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Urban plant care is increasingly important for sustainable living, but many users face inconsistent watering, insufficient care knowledge, unsuitable plant selection and delayed disease recognition. This study presents Easy Grow Plants, an integrated web and Internet of Things (IoT) ecosystem that connects plant care guidance, soil-moisture monitoring, automated watering, plant recommendation, image-based plant health assistance, marketplace functions, community interaction and plant exchange. The prototype was implemented using a React frontend, Django REST backend, SQLite database and an Arduino UNO R4 WiFi smart pot with a soil moisture sensor, relay module and DC water pump. Functional, interface, API, IoT connectivity, sensor calibration, watering control and LAN deployment tests were conducted. The results show that the core modules operated together as an integrated academic prototype. The system demonstrates a practical foundation for smart urban gardening, although cloud deployment, multi-device testing and stronger AI validation remain future improvements

This research is motivated by the problems in manual attendance systems at schools, which remain vulnerable to fraud, time-consuming, and inefficient. The expected solution is to develop an automated attendance system based on face recognition that can operate in realtime with high accuracy. The research object is vocational high school students, with the applied method implementing the YOLO v10 algorithm for face detection, followed by the face_recognition library for identification. The instruments used include an Imou CCTV camera as the input device, a mid-range laptop as the hardware platform, and Python with SQLite as the software environment for data processing and attendance storage. The results show that the developed system achieved an average face detection accuracy of 96% under normal lighting and 91% under low lighting, with an average processing speed of 27 FPS. The implementation of an anti-duplication feature also ensured data validity by allowing each student to be recorded only once per day. In conclusion, the use of YOLO v10 in face-based attendance proved to be effective, efficient, and capable of reducing fraud. The implication of this study is that the system can be applied in both Islamic boarding schools and general schools as a modernization of attendance systems, with a recommendation for further development through web-based application and cloud database integration.

Manual management of customer receivables in manufacturing companies often leads to inefficiencies, including slow analysis processes, difficulty in monitoring outstanding balances, and limited ability to track payment trends comprehensively. This study designed a Business Intelligence Dashboard using Microsoft Power BI to address these issues at PT. XX Industry, employing a Software Development Life Cycle (SDLC) approach consisting of four stages: Planning, Analysis, Design, and Implementation. During the design phase, a data warehouse was built using a star schema model in SQL Server Management Studio, followed by an Extract, Transform, Load (ETL) process to ensure data accuracy and consistency prior to integration into Power BI. Five Key Performance Indicators (KPIs) were established collaboratively with company management through a series of online discussions, comprising Total Invoice, Total Payment, Total Receivables, Payment Rate, and Average Payment Time, all implemented using DAX expressions. The resulting dashboard features monthly trend visualizations, customer-based receivables distribution, and interactive filter capabilities. System testing confirmed that all components functioned correctly, while ETL validation verified consistency between processed and source data. User Acceptance Testing (UAT) conducted by management yielded an average score of 4.7 out of 5, reflecting a very high level of user acceptance. Overall, this dashboard proved effective in improving receivables monitoring efficiency and supporting faster, data-driven decision-making.

The increasing use of web applications in various sectors has made security a major concern due to the high risk of attacks targeting the application layer. This study aims to analyze the effectiveness of the F5 Web Application Firewall (F5 WAF) in mitigating vulnerabilities in the OWASP Juice Shop application. Testing was conducted using 10 attack scenarios including SQL Injection, Cross-Site Scripting (XSS), Insecure Direct Object Reference (IDOR), and Information Disclosure before and after F5 WAF implementation. The test results showed that all tested attack scenarios were successfully mitigated after F5 WAF implementation. These findings indicate that the F5 WAF is able to provide effective protection against various vulnerabilities at the application layer and improve the security of web applications in the test environment used.

Penelitian ini bertujuan mengembangkan aplikasi simulasi matematika dasar berbasis Android sebagai media pembelajaran interaktif bagi siswa sekolah dasar. Penelitian dilatarbelakangi oleh rendahnya keterlibatan siswa dan kesulitan siswa dalam memahami konsep aritmatika dasar melalui metode pembelajaran konvensional. Aplikasi dirancang dengan mengintegrasikan modul latihan, permainan edukatif dengan tingkat kesulitan bertahap, serta sistem penghargaan berbasis pencapaian untuk meningkatkan motivasi dan minat belajar siswa. Proses pengembangan menggunakan metode Waterfall yang meliputi tahapan analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan penerapan aplikasi. Pengembangan aplikasi dilakukan menggunakan Android Studio dan bahasa pemrograman Java, sedangkan SQLite digunakan sebagai media penyimpanan data lokal. Validasi fungsional dilakukan melalui Black Box Testing untuk memastikan seluruh fitur aplikasi berjalan sesuai kebutuhan sistem. Siswa sekolah dasar dilibatkan sebagai responden untuk mengevaluasi tingkat kegunaan dan kesesuaian aplikasi sebagai media pembelajaran. Hasil penelitian menunjukkan bahwa aplikasi dapat berfungsi dengan baik pada perangkat Android serta memberikan kontribusi positif dalam meningkatkan pemahaman aritmatika dan motivasi belajar siswa.

Penelitian ini bertujuan: (1) mengembangkan sistem input nilai kinerja karyawan agar lebih akurat dan efisien; (2) merancang Entity Relationship Diagram (ERD) dan struktur basis data untuk mendukung pengolahan data karyawan; serta (3) membangun backend sistem dengan autentikasi dan otorisasi berbasis peran. Ruang lingkup mencakup pengelolaan data kinerja individu yang sebelumnya dilakukan secara manual menggunakan spreadsheet dan rentan terhadap kesalahan input. Metode yang digunakan meliputi pengumpulan data kinerja kuartal kedua, perancangan ERD, serta pengembangan backend web application IHSAN POS menggunakan JavaScript dan framework Express yang terintegrasi dengan PostgreSQL, DBeaver, dan Prisma ORM. Implementasi keamanan dilakukan melalui middleware validasi input, sanitasi data, perlindungan dari serangan SQL injection dan XSS, serta pengelolaan sesi menggunakan enkripsi JWT (JSON Web Token). Sistem yang dikembangkan mencakup enam fitur terintegrasi: Halaman Login, Halaman Profil, Formulir Edit Profil, Halaman Nilai Kinerja Individu dan Kontrak Kerja, Formulir Kontrak Kerja, serta Pratinjau Surat Kontrak Kerja. Hasil pengembangan menunjukkan bahwa sistem backend yang dibangun mampu meningkatkan efisiensi proses evaluasi kinerja, memperbaiki integrasi data, serta mempermudah validasi dan pelaporan secara digital dan terstruktur. Kesimpulannya, pengembangan sistem ini memberikan kontribusi signifikan dalam peningkatan efisiensi, akurasi, dan transparansi evaluasi kinerja karyawan, serta mendukung pengambilan keputusan strategis terkait insentif dan pengembangan karier pegawai.

Pemanfaatan aplikasi berbasis web yang semakin meluas di berbagai sektor menyebabkan meningkatnya risiko terhadap ancaman siber, termasuk serangan phising, DDoS, injeksi SQL, XSS, serta intrusi. Berbagai metode deteksi tradisional yang bersifat statis sering kali tidak mampu mengidentifikasi pola serangan baru yang bersifat dinamis. Untuk mengatasi keterbatasan tersebut, machine learning muncul sebagai pendekatan yang lebih adaptif karena mampu mempelajari pola perilaku, mendeteksi anomali, dan melakukan deteksi ancaman secara otomatis. Penelitian ini melakukan tijauan sistematis literatur (Systematic Literature Review/SLR) untuk meneliti penggunaan machine learning dalam mengingkatkan keamanan aplikasi web dan mengevaluasi performa beberapa algoritma yang digunakan. SLR dilaksanakan dengan menggunakan kerangka PICOC, yang mencakup populasi, intervensi, perbandingan, hasil, konteks. Hasil analisis menunjukkan bahwa machine learning digunakan untuk berbagai aspek keamanan web, seperti deteksi phising, penentuan URL berbahaya, pengurangan dampak serangan DDoS, serta identifikasi intrusi jaringan. Algoritma seperti Random Forest, XGBoost, dan SVM terbukti memiliki kinerja yang stabil dengan tingkat akurasi yang tinggi. Selain itu, teknik pendukung seperti ADASYN, feature selection, dan metode berbasis pemrosesan bahasa alami turut meningkatkan efektivitas model. Secara keseluruhan, hasil penelitian ini menegaskan bahwa machine learning dapat mempercepat dan meningkatkan ketepatan deteksi ancaman serta memberikan adaptasi terhadap pola serangan yang terus berubah, sehingga menjadi komponen penting dalam memperkuat keamanan aplikasi web.

Website security is an important aspect of designing a website and managing web systems. However, many developers still pay little attention to security aspects from the early stages of development. In fact, the website that has been built will be the target of attacks by hackers at any time. Therefore, this research aims to analyze the vulnerability of the SMAN 1 Banjar Agung website based on the OWASP Top 10 standard. The research method was conducted through vulnerability assessment using OWASP ZAP tools with the stages of spidering, passive scanning, and active scanning. This test allows identification of vulnerabilities such as SQL Injection, Cross-Site Scripting (XSS), and security configuration weaknesses. The scan results showed eight vulnerabilities, consisting of two medium, three low, and three informational vulnerabilities. Although the risk level is low, the website still requires mitigation through the application of security headers, dependency updates, and removal of sensitive information to make the system more secure and stable.

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.

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 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.

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).    

This study aims to analyze security vulnerabilities and mitigation on the crowdo.co.id website using the OWASP Zed Attack Proxy (ZAP) tool, which is a web application security testing tool. High-level security attacks have increasingly risen alongside the advancement of information technology, making vulnerability testing crucial to ensure the integrity and security of information systems. This research involved scanning the crowdo.co.id website to identify various vulnerabilities, including those listed in the OWASP Top 10. The research process encompassed active and passive scanning, data analysis from the scans, and the formulation of mitigation strategies for each identified vulnerability. The findings revealed that the website had 14 detected vulnerabilities, consisting of 1 high-priority vulnerability, 3 medium-priority vulnerabilities, 7 low-priority vulnerabilities, and 3 additional informational alerts. The security dimensions tested included potential XSS attacks, SQL Injection, and other deficiencies that could jeopardize user data. Based on these results, recommended mitigations include code improvements, enhanced security configurations, and the implementation of additional preventive measures. This study concludes that while the website’s security is in the medium category, further improvements are necessary to reduce vulnerability risks. Through this approach, the study provides significant contributions to enhancing web application security.

During this time, the development of technology has progressed rapidly.  In this sense, many companies have followed this technological development and introduced it into the collection of inventory data of assets, goods, and their financial reports. To obtain accurate and precise data, an inventory data collection system is required. Manual accounting calculations mean that Depot Kayu Kusen Laris III often records inventory incorrectly, which affects the resulting financial reports. Therefore, this study aims to develop an inventory information system that will support accurate data collection at Kayu Kusen Laris III Depot. The conclusion of this study is that the inventory data information system is designed using Access and SQL database.