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Harga emas dunia merupakan faktor eksternal yang berpotensi memengaruhi kinerja keuangan perusahaan pertambangan emas, namun hubungan keduanya tidak selalu bersifat linear mengingat kompleksitas struktur bisnis dan biaya perusahaan. Penelitian ini bertujuan menganalisis secara komparatif tren harga emas dunia dengan profitabilitas PT Aneka Tambang Tbk periode 2021–2025 menggunakan metode deskriptif kuantitatif dengan pendekatan komparatif tren. Data bersumber dari laporan keuangan konsolidasian audited PT Aneka Tambang Tbk tahun 2021–2025 serta data harga emas rata-rata tahunan yang diterbitkan oleh World Gold Council, dengan indikator profitabilitas Return on Assets (ROA) dan Net Profit Margin (NPM). Hasil penelitian menunjukkan bahwa harga emas mengalami kenaikan akseleratif dari USD 1.793,38 menjadi USD 3.518,43 per troy ounce dengan pertumbuhan kumulatif 96,2%, sementara profitabilitas perusahaan bergerak fluktuatif dengan puncak tertinggi pada 2025. Analisis komparatif terhadap empat fase pergerakan menunjukkan hubungan yang tidak konsisten dan non-linear, di mana dua fase bergerak searah, satu fase berlawanan, dan satu fase bersifat parsial, yang disebabkan oleh fluktuasi volume penjualan, ekspansi aset yang belum produktif, dan lonjakan beban pokok pembelian logam mulia dari pihak ketiga. Penelitian ini mengimplikasikan bahwa analisis profitabilitas perusahaan pertambangan perlu mempertimbangkan struktur biaya, strategi pengadaan, dan keputusan investasi secara simultan, tidak cukup bertumpu pada pergerakan harga komoditas semata.

This study aims to determine and analyze the impact of the work environment on employee job satisfaction at the Human Resources Development Agency (BPSDM) of Jambi Province. The research is motivated by the importance of a supportive work environment in creating comfort, increasing motivation, and improving employee job satisfaction, since preliminary observations found several work-environment problems such as inadequate room cooling, disrupted toilet water supply, and unstable Wi-Fi network. This study used a quantitative approach with an associative research design. The population consisted of 75 employees, all of whom were used as the sample through a saturated sampling technique. Data were collected using a four-point Likert-scale questionnaire and analyzed with validity tests, reliability tests, classical assumption tests, and simple linear regression using SPSS. The results show that the work environment has a significant impact on employee job satisfaction, evidenced by a significance value smaller than 0.05, with a coefficient of determination of 61.8 percent. This indicates that the better the work environment, both physical and non-physical, the higher the employee job satisfaction. This research is expected to serve as a consideration for the agency in improving the quality of the work environment to support employee job satisfaction and performance.

This study examines the effects of Net Profit Margin, audit opinion, and firm size on audit delay among construction companies listed on the Indonesia Stock Exchange from 2019 to 2025. Audit delay is measured as the period between the fiscal year-end and the issuance date of the independent auditor’s report. Timely financial reporting is particularly important in the construction sector due to its complex long-term projects, progress-based revenue recognition, cost estimation, and high financial risks. Using a quantitative approach, the study analyzes secondary data from annual financial statements and independent auditor reports. The sample includes 14 construction companies observed over seven years, producing 98 observations. Panel data regression was conducted using EViews, with the Chow, Hausman, and Lagrange Multiplier tests identifying the Random Effect Model as the most appropriate estimation method. The findings show that Net Profit Margin does not significantly affect audit delay. In contrast, audit opinion and firm size have negative and significant effects, indicating that favorable audit opinions and larger company size are associated with shorter audit completion periods. Collectively, the three variables significantly influence audit delay, although they explain only 15.75% of its variation.

The rapid growth of Solar Power Plant (PLTS) installations in Indonesia faces efficiency challenges due to the continuously changing position of the sun. Fixed panel systems cannot absorb solar radiation optimally throughout the day. This study aims to evaluate and compare the efficiency of various solar tracking system methods developed over the last five years using a simple literature review approach. The research method was conducted by collecting, screening, and synthesizing secondary data from five reputable scientific journals using a synthesis matrix. The review results indicate that single-axis tracking systems increase power efficiency by 15% to 24.5%. Meanwhile, dual-axis systems achieve higher efficiency, ranging from 30% to 35%, by tracking both horizontal and vertical solar movements. In terms of control systems, astronomical algorithms are found to be more reliable in cloudy weather conditions than pure light sensors. However, the internal power consumption of the actuator motors remains a critical factor that can reduce the system's net energy gain. The implication of this study emphasizes the importance of shifting future research focus toward energy-saving algorithm optimization to maximize net power yield in dynamic solar panel implementations.

Image Quality Assessment has become an important research area in computer vision due to the increasing use of digital imaging in medical, industrial, and remote sensing applications. This study conducted a Systematic Literature Review (SLR) using articles retrieved exclusively from the Scopus database. A total of fifteen Scopus-indexed articles were selected through the PRISMA process consisting of identification, screening, eligibility, and inclusion stages. The findings indicated that convolutional neural networks, transformer architectures, and no-reference approaches dominated recent studies because of their ability to capture complex visual features and improve evaluation accuracy. The application domain strongly influenced method selection, particularly in medical imaging, industrial quality control, and remote sensing. Deep learning methods achieved high performance but required large datasets and high computational resources. Overall, recent research trends shifted from traditional image enhancement toward artificial intelligence-based quality evaluation.

Kappaphycus striatum seaweed is a strategic commodity producing high-value carrageenan and is widely cultivated in Indonesia. This study aims to assess the growth rate of Kappaphycus striatum which is seeded with Sargassum sp. in floating net cages (KJA) and then cultivated using the longline method in the waters of Batuhopon, Huilelot Village, Semau Island, Kupang Regency. The study was conducted during August–October 2025 using a Completely Randomized Design (CRD) with four treatments, namely P0 (5 kg Kappaphycus striatum + 0 kg Sargassum sp.), P1 (4.5 kg Kappaphycus striatum + 0.5 kg Sargassum sp.), P2 (3.5 kg Kappaphycus striatum + 1.5 kg Sargassum sp.), and P3 (2.5 kg Kappaphycus striatum + 2.5 kg Sargassum sp.). Observed parameters included daily growth rate, specific growth rate, absolute growth rate, ice-ice disease incidence, and water quality. Data were analyzed using Analysis of Variance (ANOVA). The results showed that the average daily growth rate in all treatments increased until the fifth week, but some treatments decreased in the sixth week. Treatment P0 provided the highest and most stable growth. The results of the ANOVA test showed that the treatment had no significant effect on the daily growth rate (P>0.05), but had a significant effect on the specific growth rate and absolute growth (P<0.05). The highest absolute growth was obtained in treatment P0, followed by P1, P3, and P2. The incidence of ice-ice disease increased gradually from 5% in the first week to 35% in the sixth week. Water quality parameters during the study were in the range that still supported seaweed growth, namely temperature 28–30°C, salinity 30–33 ppt, pH 7.5–8.0, depth 20 cm, and current velocity 0.3–0.4 m/s.

The Entangled game is designed as an interactive medium to convey the problem of ghost nets to the 19–25 age group through a visual novel format that relies on narrative and visuals as a means of communication. This medium is presented to highlight the problem of ghost nets which are a serious threat to marine ecosystems because they destroy habitats, endanger marine biota, and impact the social and economic aspects of coastal communities, but are still poorly understood by the younger generation due to the limited availability of engaging and communicative educational media. In designing this game, character design plays a key supporting element that helps convey conservation messages emotionally and narratively through character representation, dialogue, and relationships between characters in the storyline. The method used is a mixed method with data collection through interviews, literature studies, and questionnaires, which are then developed using the Game Development Life Cycle (GDLC) approach to ensure the game design process runs systematically. 

Tomato (Solanum lycopersicum) is a high-value horticultural commodity in Indonesia, yet its cultivation is frequently disrupted by leaf diseases that are difficult to distinguish visually. Diseases such as Bacterial Spot, Early Blight, and Tomato Yellow Leaf Curl Virus often present overlapping visual symptoms, making early and accurate diagnosis a significant challenge for farmers. The manual identification methods currently in use are inefficient and error-prone, ultimately leading to reduced crop yield  and quality. The general objective of this study is to develop software capable of automatically classifying tomato  leaf diseases. Specifically, this research aims to implement the MobileNetV3 Small architecture based on Convolutional Neural  Network (CNN) with ImageNet pre-trained weights to classify 10 types of tomato leaf diseases. The research methodology encompasses dataset collection from Kaggle comprising 10,000 images (1,000 per class), image pre-processing through resizing to 224x224 pixels, and normalization, as well as hyperparameter optimization (optimizer, learning rate, epoch, batch size) via scheduler. Model performance is evaluated using a confusion matrix encompassing accuracy, precision, recall, and F1-score.

The stock market is a place to buy shares for profit. In Indonesia, energy stocks are highly unpredictable because global commodity prices change constantly. This study examines what affected energy stock returns in 2024, focusing on trading volume, price swings, company profits, and cash flow. Using financial reports and statistical analysis, all these factors were tested together and individually. The results show that combined, all these factors do affect stock returns. However, when looked at one by one, only the company's net profit truly matters to investors. On the other hand, busy trading, daily price swings, and cash flow have no impact at all. In fact, all the factors studied only account for 14% of stock return movements, while the remaining 86% is driven by other outside forces. In conclusion, for those looking to invest in energy stocks, the most important thing to watch is the company's ability to generate net profit, rather than just looking at how busy daily transactions are in the market.

This study aims to synthesize empirical and theoretical literature on the Planning–Organizing–Actuating–Controlling (POAC) framework in public sector management, identify asymmetries among its functions, and propose a reconfiguration of POAC that is relevant to digital and collaborative governance. The study employs an integrative literature review by examining classical management literature, peer-reviewed journals, government regulations, and official governance indicators. Data were analyzed thematically based on the four POAC functions and synthesized across themes, using Indonesia during the 2021–2025 period as the empirical context. The findings reveal that planning and organizing functions have developed relatively well, while actuating and especially controlling remain persistent weaknesses. This condition is reflected in improvements in several formal governance indicators, including the Electronic-Based Government System (SPBE) Index, Indonesia’s ranking in the E-Government Development Index (EGDI), Unqualified Audit Opinions (WTP), and public service compliance ratings. However, during the same period, the Corruption Perceptions Index (CPI) declined. These findings indicate a gap between administrative achievements and substantive outcomes, consistent with the concept of means–ends decoupling in neo-institutional theory. The study contributes by bridging classical management theory with contemporary governance paradigms and proposing a Data-driven, Networked, Adaptive, and Participatory (DNAP) model of POAC. Practically, the results highlight the need to strengthen controlling functions and adaptive leadership to foster more effective, transparent, and outcome-oriented public governance.

The fast fashion industry has actually become the second largest contributor to textile waste in the world due to rapid production cycles, high consumer demand, and the use of synthetic materials that are difficult to biodegrade. This phenomenon causes serious environmental impacts such as water pollution, greenhouse gas emissions, accumulation of solid waste, and microplastic pollution that threatens marine ecosystems. In Indonesia, although environmental regulations such as Law Number 32 of 2009 concerning Environmental Protection and Management and Law Number 18 of 2008 concerning Waste Management exist, the implementation of fast fashion waste management still faces various obstacles. This study aims to analyze the implementation of waste management regulations in the fast fashion industry in Indonesia and to examine why the Extended Producer Responsibility (EPR) mechanism is necessary as a legal instrument for textile waste management. The method used is normative juridical with an ecological approach, utilizing primary and secondary legal materials, as well as qualitative-descriptive and comparative analysis with France, the Netherlands, and Sweden. The findings reveal four main legal gaps: the absence of a definition for post-consumer textile waste, the lack of a binding take-back mechanism for producers, weak fiscal instruments supporting EPR, and the absence of ecodesign obligations. The implication of this study highlights the need for regulatory reconstruction that specifically addresses the responsibility of fast fashion producers throughout the product life cycle to achieve more effective and sustainable waste management.               

This study explores the role of artificial intelligence in strengthening cybersecurity threat detection frameworks for next-generation network environments. The rapid expansion of cloud computing, Internet of Things ecosystems, and distributed digital infrastructures has significantly increased cybersecurity risks and operational vulnerabilities. Traditional cybersecurity systems often struggle to detect sophisticated and evolving threats due to their dependence on static detection mechanisms. Using a qualitative research approach and content analysis method, this study examines recent developments in artificial intelligence, machine learning algorithms, and intelligent cybersecurity frameworks. The findings indicate that AI-driven cybersecurity systems improve real-time threat detection, anomaly identification, automated monitoring, and predictive security analysis. Machine learning technologies such as Random Forest, Support Vector Machine, and deep learning models demonstrate strong potential for enhancing intrusion detection accuracy and reducing false positive rates. The study also identifies critical challenges related to ethical governance, privacy protection, computational complexity, and adversarial attacks in AI-based cybersecurity systems

Electricity service quality depends not only on physical network expansion but also on the availability of accurate, traceable, and spatially integrated asset data. This study aims to formulate an infrastructure inventory plan for electricity distribution networks as a basis for optimizing electricity services in Musi Rawas Regency, Indonesia. A descriptive-technical approach was applied using administrative maps, spatial planning documents, distribution network maps, feeder single-line diagrams, January 2026 customer data, bill of quantity documents for electricity and public street lighting, and the planned network drawing for Mandi Aur Village. The results show that 14 target districts served approximately 101,932 customers, consisting of 78,564 postpaid and 23,368 prepaid customers. Tugumulyo, Megang Sakti, Muara Kelingi, and Muara Lakitan represented the largest customer concentrations and should be prioritized for detailed asset verification. The proposed inventory object includes medium-voltage lines, low-voltage lines, poles, distribution transformers, protection equipment, public street lighting, panels, and operation-worthiness documents. The inventory database should include unique asset codes, coordinates, feeder identity, specifications, physical condition, photographs, operational status, and follow-up actions. Spatial inventory is expected to improve maintenance planning, outage response, public lighting management, safety control, and evidence-based network development.

This study examines the gap between Nestlé’s sustainability commitments and the reality of ecological damage caused by the use of unsustainable raw materials in its global supply chain. Using a descriptive qualitative approach based on literature reviews and case study analysis, this study evaluates various data sources, ranging from scientific journals and corporate reports to documentation from independent organizations such as Greenpeace and the Rainforest Action Network. Findings indicate that Nestlé’s procurement of key commodities such as palm oil, cocoa, soy, dairy products, and singleuse plastics significantly contributes to deforestation, systemic plastic pollution, water extraction in vulnerable regions, and greenhouse gas emissions exceeding 87.5 million tons of CO₂e per year. In Indonesia, these highrisk areas are evident in palm oil sourcing in Sumatra and Kalimantan and cocoa sourcing in Sulawesi. Theoretically, this study argues that Nestlé’s sustainability governance exhibits a pattern of strategic decoupling, where public reporting on progress in primary supply chains is deliberately used to mask ongoing environmental damage within their hidden supply networks. Thus, this article makes a critical contribution by integrating supply chain management theory, environmental accountability, and the governance of multinational corporations.

This community service program aims to enhance farmers’ literacy on independent fertilizer production and strengthen their understanding of farmers’ rights within national fertilizer governance as an effort to achieve food sovereignty. The program was implemented in Belang Village, Bungkal Sub-district, Ponorogo Regency, involving GAPOKTAN Baungan consisting of farmer groups from Tempel, Kepuh, Pakal, Kanigoro, and Klatakan hamlets. This initiative represents cross-university synergy involving lecturers from Universitas Merdeka Malang, Universitas Soerjo Ngawi, Universitas Muhammadiyah Ponorogo, and Akademi Kesejahteraan Sosial Ibu Kartini Semarang. The implementation adopted a participatory hybrid approach combining Zoom Meeting dissemination and offline field activities. Activities included literacy enhancement on independent fertilizer production, training on organic fertilizer processing, strengthening farmer group institutions, and legal literacy regarding farmers’ rights in accessing subsidized fertilizers, including RDKK mechanisms and national policies. Methods comprised participatory socialization, hands-on training, group discussions, field practice, and monitoring and evaluation. Results show improved understanding of independent fertilizer concepts, increased technical skills in organic fertilizer production, and greater awareness of farmers’ rights and obligations in the fertilizer distribution system. The program strengthened inter-university collaboration and farmer networks, supporting sustainability, farmer independence, reduced dependence on chemical fertilizers, and community-based food sovereignty.

This qualitative literature review synthesizes current evidence on how investors navigate climate risk, legal liability, and portfolio strategy by reassessing the financial role of brown assets in high carbon transition contexts. The review finds that carbon intensive assets, traditionally viewed as stranded or declining, may provide conditional hedging value when policy trajectories remain uncertain, green technologies are not yet fully scalable, and transition risks are uneven across sectors. Legal liability emerges as a powerful driver of portfolio decisions, as fiduciaries face increasing scrutiny regarding climate disclosure, risk governance, and alignment with net zero commitments. The synthesis reveals that the strategic value of brown assets is dynamic rather than static, depending on regulatory convergence, technological maturity, and institutional investor risk preferences. Overall, the review highlights the interplay between climate related litigation pressures and investment strategy, emphasizing the need for adaptive risk assessment frameworks in a rapidly evolving transition landscape.

The increasing demand for electricity and high dependence on the utility power grid have driven the adoption of photovoltaic (PV) power generation as an environmentally friendly alternative energy source. This study aims to analyze the techno-economic feasibility of a load-sharing PV power generation system, focusing on technical analysis, operational costs, electricity bill savings, and environmental impacts. The research was conducted using quantitative methods to compare energy from photovoltaic generation and the grid, carbon emission calculations using an emission factor of 0,87 kgCO₂/kWh, and economic evaluation through parameters such as Net Present Value (NPV), Return on Investment (ROI), Cost of Energy (COE), and Payback Period (PP). The research results indicate that the photovoltaic panel generation system enables reducing utility grid energy consumption and reducing carbon emissions by 4,85 tons of CO₂ in 2024, increasing to 8,45 tons of CO₂ in 2025. The economic analysis indicates that the NPV value is not yet optimal; however, the ROI stands at 15%, the COE is Rp. 980.08/kWh, and the Payback Period is 6,56 years. The system is feasible for long-term investment. Overall, the implementation of the photovoltaic power plant demonstrates good potential in supporting carbon emission reduction, increasing the utilization of renewable energy, and reducing dependence on fossil-based energy.

This study aims to analyze the implementation of the Government Employees with Work Agreements (PPPK) orientation program at the Jambi Province Human Resources Development Agency (BPSDM). The research focuses on George C. Edward III's 1980 policy implementation theory, which encompasses communication, resources, disposition, and bureaucratic structure. The research method used is descriptive qualitative. Data collection techniques were conducted through observation, interviews, and documentation, with informants determined using a purposive sampling technique. The results of the study indicate that the implementation of the PPPK Orientation Program has run quite well and has been able to improve participants' understanding of the duties, functions, and core values ​​of the State Civil Apparatus (ASN). However, several obstacles remain in its implementation, namely internet and electricity network constraints, the lack of effective online learning, lack of participant discipline during the activity, and limited supervision and number of committee members. These obstacles affect the optimization of the learning process and the effectiveness of the online orientation activities. Therefore, efforts are needed to improve the quality of program implementation through the development of more interactive learning methods, the provision of adequate facilities, and further evaluation and mentoring to improve the competence and professionalism of ASN.

Penelitian ini bertujuan untuk merancang dan membangun perangkat yang mampu membaca, mengukur, serta mengirimkan data mengenai tegangan, arus, daya, frekuensi, dan energi secara real-time melalui aplikasi Blynk Internet of Things. Perangkat ini memungkinkan data ditampilkan pada smartphone dan layar komputer dari lokasi mana pun, dan direncanakan untuk digunakan di gardu distribusi milik PT PLN (Persero) ULP Darmo Permai. Alat ini berguna sebagai langkah tindakan korektif ketika terjadi ketidakseimbangan beban, mempermudah pengawasan dalam proses penyeimbangan, serta sebagai acuan untuk pemindahan fasa saat diperlukan. Selain itu, alat ini juga berfungsi sebagai langkah preventif untuk menjaga keseimbangan beban gardu dan sebagai referensi jika ada penambahan pelanggan baru. Metode penelitian ini melibatkan penggunaan mikrokontroler ESP32 sebagai Modbus master untuk mengatur sistem. Mikrokontroler ini menerima data digital melalui RS485 dari Power Meter Toky DS9L/7L yang mengukur tegangan dan arus dari PHB-TR. Data tersebut kemudian dikirimkan ke Cloud Blynk Internet of Things melalui nodemcu ESP32 dengan bantuan modem Wi-Fi router. Data yang diproses meliputi tegangan fasa netral RN, SN, TN (220-230 Volt), tegangan fasa-fasa RS, ST, RT (380-400 Volt), arus maksimal 400 Ampere sesuai spesifikasi sensor arus CT 400/5 A, energi (kWh), daya (Watt) untuk fasa R, S, T, daya total, serta frekuensi 50 Hz. Semua informasi ini ditampilkan pada antarmuka pengguna (UI) di smartphone dan PC.

Penelitian ini bertujuan untuk mengembangkan manajemen port I/O pada mikrokontroler ESP32 untuk mendukung sistem monitoring beban trafo secara real-time. Sistem Monitoring ini membaca, mengukur, dan mengirimkan data terkait tegangan, arus, daya, frekuensi, serta energi secara kontinu.  Data tegangan dan arus yang diperoleh dari Power Meter Toky DS9L/7L melalui RS485, diolah dan dikirimkan oleh ESP32 ke server cloud Blynk melalui koneksi internet. Namun yang perlu kita ketahui, modul ESP32 memiliki Port I/O yang sangat terbatas. Data realtime kontinyu tersebut bervariatif berupa fasa netral (RN, SN, TN), tegangan antar fasa (RS, ST, RT), arus dengan maksimal 400 Ampere, energi (kWh), daya per fasa (R, S, T) dan total daya, serta frekuensi 50 Hz. Semua data dari alat ukur tersebut dapat tersambung dengan Port I/O yang terbatas pada penelitian ini.