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Putra Muba Coal is one of the subsidiaries under the MNC Group, operating in the coal mining sector with an IUP (Mining Business Permit) area covering 2,947 hectares. During its mining operations at the Pandu Pit, PT. Putra Muba Coal experienced a landslide incident on the highwall side. Therefore, a back-analysis using the deterministic method was conducted to determine the material property values that led to the slope failure in the mining area. The slope material consists of claystone and siltstone layers, each with a cohesion value of 192.3 kN/m² and 157.0 kN/m², and internal friction angles of 25.3° and 24.4°, respectively. Based on the back-analysis results, it was found that there was a decrease in material property values, with cohesion reduced by 91% and the internal friction angle reduced by 29%. This reduction in material properties suggests that the decrease in cohesion was the primary factor causing the highwall slope failure, as indicated by the back-analysis of slope stability which resulted in a safety factor of (SF = 1.008).

The importance of data mining in Indonesia is increasing along with the growth of big data in various strategic sectors. Data mining plays an important role in transforming complex data into useful information to support data-driven decision making, which is urgently needed in the face of competitive challenges and operational complexity. This research aims to examine the development of data mining techniques and applications in Indonesia over the last decade (2015-2024). Through a systematic literature review approach, data was collected from academic publications in SCOPUS indexed databases. From the initial 95 papers found, a further selection was made based on accessibility, title, and abstract until 64 papers were included in the article review. The results show that techniques such as K-Means, Naive Bayes, and Decision Tree are most commonly used. In the business sector, clustering through K-Means is widely applied for market segmentation and consumer pattern analysis. The healthcare sector mainly utilizes classification techniques, such as Naive Bayes and Decision Tree, for disease risk prediction and early diagnosis. Meanwhile, the education sector uses data mining to assess student performance and predict potential dropouts, assisting institutions in optimizing learning strategies.

This study aims to identify the leading economic sectors in East Kalimantan Province and analyze their influence on the development of the National Capital of the Archipelago (IKN) as an economic superhub. Using secondary data from 2019–2023, the analysis applies Location Quotient (LQ), Dynamic LQ (DLQ), Shift-Share, and SWOT methods to evaluate the regional economy. Results show that the mining and quarrying sector remains dominant, while agriculture and processing industries demonstrate stable potential for sustainable growth. The study also highlights the urgency of economic diversification, human capital development, and renewable energy as strategic steps to reduce dependence on extractive sectors. The formation of a collaborative blueprint between regional governments, businesses, and communities with the IKN Authority is proposed to strengthen connectivity and economic integration. This research provides critical insights for policy formulation to support East Kalimantan’s transformation as a central player in national development.

This research examines criminal law enforcement strategies against perpetrators of illegal black stone mining in Suwawa, Gorontalo, with a normative-empirical approach. illegal mining activities in this region not only violate the law, but also damage the environment and create social conflicts. Although there is a strict legal basis, its implementation is still weak due to weak coordination between institutions, the involvement of unscrupulous officials, and the lack of economic alternatives for the community. This research identifies that repressive approaches alone are ineffective, so an integrative strategy is needed that includes restorative justice, strengthening customary law, digitizing surveillance, and empowering the local economy. Structural barriers such as power relations, weak surveillance and social resistance are the main hindering factors. This research recommends institutional reform and community engagement as keys to the success of fair and sustainable law enforcement in addressing environmental crimes such as illegal mining.

Mining activities in the Raja Ampat area have sparked various public reactions, both supportive and critical, particularly on social media platforms such as Twitter. This study aims to analyze public sentiment regarding the mining operations by employing two classification algorithms. A total of 500 tweets related to Raja Ampat were collected from the X platform, and after data cleaning, 168 were identified as positive sentiments and 303 as negative. Sentiment analysis was conducted using text mining techniques by comparing two algorithms: Support Vector Machine (SVM) and Naïve Bayes. To address the issue of data imbalance, the Synthetic Minority Over-sampling Technique (SMOTE) was applied. The analysis results showed that SVM achieved an accuracy of 80%, outperforming Naïve Bayes, which reached only 68%. This indicates that SVM performed better in classifying sentiment. Additionally, the application of SMOTE effectively enhanced both algorithms’ abilities to detect positive sentiment, as reflected in the precision, recall, and F1-score metrics. For SVM, precision reached 85%, recall 80%, and F1-score 80%, while Naïve Bayes recorded a precision and recall of 69%, and an F1-score of 68%.

Reciprocal tariff changes imposed by the United States on its trading partner countries including Indonesia, create changes in export and import tariffs in Indonesia which result in a significant impact on the Indonesian economy, which has an impact on export and import sectors such as oil and gas, then non-oil and gas which includes processing industries, agriculture, forestry, fisheries, mining as well as consumer goods, raw / auxiliary materials, and capital goods. This research aims to analyze the impact of exports and imports in the country of Indonesia due to the reciprocal tax rate policy implemented by the United States. This research uses a qualitative approach with the type of content analysis, which involves collecting data from news articles, research reports, and relevant academic publications. The results showed that the imposition of reciprocal tariffs imposed by the United States against Indonesia caused an increase in imports from 2017 to 2020 by 1.38% in the consumer goods sector. On the other hand, the export side decreased in the oil and gas sector from 2017 to 2020 by 2.37% which resulted in disruption of economic stability in the global supply chain that created inflation, and increased imports in Indonesia resulted in competing local product prices with imported products so that many Indonesian manufacturing companies reduced production and terminated employment. From this research, it is expected that Indonesia will be able to maximize the opportunities that exist from the changes and challenges of global trade.

Coal mining in indonesia mostlyuses open pit mining methods. Including coal mines owned by PT Bima Nusa Internasional. Administratively, the research area is located in the muara komam area, batu sopang sub-district, paser district, east kalimantan. Open pit mining is a direct method that is exposed to free air above the surface. This study aims to determine the effect of rainfall on the production of coal hauling equipment at PT Bima Nusa Internasional. High rainfall can affect the performance of coal hauling equipment, which in turn has the potential to disrupt operational smoothness and reduce productivity. This study uses a quantitativeapporach by analyzing daily  rainfall data for two months and coal hauling equipmentproduction data for a two months period. The results of the study show that there is a significant negative relationship between rainfall and the amount of coal transport equipment production.

Mining roads play an important role in supporting the smooth running of mining activities, especially in the process of transporting materials. The bearing capacity of the soil as a road subgrade greatly affects the stability and resistance of the road to heavy equipment loads. This study aims to analyze the effect of the plasticity index and compaction parameters on the California Bearing Ratio (CBR) value, as well as to determine the thickness of the road layer based on the laboratory CBR value. Testing was carried out at the South Pit of PT. Bina Sarana Sukses site PT. Baramulti Suksessarana with a field test method using the Dynamic Cone Penetrometer (DCP) and laboratory tests such as proctor tests, Atterberg limit tests, and CBR tests on various variations of clay and sand soil mixtures. The results showed that increasing the plasticity index decreased the CBR value, while increasing the maximum dry density and decreasing the optimum water content increased the CBR value. Based on the laboratory CBR value, recommendations were obtained for the appropriate road layer thickness to ensure optimal bearing capacity for heavy equipment passing through the research area.

Stockpiles are accumulations of materials such as coal or ore stored at specific locations. Accurate stockpile volume measurement is crucial in the mining and logistics industries for inventory management and cost efficiency. Conventional methods like Real-Time Kinematic (RTK) GPS rely on surface coordinate measurements but require numerous points, especially for irregular-shaped objects. Newer technologies like Terrestrial Laser Scanners (TLS) offer high-precision alternatives by capturing thousands of points per second, expediting and enhancing the resolution of volume measurements. This study compares TLS and RTK GPS methods in measuring the volume of andesite rock stockpiles at PT Bara Tabang. This research uses a quantitative approach, involving six Ground Control Points (GCPs) measured using the Sokkia GRX2 RTK GPS on October 24, 2024. TLS generated over 8.6 million point cloud data filtered down to 35,197 points, while RTK GPS yielded 2,276 coordinates. Accuracy testing showed very small RMSE values (RMSEr: 0.008 m; RMSEz: 0.007 m), and both LE90 and CE90 demonstrated 90% confidence within a 0.012 m range. Volume calculation using Surpac software with the cut and fill method showed TLS produced a volume of 18,766 bcm (51,982 tons/m³), while RTK GPS resulted in 18,694 bcm (51,782 tons/m³), with a difference of 72 bcm or 0.211%.These results indicate that both methods offer acceptable accuracy; however, TLS provides greater data density, efficiency, and precision, particularly for complex or large-scale stockpile objects. Therefore, TLS is recommended for high-accuracy volume measurement in mining operations that require efficiency and detailed analysis.

The policy of granting Mining Business Licenses (IUP) to universities under Article 51A of the Minerba Bill raises legal, ethical, and sustainability concerns. This study applies a qualitative approach through literature review to examine the provision from the perspectives of Indonesian law and Islamic teachings. The findings reveal that allowing universities to manage mining permits risks diminishing their academic role, compromising scholarly independence, and fostering potential conflicts of interest. From the standpoint of positive law, this policy contradicts the precautionary principle, social justice, and educational objectives enshrined in the 1945 Constitution, the Higher Education Law, and the Environmental Protection Law. In Islamic thought, irresponsible exploitation of natural resources is classified as fasād (corruption), strictly prohibited, as reflected in Hadith No. 479 narrated by Bukhari. The study concludes by rejecting the provision and recommends repositioning universities as guardians of sustainability values rather than participants in extractive industries.

P is a company engaged in logistics which is located at km 13 in the city of Balikpapan. PT. P focuses on the automotive, mining, oil and gas, materials and knowledge industries, fast-moving consumer goods (FMCG), electronics and technology, food and beverages, and e- commerce. In the PT. P department productivity is often not achieved due to the many problems that occur that hinder the company's target standards. The purpose of this research is to find out what factors can affect work productivity at PT. P department. There are several factors that can affect work productivity, including organizational culture, work ability and employee turnover. This study uses primary data and secondary data. The method used is a quantitative method.The results showed that there was a significant positive effect between organizational culture on work productivity, there was a significant positive effect between work ability on work productivity, and there was a significant positive effect between employee turnover on work productivity. The results of the F and regression tests found that there was an influence of 37.1% organizational culture, work ability and employee turnover together on work productivity and the remaining 62.9% was influenced by other variables.

The mining and excavation sector in the components of the gross regional domestic product (PDRB) in Bojonegoro Regency is still the backbone of regional income and also development in Bojonegoro Regency, starting from infrastructure development and human development index (HDI). In research with the mining and excavation sector variable which is the base sector using the location quotient (LQ) calculation. This leading sector in Bojonegoro Regency has many impacts on its region starting from regional original income (PAD) and also other income components as well as impacts on society and also progress in development in Bojonegoro Regency.

The pH value parameter in the mineral acid water of a coal mining company in South Sumatra is below the set environmental quality standards. The results of measuring the pH value using a pH meter at the inlet are 4.9 which is still below the environmental quality standard of 6-9. Therefore, it is necessary to make efforts to manage the environment before water is discharged into water bodies, one of which is by utilizing kiambang plants as phytoremediation agents in neutralizing mine acid water. This study aims to analyze changes in mine acid water quality and analyze the effectiveness of mine acid water neutralization. The initial quality of mine acid water for pH parameters was 4.9 TDS of 376 mg/l, Fe of <0.1 mg/l, and Mn of 3 mg/l. After the phytoremediation process, the water quality change for pH parameters was 6.6 and Mn was 0.05 mg/l. The neutrality effectiveness of mine acid water increased the pH by 34.69% and the effectiveness of reducing Mn levels by 98.33%. This kiambang plant can be a recommendation for phytoremediation agents for companies considering its availability around the company

The implementation of coal mining activities with an open pit system at the end of its activities will leave behind the remains of former mining holes. Control of acid mine water is something that needs to be done during mining activities until the end of the mining process because acid mine water can cause a decrease in the quality of surface water and groundwater and have an impact on the survival of humans and biota that live on land and water. The initial characteristics of water using the floating treatment method of wetland, the pH, TSS, Fe, and Mn values ​​of ex-mining lake water do not meet the quality standards of the Government Regulation of the Republic of Indonesia Number 22 of 2021. The ability of water hyacinth plants to increase pH for 25 days is quite good with an initial pH value of 4.13 to 7.34. For 25 days, the TSS parameter of water hyacinth plants is also good at reducing TSS levels with an initial value of 6 mg/L to 3 mg/L, the Fe parameter of water hyacinth plants is also good at reducing iron levels with an initial value of 1.06 mg/L to 0.34 mg/L, while the Mn parameter of water hyacinth plants is quite good at reducing manganese levels with an initial value of 1.13 mg/L to 0.32 mg/L.

This research discusses the implementation of PSAK 221, which regulates the impact of foreign exchange rate changes on the financial statements of PT Adaro Andalan Indonesia Tbk, particularly related to foreign currency transactions. PSAK 221 establishes the methods for recording and reporting foreign currency transactions and recognizing exchange rate differences arising from exchange rate fluctuations. In the context of PT Adaro, which operates in the mining sector and frequently conducts international transactions, implementing this standard is crucial to maintaining the accuracy and transparency of financial reports that stakeholders require. This research aims to guide PT Adaro in managing foreign currency transactions and recording the impact of exchange rate fluctuations by PSAK 221 provisions to ensure accurate, transparent, and compliant financial statements with applicable accounting standards. This research uses a qualitative descriptive method, with a document study approach, to analyze the annual financial statements of PT Adaro Andalan Indonesia Tbk. The data used consists of secondary data obtained from the company’s financial statements and foreign currency transaction records, covering 2024, to identify the application of PSAK 221 in foreign currency transactions and its impact on the financial statements.

In a context where students face increasingly complex academic choices, this work proposes a recommendation system based on Bayesian networks to guide new baccalaureate holders in their university choices. Using a dataset containing variables such as secondary school section, gender, type of school, percentage obtained, age, and first-year honors, we have constructed a probabilistic model capturing the dependencies between these characteristics and the option chosen. The data is collected at the Catholic University of Bukavu, the Official University of Bukavu, and the Higher Institute of Education of Bukavu, preprocessed and then used to learn the structure via the hill-climbing algorithm with the BIC score using R's bnlearn tool. The model enables us to estimate the probability that a candidate will choose a given stream, depending on their profile. The approach has been validated using metrics such as BIC, cross-validation, and bootstrap and offers a good compromise between interpretability and predictive performance. The results highlight the potential of Bayesian networks in constructing explainable recommendation systems in the field of academic guidance. The system produces orientation probability maps for each candidate, which can be used by enrollment service advisers, as well as an ordered list of options relevant to the candidate's profile. With a remarkable performance on a test sample of precision@k=0.85, recall@k=0.61, ndcg=0.8, and Map=0.88, it constitutes an effective lever for reducing the risk of being misdirected in universities in South-Kivu, in the Democratic Republic of Congo

The performance of data mining techniques has been proven accurate in many studies, but each method in data mining techniques has different accuracy depending on the type of data that is the object of research. Methods in data mining techniques are divided into several functions, namely: clustering, association, classification, and prediction, where each data mining technique objective has a superior method. Therefore, in this case the author will compare the performance of the multiple linear regression method, and neural networks with fuzzy mamdani in predicting the income of PLN Unit Takengon. In several studies, the Backpropagation method shows the highest accuracy compared to other methods. Then the prediction model with multiple linear regression also has the highest accuracy as well as the Fuzzy Mamdani method has high accuracy too. Therefore, the purpose of this study is to compare the three methods, so that it can be determined which method has a higher accuracy value. The results of this study indicate that the Back propagation method has the highest accuracy and the lowest average error, namely a MAPE value of 5.9% with an accuracy of 94.1% and an RMSE of 14398.14, followed by the multiple linear regression method obtaining a MAPE value of 6.9% with an accuracy of 93.1% and an RMSE of 15527.41, then for Fuzzy Mamdani obtaining a MAPE value of 7% with an accuracy of 93% and an RMSE of 16077.76.

Coastal areas are transitional areas between land and marine ecosystems that are very vulnerable to natural disasters, one of which is abrasion. Coastal abrasion is the process of erosion of coastal areas caused by wave activity, ocean currents, and human activities such as infrastructure development and sand mining. Ciberi Beach (Tanjung Ciberi) located in Enggros Village, Abepura District, Jayapura City, is one of the coastal areas that experiences continuous abrasion. Its strategic location and direct facing the Pacific Ocean makes this area very vulnerable to coastal erosion. Based on the author's experience while conducting Field Work Practices at the Papua River Basin Center (BWS Papua), it is known that abrasion has caused damage to public facilities and significant coastline decline since 2019 (Cepos, 2024). Strong suspicions arose from the community based on the results of interviews conducted that the construction of the Youtefa Bridge contributed to the acceleration of abrasion. Previous research also showed that the rate of abrasion in the Yos Sudarso Bay area, including Ciberi Beach, reached 0.89 meters per year. Therefore, this study aims to analyze the level of damage to Ciberi Beach due to abrasion during the period 2014–2024, and to provide recommendations for handling to reduce the impact of damage in the coastal area.

In mining activities, there is often a discrepancy between the plan and the actual conditions in the field, this discrepancy was found after reconciliation at the end of the progress (month). From the mining activities carried out by PT. Jembayan Muarabara (JMB), coal roof floor data was obtained from the survey which was then used to find survey tonnage, model tonnage data and actual tonnage scales. Then from this data it can be used to obtain coal recovery, coal looses in coal cleaning, loading, and coal transportation. The results of the study obtained tonnage data from the survey of 26,201.50 tons, a model of 26,488.50 tons and an actual tonnage of 24,885.09 tons. From the data obtained, the coal recovery value at the research location was 94.98% with coal losses in coal cleaning activities of 4.52% or 1196.39 tons and in loading activities of 0.5% or 120.02 tons with a tonnage discrepancy between planning and actual in the field of 1603.41 tons.

This article examines the shift in local government authority over mineral and coal mining management following the enactment of Law Number 23 of 2014 on Regional Government. The transfer of authority from regency/city governments to provincial and central governments has created normative disharmony between the Regional Government Law and the Mining Law, resulting in legal uncertainty at the implementation level. Using a normative juridical approach and Hans Kelsen’s theory of the hierarchy of norms, this article analyzes the legal validity of the transfer and identifies structural conflicts within the legal system. The findings indicate that the current regulation lacks both hierarchical consistency and functional clarity. Therefore, a reconstruction of the legal framework for mining governance is required to balance the principle of legality with the concept of regional autonomy. A model of limited delegation, sectoral regulatory harmonization, and the application of multilevel governance are proposed as key recommendations to ensure a fair, effective, and constitutional relationship between central and local governments.