This research aims to identify the impact of service quality and promotion on customer satisfaction at Alfamart in Semarang Regency. The research entity group includes residents in the West Ungaran area of Semarang Regency. The participant selection method uses a non-probability approach, specifically a directed selective method. Participants include West Ungaran residents who have passed the age threshold of 17 years and have previously conducted transactions at Alfamart in Semarang Regency. The information collection mechanism is carried out through the distribution of survey instruments using a multi-level assessment scale. Data is processed through multiple regression testing. The investigative findings reveal that service quality exerts a significant influence on customer satisfaction, based on statistical test results demonstrating the significance value of service quality at 0.000, which falls below 0.05 (0.000 < 0.05), with a test statistic of 5.727 surpassing the critical threshold of 1.986 (5.727 > 1.986). Promotional efforts similarly contribute meaningfully to customer satisfaction, reflected through testing that generated a significance value of 0.002 beneath the 0.05 threshold (0.002 < 0.05) and a test statistic of 3.211 exceeding the critical limit of 1.986 (3.211 > 1.986). Subsequently, customer satisfaction is simultaneously influenced by service quality and promotional strategies, evident from the analysis with a significance value of 0.000 < 0.05 in the simultaneous test and a statistic of 153.608 transcending the critical value of 3.09 in Semarang Regency at Alfamart.

This research is conducted to assist the performance of cooperatives by utilizing financial management information system for savings and loan management and financial report in Cooperatives. Data collection methods used in this study is to conduct interviews on the financial and secretary of the cooperative with the object of research on the Business Cooperative "OENGARAN TEMPO DOELOE SEJAHTERA". Activities undertaken by KSU "OTD Sejahtera" include savings and loan activities, waserda and trading units and services. The system development method used in this research is Research and Developmnet Borg and Gall, 1983 which consists of: Research and Information Collection, Planning, Develop Preliminary Form of Product, Preliminary Field Testing, Main Product Revision, Main Field Testing, Operational Product Revision , Operational Field Testing, Final Product Revision, Dissemination and Implementation. The result of the research shows that by utilizing financial management information system can help the cooperative in processing the data of saving and loan become more effective and efficient. Control of savings and loans and the preparation of financial statements can be presented quickly and accurately. System performance becomes more precise, valid and more optimal.

Penelitian ini dilaksanakan di Zao Martial Art yang merupakan salah satu usaha industri konveksi yang bergerak dalam memproduksi seragam dan perlengkapan alat-alat taekwondo yang terletak di Jl. Raya Manyaran-Gunungpati, Cepoko, Kec.Gunung Pati, Kota Semarang. Perhitungan penerimaan dan pengeluaran kas setiap bulannya menggunakan Microsoft Excel dan untuk pencatatannya masih menggunakan tulis tangan pada selembar kertas. Belum adanya sistem informasi berbasis dekstop yang dapat memudahkan bagian pencatatan dan perhitungan penerimaan serta pengeluaran kas pada Zao Martial Art.
Sistem informasi berbasis dekstop ini bertujuan untuk membantu mengelola pencatatan data serta perhitungan penerimaan dan pengeluaran kas. Pengumpulan data untuk penelitian dilakukan dengan beberapa opsi, diantaranya wawancara, observasi dan studi pustaka. Sistem ini dikembangkan dengan Microsoft Visual Studio 2013,  Xampp, MySql. Perancangan sistem menggunakan UML (Unifed Modeling Language) dengan metode R&D (Research and Development) sebagai metode pengembangannya.
 

Capital markets play a strategic role in the global economy; however, high volatility often poses challenges for investors in making optimal investment decisions. Stock price prediction has become one of the key elements in effective portfolio management, but the complexity of market data demands more advanced analytical approaches. This study aims to explore the potential of Long Short-Term Memory (LSTM) models in predicting stock price movements and integrating these predictions into portfolio optimization strategies based on modern portfolio theory. The research methodology utilizes historical stock data from the S&P 500 and IDX Composite indices with daily frequency. The LSTM model is compared with Recurrent Neural Networks (RNN), Support Vector Machines (SVM), and Artificial Neural Networks (ANN) using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and accuracy. The LSTM model demonstrated superior performance with an MSE of 0.0018, RMSE of 0.042, and prediction accuracy of 91.5%, significantly outperforming RNN (87.3%), SVM (80.2%), and ANN (82.7%). The prediction results were then integrated into portfolio optimization using the Mean-Variance Optimization approach, resulting in an increase in expected returns from 8.5% to 12.3%, a reduction in risk from 6.2% to 5.8%, and an improvement in the Sharpe ratio from 1.37 to 2.12. This study demonstrates that the LSTM model not only excels in stock price prediction accuracy but also contributes significantly to enhancing portfolio management efficiency. This Deep Learning-based approach offers a more adaptive, data-driven investment strategy, supporting more informed decision-making in the dynamic capital market

This study examines the effect of personalization-based digital marketing strategies on brand loyalty within cross-cultural contexts, employing A/B testing and multivariate analysis methods. The research is motivated by the critical role of digital marketing in fostering consumer relationships and the challenges of understanding cultural differences that influence consumer responses to marketing strategies. The primary objective of the study is to analyze how cultural dimensions moderate the effectiveness of personalized marketing content in enhancing brand loyalty. The study was conducted through an experiment involving 200 participants divided into two groups: one group received personalized digital content, while the other received standard content. Multivariate Analysis of Variance (MANOVA) was used to evaluate the effects of culture and marketing strategies on brand loyalty, consumer satisfaction, and product recommendations. The results indicate that personalized content significantly increases brand loyalty (M = 4.5, SD = 0.8) compared to standard content (M = 3.8, SD = 1.0; p < 0.05). Additionally, consumers from collectivist cultures demonstrated a more positive response to personalized content, with higher brand loyalty scores (M = 4.6) compared to those from individualist cultures (M = 4.0). This study underscores the importance of cultural sensitivity in digital marketing strategy planning. Integrating personalization elements with an understanding of cultural contexts has been shown to enhance consumer engagement and foster stronger brand loyalty. These results provide both empirical contributions and practical guidance for companies in designing effective marketing campaigns for diverse global markets.

This research aims to explore a web-based payroll information system. The location of the research is at D'Soccer Ungaran Football Stadium, a mini soccer field rental business. From observations, several risks were found in salary management, including: 1) The risk of salary calculation errors due to conventional methods. 2) Risk of corruption and data loss because there is no database yet. 3) Employee salary reports are still prepared manually, less efficient. Based on this problem, the author designed a payroll system with a net method for withholding income tax 21. The use of this method aims to help employees reduce dissatisfaction due to tax deductions. The results of the effectiveness test showed that the new system was more effective than the old system, with a score ratio of 11:20 and performance effectiveness of 44%:80%.

This study examines the implementation of machine learning (ML) in predicting sales performance and managing inventory in manufacturing companies. The results indicate that ML, particularly neural networks, significantly improves sales prediction accuracy, reaching 92.5%, while enhancing operational efficiency through a 20% reduction in storage costs and faster distribution. The study also highlights the positive impact of ML on profitability, with companies reporting a 15% increase in net profits after adopting ML. However, challenges such as data quality and system integration remain, requiring companies to focus on data cleansing and technological infrastructure. The results suggest that ML can provide substantial long-term benefits in improving business operations, especially when quality data and appropriate algorithms are used, making it a crucial tool for companies aiming to enhance competitiveness in the digital era.

The rise of Industry 4.0 has introduced significant transformations in business operations, with Artificial Intelligence (AI) playing a central role in automating processes, enhancing decision-making, and improving efficiency. However, despite its potential, many organizations face critical challenges in implementing AI, particularly in terms of technological infrastructure readiness, workforce capabilities, and ethical considerations. This research aims to identify the challenges and propose effective strategies for AI implementation in business processes, particularly within the context of Industry 4.0. A systematic literature review (SLR) was employed to analyze peer-reviewed studies that discuss AI integration across various industrial sectors. The findings indicate that the primary challenges include the integration of AI with existing legacy systems, data privacy concerns, and employee resistance due to the perceived threat of automation. Additionally, the lack of adequate training and infrastructure investment further hampers AI adoption. In response, the research highlights strategies such as upgrading technological infrastructure, continuous employee training, and the development of clear ethical guidelines to address these challenges. The research contributes by providing a comprehensive framework for businesses to successfully navigate AI implementation, offering a novel perspective on balancing technological advancements with human resource development and ethical concerns, essential for long-term business sustainability in the digital era

Pendidikan merupakan faktor terbesar untuk kemajuan suatu bangsa. Disini peranan teknologi informasi sangat diperlukan dengan semakin berkembangnya suatu lembaga pendidikan, bertambahnya siswa dan ilmu pengetahuan serta kualitas sumber daya manusia yang ada. Lembaga yang baik tentunya harus memiliki sistem informasi. Hampir semua lembaga pendidikan telah menggunakan sistem informasi untuk mempermudah segala kegiatan yang ada di dalamnya. MTs NU Ungaran merupakan salah satu Madrasah Tsanawiyah swasta yang terletak di Jl. Kaligarang No.09, Kecamatan Ungaran Barat, Kabupaten Semarang. Selama ini, dalam proses pencatatan pembayaran SPP di MTs NU Ungaran masih menggunakan sistem manual, akibatnya proses pencatatan pembayaran SPP masih tidak efektif dan efisien. Banyak sekali kesalahan proses dalam pencatatan, misalnya dalam peginputan nama siswa, nominal pembayaran, dan hal lainnya. Semakin berkembangnya suatu lembaga pendidikan dan mengikuti perkembangan era digital, Madrasah tersebut akan menerapkan sistem informasi dalam proses kegiatan, dengan cara melakukan praktek langsung terhadap permasalahan yang terjadi. Oleh karena itu, penulis merancang sebuah sistem khusus yang digunakan untuk pencatatan pembayaran SPP. Yaitu sistem informasi berbasis multiuser dengan bahasa pemrograman Vb.Net untuk mempermudah pembuatan aplikasi tersebut, karena memiliki keunggulan mudah dikembangkan, fleksibel, dan akses informasi lebih mudah.
 
Penulis berharap dengan adanya Sistem Informasi Pencatatan Pembayaran SPP ini dapat mengurangi kesalahan-kesalahan yang mungkin terjadi serta dilakukan dengan lebih akurat dan efisien oleh staff admin di MTs NU Ungaran

Penelitian ini dilakukan di Apotek Balongsari Sehat yang terdapat di Balongsari, Pringapus Kabupaten Semarang. dalam pencatatan persediaan barang yang masih menggunakan cara manual yaitu dengan menulis data barang di buku besar. Pengelolaan persediaan barang dagang dengan cara manual, dapat menimbulkan kesalahan dalam perhitungan dan besar resiko terjadinya kehilangan data.
Tujuan Metode yang digunakan dalam pencatatan persediaan barang dagang yaitu metode FIFO (first in first out), dimana penentuan persediaan  didasarkan pada anggapan bahwa barang yang pertama kali masuk diasumsikan keluar pertama kali. Metode penelitian menggunakan R & D (Research and Development) yaitu metode penelitian yang digunakan untuk menghasilkan produk tertentu dan menguji keefektifan produk tersebut. Teknik pengumpulan data yang digunakan meliputi observasi (penelitian), wawancara terhadap objek penelitian dan studi dokumen melalui jurnal, gambar atau karya dari peneliti sebelumnya.
Hasil penelitian adalah suatu sistem informasi akuntansi dengan metode FIFO yang di bangun menggunakan Visual Basic.Net. sistem membantu proses pencatatan persediaan barang dagang, mempermudah pembuatan laporan barang. Sistem memberikan fitur pencarian data, menghitung harga jual dengan ketentuan obat bebas 1,7% dan obat keras 2,5% dilakukan otomatis oleh sistem dan menggunakan data base MySQL serta memiliki 3 akses pengguna. Hasil angket validator internal 3,1 dan eksternal 3,2 Perbandingan kinerja sistem lama dan baru di tunjukan dari hasil penilaian angket sebesar 43,33% : 85,00%. Terdapat peningkatan kinerja sistem sebesar 41,67%, sehingga sistem baru tergolong dalam kategory sangat efektif