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This study aims to know the form and form of moral values contained in the novel of the love of ayu utami in her daily life. the method used is qualitative. The object of research in the novel love story of entrico, this study will focus on analyzing moral values in the novel. Data collection techniques are reading and notes. The reading technique is carried out by reading the story novel of enriek repeatedly and as a whole to clearly understand the contents of the story novel Enico by Utami's love story. Then the next step is to look for moral values in the novel langakah the next is to record the moral values contained in the novel Enico love story. This recording technique is to determine and analyze moral values in the novel of Enico's love story. The results of the study showed that the novel of the love story of Enico by ayu Utami includes, moral, religious, and education values. The moral value that we learn in Enrico love story is, as humans should have a clear life goal so that in the future we get life and kebahagin. The religious value is seen from his parents who are one religious Muslim and others are Christians, then Enrico himself does not choose a religion and belief. The value of education, namely Enrico, continues his education at a university in one of the universities in Bandung which is known as ITB, majoring in mining.

This study aims to know the form and form of moral values contained in the novel of the love of ayu utami in her daily life. the method used is qualitative. The object of research in the novel love story of entrico, this study will focus on analyzing moral values in the novel. Data collection techniques are reading and notes. The reading technique is carried out by reading the story novel of enriek repeatedly and as a whole to clearly understand the contents of the story novel Enico by Utami's love story. Then the next step is to look for moral values in the novel langakah the next is to record the moral values contained in the novel Enico love story. This recording technique is to determine and analyze moral values in the novel of Enico's love story. The results of the study showed that the novel of the love story of Enico by ayu Utami includes, moral, religious, and education values. The moral value that we learn in Enrico love story is, as humans should have a clear life goal so that in the future we get life and kebahagin. The religious value is seen from his parents who are one religious Muslim and others are Christians, then Enrico himself does not choose a religion and belief. The value of education, namely Enrico, continues his education at a university in one of the universities in Bandung which is known as ITB, majoring in mining.

This study aims to analyze the effect of audit materiality, compliance with audit standards (SA), and material misstatements on sustainability performance and audit opinion, with the principle of fairness as a moderating variable in mining companies listed on the Indonesia Stock Exchange ( IDX) for the 2019-2023 period. This research was conducted with a quantitative approach, using secondary data in the form of financial reports, sustainability reports, and independent audit reports. The results showed that compliance with audit standards has a significant effect on sustainability performance and audit opinion, while audit materiality and material misstatement do not have a significant effect directly on these two variables. In addition, the principle of fairness as a moderating variable does not strengthen the relationship between sustainability performance and audit opinion. These findings suggest that mining companies need to improve transparency and compliance with audit standards to support sustainability and obtain better audit opinions. This research provides a theoretical contribution to the study of sustainability accounting as well as practical guidance for auditors and company management in improving the quality of financial reporting and sustainability.

The financial performance of mining companies listed on the Indonesia Stock Exchange (IDX) during the 2020-20203 period was greatly influenced by fluctuations in global commodity prices and macroeconomic conditions that had an impact on the company's competitiveness and profitability. Therefore, it is important to assess how companies in this sector are managing their financial performance amid various challenges and opportunities. This study analyzes financial performance using several main financial ratios, including liquidity ratios (Current Ratio and Quick Ratio), solvency ratios (Debt to Equity Ratio and Debt to Asset Ratio), profitability ratios (Return on Assets, Return on Equity, and Net Profit Margin), and activity ratios (Total Asset Turnover and Inventory Turnover). The method used to conduct the analysis is the quantitative descriptive analysis method, using data that has been taken based on the annual financial statements of companies listed on the IDX during the period. Sample selection using the purposive sampling method, resulted in 3 companies being analyzed. The results of the analysis of 81 data observed using the Multiple Linear Regression method showed that environmental performance and environmentally friendly products had a positive impact on the company's financial performance, while environmental poroscope and environmental activities did not show a significant influence on the company's financial performance.

Indonesia, dengan tanahnya yang subur, memiliki potensi besar dalam pertanian, terutama berkat letak geografisnya di wilayah tropis yang ditandai dengan curah hujan tinggi. Kondisi ini mendukung pertumbuhan berbagai jenis tanaman secara optimal, menjadikan Indonesia dikenal sebagai negara agraris. Sebagian besar penduduknya menggantungkan hidup pada sektor pertanian. Salah satu komoditas penting adalah cabai rawit, yang memiliki rasa pedas khas dan sering digunakan sebagai bahan masakan. Selain memberikan rasa pedas yang kuat, cabai rawit juga mempercantik tampilan hidangan dan mampu meningkatkan nafsu makan. Karakteristik ini menjadikan cabai rawit sebagai elemen penting dalam kuliner Indonesia. Cabai rawit adalah salah satu komoditas utama di Indonesia. Oleh karena itu, penting untuk melakukan kajian mendalam terkait tingkat produksinya, termasuk upaya mengoptimalkan hasil produksi melalui analisis berbagai faktor yang memengaruhinya. Metode data mining memungkinkan penggalian pola-pola tersembunyi yang menarik dalam kumpulan data. Selain itu, metode ini dapat digunakan untuk mengurangi kesalahan pengguna dalam proses pengolahan data. Salah satu pendekatan data mining yang efektif untuk memetakan atau mengelompokkan data serupa adalah klastering. Klastering memiliki kelebihan unik dibandingkan metode lain karena mampu mengklasifikasikan data tanpa memerlukan pengetahuan awal. Teknik ini membagi data menjadi kelompok-kelompok berdasarkan kemiripan karakteristik. Ada berbagai algoritma yang digunakan dalam klastering, dan salah satu yang paling populer adalah algoritma K-Means

Indonesia, dengan tanahnya yang subur, memiliki potensi besar dalam pertanian, terutama berkat letak geografisnya di wilayah tropis yang ditandai dengan curah hujan tinggi. Kondisi ini mendukung pertumbuhan berbagai jenis tanaman secara optimal, menjadikan Indonesia dikenal sebagai negara agraris. Sebagian besar penduduknya menggantungkan hidup pada sektor pertanian. Salah satu komoditas penting adalah cabai rawit, yang memiliki rasa pedas khas dan sering digunakan sebagai bahan masakan. Selain memberikan rasa pedas yang kuat, cabai rawit juga mempercantik tampilan hidangan dan mampu meningkatkan nafsu makan. Karakteristik ini menjadikan cabai rawit sebagai elemen penting dalam kuliner Indonesia. Cabai rawit adalah salah satu komoditas utama di Indonesia. Oleh karena itu, penting untuk melakukan kajian mendalam terkait tingkat produksinya, termasuk upaya mengoptimalkan hasil produksi melalui analisis berbagai faktor yang memengaruhinya. Metode data mining memungkinkan penggalian pola-pola tersembunyi yang menarik dalam kumpulan data. Selain itu, metode ini dapat digunakan untuk mengurangi kesalahan pengguna dalam proses pengolahan data. Salah satu pendekatan data mining yang efektif untuk memetakan atau mengelompokkan data serupa adalah klastering. Klastering memiliki kelebihan unik dibandingkan metode lain karena mampu mengklasifikasikan data tanpa memerlukan pengetahuan awal. Teknik ini membagi data menjadi kelompok-kelompok berdasarkan kemiripan karakteristik. Ada berbagai algoritma yang digunakan dalam klastering, dan salah satu yang paling populer adalah algoritma K-Means

Riau Province is one of the largest contributors to GRDP in Indonesia with several leading sectors. This study aims to determine the leading sectors or base and non-base sectors in Riau Province. The data used in this study are secondary data obtained from the Riau Province Central Bureau of Statistics (BPS). The data was processed and analysed using the Location Quotient (LQ) analysis method. The results of Location Quotient (LQ) analysis show that there are 3 basic sectors or leading sectors in Riau Province for the 2018-2022 period. It is known that there are 3 basic sectors or leading sectors in Riau Province, the 3 sectors are the Agriculture, Forestry and Fisheries sector, the Mining and Quarrying sector, and the Manufacturing Industry sector with LQ analysis values of 2.15, 2.23, and 1.52, respectively. While the other 14 sectors are non-base sectors. For this reason, the government must better understand what sectors need to be improved and the need for cooperation from many parties so that these leading sectors can be maintained and further developed in the following year.

Sand mining in coastal regions, particularly on Kodingareng Lompo Island, has emerged as an environmental concern that profoundly affects ecosystem sustainability and the livelihoods of local populations. This study aims to analyze the impact of sand mining activities on coastal ecological conditions and their relationship to Sustainable Development Goal (SDG) 12 on sustainable consumption and production. A qualitative approach will be adopted, using interviews with local stakeholders such as fishermen, women entrepreneurs, the Neighborhood Association, and the Neighborhood Unit. Sand mining causes coastal erosion, habitat destruction, and water quality degradation. As a result, fishermen's catches and the economic incomes of local communities decline dramatically. This practice accelerates environmental damage contrary to the SDGs and exacerbates damage contrary to the principles of SDG 12. Recommendations for stricter regulations and implementing environmentally friendly mining methods can reduce adverse environmental impacts and support the sustainability of coastal ecosystems and the well-being of local communities. Such policies are essential to balance natural resource utilization and conservation efforts, aligning with SDG target 12. The novelty of this study lies in the need for more literature discussing this issue in Kodingareng Lompo Island.  

Students reading interest is a crucial factor in enhancing the quality of education. However, the lack of structured data makes it challenging to identify specific patterns of reading interest. This study aims to implement a data mining method using the Naive Bayes algorithm to analyze students' reading interest at SMP Negeri 2 Palembang's library. The data used includes book borrowing history, types of books, and library visit frequency over one semester. The analysis results indicate that the Naive Bayes method achieves an accuracy rate of 80% in classifying reading interest based on predetermined categories. These findings are expected to assist the school in designing more effective literacy programs.  

Data mining atau penambangan data merupakan proses pengumpulan dan pengolahan data untuk mengekstrak informasi penting. Metode data mining K-Nearest Neighbor dapat menganalisis pada aplikasi Redbus. RedBus merupakan salah satu aplikasi resmi pembelian tiket bus kota di Indonesia. Permasalahan yang muncul setelah pembaruan aplikasi RedBus adalah bertambahnya ulasan bintang satu yang menyatakan bahwa versi terbaru tidak sesuai dengan versi sebelumnya. Data Mining yang dugunakan untuk menganalisis sentimen Access by Bus Kota di seluruh Indonesia menggunakan metode K-Nearest Neighbors. Data yang digunakan adalah data yang diperoleh dari ulasan pengguna aplikasi redBus selama satu bulan terhitung dari tanggal 20 September 2024 sampai dengan 20 Oktober 2024 dengan total 1291 ulasan. Analisis sentimen pada penelitian ini menggunakan metode K-Nearest Neighbors melalui bahasa pemrograman Python. Hasil penelitian menunjukkan bahwa kinerja terbaik pada percobaan dengan pembagian data latih dan data uji, serta nilai k yang bervariasi diperoleh pada percobaan dengan pembagian 90% data latih, 10% data uji dan menggunakan nilai k = 5 dengan nilai akurasi, presisi, dan recall masing-masing sebesar 90,23%; dan nilai recall sebesar 72,38%. Klasifikasi sentimen dengan model terbaik menggunakan parameter k = 3 menghasilkan 79,26% sentimen positif, 17,25% sentimen netral, dan 3,49% sentimen negatif. 

Data mining atau penambangan data merupakan proses pengumpulan dan pengolahan data untuk mengekstrak informasi penting. Metode data mining K-Nearest Neighbor dapat menganalisis pada aplikasi Redbus. RedBus merupakan salah satu aplikasi resmi pembelian tiket bus kota di Indonesia. Permasalahan yang muncul setelah pembaruan aplikasi RedBus adalah bertambahnya ulasan bintang satu yang menyatakan bahwa versi terbaru tidak sesuai dengan versi sebelumnya. Data Mining yang dugunakan untuk menganalisis sentimen Access by Bus Kota di seluruh Indonesia menggunakan metode K-Nearest Neighbors. Data yang digunakan adalah data yang diperoleh dari ulasan pengguna aplikasi redBus selama satu bulan terhitung dari tanggal 20 September 2024 sampai dengan 20 Oktober 2024 dengan total 1291 ulasan. Analisis sentimen pada penelitian ini menggunakan metode K-Nearest Neighbors melalui bahasa pemrograman Python. Hasil penelitian menunjukkan bahwa kinerja terbaik pada percobaan dengan pembagian data latih dan data uji, serta nilai k yang bervariasi diperoleh pada percobaan dengan pembagian 90% data latih, 10% data uji dan menggunakan nilai k = 5 dengan nilai akurasi, presisi, dan recall masing-masing sebesar 90,23%; dan nilai recall sebesar 72,38%. Klasifikasi sentimen dengan model terbaik menggunakan parameter k = 3 menghasilkan 79,26% sentimen positif, 17,25% sentimen netral, dan 3,49% sentimen negatif. 

This research aims to empirically test the effect of sustainability report disclosure on company value with profitability as a moderating variable (Empirical Study of Mining Companies Listed on the Indonesia Stock Exchange 2019-2023). The population of this research is all mining companies listed on the Indonesia Stock Exchange for 2019-2023, totaling 63 companies. The sample used in this research was 12 companies. This research uses a purposive sampling technique, namely a sampling technique that provides the opportunity to become a sample member with certain criteria. Then the data collection method is through questionnaires and data analysis using SPSS 25 which includes validity, reliability, classical assumption tests, multiple regression analysis, hypothesis testing using the t test and R2 test. The results of this research show that the Sustainability report variable has a positive effect on the value of mining companies listed on the Indonesia Stock Exchange in 2019-2023, so (H1) is accepted. The Profitability variable has no effect on the Company Value of mining companies listed on the Indonesia Stock Exchange in 2019-2023, so (H2) is rejected. The profitability variable is not able to moderate the relationship between sustainability reports and company value.

Based on Ministry of Energy and Mineral Resources data, regarding the target achievement of mechanical equipment performance in mining companies, PT Bumi Nikel Nusantara has a level of achievement value of equipment performance less than the value set in the Minister of Energy and Mineral Resources Decree No.1827/2018. A mechanical equipment performance value can be achieved by examining ongoing mining activities on one mining front that includes loading and transportation activities. One of the efforts is to know the productive time, calculate the obstacle time and repair time of the equipment in case of damage. The results of the performance for the Use of Availability (UA) parameter of the EHJ Block Mawar pit loading equipment is 74% (not achieved), 71% Pit Mawar transport equipment, pit 3 loading excavation equipment 75% (achieved), and Pit 3 transport equipment 71% (not achieved). While the results of the study of the achievement of productivity of the loading and unloading equipment show the achievement with a value for loading equipment of 76,71% (not achieved) and transport equipment of 65,63% (not achieved). 

PAB Rehandling office workers in the mining sector, these stressors have a greater impact due to the dynamic and often dangerous nature of the work. Office workers responsible for transporting materials and processing associated paperwork are often under pressure to meet strict production targets. This pressure can be exacerbated by a work environment fraught with safety risks, leading to increased levels of anxiety and stress. To determine the correlations of individual stressors (age, gender, and tenure) with occupational stress. Using quantitative methods using a cross sectional design. The sampling technique used was total sampling so that the sample in this study was office workers in the PAB Rehandling section in the Mining Sector, totaling 56 respondents. Data analysis using Spearman test for ordinal data types (age and tenure) and Chi Square test for nominal data types (gender). The study showed that there was a correlation between age with a p-value of 0.032, there was no correlation between gender with a p-value of 0.873, there was a correlation between tenure with a p-value of 0.000. To minimize the high level of stress in PAB Rehandling office workers, it is possible to implement a program to implement stress management in the workplace.

This study aims to select four Mining Companies that have the best implementation of Occupational Safety and Health and to identify the implementation of Occupational Safety and Health that has been carried out by the Company so that it can be assessed as a whole. Therefore, data collection in this study was carried out by conducting observations, interview sessions with employees and observations of locations that have been selected as research objects as primary data and making location maps as secondary data. 4 (Four) Companies selected as research objects are located in SG Village Arso Satu Keerom Regency, Papua Province. The results showed that there were 4 (Four) companies that became the object of research, namely CV. SG, CV. ABC, CV. CTT Keerom and CV. JT XXX of the four Rock Mining companies have not implemented the Occupational Safety and Health Policy in the work environment in the Company. For this reason, it is hoped that the Keerom Regency government can pay attention to this matter.

Sentiment Analysis is a technique for extracting text data to obtain information about positive, neutral or negative sentiments. The purpose of sentiment analysis is given by internet users on social media to provide a personal assessment or opinion. Paga Lewu Shop that often gets user sentiment through social media is Paga Lewu Shop. The existence of consumer opinion sentiments about Paga Lewu Shop can be analyzed and utilized to obtain useful information for other customers and the Paga Lewu Shop. By using the Text Mining technique classification method, a sentiment will be known as positive, neutral or negative. One of the algorithms widely used in sentiment analysis is the Naïve Bayes classification method. This study uses the Naïve Bayes Classifier (NBC) method with tf-idf weighting accompanied by the addition of an emotion icon conversion feature (emoticon) to determine the existing sentiment class from tweets about the Paga Lewu Shop. The results of the study show that the Naïve Bayes method without additional features is able to classify sentiment with an accuracy value of 96.44%, while if the tf-idf weighting feature is added along with the conversion of emotion icons, the accuracy value can be increased to 98%.

This study aims to analyze the social aspects in the novel Laskar Pelangi by Andrea Hirata. This novel depicts the social reality of the Belitong Malay community which faces various challenges, especially in the fields of education, economy, and culture. Through a literary sociology approach, this analysis reveals how social, economic, and cultural backgrounds shape the characters and conflicts in the story. The results of the study show that the novel Laskar Pelangi represents the struggle of the lower class in accessing education, the social inequality that occurs due to the exploitation of natural resources by mining companies, as well as the spirit of friendship and solidarity that is a strength in facing difficulties. This novel not only inspires readers with its moral messages but also reflects the complex and dynamic social conditions of Indonesian society.

Still today, Indonesia's agricultural industry provides the bulk of the country's GDP. Agricultural output and job prospects are deteriorating as a result of the COVID-19 pandemic, which is particularly severe from 2020 to 2022. These underlying causes highlight the need of having a framework to estimate and anticipate output for the next year. The objective is to examine how the transition of farm and non-agricultural labour has affected family welfare in the districts of West Aceh and South Aceh. Shift Share and Location Quotient (LQ) are the tools used in this study. Using the contribution criterion in particular, LQ analysis is a powerful analytical technique for revealing an area's economic foundation. One way to look at regional economic development is via shift share analysis, which tracks how a key indicator of regional economic growth changes or increases over a certain time period. Agriculture, forestry, and fisheries make up the basic sector in South Aceh Regency's LQ calculation. The manufacturing industry, construction, financial and insurance services, and government administration, defence, and compulsory social security make up the other three subsectors. Agriculture, forestry, and fishing make up the backbone of West Aceh Regency's LQ calculation. The quarrying and mining industry. All sectors in South Aceh Regency had a negative value in the GRDP of South Aceh Regency shift share study, which suggests that overall, the sectors in South Aceh Regency are not expanding faster than their counterparts in Aceh Province and West Aceh Regency. All of the sectors in West Aceh Regency's GDRP are positive, which indicates that overall, the South Regency's sectors are developing at a quicker rate than both Aceh Province and South Aceh Regency's sectors.

The export of marine sand from Indonesia to Singapore has been a controversial issue for decades, involving economic, environmental, and political interests. This study examines Indonesia's marine sand export policy, especially after the issuance of Government Regulation Number 26 of 2023, which reopened export permits after more than 20 years of prohibition. This policy aims to manage marine sedimentation to prevent disruption to ecosystems and shipping and meet domestic reclamation needs. However, there are many pros and cons that arise. On the one hand, this policy is expected to increase state revenue and open up employment opportunities. On the other hand , sea sand mining activities can cause serious environmental damage. This study uses qualitative methods with literature analysis to understand the impact of the policy. The results show that this policy provides more short-term benefits to the government and business actors, but poses long-term threats to the environment and society. Unsupervised marine sand mining has the potential to damage marine ecosystems, reduce fishermen's productivity, and threaten the sustainability of Indonesia's coastal areas. Therefore, more effective supervision and implementation of policies regarding this activity is needed.

Topic modeling is an integral text mining component, employing diverse algorithms to uncover hidden themes within texts. This study examines the comparative performance of prominent topic modeling techniques on news headlines, which is characterized by brevity and specific linguistic style. Given the corpus originates from a non-native English-speaking country, an additional layer of complexity is introduced to the task. Our research explores the feasibility of employing a committee approach for topic modeling, evaluating the efficacy and challenges of various methods in practical settings. We applied three techniques—Latent Dirichlet Allocation (LDA), Non-negative Matrix Factorization (NMF), and BERTopic—to create models with a fixed number of topics (n=40). These models were then tested on approximately 150,000 news headlines. To assess topic coherence, we utilized Word2Vec, human evaluators, and two large language models. Statistical tests confirmed the significance and impact of our findings. BERTopic demonstrated superior coherence compared to NMF, though slightly, but consistently outperformed NMF and LDA according to human and LLM evaluations. The notable disparity in LDA's performance relative to BERTopic and NMF underscores the importance of carefully selecting a topic modeling technique, as the choice can significantly influence the outcome of the analysis.