This paper aims to overcome the problem of manual financial recording that is still commonly used by MSMEs, which often causes data loss and inefficiency in financial management. To answer this challenge, researchers developed a mobile-based financial recording application using Flutter and a number of available supporting packages. This application is designed to be able to record and store income and expenditure data directly on the user's mobile device, making it easier for MSMEs to monitor their financial condition in real time. The development was carried out using a waterfall model approach, which includes the stages of analysis, design, implementation, and testing. To test the functional performance of the application, the Black Box testing method is used to assess the accuracy and reliability of the features without looking at the internal code structure. The test results show that all features can function as they should and the application is considered effective in supporting digital MSME financial recording.

The concept of lack being the apex of today’s human being’s stratums of dithered truth is an equivocated issue in the contemporary postmodern era. As is for the amalgamation of postmodern approaches toward subjectivity, the subject is decentered, displaced, and/or pluralized; for Slavoj Žižek, on the contrary, the very lack is inherent in the very core of subjectivity. In Paul Auster’s City of Glass, a juxtaposition of both the postmodern approach and that of Žižek’s Neoclassical revisiting of subjectivity is presented. The protagonist, who is a detective in this novella, acts as if he lags behind some internal reality. For Paul Auster, the detective genre is not the conventional one; that of the classical detectives who search for clues as a means to reach causality to work out the case; it is rather a genre so confusing that the detective not only does not yield any definite result, but with his ebullient sentiments exculpate himself as a detective from coming to any logical deduction. Taking City of Glass as the center for the present discussion, this paper, in an analytic approach, is to render a rereading of the novella now from a Žižekian perspective.

This community service program aims to develop nutraceutical-based health products from temu mangga (Curcuma mangga Val.van Zip) and probiotics, called "TEMAPRO". Research and socialization were conducted in Pulau Semambu Village, South Sumatra, targeting village mothers who have limited knowledge about the benefits of herbs and probiotics. Temu mangga, which is traditionally consumed as a salad and herbal medicine, contains various active compounds that have the potential as antioxidants and anti-cancer. Combined with the probiotic Lactobacillus rhamnosus, this product is expected to support digestive health and increase body immunity. Implementation methods include education, training in making temu mangga extract, mixing with probiotics, and product packaging techniques. The results of the activities showed an increase in community understanding and skills in processing local materials into health products with economic value. It is hoped that "TEMAPRO" will not only improve the quality of public health, but also open up business opportunities in the village through local nutraceutical products.

Abstract: This research aims to identify the local wisdom values ??of Sanghyang Siksakandang Karesian relevant to history learning. To achieve the stated objective, the investigation included using qualitative methods with a single case study, and data were collected using observation, interviews, and document reviews. Furthermore, the obtained data was analyzed using an interactive model consisting of phases: data condensation, data presentation, and conclusion. The results showed that (1) the local wisdom values ??of Sanghyang Siksakandang Karesian included dasakerta, Dasaperbakti, people's behavior (hulun), and complementary actions. Dasakerta is a guideline for human sensory behavior in daily life. Dasaperbakti describes the social hierarchy that requires legitimacy. While Panimbuh ning twah shows complementary rules in society, (2) History learning based on local wisdom values of Sanghyang Siksakandang Karesian is carried out through contextual learning by introducing and providing an understanding of Kagaluhan values to students to be applied in everyday life. This research can improve the understanding of local history and the character of students who are more rooted and culturally responsive, and strengthen the character of students. However, limited curriculum, learning resources, and teacher understanding are challenges. This study contributes to the literature gap by offering a local wisdom-based history learning model. The implication of this study emphasizes the importance of policy support to accommodate local history in the high school education curriculum for character building.
Abstrak: Penelitian ini bertujuan untuk mengidentifikasi nilai-nila kearifan lokal Sanghyang Siksakandang Karesian dan nilai-nilai yang relevan untuk pembelajaran sejarah. Penelitian ini menggunakan metode kualitatif dengan studi kasus tunggal. Teknik pengumpulan data terdiri dari observasi, wawancara, dan studi dokumen. Analisis data yang digunakan adalah analisis data model interaktif yang melalui tahapan kondensasi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa (1) nilai-nilai kearifan lokal Sanghyang Siksakandang Karesian meliputi dasakerta; Dasaperbakti; perilaku rakyat (hulun); dan pelengkap perbuatan (Panimbuh ning twah). Dasakerta merupakan pedoman perilaku indra manusia dalam kehidupan sehari-hari. Dasaperbakti menggambarkan hirarki sosial dalam masyarakat yang membutuhkan legitimasi. Sedangkan Panimbuh ning twah  menunjukkan aturan pelengkap dalam masyarakat (2) Pembelajaran Sejarah yang berbasis nilai-nilai kearifan lokal Sanghyang Siksakandang Karesian dilakukan melalui pembelajaran kontekstual dengan mengenalkan dan memberikan pemahaman nilai-nilai Kagaluhan pada peserta didik untuk diterapkan dalam kehidupan sehari-hari. Penelitian ini dapat meningkatkan pemahaman sejarah lokal dan karakter peserta didik yang lebih mengakar dan tanggap budaya, serta memperkuat karakter peserta didik. Namun, keterbatasan kurikulum, sumber belajar, dan pemahaman guru menjadi tantangan. Studi ini memberikan kontribusi terhadap kesenjangan literatur dengan menawarkan model pembelajaran sejarah berbasis kearifan local. Implikasi penelitian ini menegaskan pentingnya dukungan kebijakan untuk mengakomodasi sejarah lokal dalam kurikulum Pendidikan sekolah menengah atas untuk pembentukan karakter.

This study discusses the construction system in Japan from the perspective of Sharia business management. Japan is known for its high construction standards, advanced technology, and disciplined work system. The study aims to analyze how Sharia business principles can be applied in the construction industry in Japan, particularly in workforce management, finance, and business ethics. Using a qualitative descriptive method, this research explores the firsthand experiences of construction workers in Japan and the policies that support Sharia business practices in the industry. The findings indicate that there are opportunities to implement Sharia concepts in human resource management and financial transparency.

Nowadays, the number of cyber terrorists that using Internet as a medium keep increasing around the world are really worrying. Even though the cyber terrorist is publishing their post openly and public, there are quite difficult to recognize their main communication media. This happen because the cyber terrorist might hide their agenda through any sympathetic base website. Therefore, the aim of this project is to formulate tracing and linking algorithm using data mining technique in order to identify the relationship between each cyber terrorism components that may result to cyber terrorism website.
 
 
 

Cyber-Physical Systems (CPS) are increasingly deployed in critical infrastructure yet remain vulnerable to adversarial attacks that manipulate sensor data to mislead AI-based decision-making. These threats demand not only high-accuracy detection but also transparency in model reasoning. This study proposes a Hybrid Explainable AI (XAI) Framework that integrates Convolutional Neural Networks (CNN), SHAP-based feature interpretation, and rule-based reasoning to detect adversarial inputs in CPS environments. The framework is tested on two simulation scenarios: industrial sensor networks and autonomous traffic sign recognition. Using datasets of 10,000 samples (50% adversarial via FGSM and PGD), the model achieved an accuracy of 97.25%, precision of 96.80%, recall of 95.90%, and F1-score of 96.35%. SHAP visualizations effectively distinguished between normal and adversarial inputs, and the added explainability module increased inference time by only 8.5% over the baseline CNN (from 18.5 ms to 20.1 ms), making it suitable for real-time CPS deployment. Compared to prior methods (e.g., CNN + Grad-CAM, Random Forest + LIME), the proposed hybrid framework demonstrates superior performance and interpretability. The novelty of this work lies in its tri-level integration of predictive accuracy, explainability, and rule-based logic within a single real-time detection system—an approach not previously applied in CPS adversarial defense. This research contributes toward trustworthy AI systems that are robust, explainable, and secure by design.

The rapid advancement of deepfake technology has raised significant concerns regarding misinformation, privacy breaches, and digital fraud. Existing deepfake detection models, particularly those based on deep learning, often require high computational resources, making them unsuitable for real-time applications on mobile devices. This study aims to develop a lightweight deepfake detection model that enhances accuracy while maintaining computational efficiency. To achieve this, we propose a hybrid approach that integrates Fast Fourier Transform (FFT), MobileNet, and an Attention mechanism. The FFT component enables frequency-domain analysis to detect subtle deepfake artifacts, while MobileNet provides a lightweight convolutional backbone, and the Attention layer enhances feature extraction. The proposed model was evaluated on a benchmark deepfake dataset, and the results demonstrated its superior performance compared to the standard MobileNet model. Specifically, the model achieved an accuracy of 94.2%, an F1-score of 93.8%, and a computational efficiency improvement of 27.5% in comparison to conventional CNN-based approaches. These findings indicate that the integration of FFT and Attention mechanisms significantly enhances the model's capability to distinguish real and manipulated media while reducing computational overhead. The contribution of this study lies in presenting a deepfake detection model that balances accuracy and efficiency, making it suitable for deployment in mobile and resource-constrained environments. Future research should explore further optimization for energy efficiency, the adoption of lightweight Transformer architectures, and extensive testing on diverse datasets to improve robustness against real-world variations.

Education is one of the most important things for people to have. Many people are competing for education to increase their abilities. Technology plays a big role in developing access to education to make it easier with many online applications and online classes education becomes easier. However, there are still many unresolved problems in this field of education, namely the emergence of the phenomenon of incompatibility between educators and students so that student interest decreases dramatically because of this. And also, the lack of learning materials taught that are not school subjects such as programming. Therefore, the author and team designed an application where this application can find students a learning mentor outside of school so that they can increase their knowledge. The application also provides a matching feature based on the student's personality so that the student can find a suitable tutor.

The exchange of information on the Internet requires increased protection to avoid potential threats to privacy and security. This study identified the main issues in this regard: the need for simple and effective tools for encoding and decoding messages, and the need to understand Base64 encoding algorithms and concepts. However, to overcome this problem the author developed an application to encode and decode messages/text using the Base64 algorithm and the Python programming language. This application allows users to send secret messages/text securely via and convert the data into Base64 format for secure transmission via text media. It also covers the basics of cryptography, Base64 algorithms, and how to use the Python programming language to develop secure applications. The result of this research is a simple and effective encryption and decryption application. This application provides a solution for users to protect messages or text when they want to change confidential information by converting it to Base64 format. With this application, you can send secret messages or texts with the confidence that only authorized parties can read them. Implementing message encryption and decryption using the Base64 algorithm using Python is an important step in maintaining message privacy and security in the current digital era. This research succeeded in developing an application suitable for this purpose. Therefore, the next step is to improve the security of your application by implementing stronger encryption algorithms. Additionally, we provide a more comprehensive user guide to help users better understand cryptographic concepts. Further research may focus on integrating applications with broader Internet security protocols to address increasingly complex security threats.