This study aims to determine and analyze the direct influence of store atmosphere on impulse buying in Consumers of Kartasura Mitra Department Store, to determine and analyze the direct influence of sales promotion on impulse buying in Consumers of Kartasura Mitra Department Store, to determine and analyze the direct influence of product completeness on impulse buying in Consumers of Kartasura Mitra Department Store and to determine and analyze the simultaneous influence of store atmosphere, sales promotion, product completeness on impulse buying in Consumers of Kartasura Mitra Department Store. This study uses a quantitative method with a sample of 100 employee respondents at Consumers of Kartasura Mitra Department Store. Data were analyzed using multiple linear regression analysis using IBM SPSS Statistics. The results of the study indicate that directly store atmosphere has a significant effect on impulse buying in Consumers of Kartasura Mitra Department Store, directly product completeness has a significant effect on impulse buying in Consumers of Kartasura Mitra Department Store, directly sales promotion has a significant effect on impulse buying in Consumers of Kartasura Mitra Department Store, and directly and simultaneously store atmosphere, sales promotion, and product completeness have a significant effect on impulse buying in Consumers of Kartasura Mitra Department Store

Handwritten digit recognition is one of the key challenges in the field of digital image processing and artificial intelligence, with significant potential in various applications such as automatic form input systems, handwritten data correction, and attendance systems based on handwriting. This study aims to develop a web-based information system capable of automatically recognizing handwritten digits using the K-Nearest Neighbors (KNN) classification method. The system is designed through several main stages, including image preprocessing (conversion to grayscale, thresholding, and image size normalization), feature extraction using the zoning technique, and classification using the KNN algorithm. This research utilizes the MNIST dataset, which contains thousands of handwritten digit images ranging from 0 to 9. The system is developed using the Google Colab platform, supported by Python libraries such as OpenCV, NumPy, and Scikit-learn. Test results show that the system can achieve an accuracy of over 90% at certain K values, indicating that the KNN method is quite effective and efficient in recognizing handwritten digit patterns. This system is expected to be applicable for various digitization needs of handwritten numbers in education, administration, and information technology sectors

The rapid advancement of wireless communication technology has significantly influenced industrial automation, particularly in collaborative robotics (cobots). With the expected commercial deployment of 6G by 2030, this technology offers ultra-high-speed data transmission, low latency, and deep integration of Artificial Intelligence (AI). This study investigates the impact of 6G on enhancing the performance and efficiency of cobots in industrial settings, addressing challenges related to real-time coordination, network latency, and economic implications. The results indicate that cobots powered by 6G achieve a 25-30% increase in throughput, a latency reduction to 0.5 - 0.8 ms, and a 15-20% improvement in energy efficiency compared to 5G-based cobots. These enhancements facilitate more precise and adaptive human-robot interactions, improving operational flexibility and productivity across various sectors. However, challenges such as infrastructure readiness, cybersecurity risks, and high implementation costs remain key concerns. This study provides a comprehensive analysis of the synergy between 6G and collaborative robotics, offering valuable insights for industries preparing for next-generation automation.

This study analyzes the impact of service quality, store atmosphere, and price fairness on customer satisfaction and its effect on loyalty at Kaisar Barbershop Semarang. A quantitative approach using PLS-SEM was employed, with 145 purposively sampled respondents (criteria: customers who used the service at least twice in the last three months). Data was collected via a 7-point Likert scale questionnaire and analyzed using SmartPLS. Results show that service quality is the most dominant factor (path coefficient 0.732), followed by store atmosphere and price fairness (each 0.135). Customer satisfaction also significantly influences loyalty (0.935). These findings assist management in improving strategies to maintain customer loyalty in a competitive market

The purpose of this study is to analyze in depht how taxprayer  awareness (X1), education level (X2), and income (X3) affect the level of community compliance in paying land and building taxes (Y) in Kebonagung Village, Demak.
The population of this research is the people of Kebonagung village community, the sampling technique used is purposive sampling in the Kebonagung village community with a total of 100 people. This study uses an instrument in the form of a quesionnarire with a Likert scale as a measurement tool, and testing is done using SPSS. Meanwhile, the data testing techniques used in this study include validity tests, reliability tests, with Cronbach Alpha as a comparison. And to test and prove the research hypothesis, classical assumption tests and multiple linear regression analysis were used.
The research results  show that taxpayer awareness (X1), education level (X2), and income (X3) have an effect on compliance in paying land and building taxes (Y). Where the coefficient of determination (Adjusted R Square) value was obtained as 0.544, which means that the variables used in the research have an influence of 54.4%.
To increase compliance in paying land and building tax, public awareness is needed in making payments, so there needs to be zocialization of laws and regulations related to taxation and the public needs to be aware that someone who already has their own income must be able to pay land and building tax

This study explores high school students' perceptions and awareness of human rights violations (HRV) on social media. Using a mixed-method approach involving interviews and questionnaires with 100 students from five schools in Pekanbaru, the research reveals that the majority of students recognize various HRV issues such as hate speech, cyberbullying, discrimination, and privacy violations, and understand their impacts. Approximately 75% of students feel responsible to report HRV incidents, though some hesitate due to fear or perceived helplessness. While most students are familiar with the term HR, only 60% can accurately define protected rights like privacy and freedom from bullying. The average awareness score is 7.5 out of 10, influenced by socio-economic background and parental education. Findings indicate that 70% have witnessed hate speech, 55% have experienced or observed cyberbullying, and 60% acknowledge that spreading hoaxes infringes on the right to information. A significant majority (85%) agree that HR education should be integrated into school curricula. Despite high awareness levels, students' understanding of the boundaries and consequences of digital expression remains limited, highlighting the need for ongoing educational interventions and curriculum development in digital ethics and human rights. The study emphasizes the importance of continuous literacy programs and recommends further research with broader geographic scope and qualitative methods to deepen understanding.

Perkembangan teknologi digital telah mendorong generasi milenial dan Gen Z di Indonesia untuk aktif berinvestasi melalui instrumen berbasis teknologi. Namun, keputusan investasi mereka masih dipengaruhi oleh bias perilaku seperti overconfidence, herding, dan loss aversion, yang berdampak pada tingkat toleransi risiko keuangan. Penelitian ini bertujuan menganalisis pengaruh ketiga jenis bias tersebut terhadap toleransi risiko serta membandingkan perbedaannya antara Milenial dan Gen Z. Penelitian dilakukan dengan pendekatan kuantitatif melalui survei kepada 500 responden dari kedua generasi, menggunakan kuesioner skala Likert 5 poin. Data dianalisis menggunakan Structural Equation Modeling (SEM) melalui SmartPLS, termasuk uji multi-group analysis untuk membandingkan antar generasi. Hasil menunjukkan bahwa overconfidence meningkatkan toleransi risiko, sementara loss aversion menurunkannya. Pengaruh herding bervariasi di antara kedua generasi, menunjukkan perbedaan karakteristik perilaku investasi. Temuan ini memperkaya literatur perilaku keuangan dengan konteks lokal dan menyoroti pentingnya pendekatan edukasi keuangan yang disesuaikan dengan profil generasi. Selain itu, hasil penelitian ini membuka peluang pemanfaatan teknologi, termasuk kecerdasan buatan (AI), untuk membantu investor muda dalam mengenali dan mengelola bias perilaku serta meningkatkan pengambilan keputusan keuangan yang lebih rasional dan adaptif di era digital.

This study aims to analyze the impact of ESG on company performance as measured by Return On Assets (ROA) and the moderating role of Corporate Reputation. Secondary data used in this study comes from the Bloomberg website and annual reports of companies indexed by Sri-Kehati and listed on the IDX during 2020-2023. The census sampling method was used in the process of selecting research samples which resulted in 33 companies being sampled. Data analysis of this study uses SEM (Structural Equation Modeling) Analysis with SmartPLS. The results of this study show that ESG has a positive and significant impact on company performance and the role of corporate reputation strengthens the influence of ESG on company performance.

UMKM kuliner, terutama Rumah Makan Padang Ujuang Pulau, sangat bergantung pada ketersediaan bahan baku segar dalam jumlah dan waktu yang tepat, yang dapat meminimalkan biaya untuk operasional dan meningkatkan efisiensi pada produksi. Studi ini bertujuan untuk membandingkan dan menganalisis seberapa efektif metode EOQ dan JIT dalam mengendalikan stok bahan baku di Rumah Makan Padang Ujuang Pulau. Penelitian ini menggunakan pendekatan kuantitatif deskriptif. Cara untuk mengumpulkan data penelitian ini dilakukan dengan melakukan observasi, dokumentasi, dan wawancara. Data dianalisis menggunakan metode Economic Order Quantity (EOQ) dan Just In Time (JIT). Data diolah dengan menggunakan Microsoft Excel. Hasil penelitian menunjukkan bahwa metode EOQ dapat menekan biaya persediaan menjadi Rp 51.055 dengan frekuensi pemesanan rata-rata 3,1 kali per tahun, sedangkan metode JIT dapat menekan biaya persediaan menjadi Rp 1.160.301 dengan frekuensi pembelian 1,2 kali per tahun. Dengan demikian, dapat disimpulkan bahwa EOQ menjadi metode paling efektif untuk mengendalikan persediaan bahan baku pada UMKM ini, meskipun JIT dapat dipertimbangkan untuk kebutuhan efisiensi frekuensi pemesanan. Ini berbeda dengan kebijakan persediaan UMKM saat ini, yang memiliki biaya persediaan tertinggi.

Indonesia's financial reforms, starting in 2003, introduced accrual-based Government Accounting Standards (PP No. 71/2010) for transparent and efficient financial management. The Provincial Government of Yogyakarta (DIY) is required to produce accurate financial reports, including inventory management under PSAP No. 05. BPKA DIY plays a key role but faces challenges due to discrepancies between financial and inventory systems. This study examines the importance of an integrated inventory accounting system in improving the quality of financial reporting at BPKA DIY, offering recommendations to enhance efficiency and transparency.