Publication Search

Financial distress has become a critical issue for companies operating in highly competitive and capital-intensive industries, making effective corporate governance and the efficient utilization of intangible resources increasingly important for ensuring long-term financial sustainability. This study aims to examine the effect of Good Corporate Governance on Financial Distress and to investigate the mediating role of Intellectual Capital in this relationship. The research employs a quantitative explanatory approach using panel data from 23 energy and mining companies listed on the Indonesia Stock Exchange during the 2021–2024 period, resulting in 92 firm-year observations. Secondary data obtained from annual reports and financial statements were analyzed using descriptive statistics, classical assumption tests, panel regression analysis, and mediation analysis. The findings indicate that Good Corporate Governance has a significant negative effect on Financial Distress, suggesting that stronger governance practices improve financial stability and reduce the likelihood of financial difficulties. Intellectual Capital also demonstrates a significant negative effect on Financial Distress and partially mediates the relationship between Good Corporate Governance and Financial Distress. These findings imply that effective governance combined with the strategic management of intellectual resources enhances organizational resilience and supports sustainable corporate performance. The study contributes to the literature by integrating governance quality and intellectual capital into a single framework for explaining financial distress and provides practical insights for managers, investors, and policymakers in strengthening corporate sustainability.

The increasing emphasis on sustainable business practices has encouraged companies to integrate environmental and social responsibilities into their strategic and financial decision-making processes. This study investigates the influence of Green Accounting on Firm Value and examines the moderating role of Corporate Social Responsibility (CSR) within the Triple Bottom Line framework. A quantitative research design was employed using panel data from 23 energy, mining, and infrastructure companies listed on the Indonesia Stock Exchange during the 2022–2024 period, resulting in 69 firm-year observations. Secondary data were collected from annual reports and sustainability reports and analyzed using descriptive statistics, classical assumption tests, and Moderated Regression Analysis (MRA). The findings indicate that Green Accounting does not have a significant direct effect on Firm Value, while CSR also shows no significant direct influence. Furthermore, CSR is unable to significantly moderate the relationship between Green Accounting and Firm Value. These results suggest that sustainability initiatives implemented by Indonesian companies have not yet generated measurable short-term financial benefits, although they may contribute to long-term corporate legitimacy, stakeholder trust, and sustainable competitiveness. The study provides practical implications for corporate managers, investors, and policymakers by emphasizing the importance of strengthening sustainability reporting quality and integrating environmental and social strategies into long-term corporate value creation.

Early Marriage in Pagar Alam City is currently still quite high, the Pagar Alam Religious Court only relies on a recap of the number of cases per year to draw conclusions about the early marriage data. This method has limitations in classifying early marriage factors, so the Religious Court has difficulty in monitoring and controlling the occurrence of Early Marriage in Pagar Alam City. The purpose of this research thesis is to produce a classification system for Early Marriage factors using the K-Nearest Neighbor Algorithm to find out what factors influence the occurrence of Early Marriage, the method used in this study is the Cross Industry Standard Process for Data Mining (CRISP-DM) which has 6 stages, namely: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The testing stage in this study uses Confusion Matrix and BlackBox Testing. The final results of this study indicate that the system can classify Early Marriage factors. The classification model built achieved an Accuracy of 94.12% and a Precise value of 85.71% and a Recall value of 100.00%, while testing using Black Box testing in the form of alpha obtained a feasibility value of 83.2%, so this system is very suitable for use.  

This study aims to analyze the effect of liquidity and profitability ratios on stock returns through Price to Book Value (PBV) in coal mining companies listed on the Indonesia Stock Exchange (IDX) during 2020-2024. The research uses secondary data analysis from financial reports of the companies collected through documentation techniques, and the data is analyzed using Partial Least Squares (PLS) based on Structural Equation Modeling (SEM). The results show that profitability significantly influences stock returns and PBV, while liquidity has a negative but insignificant effect on PBV and stock returns. Moreover, PBV does not mediate the relationship between liquidity and stock returns or profitability and stock returns. This study recommends that companies focus on improving profitability to enhance stock returns, while investors should consider profitability performance when making investment decisions. Recommendations for future research include adding other independent variables such as leverage or macroeconomic factors and expanding the sector and period coverage for greater generalization.

Corruption committed by the leader of an independent state oversight institution represents a paradox that fundamentally undermines the legitimacy of government governance. This study examines the case of Hery Susanto, Chairman of the Ombudsman of the Republic of Indonesia, who was designated as a corruption suspect by the Attorney General's Office on April 16, 2026—merely six days after his inauguration—in connection with alleged bribery of Rp1.5 billion from PT Toshida Sulawesi Hijau Indonesia involving the management of Non-Tax State Revenue (PNBP) in the nickel mining sector for the period 2013–2025. This study aims to analyze the manifestation of the three elements of the Fraud Triangle—pressure, opportunity, and rationalization—within this case, and to formulate systemic implications for corruption prevention in independent state institutions. Employing a normative-empirical legal research approach with a case study method, data were collected through documentation and qualitative content analysis of legal documents, official press releases from the Attorney General's Office, and verified media reports. The findings reveal that pressure stemmed from financial motivation and career ambition; opportunity arose from weak internal oversight mechanisms, the perpetrator's strategic position, and regulatory gaps in Law Number 37 of 2008; while rationalization manifested through cognitive justification that framed the receipt of compensation as a reasonable reward for services rendered. This study contributes to the literature on forensic accounting and corruption criminology, while recommending the establishment of an independent Ombudsman Supervisory Board and the strengthening of a digital-based early detection system.

This study aims to compare the performance of three boosting algorithms, namely XGBoost, LightGBM, and CatBoost, to predict the success of MSMEs. The data used consists of 250 entries with 13 attributes that include business actor characteristics, initial capital, industry experience, financial record-keeping, internet utilization, business planning, partnerships, and the target variable success. The pre-processing stage includes checking for missing values, standardizing numerical attributes, and splitting the data into 80% training data and 20% test data. The evaluation results show that XGBoost provides the best performance with an accuracy of 0.92, precision of 0.8333, recall of 0.8333, F1-score of 0.8333, and ROC-AUC of 0.9715. LightGBM has an accuracy of 0.88, while CatBoost achieves an accuracy of 0.90. The research results show that XGBoost has the best ability to classify successful and unsuccessful MSMEs. The feature importance results also show that the success of MSMEs is influenced by a combination of several key factors. This research emphasizes that boosting algorithms are effectively used as predictive models to support the analysis of MSME success.

This study aims to formulate an engineering strategy for water quality management and pollution control in the Tiku Sub-watershed, North Musi Rawas Regency. The study used a descriptive approach by integrating selected technical data from a dissertation-based assessment with semi-structured interviews involving 20 key informants representing technical agencies, village and subdistrict governments, community leaders, artisanal and small-scale gold mining actors, farmers, and riverbank communities. The analysis focused on water quality status, water availability and demand, pollution sources, perceived impacts, implementation constraints, and priority interventions. The results showed that the Tiku Sub-watershed is under significant environmental pressure. The average pollution index was 6.65, indicating a moderately polluted status, while mercury, cadmium, phosphate, and ammonia were the dominant parameters of concern. Surface water availability remained relatively adequate at 45,842,699.79 m3/year, and the average Criticality Ratio was 0.266; however, the water pollution carrying capacity was poor. Interview results indicated that mercury use and processing waste from artisanal gold mining were the most urgent issue (35%), followed by land-cover change and riparian degradation. The recommended strategy combines mercury-free processing technology, alternative livelihood development, cross-sectoral supervision, riparian rehabilitation, and transparent water-quality monitoring. The findings imply that watershed engineering should integrate technical, institutional, and socio-economic interventions.

Hypertension is one of the leading non-communicable diseases contributing significantly to cardiovascular morbidity and mortality worldwide. Despite the availability of extensive electronic medical record data in healthcare institutions, these data are often utilized only for administrative reporting rather than predictive analysis. Consequently, opportunities to identify age groups with a higher probability of developing hypertension remain underutilized. This study aims to implement the Naïve Bayes classification algorithm to analyze age distribution and classify the risk of hypertension among patients using healthcare data. The research adopted the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology, including business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Patient medical record data consisting of demographic and clinical attributes, including age, systolic blood pressure, diastolic blood pressure, body weight, gender, and hypertension status, were processed using the Naïve Bayes algorithm. Model performance was evaluated using a confusion matrix by measuring accuracy, precision, recall, specificity, and balanced accuracy. The implementation demonstrates that the Naïve Bayes algorithm is capable of classifying hypertension risk efficiently while providing probabilistic information regarding age groups with a higher tendency to experience hypertension. The resulting classification model offers an effective decision-support tool for healthcare providers in conducting targeted screening, preventive interventions, and evidence-based health planning. The findings also indicate that data mining techniques can transform routinely collected medical records into valuable clinical knowledge for early hypertension prevention and healthcare decision-making.

The governance of sand and gravel mining requires an integrated assessment of technical planning, occupational safety, environmental control, reclamation, and regulatory compliance. This study evaluated the governance of CV. Ria Bersaudara, a sand and gravel mining company located in Pasar Surulangun, Rawas Ulu District, Musi Rawas Utara Regency, using the Good Mining Practice framework. The study used a descriptive evaluative approach based on field observation, document review, indicative resource estimation, equipment productivity analysis, occupational safety and environmental risk assessment, and compliance mapping. The results show that the company has a basic legal foundation through an exploration mining permit covering 12.5 ha; however, several governance components require improvement. The indicative prospective area was approximately 2.50 ha, with an effective follow-up area of 1.80 ha and an estimated indicative resource of 21,600 m³ or 35,640 tons. Productivity analysis indicated that excavator capacity reached about 61 m³/hour, while one dump truck only transported about 10.3 m³/hour, creating a haulage bottleneck if the truck fleet is insufficient. Safety implementation was also not optimal, with personal protective equipment compliance estimated at only 55%. The study recommends validating permit documents, strengthening technical exploration data, improving drainage and sediment control, enforcing safety procedures, implementing progressive reclamation, and establishing daily operational records.

This study aims to analyze the impact of nickel mining activities on the religious life of the community in West Kabaena District, Bombana Regency. The research employed a qualitative method with a descriptive approach to obtain an in-depth understanding of the social and religious changes occurring within the community. Data were collected through interviews, observations, and documentation involving religious leaders, community leaders, youth representatives, and mining workers. The collected data were analyzed through data reduction, data display, and conclusion drawing. The findings indicate that nickel mining activities have not diminished the community’s understanding of environmental stewardship as a religious responsibility. However, increasing economic dependence on the mining sector has gradually reduced public concern for environmental preservation. In the religious sphere, mining activities have contributed positively by supporting the construction and improvement of worship facilities and religious programs. Nevertheless, work-related demands have reduced the participation of some community members in religious activities. Furthermore, mining activities have affected social solidarity within the community. Values such as brotherhood, mutual cooperation, and social care remain preserved, although changes in social interaction patterns and widening economic disparities have become increasingly apparent. The study concludes that nickel mining activities generate both positive and negative impacts on the religious life of the West Kabaena community. Therefore, balanced policies integrating economic development, environmental sustainability, and religious values are essential to promote sustainable community welfare and strengthen social harmony.

Artisanal and small-scale gold mining (ASGM) provides short-term income for rural communities but frequently creates environmental, safety, and governance problems when it operates outside formal control. This study aimed to analyze the existing condition of ASGM, identify the driving and inhibiting factors of its arrangement, describe the perceived impacts, and formulate strategic directions for ASGM arrangement in Karang Jaya District, North Musi Rawas Regency, Indonesia. A qualitative descriptive approach was applied using semi-structured interviews supported by secondary data on the study area, population, and agricultural land use. Twenty-two informants represented district officials, village officials, technical agencies, company representatives, community leaders, nearby residents, and ASGM actors. Data were analyzed through reduction, presentation, interpretation, and conclusion drawing. The findings show that ASGM development is driven by gold potential, mining history, household economic pressure, limited alternative employment, and weak field control. The main impacts include land degradation, open mining pits, landslide and occupational accident risks, and mercury-related water and soil contamination. The recommended strategy combines alternative livelihood development, skills training, local economic institutional strengthening, gradual area monitoring, land rehabilitation, and mercury-risk education.

The Free Nutritional Meal Program (MBG) is a government policy that is widely discussed by the public through social media, especially TikTok. Various comments that have emerged indicate differences in public opinion towards the program, so an analysis is needed to determine the tendency of public sentiment. This study aims to analyze TikTok user sentiment towards the Free Nutritional Meal Program using the Naive Bayes method. The research method is carried out through several steps, namely collecting TikTok comment data, preprocessing text, labeling sentiment data into positive, negative, and neutral, feature transformation using TF-IDF, and classification using the Naive Bayes algorithm. Based on the analysis of 500 comment data, the results show that positive sentiment dominates public opinion by 42% (210 data), followed by negative sentiment by 36% (180 data), and neutral sentiment by 22% (110 data). Testing the classification model using Naive Bayes produces excellent performance with an accuracy rate of 86%, precision of 84%, recall of 85%, and F1-score of 84%. The conclusion of this study shows that the Naive Bayes method is effective as an approach in social media sentiment analysis to map public responses to government policies.

Bangka Belitung Islands Province as the largest tin producer faces legality dilemmas and criminalization of artisanal miners due to permit centralization through Law Number 3 of 2020. This study aims to analyze the impact of centralization on artisanal miners' legal access, criminalization practices under Article 158 of the Mineral and Coal Law, and the form of Bangka Artisanal Miners Alliance (ATRB) struggle demanding legal certainty. The research employs qualitative case study approach with data collection techniques through literature study and document analysis of regulations, court decisions, and media reports. Findings show centralization narrows legal access causing slow and bureaucratic process for Artisanal Mining Area (WPR) designation and Artisanal Mining Permit (IPR) issuance. Criminalization practices more frequently affect small-scale miners major actors, creating injustice perceptions and worsening socio-economic conditions of mining households. ATRB emerges as a social movement demanding legal recognition through accelerated WPR and IPR plus economic redistribution through fair tin trade governance. Non-transparent royalty management reaching Rp1.7 trillion worsens community vulnerability. This research contributes to social movement and natural resource politics studies by emphasizing the importance of participatory legalization and governance reform to reduce social conflict.

Population growth is an important indicator in regional development planning because it influences the provision of public services, infrastructure development, and policy formulation. Accurate population estimation is therefore essential to support data-driven decision-making by local governments. This study aims to estimate the population growth rate of Serdang Bedagai Regency by applying data mining techniques using the Multiple Linear Regression method. The data used were obtained from the Central Statistics Agency (BPS) of Serdang Bedagai Regency for the period 2019–2023 and include the number of male and female residents. The research process involved several stages, including data collection, data preprocessing, model development, and statistical analysis. Based on the analysis, a regression model was obtained with the equation Y = 0 + 1.5558X1 + 0.4367X2, where Y represents the total population, X1 represents the number of male residents, and X2 represents the number of female residents. The results indicate an estimated population of 683,056 people in 2024, showing an increase compared to the previous year. These findings suggest that the Multiple Linear Regression method can provide reliable population estimates and serve as a useful reference for supporting evidence-based regional development planning and population management strategies in Serdang Bedagai Regency.

Nature tourism is one of the sectors that plays an important role in supporting the development of regional tourism, including in Lahat Regency, which has significant waterfall tourism potential. Currently, many visitors share their reviews and experiences through digital platforms such as Google Maps. This review can be used as a source of information to understand the public's evaluation of the quality of tourist attractions. This study aims to examine public perception of tourist attractions in Lahat Regency using the Support Vector Machine (SVM) method. Research data were collected through scraping from Google Maps, totaling 500 reviews from five tourist attractions, namely Curup Maung, Curup Buluh, Senyawe Waterfall, Panjang Waterfall, and Green Canyon. The research stages include data preprocessing, consisting of cleaning, case folding, normalization, tokenization, stopword removal, and stemming. After that, feature extraction was carried out using the TF-IDF method and the classification process using the SVM algorithm. Based on the research results, the Support Vector Machine (SVM) method is able to perform sentiment classification quite well, although the accuracy level varies for each tourist attraction. Curup Maung and Panjang Waterfall achieved the highest accuracy level of 90%. Nevertheless, most visitor reviews were dominated by negative sentiments. This indicates that there are still several aspects that need to be improved, particularly related to tourist facilities and services. This research is expected to serve as a consideration for tourism managers and local governments in efforts to improve management quality as well as the development of tourism in Lahat Regency.

 Education in vocational high schools (SMKs) requires effective data management to improve students’ academic achievement and discipline. At SMK Islam Secang, students’ academic scores and attendance data have so far functioned merely as administrative archives, making it difficult to identify patterns of student performance. This study aims to classify students based on academic achievement and discipline by applying the K-Means Clustering algorithm using RapidMiner. The data used in this study consist of scores from six subjects and attendance records of 35 students from the Light Vehicle Engineering (TKR) department over two semesters. The data were obtained from original school records, compiled using Microsoft Excel, and processed in RapidMiner. The clustering process employed four clusters for academic achievement and two clusters for discipline, with Euclidean Distance used as the similarity measure. The results show that in the first semester, students were grouped into four academic achievement clusters: high achievement (6 students), moderate achievement (7 students), potentially problematic (14 students), and problematic (8 students). In the second semester, the distribution changed to high achievement (19 students), moderate achievement (14 students), potentially problematic (4 students), and problematic (1 student). Meanwhile, student discipline was divided into two clusters: disciplined (31 students) and undisciplined (4 students). These results demonstrate that K-Means Clustering is effective in mapping student conditions, revealing patterns in academic performance and attendance, and supporting educational evaluation, learning planning, and early detection of students who require academic or disciplinary intervention. Keywords: Data Mining, K-Means Clustering, Academic Achievement, Discipline, RapidMiner, Vocational High School (SMK)

Gorontalo Province possesses significant mineral resource potential, particularly gold, silver, and copper, positioning the mining sector as a key driver of regional economic growth. However, a shortage of skilled local labor and the scarcity of vocational educational institutions in the mining field severely hamper human resource development in this sector. This study aims to design a Mining Polytechnic Campus in Gorontalo by applying sustainable architecture principles, encompassing energy efficiency, environmentally friendly materials, sound wastewater management, and user comfort. The research approach involves literature studies, field observations, interviews with relevant stakeholders, and quantitative data analysis regarding resource potential, the number of senior high school students, and educational space requirements. The design results emphasize site arrangement, building mass configuration, utility systems, and interior and exterior spaces that support academic, social, and community activities. The application of sustainable architecture principles is expected to create a campus that not only meets the needs of mining vocational education but also contributes to environmental conservation and sustainable regional development.

Coal hauling activities are an important part of mining operation because they affect production continuity, cycle time efficiency, and operational safety. This study aims to analyze the requirements of road support equipment on the coal hauling road from Sector 4 to the new Coal Processing Plant (CPP) at PT. Asmin Bara Bronang, Central Kalimantan. Based on road geometry, traffic density, California Bearing Ratio (CBR), and Unsurfaced Road Condition Index (URCI). The research method used was applied research with a quantitative approach. Primary data ware collected through field measurements consisting of road geometri observations, traffic density observations, Dynamic Cone Penetrometer (DCP) testing to obtain CBR values, and road surface condition assessment using the URCI method. Secondary data were obtained from the company records. The results showed that the hauling road has a total length of 9.1 km with an average width of 16 m, and grade values ranging from -7.68% to 10.52%, which are still below the maximum standard of 12%. Traffic density reached 184 dump trucks/day, for coal hauling and 62 units/day for construction material transportation, indicating high traffic intensity. CBR values ranged from 7% to 100%, showing variations in subgrade bearing capacity. The URCI value ranged from 72,50 to 91.00, indicating fair to good road conditions. Based on the analysis of road conditions and maintenance area requirements, the recommended support equipment for maintaining the hauling road consists of 1 motor grader unit, 1 compactor unit, 1 bulldozer unit, and 1 water truck unit.

-

This article analyzes the recurring flash floods in North Konawe Regency which occurred in 2000, 2013, 2016, 2018, 2019, 2020, and 2021 as ecological disasters causally linked to three decades of natural resource exploitation through logging, oil palm plantations, and open-pit nickel mining. Using the dual framework of political ecology and environmental justice, this article argues that these disasters are not neutral natural events, but rather the product of a structured system of injustice: the indigenous Culambacu People and Tolaki People communities who were excluded from decision-making processes regarding extractive permits have borne the greatest burden of the destructive impacts of such exploitation. The most dramatic event was the 2019 flood that devastated Tapuwatu Village, causing losses amounting to Rp 674.8 billion and displacing 9,908 people. The findings demonstrate that the dominant government narrative framing the floods as “natural disasters caused by high rainfall” constitutes a strategic denial that obscures structural responsibility. Empirical data including rates of deforestation, exceeded river carrying capacity, and the chronology of concession expansion correlated with disaster escalation support the ecological disaster thesis. Persistent poverty amid abundant natural resource wealth confirms the condition of a “sacrifice zone,” characterized simultaneously by distributive, recognitional, and procedural injustices.