinois, and Alabama. We used rapid content analysis and thematic content analysis to develop and refine themes related to uncertainty in permanent contraceptive decision-making. Main FindingsMost patients reported full certainty in their decision regarding permanent contraception, although some expressed doubts. After receiving permanent contraception, some patients discussed grief but overall affirmed their decision. One patient said they wished they had considered other contraceptive options. Physicians reported using a range of strategies to safeguard from patient regret, including ensuring patients were 100% certain with their decision, inferring certainty based on their characteristics, asking patients to think through all scenarios that could affect decision-making, and repeat counseling during multiple interactions. Principal ConclusionsPatient experiences reveal the depth, fluidity, and nuance of patients' contraceptive decision-making processes. Physicians sometimes failed to grapple with this nuance by centering potential regret in their counseling. Personalized and supportive contraceptive counseling that acknowledges the complexity of contraceptive decision-making is imperative. Shared decision-making can help ensure patients can make informed and autonomous decisions about their reproductive lives.

An integrated multi-attributive border approximation area comparison (MABAC) method for evaluating resilience and knowledge sharing of suppliers in pythagorean fuzzy environment

This paper aims to determine the resilience scores of suppliers by considering the importance of knowledge sharing and incorporating a set of criteria that affect the supply chain’s resilience, along with knowledge sharing. In order to achieve this goal, we propose a new multi-criteria decision-making (MCDM) method named MULTIMABAC to evaluate suppliers’ resilience. This method is based on the multi-attributive border approximation area comparison (MABAC) method. The new method consists of criteria weighting, expert weighting, and supplier evaluation. In the criteria weighting section, we extend the BWM (Best–Worst method) using Pythagorean fuzzy sets (PFSs). The weight of experts is determined by incorporating the average concept into the MABAC method. The resilience score of suppliers is calculated using an extended MABAC method with ideal positive and negative solutions. All indices are aggregated using the ordinal priority approach (OPA) to obtain a unique ranking. Additionally, we extend the MULTIMABAC method using PFSs to address uncertainty in supply chain decision-making. Results and sensitivity analysis demonstrate that the proposed method effectively facilitates knowledge sharing in selecting resilient suppliers. Therefore, organizations can use the proposed method to evaluate and choose resilient suppliers. Moreover, the MULTIMABAC method demonstrates robustness to variations in the weights of its constituent parameters.

Nurses’ perception of uncertainty in clinical decision-making: A qualitative study

BackgroundUncertainty is a common challenge for nurses in clinical decision-making, which can compromise patient care quality and safety. To address this issue, it is essential to understand how nurses perceive and cope with uncertainty in their practice. AimThis study aimed to explore nurses’ perceptions of uncertainty in clinical decision-making using a qualitative approach. MethodsThis study was conducted with a qualitative approach and conventional content analysis in 2020. Participants consisted of 17 nurses from different wards of teaching hospitals in Northwestern Iran, recruited using the purposive sampling method. Data were collected through semi-structured interviews and analyzed simultaneously with data collection (June to December 2020). The data were analyzed using the content analysis approach suggested by Wildemuth. Data were managed with MAXQDA10 software. The analysis revealed four main themes and ten subthemes that described the nurses' experiences of uncertainty in clinical decision-making. ResultsThe main themes were: difficult choice, difficult situation, insufficient judgment, and emotional burden. ConclusionsThe study participants defined uncertainty in clinical decision-making as a difficult choice that occurs in difficult situations, which influenced their clinical judgment and emotional well-being. These findings provide valuable insights for developing interventions to help nurses manage uncertainty and improve their decision-making skills and safety.

Changes in the Language of the Reformed Church in the Second Half of the 20th Century: The Convergence of Oral History and Big Data

The author’s journey begins with a deep immersion in his traditional Protestant faith, where he was taught to thoroughly know both the Old and the New Testament. As he reflects on his faith, the concept of being a “stranger and sojourner” comes to the forefront, highlighting the feeling of alienation within the secular world. The narrative takes an interesting turn when the author discusses the impact of changing political language on his perspective. The introduction of new political ideas and discourse challenges the previously straightforward worldview, leading to a sense of uncertainty in decision-making. Believers find themselves in a world with a multiplicity of perspectives that require a re-evaluation of what it means to “deny” or to make choices. In a changing social and political context, the narrative continually explores the intricate connection between faith and language. The author’s experiences and reflections provide a compelling insight into the complexities of navigating a shifting spiritual landscape while grappling with the ever-evolving meaning of words and beliefs. The second half of the article presents the results of a computer analysis of the vocabulary of two Bible translations that defined the language usage of the Reformed Church in the second half of the 20th century: the 1908 Károli and the 1975 New Translation. The analysis focuses on words that present difficulties in understanding due to their archaic or religious nature. As a point of comparison, it also showcases the vocabulary of the Gospel of John, where a mere 199 word roots constitute 80% of word occurrences. Keywords: language of the church, Bible translation, vocabulary of the Bible, letter and soul, protestant language use

Literature Review: Pemanfaatan Instrumentasi Tes Minat terhadap Layanan Bimbingan dan Konseling

Interest and aptitude tests help in recognizing children's potential early on, so that parents and educators can plan education that is more suitable and supports the optimal development of children's potential. The purpose of this study is to help individuals know that interest and aptitude test instrumentation has a major impact in directing individuals in developing themselves, both in academics and careers. Children who study and work according to their interests tend to be more motivated, happy and accomplished. With a clear understanding of interests and aptitudes, children can make better decisions regarding future education, major and career choices. In this study we used the Literature Review method by collecting several sources. The results and discussion of the literature review discussion regarding interest tests, interest inventories, and Android-based psychological test applications in guidance and counseling in schools show that these tools are very important to help students determine educational and career paths according to their interests and talents. Interest tests help reduce uncertainty in career decision-making, improve the fit between individuals and jobs or study programs, and expand understanding of the psychological tendencies underlying their choices.