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This research presents the design and testing of an automatic color detection system using TCS3200 color sensor integrated with Arduino Uno microcontroller. The system was developed and tested using Wokwi virtual simulation platform before physical implementation. The TCS3200 sensor converts RGB light intensity reflected from objects into frequency signals, which are processed by Arduino Uno to classify colors into red, green, and blue categories. The system incorporates audio feedback using DFPlayer Mini module to provide sound notifications for detected colors. Testing results show that the system can accurately detect and classify primary colors with frequency-based thresholds: red (R<48 &R>37 & G<95 & G>85), blue (G<75 & G>65 & B<33 & B>23), and green (R<55 & R>40 & B<25 & B>5). The simulation validation demonstrates stable performance with consistent color recognition capabilities, making it suitable for industrial sorting applications and assistive technology for visually impaired individuals.

The reliability of power distribution systems is a crucial factor in ensuring stable electricity supply for industrial, commercial, and household users. Conventional protection systems often face limitations in terms of real-time monitoring, remote control, and adaptive responses to fault conditions, which can result in longer outage durations and higher operational costs. This research aims to develop a smart protection system for power distribution using Internet of Things (IoT) technology to enhance system reliability. The proposed method integrates IoT-enabled sensors, microcontrollers, and communication modules to monitor critical parameters such as voltage, current, and frequency in real time. Data are transmitted to a cloud-based platform for analysis and decision-making, enabling rapid detection of abnormalities and remote tripping of circuit breakers. The prototype was tested under various fault scenarios, including short circuits and overloads, and demonstrated faster response times compared to conventional systems. Results show that the IoT-based protection system improved fault detection accuracy, reduced downtime, and provided predictive maintenance insights through data analytics. The synthesis of these findings highlights that integrating IoT into protection mechanisms not only increases operational reliability but also supports the transition toward smart grids. In conclusion, the developed system proves effective in addressing the limitations of traditional protection systems by offering real-time monitoring, automation, and enhanced decision-making for modern power distribution networks.

The integration of Augmented Reality (AR) and Explainable AI (XAI) within Cyber-Physical Systems (CPS) design is transforming the industrial automation landscape. This study explores how combining AR’s immersive visualization with XAI’s decision transparency enhances collaborative design processes in CPS. The AR-XAI platform developed in this research improves team collaboration by offering real-time visual feedback and enabling interactive decision-making. The platform provides interpretable insights into AI-driven decisions, fostering trust among engineers and decision-makers. Key features of the platform include the ability to visualize complex CPS models, facilitating faster iterations, reducing design errors, and improving design accuracy. The integration of XAI ensures transparency in decision-making by offering clear explanations of AI predictions, which is essential for ensuring accountability and building trust in automated systems. Testing with industrial engineers confirmed that the AR-XAI platform significantly improved design outcomes, with a reduction in errors and enhanced team performance compared to traditional design methods. Moreover, the platform enabled faster decision-making and improved collaboration across diverse teams, demonstrating its potential to optimize CPS design workflows. This research provides valuable insights into the role of AR and XAI in advancing Industry 4.0 and paves the way for more advanced integrations of these technologies in industrial settings. Future research should focus on developing scalable solutions for various industrial applications and exploring more sophisticated AR-XAI integrations for emerging fields like smart cities and autonomous manufacturing.

Empowering women through the development of home-based industries plays a crucial role in improving household welfare and strengthening community-based economies in Papua. This study aims to analyze the triple role of Indigenous Papuan Women (OAP) in the D’TOMU Home Production in Sebyar Rejosari Village, Tomu District, Teluk Bintuni Regency, and to evaluate the implementation of Regional Regulation No. 1 of 2019 concerning the Recognition and Protection of Indigenous Peoples’ Rights. This research employs a qualitative method using in-depth interviews, observations, and documentation with ten key informants, including OAP women, community leaders, and production facilitators. The findings indicate that the home production initiative has a significant positive impact on three main aspects: (1) better time management balance in handling domestic, productive, and social roles; (2) increased household income by 25%–35% through product diversification such as sago flour, keladi chips, fish crackers, shrimp crackers, and traditional Papuan handicrafts; and (3) improved social recognition of women within families, communities, and indigenous societies. This study highlights the importance of government support, entrepreneurship training, digital literacy enhancement, and multi-stakeholder collaboration to achieve sustainable and competitive empowerment of Indigenous Papuan women.

The capital market is a place for various investment instruments, ranging from short-term to long-term. Before buying shares in the capital market, investors need to analyze the share prices of selected companies to predict large profits. The higher the share price, the greater the possibility of making a profit. This study aims to determine the factors that influence the stock prices of companies in the hotel, resort, and shipping sub-sectors listed on the IDX for the period 2019–2024. The dependent variable in this study is stock price, while the independent variables are financial performance and sustainability report disclosure. Financial performance variables are proxied by DER, Current Ratio, ROA, and TATO. This is a quantitative study using secondary data obtained from annual reports and sustainability reports taken from the companies' official websites. The number of samples used in this study is 10 companies using classical assumption techniques, multiple linear regression analysis, determination tests, and ending with hypothesis testing. The results show that DER and Current Ratio have a negative effect on stock prices. ROA, TATO, and sustainability report disclosure partially have no effect on stock prices. Meanwhile, financial performance and sustainability report disclosure simultaneously affect stock prices.

Increasing competition in the food industry requires companies to not only focus on product innovation and market expansion but also on strengthening internal human resource capabilities through long-term strategies. PT. Surya Pratista Hutama addresses this challenge by implementing a Talent Management Sistem (TMS) designed to identify, develop, and retain high-potential employees (HiPos), while simultaneously ensuring sustainable leadership development and succession planning. This study employed a qualitative case study approach by utilizing observations, in-depth interviews, and a paper review to obtain comprehensive insights into the company’s practices. The findings reveal that the identification of HiPos is carried out through a rigorous and consistent process using the 9-box grid as a key assessment tool. The emphasis on consistency in evaluation highlights the organization’s effort to ensure fairness and accuracy. Employee development is facilitated through multiple strategies, including formal training, mentoring programs, job rotation, and other structured learning initiatives. Retention strategies focus on providing competitive compensation packages, developing financial literacy skills, and fostering a collaborative organizational culture that values employee contributions. The implementation of TMS at PT. Surya Pratista Hutama has shown positive impacts, particularly in reducing employee turnover rates and improving leadership performance. However, the study also identifies several challenges, especially related to the need for clearer procedural guidelines and more specific development strategies to optimize outcomes. Overall, this research demonstrates that a well-structured TMS can serve as an effective mechanism for building sustainable human resource capabilities in highly competitive industries such as food manufacturing.

Penelitian ini bertujuan untuk mengetahui pengaruh kualitas produk dan kualitas pelayanan terhadap keputusan pembelian di Wingstop Margonda Depok. Fenomena yang melatarbelakangi penelitian ini adalah meningkatnya persaingan di industri kuliner, khususnya restoran cepat saji, yang menuntut setiap perusahaan untuk meningkatkan kualitas produk dan pelayanan guna mempertahankan pelanggan. Metode penelitian yang digunakan adalah metode kuantitatif dengan pendekatan deskriptif. Populasi dalam penelitian ini adalah pelanggan Wingstop Margonda Depok sebanyak 177 orang, dan jumlah sampel sebanyak 122 responden yang ditentukan menggunakan rumus Slovin dengan tingkat kesalahan 5%. Teknik pengumpulan data menggunakan kuesioner, sedangkan analisis data dilakukan dengan uji validitas, uji reliabilitas, uji asumsi klasik, analisis regresi linier berganda, uji t, uji F, dan koefisien determinasi (R²). Hasil penelitian menunjukkan bahwa kualitas produk dan kualitas pelayanan secara parsial maupun simultan berpengaruh positif dan signifikan terhadap keputusan pembelian. Dengan demikian, dapat disimpulkan bahwa semakin baik kualitas produk dan kualitas pelayanan yang diberikan Wingstop, maka semakin tinggi pula keputusan pembelian konsumen.

This research analyzes the business licensing process for plywood products at PT Anugerah Albasia Abadi Talun, Blitar Regency. It aims to identify the processes undertaken, the obstacles encountered, and to provide recommendations. Employing a descriptive qualitative approach and the Triple Bottom Line framework, data was collected through interviews, observation, and documentation studies. The research findings indicate that the company has successfully fulfilled all complex formal licensing requirements, including the Business Identification Number (NIB), Industrial Business License (IUI), Timber Legality Verification Sistem(SVLK) certificate, Environmental Management and Monitoring Efforts (UKL-UPL), and Forest Product Transportation and Trading License (IPHH), demonstrating a commitment to regulatory compliance. Nevertheless, the licensing process is still hampered by the disharmony between the digital Online Single Submission (OSS) system and manual practices, dynamic regulatory changes that are not yet widely disseminated, limited internal human resource capacity, and a lack of harmonization and coordination among government agencies. The Triple Bottom Line analysis reveals that licensing legality supports economic competitiveness and market access, while social aspects are well-established through local job creation and CSR programs. However, environmental management remains administrative and not yet fully performance-based. Therefore, the research recommendations focus on strengthening internal capacity, optimizing the OSS system, developing proactive environmental management, and enhancing continuous community involvement to achieve higher operational efficiency and sustainability

This study aims to analyze the forms, processes, and impacts of agricultural entrepreneurship service and product innovation conducted by university students on the development of micro, small, and medium enterprises (MSMEs) in Sumbawa Regency. The research employed a descriptive qualitative approach, utilizing in-depth interviews, participatory observation, and document analysis as data collection techniques. The participants included student entrepreneurs, agricultural MSME actors, and academic supervisors. The findings indicate that students play a significant role in developing knowledge- and technology-based innovations, particularly through local product branding, digital marketing, and the application of design thinking. These innovations contribute to increasing product value, expanding market reach, and enhancing managerial capacity among MSME actors. However, challenges such as limited resources and low digital literacy still affect the sustainability of innovation programs. The study highlights the importance of a quadruple helix collaboration model—linking universities, local governments, industries, and communities—to establish a sustainable and inclusive agricultural innovation ecosystem.

This study aims to examine and analyze the effect of profitability and capital structure on corporate income tax (PPh) payable at PT Kediri Tani Sejahtera during 2018–2022. The research uses a quantitative descriptive approach with primary data obtained through interviews and documentation of the company’s financial statements, including annual income statements and balance sheets. The analysis involves calculating profitability ratios, namely Return on Assets (ROA) and Return on Equity (ROE), as well as capital structure ratios, namely Debt to Asset Ratio (DAR) and Debt to Equity Ratio (DER), and comparing them with the annual corporate income tax payable. The results indicate that net profit before tax and PPh payable were below 4.8 billion IDR annually. Trend Moment analysis shows that profitability has a significant relationship with PPh payable, while capital structure also affects PPh, though not directly. The company’s asset size impacts depreciation recognized as an expense in the income statement, influencing the tax amount due. This study confirms that managing profitability and capital structure is crucial for tax planning and compliance in manufacturing companies, particularly in the organic fertilizer industry.

Penelitian ini bertujuan untuk menganalisis pengaruh Tanggung Jawab Sosial Perusahaan (CSR), ukuran perusahaan, dan profitabilitas terhadap kinerja keuangan pada perusahaan manufaktur di subsektor apparel dan barang mewah yang terdaftar di Bursa Efek Indonesia (BEI) selama periode 2021-2023. Metode yang digunakan adalah pendekatan kuantitatif dengan analisis regresi linier berganda. Data yang digunakan berasal dari laporan tahunan dan laporan keuangan publik perusahaan. Hasil penelitian menunjukkan bahwa CSR dan profitabilitas memberikan pengaruh signifikan terhadap kinerja keuangan, sementara ukuran perusahaan tidak memiliki dampak yang signifikan. Temuan ini diharapkan dapat menjadi acuan bagi manajemen dan investor dalam menyusun strategi yang berfokus pada peningkatan kinerja keuangan secara berkelanjutan.

This article presents an overview of the latest research results discussing the impact of earnings management practices on company value during the 2019-2023 period. This research aims to explore the relationship between earnings management and company value from various perspectives, using qualitative research methods and a case study approach. The researchers searched, analyzed and developed data from previous research, then adapted it to current conditions. The research findings outline the influence of earnings management on company value in the 2019-2023 time period. The research results highlight several trends, including an increased focus on transparency, accountability, as well as the impact of technology on earnings management practices and assessing corporate value. In conclusion, recent research trends show a shift towards deeper and more relevant understanding, with an emphasis on transparency, accountability, the influence of technology, as well as research based on specific industries and country contexts.

Modern industries require automation to enhance operational efficiency and productivity. This study designs and implements an automatic sorting system based on the Internet of Things (IoT) using a mini conveyor, ESP32 microcontroller, TCS3200 color sensor, servo motor, and the Blynk application. The system is designed to accurately detect object colors, sort objects based on color, and enable remote monitoring and control via mobile devices. Testing results indicate that the system can detect and sort objects with a high level of accuracy, although some errors occur due to changes in lighting conditions. The conveyor speed is consistently recorded at 0.335 m/s, while the system's response time, including color detection, servo movement, and application updates, operates within an optimal range. The Blynk application enhances the flexibility of real-time system control. This study demonstrates that IoT-based sorting systems can serve as an efficient solution to support industrial automation. Further development is recommended to improve color detection accuracy and expand the system's application in more complex industrial scenarios.

The rapid advancement of intelligent systems has accelerated the adoption of data-driven solutions across diverse industries, creating an increasing need for models that are both efficient and privacy-preserving. While traditional centralized machine learning approaches offer strong predictive capabilities, they often struggle with challenges related to data privacy, network latency, and computational inefficiency-especially in distributed environments with heterogeneous devices. To address these limitations, recent research has explored hybrid learning frameworks that integrate federated learning, edge computing, and dynamic model optimization techniques. These hybrid approaches enable models to process and learn from data closer to the source while maintaining stringent privacy requirements by keeping raw data localized. Additionally, the incorporation of pruning strategies, adaptive model compression, or multimodal data fusion contributes to improved speed, scalability, and accuracy in real-time inference tasks. Such frameworks have demonstrated notable promise in settings characterized by high data volume, operational complexity, and the necessity for fast anomaly detection or decision-making. However, despite these advancements, several challenges remain, including synchronization delays across edge nodes, variability in hardware capabilities, and the need for more efficient aggregation algorithms. Future developments may involve leveraging next-generation pruning techniques, energy-aware edge scheduling, decentralized orchestration protocols, or the integration of digital twin technologies to further enhance performance. Overall, hybrid distributed learning frameworks represent an important evolution toward more intelligent, secure, and autonomous computational ecosystems capable of supporting the next wave of smart applications.

Al–Mg–Si aluminum alloys are widely utilized in engineering applications due to their low density, excellent corrosion resistance, and mechanical properties that can be modified through heat treatment. This study investigates the effect of homogenization on the microstructure and hardness of Al–Mg–Si alloys produced by the squeeze casting process. The experimental procedure involved alloy melting, squeeze casting at 76 MPa using preheated metal molds, followed by homogenization at 400 °C for 4 hours. Microstructural characterization was performed using optical microscopy to examine the dendritic morphology and measure the secondary dendrite arm spacing (SDAS). Mechanical properties were evaluated through Vickers microhardness and Rockwell macrohardness testing. The results show that homogenization increases the SDAS from 32.59 μm to 36.88 μm and decreases the volume fraction of interdendritic phases from 15.51% to 13.57%. Furthermore, microhardness decreased from 50.22 VHN to 38.58 VHN, while macrohardness decreased from 54.60 HRE to 46.64 HRE. These reductions are attributed to the partial dissolution of Mg₂Si precipitates into the aluminum matrix during homogenization. Overall, this research provides valuable insight into the optimization of initial heat treatment parameters for Al–Mg–Si alloys produced by squeeze casting. The findings highlight the role of homogenization in improving microstructural uniformity and preparing the alloy for subsequent deformation processes such as cold rolling and extrusion, particularly for structural components used in mining and heavy transportation industries.

This study aims to analyze the effect of capital structure and Corporate Social Responsibility (CSR) disclosure on the financial performance of industrial sector C IDX-IC companies listed on the Indonesia Stock Exchange during 2021–2023. Capital structure is proxied by the ratio of long-term debt to equity, while financial performance is measured using Return on Assets (ROA). A quantitative approach with multiple linear regression analysis was employed, and the sample was selected using purposive sampling. The results reveal that capital structure has a significant positive effect on ROA, whereas CSR disclosure has a significant negative effect on ROA. These findings suggest that strategic use of long-term debt can enhance profitability, while the costs and commitments arising from CSR disclosure may reduce financial performance. The study implies that company management should optimize capital structure and carefully balance sustainability strategies through CSR disclosure to avoid diminishing profitability.

This study aims to analyze the role of communication in Customer Relationship Management (CRM) systems in creating customer satisfaction at PT Bangkit Jaya Teknik Indonesia, a business-to-business (B2B) cold storage installation service company. The research background lies in the increasing number of customer complaints during 2022–2024, mainly due to delayed responses, suboptimal after-sales service, and the absence of a centralized communication record system. This study employed a qualitative approach with a case study design. Data were collected through observation, semi-structured interviews with internal parties (marketing project, project manager, project PIC) and customers, as well as company archival documentation. The findings reveal that responsive, open, and two-way communication plays a significant role in enhancing customers’ sense of being valued, trust, and loyalty, which ultimately fosters satisfaction. However, communication barriers such as delays in after-sales service, gaps between customer expectations and company procedures, and the lack of a communication database remain major challenges. To overcome these, the company has initiated strategies including the development of a customer communication database, improved after-sales monitoring, and the adjustment of communication standard operating procedures to align with customer needs. These results reinforce the relevance of Relationship Management theory and the IDIC model, both of which emphasize communication as the core of CRM. Theoretically, this study contributes to organizational communication studies, while practically, it provides recommendations for B2B service companies to prioritize communication in CRM strategies to strengthen customer satisfaction and loyalty.

UMKM pada industri kreatif berkembang begitu pesat, tingkat literasi sangat berpengaruh terhadap tingkat pemahaman dan wawasan seseorang sehingga dapat berdampak positif dalam perkembangan ekonomi dan lingkungan tidak terkecuali pada UMKM D&R Snack. Permasalahan utama pada usaha UMKM D&R Snack adalah kurangnya pemahaman tentang digitalisasi pemasaran serta minimnya kemampuan dalam membuat packaging yang menarik calon konsumen sehingga barang yang di jual cenderung memiliki tampilan yang sama sehingga membuat diferensiasi produk sangat minim sehingga sulit mendapatkan konsumen yang loyal. Solusi yang di tawarkan kepada mitra adalah melakukan sosialsiasi digital marketing, pelatihan packaging dan pendampingan secara berkelanjutan. Hasil dari kegiatan ini yaitu meningkatnya pengetahuan UMKM D&R Snack untuk mengaplikasikan penggunaan digital marketing serta memperbaiki packaging yang di jual ke konsumen sehingga dapat memiliki identitas produk serta memiliki pangsa pasar yang lebih luas.

This article presents a review study that proposes a blended model combining actual programming techniques with queuing theory to improve the performance and service quality of service systems. The main objective is to design a system that is capable of serving customers as efficiently as possible, using solutions derived from queuing theory to regulate and optimize customer flow, while applying accurate programming methods to ensure that the system operates correctly and in accordance with established standards. The study discusses how these two approaches complement each other and demonstrates that integrating them provides a balance between operational efficiency and the quality of services delivered. To illustrate the effectiveness of this hybrid model, a case study is examined to highlight the practical impact and real-world implications of the proposed framework. Both mathematical formulations and experimental analyses were employed to evaluate the model’s effectiveness. Findings indicate that this combined approach not only enhances system reliability but also provides measurable improvements in customer satisfaction and service outcomes. By offering a structured way to integrate queuing solutions with precise programming, this research contributes to the development of more sustainable and effective service management strategies. The model therefore has significant potential for broader application in industries that rely heavily on service delivery and customer flow optimization.

Oil palm (Elaeis guineensis) is a major tropical commodity in Southeast Asia that plays an important role in the global economy, especially as a raw material for the food, cosmetics, and bioenergy industries. West Kalimantan Province is one of the regions with the largest oil palm plantations in Indonesia, where its area increased from 1,166,282 Ha in 2020 to 1,449,274 Ha in 2022. Landak Regency contributes 119,326 Ha, but its productivity is still relatively low with a total production of 184,592 tons or around 1.54 tons/Ha. PTPN IV Ngabang in Landak Regency as one of the largest palm oil companies in the area also faces the problem of low productivity, thus hindering harvest rotation and the achievement of daily targets. This study aims to describe the productivity of oil palm harvester labor and find out what factors affect the productivity of oil palm harvester labor in PTPN IV, Ngabang District, Landak Regency. The method uses qualitative as an approach in finding answers with a sample of 78 respondents. The variables in this case study are labor productivity (Y) and independent/independent variables (X), namely age, working period, family dependents, mileage, and education. The data analysis technique used in this case study is analysis on multiple linear regression. The results of the study concluded that the productivity of oil palm harvesters in PTPN IV Ngabang averaged 1200,71 kg/day. Simultaneously, age, family dependents, working period, mileage, and education affect the productivity of oil palm harvester labor at PTPN IV Ngabang. Partially, the factor that greatly affects the productivity of the oil palm harvester workforce at PTPN IV Ngabang is the age factor of the worker and working period. Meanwhile, the factors of family dependents, distance traveled and labor education partially did not have a significant effect.