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Administrative services for civil servants (ASN) play a crucial role in ensuring the rights and obligations of government employees. One of these services is the submission process for the Wife Card (KARIS) and Husband Card (KARSU), which serve as official proof of marital status for civil servants. At the BKPSDM of Sumba Barat Daya, the current submission process for KARIS and KARSU is still carried out manually by filling out paper forms and attaching physical documents. This manual method is time-consuming, prone to data errors, and complicates the monitoring process. Therefore, this study aims to develop a digital information system to simplify the submission, verification, and issuance process of KARIS and KARSU online. This research applies a Research and Development (R&D) approach using the Waterfall model, consisting of requirement analysis, system design, implementation, testing, and evaluation stages. The system is developed using the Python (Streamlit) programming framework and a SQLite3 database, designed to be easily accessible to both ASN users and BKPSDM officers through local networks or the internet. The results show that the developed system successfully reduces processing time by up to 60%, improves data accuracy by 90%, and significantly decreases the use of physical documents. The implementation of this digital information system makes the KARIS and KARSU administrative service more efficient, transparent, and accountable, supporting the ongoing digital transformation within the local government of Sumba Barat Daya Regency.

The rapid growth of web technologies and online services has increased the exposure of web applications to cyber threats such as Cross-Site Scripting (XSS) and SQL Injection (SQLi). Conventional rule-based mechanisms, such as Web Application Firewalls (WAFs), often fail to detect emerging attack patterns. To address this, Machine Learning (ML) and Deep Learning (DL) have emerged as adaptive approaches for enhancing web attack detection. This study performs a Systematic Literature Review (SLR) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to analyze recent ML/DL-based detection methods. Of the 263 retrieved studies, 15 met the inclusion criteria for detailed review. The findings reveal that Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) are the most applied algorithms. At the same time, recent works emphasize Transformer-based and hybrid ML–DL models. These approaches achieved robust performance (accuracy 85–97%, F1-score >90%) but still face challenges in dataset representativeness, class imbalance, and computational cost. This review highlights future research directions in Explainable Artificial Intelligence (XAI), Federated Learning (FL), and adversarial robustness to develop more efficient and trustworthy web attack detection systems.

Proses pengelolaan stok barang di PT Wahanamas Pancajaya Kudus masih dilakukan secara manual menggunakan kartu stok dan catatan fisik. Hal ini sering menimbulkan masalah seperti kesalahan pencatatan, keterlambatan pelaporan, dan terbatasnya visibilitas data persediaan secara real-time. Penelitian ini bertujuan untuk mengembangkan aplikasi stok barang berbasis mobile yang dirancang untuk meningkatkan efisiensi, akurasi, dan kecepatan pengelolaan data persediaan. Arsitektur yang diusulkan mengintegrasikan Laravel sebagai backend framework, SQLite sebagai basis data lokal, dan Flutter/Dart sebagai platform mobile client, yang memungkinkan terjadinya sinkronisasi data secara real-time antara client dan server. Metode pengembangan yang dipilih adalah Rapid Application Development (RAD) karena bersifat iteratif, cepat, dan memastikan keterlibatan aktif pengguna dalam setiap tahapan pengembangan prototipe. Sistem yang dihasilkan menyediakan fungsionalitas utama, termasuk pencatatan barang masuk dan keluar, pemantauan stok secara real-time, notifikasi otomatis stok menipis, serta pembuatan laporan digital yang dapat diakses dari berbagai perangkat. Pengujian dilakukan melalui simulasi server lokal menggunakan XAMPP, di mana beberapa klien mobile mengakses server melalui jaringan berbasis IP. Berdasarkan pengujian black-box, seluruh fitur sistem berfungsi dengan baik dan telah memenuhi persyaratan operasional perusahaan. Temuan ini menunjukkan bahwa sistem yang diimplementasikan berhasil meningkatkan efisiensi operasional, mengurangi kesalahan input data, dan menyediakan akses yang lebih cepat terhadap informasi inventaris. Kontribusi penelitian ini adalah mendukung transformasi digital proses manajemen stok di industri manufaktur skala menengah dan menjadi referensi praktis untuk implementasi sistem inventaris mobile berbasis API yang ringan.

The waste detection application is a solution to identify and classify waste. With the increasing waste problem, this application aims to assist in classifying waste into organic, inorganic, and unknown categories. This research implements a waste detection application that runs on smartphones with the Android operating system. The application is the result of a capstone project from the Bangkit program in the MSIB batch 6. The development of this application is divided into several parts, namely backend, frontend, and deployment. The author focuses on the deployment process of the application using Google Cloud Platform. The Google Cloud Platform infrastructure was chosen due to its scalability and flexibility. The services utilized include Google Compute Engine (GCE), Google Virtual Private Cloud (VPC), and Google Cloud Storage (GCS). The deployment process involves creating a new project in Google Cloud, configuring virtual machines, and setting up Google Cloud Storage. The server VM configuration includes the installation of SQL Server (MariaDB), deployment of the Machine Learning API, and Backend API. Testing was carried out on the Machine Learning API using Postman and the Backend API through a browser. The results show that Google Cloud Platform can be implemented as a cloud computing infrastructure for waste detection applications. The Machine Learning API is able to read objects in the form of images sent by users.

The academic information system is a crucial element in managing academic data in higher education institutions. Universities require an efficient information system to manage student data, faculty, courses, and other academic administration. This study develops an SQLPage-based information system to provide a lightweight and user-friendly web-based solution. SQLPage enables the creation of web applications directly from a MySQL database without requiring complex programming. The research results show that this system can improve the efficiency of academic data management and ease of access to information for users

The development of e-learning platforms has transformed the landscape of education by providing flexible and accessible learning methods. However, security threats targeting web-based applications pose significant risks to the confidentiality, integrity, and availability of academic data. This research aims to analyze the security vulnerabilities of the ILMU2 e-learning website at UPN “Veteran” Jawa Timur using the Web Application Security Project Zed Attack Proxy (OWASP ZAP) methodology. The study applies a black-box testing approach to simulate attacks and identify potential weaknesses in the website's security mechanisms. Expected findings include the identification of vulnerabilities such as cross-site scripting (XSS), SQL injection, and security misconfigurations. The results are intended to provide insights for improving the security posture of the ILMU2 platform and contribute to the broader discourse on securing educational technology in higher education institutions.

Relational databases, an essential component in modern information systems, are vulnerable to various security threats, both internal such as abuse of access rights, and external such as SQL injection, malware, and hacking. Given these conditions, how can relevant mitigation strategies be implemented to protect data security in relational databases? This article aims to identify the main threats to relational database security and map out relevant mitigation strategies. The method used is a literature review of various recent scientific journals that discuss aspects of data security in the context of relational databases. The results of the review indicate that threats such as SQL injection can be overcome by strict input validation, abuse of access rights can be prevented through role-based access control (RBAC), malware attacks can be detected using an intrusion detection system (IDS), and hacking actions can be minimized through the implementation of data encryption. This study is expected to be a reference in designing effective security strategies to protect data in relational databases.

A database is a fundamental element in an information system that is used to manage and store data. Two commonly used database types are NoSQL (Not Only SQL) and SQL (Structured Query Language). SQL uses a structured relational model with a fixed schema, while NoSQL is more flexible with various storage models such as document, key-value, column-width, and graph. This research aims to conduct a literature study on the comparison of these two types of databases, including their advantages, disadvantages, and applicability in various information system scenarios. The study results show that the choice between SQL and NoSQL is highly dependent on the specific needs of the application, in terms of performance, scalability, and data complexity.

Databases play an essential role in modern information systems because they enable the efficient storage, management, and retrieval of structured data. This study focuses on the implementation of a simple database using two relational database management systems (RDBMS), namely MySQL and PostgreSQL. The research stages are carried out through requirements analysis, designing entity-relationship diagrams, implementing tables and their relationships, and testing the system to assess functionality. The case study used is student data recording, where both RDBMSs are tested through a series of basic CRUD (Create, Read, Update, Delete) operations. The results show that both MySQL and PostgreSQL are capable of carrying out these operations effectively while maintaining data integrity and consistency. However, PostgreSQL offers additional advantages due to its support for more complex data types, a better level of compliance with SQL standards, and advanced features that support the needs of large-scale application development. Conversely, MySQL remains superior in terms of ease of use and application to simpler needs, making it more practical for small projects or applications with standard workloads. Based on these findings, it can be concluded that both RDBMSs are equally suitable for use, but the ideal choice depends heavily on the context of the needs; PostgreSQL is more suitable for applications that demand high scalability and size, while MySQL remains relevant for lightweight and efficient implementations.

Ambarawa Regional General Hospital (RSUD) is a Public Service Agency Regional (BLUD) belonging to Semarang Regency which operates in the field of public health services. Ambarawa Regional Hospital is located at Jalan Kartini No. 101 Ambarawa. So far, inventory data processing. At the Ambarawa Regional General Hospital (RSUD) it is still processed manually, there are several problems. What often arises is not knowing the depreciation value of goods each month, not yet applying it database system and low inventory data security system. The author used 3 research methods for data collection in this research, namely observation, interviews and literature study. The observation method used by the author is by carry out direct practice on problems that occur. Interview conducted by the author with the employees concerned, while in the literature study the author looked for related literature with research and used as a theoretical basis. From the analysis and research results, it can be seen that the solution to the problem above is: create an Inventory Data Recording Information System that uses a programming language Microsoft Visual Basic 6.0 and Microsoft SQL Server 2000 database processing system. Procedures will consist of p5 main parts, namely inventory data collection, room data collection, inventory item placement transactions, inventory item mutation transactions and line method depreciation straight. This system is expected to increase the effectiveness of inventory data processing in hospitals Ambarawa Regional General Hospital (RSUD).