This research aims to test the variables of tax rates and tax sanctions on motor vehicle taxpayer compliance at SAMSAT Salatiga City, Central Java. The population in this research is motor vehicle taxpayers who are currently paying vehicle tax at SAMSAT Salatiga City. The sample consisted of 60 respondents taken using a non-random sampling method with a purposive sampling technique. Data collection used a questionnaire with a five-point Likert scale parameter as primary data. Data analysis in this research used the multiple linear regression method and was processed using Predictive Analytics SoftWare, namely SPSS 29. The results of multiple regression testing showed that the variables of tax rates and tax sanctions had a significant positive effect on motor vehicle taxpayer compliance. The results of simultaneous testing also showed that the variables of tax rates and tax sanctions had a significant positive effect on motor vehicle taxpayer compliance.

This study aims to design and develop a web-basedinventory information system to improve stockmanagement and transaction recording efficiency atToko Sahabat. The main issues faced include frequentcashier system failures resulting in manualtransactions, stock data inaccuracies, and delayedsales reporting. The research employed the RapidApplication Development (RAD) method to enable fastand iterative system development based on userfeedback. Key features include user management,automatic stock tracking, real-time transactionrecording, and sales reporting. Using PHP, MySQL,and Bootstrap, the system significantly improvesoperational efficiency, reduces stock recording errors,and accelerates reporting. Implementation of thissystem supports better data-driven decision-making forToko Sahabat.

In the era of Industry 4.0, integrating artificial intelligence (AI) and big data analytics in the industrial sector demands high-performance computing infrastructure to handle increasingly complex and voluminous datasets. This study investigates the optimization of AI performance by implementing a hybrid computing architecture, integrating CPUs, GPUs, FPGAs, and edge-cloud computing. The research aims to enhance processing speed, model accuracy, and energy efficiency, addressing the limitations of standalone computing systems. A quantitative methodology was employed, using over 1 TB of industrial data from IoT sensors and production logs. A hybrid architecture was implemented with dynamic workload scheduling to distribute tasks efficiently across computational components. Performance metrics included processing time, model accuracy, energy consumption, and cost analysis. Results demonstrated that hybrid architectures significantly improved performance: the CPU-GPU combination reduced processing times to 650 ms, increased model accuracy to 88.3%, and achieved an energy consumption of 2.1 kWh. Meanwhile, the CPU-FPGA configuration, while slightly less accurate (87.5%), proved more energy-efficient at 1.3 kWh. AI models developed using hybrid systems exhibited superior predictive accuracy, with Mean Squared Error (MSE) as low as 0.0248 and R² of 0.91. The study concludes that hybrid computing architecture is a transformative approach for optimizing AI systems in industrial applications, balancing speed, accuracy, and energy efficiency. These findings provide actionable insights for industries aiming to leverage advanced computing technologies for improved operational efficiency and sustainability. Future research should focus on advanced workload scheduling and cost-effectiveness strategies to maximize the potential of hybrid systems.

SDIT NIDAUL HIKMAH SALATIGA is a private school with more than 600 students. Despite the large number of students, administrative services are still manually performed, including writing and compiling payment receipts in Microsoft Excel, manual data retrieval, and printing invoices from Excel. This method is not only impractical and inefficient but also often leads to calculation discrepancies.
 
This study aims to develop an information system using the CodeIgniter framework. CodeIgniter, with its Model, View, Controller (MVC) concept, provides ease in designing information systems. The implementation of the WhatsApp API aims to create an up-to-date system by introducing WhatsApp notification features containing detailed billing and transaction information to parents/guardians of students. The research also aims to design a practical and effective information system in school administration services, making it easier and faster to perform administrative tasks.
 Through validation conducted by experts and users, it can be concluded that this system has received excellent ratings and can be applied as a tool for school administrative payment services, with revisions made if any issues are found. User Acceptance Testing (UAT) was conducted on sample respondents by asking users to try accessing the system and provide feedback by completing the provided questionnaire. From the test results, respondents gave a total score of 90% for ease of use, 86% for appearance, and 91% for functionality, indicating that users strongly agree that this school payment information system is easy to operate, has comprehensive features, and facilitates administrative services.

Dalam tahun tahun terakhir ini  teknologi informasi dan komunikasi (TIK) telah memasuki seluruh elemen kehidupan, yang menyebabkan perubahan pada pola kehidupan sosial dan ekonomi, dan juga pada bidang pendidikan. TIK telah meresap memasuki kehidupan sehari-hari, dan penggunaannya menjadi persyaratan mendasar dalam proses  pendidikan yang bermutu. Pendidikan yang bermutu sendiri akan terjamin oleh guru-guru yang berkompeten di bidangnya . IN HOUSE TRAINING (IHT) dalam rangka PENINGKATAN KOMPETENSI GURU  pada lembaga SDIP H.M Subandi Kab. Semarang ditujukan  dalam usaha peningkatan  kinerja dan performa para guru di SDIP H.M Subandi Wilayah Kab. Semarang. Kegiatan ini didasarkan dari hasil observasi yang menunjukkan masih minimnya pengetahuan di bidang Teknologi Informasi yang dimiliki  Kepala Sekolah setempat beserta Guru tentang teknologi informasi, khususnya terkait kesulitan dalam pembuatan soal-soal secara Online atau CBT. peserta pelatihan merasa terpuaskan dengan adanya Program In House Training (IHT) Peningkatan Kompetensi Guru Dalam Pemanfaatan IT ini  karena melalui program ini mereka telah dapat mempraktekkan dalam pelatihan dan telah menguasai pengaplikasian ilmu yang diperoleh  dalam materi pelajaran dalam upaya meningkatkan skill dan performa guru   dalam menggunakan Teknologi Informasi.
 
 

In the healthcare industry, professionals develop big amounts of disorganized data. The complexity of this data and the loss of computational capability lead to delays in the investigation. Nevertheless, with the advent of Deep Learning algorithms and connection to computing power such as Graphic Processor Units (GPUs) and Tensor Processing Units (TPUs), text and image processing has become usable. Deep Learning (DL) data bring about a big outcome in Natural Language Processing (NLP) and computer perception. The main purpose of this study is to build an undivided approach that can relate social platforms, literature, and scientific records to develop an approach to medicinal education for the public and experts.
This study focuses on NLP in the healthcare industry and compiles data by Electronic Medical Records (EMR), medical literature, and social platforms. The framework proposed in this study is one for connecting social platforms, medical literature, and Electronic Medical Records scientific records using Deep Learning algorithms. Linking data sources requires defining the relationships between them, and finding concepts in medical texts. The National Library of Medicine (NLM) introduced the Unified Medical Language System (UMLS) and uses this system as the basis for the proposed system. The dynamic nature of a social platform can be recognized and supervised methodologies can be applied under supervision to develop conception. Named entity Recognition (NER) enables the active eradication of data or individuals by the pharmaceutical literature.

The information system for purchases and cash disbursements is one of the entire information systems. In retail sales companies need control of purchases and cash disbursements that are precise and fast. In an effort to minimize sudden out-of-stock inventory, it is necessary to secure an inventory to cope with a sudden out of stock due to delays in purchasing goods that occur at CV. New Space. This is what encourages the author to conduct research on CV. Angkasa Baru and choose the title "Purchasing Information System and Cash Distribution at CV. New Space.
In writing this research systemin formation, the author uses the Microsoft Visual Basic 6.0 application, the research writing method uses the Research and Development (R&D) model, while the stages of this research model go through the stages of observation or interviews with parties related to the data required in writing this thesis, stages of designing the application system, designing specifications, validation test stages, revision of validation until the system passes. The development method used by the author is the prototype method, where the system created will be tailored to the needs of the user, if there is a change in the system it will be repaired until the user is satisfied with the system.

Abstract Digital information in the economic science developed in the upstream and downstream sectors. Developments are followed by many UKM using digital technology in marketing. The forecasting uses the Exponential Smoothing algorithm Exponential Smoothing method is a procedure of continuous repairs on the latest forecasting of data. UKM Batik Tinctori Natural Dye is one of the batik producers who produce batik from customer orders and fulfill distributor requests from batik trendsThe demand of customers and distributors has an effect on the number of production batik of Tinctori Natural Dye UKM which has resulted in any batik trend that is in demand in the following month. Forecasting is calculated using the Exponential Smoothing method and Eviews software and manual comparison to lead the accuracy of the forecasting value. This prediction can be used to predict the production of batik types from the demands of consumers and distributors. Forecasting uses several methods to make predictions using different alpha and beta constants. The Comparisons of forcasting for next three months 13, 14, 15 and forecast comparisons of original values by forecasting data that already exists three months before 10, 11, 12 to find better constants that can approach the original values.