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Objective– This article aims to comprehensively examine the main types of food crop pests and their attack patterns through a systematic literature review approach. The research focuses on the dynamics of pest attacks, changes in ecological patterns due to climate change, and advances in modern identification technology that enable more accurate early detection. This study also highlights the significance of new paradigms of pest identification based on artificial intelligence (AI), genomics, and landscape mapping in supporting food security at the regional and national levels. Design/methodology/approach– This study used the Systematic Literature Review (SLR) method for scientific publications from 2015–2025 from reputable sources such as Scopus, Web of Science, PubMed, ScienceDirect, SpringerLink, Taylor & Francis, Wiley, AGRIS, and Google Scholar. Of the 326 articles identified in the initial stage, 30 articles in English and Indonesian were selected through a screening process based on strict inclusion–exclusion criteria. All articles were then analyzed using thematic coding techniques to produce an in-depth, evidence-based synthesis. Findings– The study produced four key findings: (1) there are five dominant pests in global food crops, namely Thrips tabaci, Spodoptera exigua/frugiperda, Helicoverpa armigera, Nilaparvata lugens and Sitophilus oryzae; (2) attack patterns are strongly influenced by temperature, humidity, pesticide resistance, and monoculture; (3) modern identification technology AI, drone imagery, multispectral sensors, and DNA Barcoding have increased detection accuracy to 94–98%; and (4) community-based early warning systems accelerate field response and reduce the risk of crop failure. Practical implications– These findings provide a scientific basis for local governments, agricultural extension workers, and farmers to gradually adopt pest identification technology and strengthen integrated monitoring systems at a regional scale. Authenticity/value– This article offers a new conceptual model of “Pest Identification Pyramid – Attack Pattern – Early Warning System” that integrates pest biology, digital technology, and community response to improve national food security.

The aim of this research is to develop a new strategic model for Indonesian border defense by recalibrating the Lykke Framework. It assesses the relevance of the traditional ends–ways–means framework in addressing modern border threats and proposes adding a risk pillar to improve adaptability and multi-domain integration. Using a Systematic Literature Review (SLR), the study examines policy developments, defense doctrines, surveillance technologies, and geopolitical dynamics influencing Indonesian border security. Literature was sourced from international and national databases (ScienceDirect, SpringerLink, SINTA, BRIN, etc.) for publications between 2018–2025. The findings reveal that Indonesia's border regions face complex threats such as sovereignty violations, transnational crime, cyberattacks, and ideological penetration. These challenges highlight the inadequacy of the traditional ends–ways–means framework without incorporating a fourth risk pillar. The study introduces the New Lykke Model, which enhances the strategic framework for integrated military management, considering geopolitical, operational, socio-cultural, and environmental risks. This model offers practical guidance to stakeholders like the Indonesian National Armed Forces (TNI), Bakamla, and the National Police (Polri), aiming to improve border security operations and policy planning. The study is among the first to adapt the Lykke Model to Indonesian border defense, incorporating an integrated risk pillar for a more comprehensive security strategy.

This study aims to analyze production levels and identify leading vegetable commodities in Rejang Lebong Regency during the period of 2023–2024. The data used is secondary data sourced from the Rejang Lebong Regency Agriculture Office and empirical calculations based on Location Quotient (LQ) analysis. The results show that the total vegetable production in Rejang Lebong Regency in 2023 reached 3,451,596 quintals and decreased to 3,198,925 quintals in 2024. The commodities with the highest average production were cabbage (647,021 quintals), eggplant (646,994.5 quintals), and carrots (339,041.5 quintals), while the lowest production was found in kale and long beans. LQ analysis shows that there are eight leading commodities (LQ > 1), namely spring onions, green beans, cauliflower, potatoes, cabbage, mustard greens, carrots, and large chilies, most of which are highly competitive highland crops. The results of this study confirm that Rejang Lebong Regency has strong potential as a horticultural center in Bengkulu Province. Therefore, a commodity-based agricultural development strategy is needed that is oriented towards increasing productivity, added value, and the region's competitiveness in a sustainable manner.

The purpose of this study is to analyze the strategic role of the Green Human Resource Information System (Green HRIS) in bridging the transformation of human resource management with the demands of Environmental, Social, and Governance (ESG) principles, specifically examining how Green HRIS contributes to sustainable HR practices, organizational performance, and digital HR transformation. Using a Systematic Literature Review (SLR) approach, this study identifies, evaluates, and synthesizes prior research by conducting a structured search across major academic databases—Scopus, Web of Science, Springer, Elsevier, and Wiley—for publications from 2020 to 2025 that address green HRM, HR digitalization, sustainable HR practices, and ESG integration. The review process includes screening titles, abstracts, and full texts, extracting key data, and categorizing findings into environmental, social, and governance dimensions. The results demonstrate that Green HRIS strengthens ESG implementation by reducing paper usage, lowering carbon emissions, and promoting sustainable HR practices such as digital recruitment and e-learning, while also improving governance through enhanced transparency, accountability, regulatory compliance, and real-time reporting. Empirical evidence indicates that Green HRIS fosters employee engagement, organizational innovation, and the development of green competitive advantages. Practically, the study highlights how organizations, policymakers, and HR managers can utilize Green HRIS to optimize digital transformation and meet ESG requirements, thereby reinforcing legitimacy and long-term competitiveness within the green economy. This research offers originality as one of the first systematic reviews addressing Green HRIS in the ESG era, integrating theories such as the Resource-Based View, Technology Acceptance Model, and organizational sustainability theory, while also mapping trends, best practices, and gaps for future research.

This study aims to systematically review performance measuring factors in MSMEs in the digital era in Indonesia. The research method uses Systematic Literature Review (SLR) with the design of the PRISMA framework. The data sources used were obtained from various databases of quality scientific publications including emerald, taylor and francis, springerlink, and sciencedirect, with a time span from January 2020 to June 2025. A total of 24 international scientific articles published in the period were analyzed for further identification on the main trends, main topics, and research directions. The results of the study show that the role of digital transformation has become an important factor in shaping the performance of MSMEs in the modern era. The factors that measure the performance of MSMEs are related to entrepreneurial competence, adaptation to technology, innovation ability, and government support. Some of these supporting factors also support resilience and sustainability for micro, small, and medium enterprises (MSMEs). However, the success of work achievements for business actors cannot be separated from adequate organizational readiness and resources, as well as good governance. This study contributes academically in the form of a conceptual framework for performance improvement measures for MSMEs, as well as providing recommendations as strategies for micro, small, and medium business actors to increase productivity so that businesses can grow and be sustainable in the digital era.

This study aims to systematically review the determinants of innovative work behavior in MSMEs in the digital era in Indonesia. The research method uses Systematic Literature Review (SLR) with the design of the PRISMA framework. The data sources used were obtained from various databases of quality scientific publications including emerald, taylor and francis, springerlink, and sciencedirect, with a time range from 2020 to 2025. A total of 15 international scientific articles published in the period were analyzed for further identification of the main trends, main topics, and research directions. The results of the study show that the results of the study show that three main components consist of Innovative Work Behavior Determinants (PKI) in Micro, Small, and Medium Enterprises (MSMEs) in the modern era: Organizational/Interpersonal Factors, Leadership Factors, and Individual Factors. This Systematic Review serves as a comprehensive summary of evidence that collectively corroborates individual findings, increases confidence in applicable practices, and directs MSME strategies to ensure survival and competitive advantage amid the challenges of the digital age.

The purpose of this study is to investigate the strategic role of air transportation management in Military Operations Other Than War (MOOTW), particularly in archipelagic contexts such as Indonesia, where rapid humanitarian response, territorial surveillance, and civil–military cooperation are essential for resilience. By applying a Systematic Literature Review (SLR), this article synthesizes findings on humanitarian logistics, technological transformation, and policy frameworks for strengthening national defense readiness. Design/methodology/approach – This study employs a qualitative Systematic Literature Review (SLR) methodology guided by PRISMA principles, analyzing 30 scholarly contributions from 2009–2025, including international peer-reviewed journals, Routledge and Springer volumes, arXiv preprints, and Indonesian academic publications.Results highlight that strategic air  transportation is indispensable for disaster relief, medical evacuation, and supply delivery in archipelagic nations. The adoption of AI, machine learning, UAVs, and reinforcement learning has enhanced responsiveness and equity in humanitarian supply chains. However, persistent challenges include aging fleets, interoperability constraints, and fragmented civil–military coordination. The study underscores the need for modernization of air assets, institutionalized civil–military collaboration, and integration of AI-based routing and command systems. Strengthening these aspects can enhance Indonesia’s resilience and preparedness in MOOTW scenarios. This article uniquely bridges global research on data-driven air power with Indonesian defense perspectives, proposing a scalable strategic framework for air transportation management that advances archipelagic resilience.

Purpose –This article aims to examine Territorial Defense Management (TDM) as an adaptive defense strategy in the contemporary era, with a focus on the synergy of UAV–sensor fusion–C2 technologies, whole-of-defense cyber orchestration and strengthening community resilience in facing multidimensional threats. Design/methodology/approach –This study employed a Systematic Literature Review (SRB) approach, using scientific literature sources from 2021–2025 from Scopus, IEEE, Springer, ScienceDirect, Garuda, and ResearchGate. Thirty-one primary articles were selected through rigorous screening and then analyzed using thematic coding and data triangulation to ensure the validity of the findings. Findings –The study results show that: (1) UAVs with sensor fusion increase the effectiveness of regional surveillance, although they require a counter-UAV system and good spectrum governance; (2) whole-of-defense cyber is proven crucial with the support of threat intelligence, territorial cyber operations centers, and AI for anomaly detection and automated response; (3) community resilience strengthens defense through emergency communications, early warning systems, and community participation in joint training with authorities. Practical implications –The effectiveness of MPT can be enhanced through standardization of IoMT architecture across the military services, counter-UAV and cyber exercises at the regional level, and the development of quantitative metrics to measure community resilience linked to military-level readiness. Originality/value –This article contributes by integrating technology, cyber, and community perspectives into a single adaptive MPT framework, thereby strengthening deterrence, rapid response, and socio-technological resilience. This approach is relevant for strengthening Indonesia's modern defense doctrine.

Purpose –The objective of this research is to analyze the role of advanced materials as a foundation for technological innovation and as a strategic element in strengthening the national defense system. The study focuses on the interrelationships between policy aspects, industry dynamics, and theoretical frameworks to explain the urgency of adopting advanced materials in Indonesia. Design/methodology/approach –This study uses a conceptual approach based on a systematic literature review (SLR) by examining reputable international publications published by Elsevier, Springer, Wiley, Taylor & Francis, IEEE, ACM, ScienceDirect, SAGE, JSTOR and DOAJ as well as national literature indexed by SINTA. The analysis was conducted using a thematic synthesis method that combines regulatory and policy dimensions, empirical data related to budget trends and industrial implementation, and theoretical models including diffusion of innovation, technology acceptance models, and behavioral reasoning theory. Findings –Studies have shown that advanced materials such as lightweight composites, high-entropy materials, smart materials, and functional coatings have a significant role in strengthening military resilience, reducing dependence on imports, and improving the efficiency of defense logistics. However, the adoption of these materials still faces obstacles such as high production costs, limited human resources, and the vulnerability of critical mineral supply chains, which are heavily influenced by global geopolitical dynamics. Practical implications –This study emphasizes the importance of strengthening national research, integrating the defense industry into the DEFEND ID ecosystem, and international collaboration to accelerate technology transfer. Mapping the critical mineral supply chain also needs to be a strategic priority to ensure the sustainability of defense materials development. Originality/value –This article offers a novel contribution through the simultaneous integration of policy perspectives, empirical data, and theoretical frameworks in the context of advanced materials development in Indonesia, an aspect that has rarely been comprehensively explored in previous studies.

Purpose –This article aims to integrate three strategic pillars in strengthening Indonesia's defense human resources (HR), namely Crew Resource Management (CRM) in military medicine, national biological defense, and STEM-based education. Design/methodology/approach –The research used a systematic literature review approach by examining literature from international databases (Elsevier, Springer, Wiley, Taylor & Francis, ACM, IEEE, ScienceDirect, SAGE, DOAJ, JSTOR) and reputable national journals (SINTA, GARUDA, BRIN). The analysis was conducted thematically with normative, empirical, and conceptual approaches. Findings –The study results show that: (1) CRM effectively improves communication, coordination, and decision-making of military medical teams in crisis situations; (2) the establishment of a Biological Defense Agency is urgently needed to address the threat of pandemics, bioterrorism, and transnational biosecurity; and (3) STEM education has been proven to strengthen innovation, adaptability, and the competence of the younger generation of defense personnel. The integration of these three aspects results in the CRM–Bio-Defense–STEM Nexus conceptual framework as the foundation for developing Indonesian defense human resources towards the 2045 vision. Practical implications –This study recommends strengthening national policies through: (1) a STEM-based defense curriculum, (2) CRM training in military medical education and operations, and (3) the establishment of a special biological defense institution as the front line in facing biological threats.Originality/value –This article provides a new contribution in the form of an integrative conceptual model of CRM–Bio-Defense–STEM that has never been studied holistically in the context of Indonesian defense, while also offering a strategic framework for the development of adaptive, innovative, and resilient national defense human resources.

Purpose – Purpose This is for explore interconnection strategic between system energy and defense in support resilience national with propose draft paradigm energy dual role paradigm This positioning energy No only as protected objects​ from threat external, but also as subject strategic support​ operation military through energy renewable, implementation network smart, and technology storage battery. Design/ methodology / approach – Research This use approach review library systematic (SLR) for synthesize findings academic and reports policy from three year lastly, which involves source journal national (SINTA indexed) and international (Elsevier, Springer, IEEE, etc.), with focus on intersection between resilience energy and defense strategy national. Findings – Review This disclose that infrastructure resilient energy​ increase capability defense, while system formidable defense​ ensure continuity supply energy national research​ This propose an integrative model consisting of from three layer strategic: integration policy national (between RUEN and RENSTRAHAN), development infrastructure green and digital, and development capacity source Power man together. Framework Work integrative This strengthen reciprocal resilience​ between sector energy and defense. Implications practical – The makers policies, institutions military, and stakeholders interest energy pushed for together implementing synchronized strategies, integration curriculum and investment in infrastructure digital energy use reach resilience national term long in face uncertainty geopolitics and environment. Originality / Value – Study This introduce framework Work new paradigm energy role double in defense national, which provides runway theoretical and practical for integrate transition energy sustainable with planning defense strategic. Study This contribute in a way conceptual for bridge gap between policy energy and defense strategy, especially in context threat hybrids and vulnerabilities system cyber-physical.

This study aims to systematically examine the influence of digital literacy on the learning outcomes and 21st-century skills of high school students. The method used is a Systematic Literature Review (SLR) following the PRISMA guidelines. Data sources were obtained from various academic databases, including Google Scholar, ERIC, ScienceDirect, and SpringerLink, with publications ranging from 2019 to 2025. A total of 30 articles were selected based on predetermined inclusion and exclusion criteria. The analysis was conducted using a thematic approach to identify patterns, relationships, and the contribution of digital literacy to learning outcomes and the development of 21st-century skills, such as critical thinking, collaboration, communication, and creativity. The synthesis results show that digital literacy has a significant influence on improving learning outcomes and strengthening 21st-century competencies. This study emphasizes the importance of integrating digital literacy into secondary school curricula and teacher training to support effective 21st-century learning.

This research aims to develop a digital-based governance model for village finance to support the realization of a Smart and Green Village. The study analyzes how digital transformation in village finance management can increase transparency, accountability, and efficiency, while promoting sustainability-oriented budgeting and environmental practices. A Systematic Literature Review (SLR) was used to identify, evaluate, and synthesize scientific publications from 2022 to 2025, accessed through reputable databases such as ScienceDirect, Springer, Wiley, Taylor & Francis, SAGE, ACM, and IEEE. The review focused on topics including digital governance in villages, digital public finance, smart village development, green budgeting, environmental sustainability, and rural digital transformation. Findings indicate that digital-based village finance governance enhances administrative efficiency, strengthens budget transparency through real-time monitoring, minimizes financial deviation risks, and boosts public participation in fiscal accountability. Integrating digital systems with green budgeting features enables the prioritization of sustainable programs, such as renewable energy, waste management, climate change mitigation, and green infrastructure development. The study suggests a comprehensive digital-based governance model that includes e-budgeting, e-accounting, digital payment systems, public transparency dashboards, and environmental performance indicators to support the implementation of a Smart and Green Village. This research offers strategic insights for village governments, policymakers, and practitioners on the importance of adopting digital governance tools to improve financial management and strengthen sustainable development at the local level.

This study aims to compare and analyze the accuracy levels of four financial distress prediction models—Altman Z-Score, Springate, Grover, and Zmijewski—in anticipating the potential bankruptcy of companies subjected to delisting from the Indonesian Stock Exchange (IDX). The delisting phenomenon, which is strongly linked to severe financial deterioration, provided the core motivation for identifying the most reliable predictive instrument, utilizing secondary data from the annual financial reports of delisted companies during the 2019-2023 observation period. Descriptive analysis techniques were employed to calculate the accuracy rate and Type Error for each model. The comparative results consistently indicate that the Springate Model is the most effective, consistent, and accurate model for predicting financial distress in delisted firms, achieving an accuracy rate of 89% in both the first and second years prior to delisting, while the Altman Z-Score model exhibited lower accuracy (68.75% and 62.50%). This key finding emphasizes the superiority of the Springate Model as a crucial diagnostic tool for investors and regulatory bodies in assessing corporate bankruptcy risk.

This study aims to analyze the prediction of financial distress using the Altman Z-Score, Springate, and Zmijewski methods at PT Sri Rejeki Isman Tbk in 2019-2023. This type of research is descriptive research with a quantitative approach. Using secondary data with documentation techniques and literature studies in the form of related company financial reports, books, articles, journals and other publications related to the research topic. The sampling technique was carried out using a purposive sampling method. The sample in this study was obtained using a purposive sampling technique and obtained as many as 5 financial reports from the company PT Sri Rejeki Isman Tbk for the period 2019-2023. The results of the study show that the results of calculations using the Altman Z-Score method indicate that in 2019-2023 PT Sri Rejeki Isman Tbk experienced fluctuations in the company consistently still in the category of bankruptcy, the Springate method shows that the company experienced a decline in its financial performance, and the Zmijewski method shows that companies that experience fluctuations in financial performance conditions, Although there are fluctuations in the X-Score value and improvements in certain years.

Unstable financial conditions in insurance companies can serve as an early indicator of potential bankruptcy, which may have wide-ranging impacts on policyholders, shareholders, and the overall stability of the financial sector. Therefore, early detection of bankruptcy risk is critically important. This study aims to evaluate the effectiveness of the Springate model in identifying potential bankruptcy among insurance companies listed on the Indonesia Stock Exchange during the 2022–2024 period. The Springate model was chosen due to its simplicity and its ability to provide quantitative insights into a company's financial condition. Data were collected from the annual financial statements of 16 companies selected through purposive sampling based on the completeness and consistency of their financial reporting. The model applies the S-Score calculation as the basis for classifying companies into financial distress or non-financial distress categories. The analysis revealed that six companies consistently exhibited signs of financial difficulty, with three of them identified as being in a state of financial distress for three consecutive years. Meanwhile, the other ten companies demonstrated stable and healthy financial conditions throughout the observation period. These findings indicate that the Springate model is reasonably practical as an early detection tool for bankruptcy risk, particularly in the insurance sector, which is influenced by various internal factors such as risk management, as well as external factors like economic fluctuations and government regulations. Therefore, this model can be utilized as a decision-support tool for both management and investors in making strategic financial decisions.

This research is motivated by significant fluctuations and a decline in profits for companies in the clothing and luxury goods subsector listed on the IDX for the period 2021-2023, indicating potential financial difficulties. This research aims to evaluate the company's condition using four prediction models, namely Altman-ZScore, Springate, Fulmer, and Taffler, and to determine the most suitable model for the sector. The method applied is quantitative comparative with a purposive sample of 11 companies, using financial statement data from 2021-2023 and analyzed using the formulas for each predictive model. The research findings indicate that the four models produce different predictions regarding the company's financial condition. Additionally, there are differences in the accuracy levels of the four models. The Springate and Taffler models achieved the highest accuracy rate of 85%, followed by Altman at 67% and Fulmer at 64%. The findings of this study confirm that the Springate model is the most reliable tool for early warning for companies and stakeholders, enabling faster preventive measures to prevent bankruptcy.

Bankruptcy is a condition where a business cannot operate effectively due to severe financial difficulties it is currently experiencing.  This research purposes to analyze the ratio of the Altman, Springate, and Grover models in analyzing bankruptcy in food and beverage corporations listed on the IDX with reference to signaling theory. The data analysis approach used are One Way Anova test and accuracy level test. Using 20 company samples with purposive sampling method. The final proceeds of the research explain that there are significant differences between the Altman and Springate models, significant differences between the Altman and Grover models, and no significant differences between the Springate and Grover models in predicting bankruptcy in food and beverage companies for the period 2019-2023. The very accurate prediction model was achieved by the Grover model.

The purpose of this study is to determine the trends and developments in corporate tax avoidance studies using a mixed method approach. This method includes a quantitative approach in bibliographic analysis and literature review. Data were collected through searching national and international journals indexed in Emerald, Springer, and Scopus by referring to relevant publications. Data analysis includes: (1) mapping trends and developments in corporate tax avoidance research with Vosviewer software based on bibliographic studies; and (2) identifying trends and issues in corporate tax avoidance through literature review. The results of the Vosviewer analysis found five large groups with 40 main topics after selection. All topics are explained comprehensively through a literature review. This study provides a comprehensive picture of themes that are often studied in previous literature, thus becoming a reference for further research.

This study systematically analyses the predictive ability financial ratios have in relation to the emergence of financial distress among non-cyclical companies on the Indonesia Stock Exchange during the period 2020-2023. Secondary data was collected from a sample of 151 secondary data companies listed on the Indonesia Stock Exchange, spanning the years from 2020 to 2023. In order to ascertain the relationship between the independent variables (X1, X2, X3) and the dependent variable, Multiple Linear Regression models are utilised by employing the Eviews calculation application. As a model, the Springate model is employed, which is used to measure financial distress. The financial ratios selected for analysis encompass the liquidity ratio, the leverage ratio, and the profitability ratio. The findings of this study suggest that the profitability ratio exerts a substantial positive effect, or a moderate effect, on the phenomenon of financial distress. In contrast, the liquidity ratio and leverage ratio demonstrate an absence of statistically significant influence on the phenomenon of financial distress. Extensive analysis of the results indicates that financial distress, as measured by Springate, does not exert a substantial influence on the findings obtained from this study. The incorporation of diverse samples and models in subsequent studies is likely to introduce variations into the research outcomes.