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Enhancing Inventory and Transaction Management with Integrated E-Commerce Solutions: A Case Study of Desasa Home Decor
Full text linkEsasa Home Decor is a store that specializes in selling various types of artificial flower home decorations. The use of information technology in data management is essential to ensure that inventory and transaction management are conducted swiftly and generate accurate reports. This system is integrated with the Shopee API to automatically retrieve product and transaction data. This integration allows for better monitoring of stock levels and transactions on the e-commerce platform, ensuring that the information remains up-to-date. The development method used in this study is Extreme Programming, which emphasizes close collaboration within the team and continuous testing to produce high-quality software. Data collection was conducted through interviews, analysis, and direct observation of the ongoing business processes at Esasa Home Decor. The result of this research is a management information system that facilitates store management and is integrated with the Shopee e-commerce platform. The User Acceptance Testing (UAT) yielded a score of 97.714%, indicating that the system is highly suitable for use. Additionally, the Black-Box testing concluded that the system functions as expected and according to plan. Thus, this system enhances the operational efficiency of Esasa Home Decor by streamlining inventory and transaction management while providing more accurate and timely reports.Desasa Home Decor is a store that specializes in selling various types of artificial flower home decorations. The utilization of information technology is essential in data management to ensure that inventory and transaction management are conducted swiftly and generate accurate reports. This system is already integrated with the Shopee API to obtain product and transaction data. The development method used in this study is Extreme Programming, with data collected through interviews, analysis, and observation. The result of this research is the Desasa Home Decor management information system, which is integrated with Shopee e-commerce. The User Acceptance Testing (UAT) yielded a score of 97.714%, indicating that the system is highly suitable for use, while Black-Box testing concluded that the system operates as expected and planned
Implementasi Tarpit Firewall untuk Optimasi Keamanan Jaringan dengan Metode NIST SP800-86 Pada Ruangan KP
No full textNetwork optimization is one of the important aspects that aims to improve the performance, efficiency and reliability of network systems and security on the network, but if the optimization is not carried out effectively it will pose a security threat to the network, one of the real threats is DdoS Attack, DdoS attack is a dangerous attack because this attack can paralyze the network server, Therefore, optimization needs to be carried out in the KP Room in order to avoid the threat of DdoS attacks, so the initial stage of this research will test the network to find out how optimal the network is in the KP room so that optimization is needed. The research method used is NSIT, which includes collection, examination, analysis, and reporting, the results after the research is carried out where, on the network in the kp room after testing at the examination stage and then by identifying the test results, it can be concluded that the network is not optimal enough against DdoS attacks and connection type attacks which, The optimization step taken is to apply a Tarpit firewall on the router. The implementation of Tarpit Firewall successfully overcomes DdoS attacks by slowing down incoming connections and stopping attacks, thereby improving network security from Port Scanning, DDoS, and Brute force attacks.Optimasi jaringan merupakan salah satu aspek penting yang bertujuan untuk meningkatkan kinerja, efisiensi dan keandalan sistem jaringan dan keamanan pada jaringan, namun jika optimasi tidak dilakukan secara efektif maka akan menimbulkan ancaman keamanan bagi jaringan, salah satu ancaman nyata adalah Serangan DdoS, serangan DdoS merupakan serangan berbahaya karena serangan ini dapat melumpuhkan server jaringan, Oleh karena itu, optimasi perlu dilakukan di Ruang KP agar terhindar dari ancaman serangan DdoS, sehingga tahap awal penelitian ini akan menguji jaringan untuk mengetahui seberapa optimal jaringan di ruang KP sehingga diperlukan optimalisasi. Metode penelitian yang digunakan adalah NSIT, yang meliputi pengumpulan, pemeriksaan, analisis, dan pelaporan, hasil setelah penelitian dilakukan dimana, pada jaringan di ruang kp setelah pengujian pada tahap pemeriksaan dan kemudian dengan mengidentifikasi hasil pengujian dapat disimpulkan bahwa jaringan tersebut tidak cukup optimal terhadap serangan DdoS dan serangan jenis koneksi yang, Langkah optimasi yang diambil adalah menerapkan firewall Tarpit pada router . Implementasi Tarpit Firewall berhasil mengatasi serangan Ddo S dengan memperlambat koneksi yang masuk dan menghentikan serangan , sehingga meningkatkan keamanan jaringan dari serangan Port Scanning , DDoS , dan Brute force
PENGARUH PEMANFAATAN TEKNOLOGI INFORMASI PADA PEDAGANG PASAR LAMA TANGERANG
No full textTechnological progress is reshaping traditional markets, bringing improvements in speed, convenience, and reach to day-to-day trading. Digital payment platforms such as QRIS and All Payment along with e-commerce channels allow merchants to process transactions more quickly and give customers flexible, cash-free options. Although these innovations promise greater operational efficiency, widespread uptake remains uneven. Two persistent hurdles are low digital literacy and anxieties over data security, issues that often breed resistance and mistrust among stallholders. Findings from surveys and in-depth interviews suggest that tailor-made education and hands-on training are pivotal in changing perceptions. By demonstrating practical advantages like simplified bookkeeping, real-time sales tracking, and broader customer access training sessions help traders see technology as an ally rather than a threat. Equally important is the coordinated support of local governments, market management bodies, and technology vendors. Their collaboration can produce policies that lower adoption costs, provide subsidies for devices, and establish on-site help desks to address technical problems swiftly. Such institutional backing both incentivizes merchants and accelerates the diffusion of digital tools throughout the market ecosystem. Furthermore, guaranteeing reliable internet connectivity and user-friendly interfaces reduces friction in daily use, reinforcing trader confidence. Early adopters already report smoother workflows, faster customer turnover, and better record-keeping accuracy. These outcomes highlight the need for a multifaceted strategy combining capacity-building, stakeholder engagement, and infrastructure enhancement to modernize traditional commerce while safeguarding its cultural vibrancy and social relevance.Teknologi saat ini sudah sangat berkembang dimana setiap orang sudah mulai menggunakan teknologi, salah satunya pada bisnis yang ada di pasar lama dimana teknologi sangat membantu dalam aktivitas perdagangan. Penggunaan teknologi memberikan berbagai manfaat yang dapat memudahkan para pedagang dalam menjalankan aktivitas perdagangan yang mereka lakukan. Teknologi juga bertujuan untuk meningkatkan efisiensi dan efektivitas operasional bagi para pedagang pasar lama. Misalnya dengan adanya sistem pembayaran digital (Qris, All Payment) dan platform e-commerce yang dapat mempermudah para pedagang dan juga pelanggan dalam melakukan transaksi dengan lebih cepat dan efisien. Namun terdapat hambatan seperti, kurangnya pemahaman teknologi dan ketidakpercayaan terhadap keamanan data yang ada dalam sebuah teknologi. Dimana hal ini membuat banyak pedagang masih tidak mau untuk menggunakan teknologi dalam aktivitas dagangannya. Melalui metode kuesioner dan wawancara, dapat ditemukan bahwa pendidikan dan pelatihan terarah dapat meningkatkan adopsi teknologi. Sehingga dengan pelatihan dapat meningkatkan pengetahuan dan pemahaman para pedagang mengenai adopsi teknologi dan manfaat utama yang dapat dihasilkan dalam penggunaan teknologi dalam aktivitas yang dilakukan pedagang. Pentingnya dukungan dari pihak terkait juga tidak bisa diabaikan, karena hal ini dapat memotivasi pedagang untuk lebih terbuka terhadap teknologi yang dapat mempermudah aktivitas perdagangan yang mereka lakukan. Dengan kolaborasi yang baik, adopsi teknologi bisa lebih cepat dan luas. Selain itu, kemudahan akses terhadap perangkat teknologi dan dukungan teknis yang berkelanjutan juga dapat membantu mengurangi ketidakpercayaan dan meningkatkan kepercayaan pedagang terhadap teknologi baru. Maka dari itu sudah banyak para pedagang di pasar lama sudah mulai mengunakan teknologi dan mereka juga sudah merasakan kemudahan dari penggunaan teknologi tersebut.
 
SISTEM INFORMASI MANAJEMEN KEUANGAN PAUDQU NURUL IZZAH MENGGUNAKAN METODE RAPID APLICCATION DEVELOPMENT (RAD) BERBASIS WEB
No full textThis study presents the design and development of a web-based Financial Management Information System (FMIS) for PAUDQU Nurul Izzah using the Rapid Application Development (RAD) methodology to replace error-prone and time-consuming manual processes. Through stakeholder interviews with administrators, accounting staff, and teachers, we identified essential functional requirements such as transaction entry, automated report generation, and role-based access controls and nonfunctional needs for performance, security, and user-friendliness. Based on these requirements, we created data models, user interface mockups, and workflow diagrams, then rapidly built and refined a prototype in successive iterations of demonstration and feedback until it satisfied predefined accuracy and usability criteria. Comprehensive testing including unit, integration, and user acceptance tests confirmed that the system reliably records financial transactions and generates income statements, balance sheets, and cash flow summaries without manual intervention. Initial evaluations show a 60 percent reduction in transaction processing time and a decrease in month-end reporting from days to hours, while built-in audit trails and access controls enhance accountability and data integrity. By delivering digital ledgers, real-time dashboards, and automated reporting, this RAD-driven FMIS not only streamlines financial workflows at PAUDQU Nurul Izzah but also establishes a scalable model for modernizing administrative operations in other early childhood education institutions.Penelitian ini bertujuan untuk merancang dan mengembangkan Sistem Informasi Manajemen Keuangan berbasis web pada PAUDQU Nurul Izzah menggunakan metode Rapid Application Development (RAD). Sistem ini dibangun untuk menggantikan pencatatan keuangan manual yang rawan kesalahan dan keterlambatan pelaporan. Pengembangan dilakukan secara iteratif melalui tahapan analisis kebutuhan, perancangan, pembuatan prototipe, dan pengujian sistem. Hasil penelitian menunjukkan bahwa sistem mampu mencatat pemasukan dan pengeluaran secara digital, menghasilkan laporan otomatis, serta meningkatkan efisiensi dan akuntabilitas pengelolaan keuangan di lingkungan PAUD
SIMULASI PERBANDINGAN MANAGEMENT BANDWITDH MENGGUNAKAN TEKNIK QUEUE TREE DAN PCQ
No full textThe IT services at PSP Pusri Building are equipped with adequate internet network facilities. However, the distribution of bandwidth across the network is uneven, which leads to bandwidth contention among users and consequently slows down internet connections. This issue arises due to the absence of specific upload and download limits for each room, which affects network stability. Managing upload and download speeds is crucial for efficient data transmission, and bandwidth management is needed to address this problem. This study employs an action research methodology, which includes the stages of Diagnosis, Action Planning, Action Taking, Evaluating, and Specifying Learning. The research focuses on improving network performance by implementing bandwidth management. The Per Connection Queue (PCQ) tree and queue techniques are applied to organize data flow based on priority, ensuring better distribution of bandwidth across all rooms. The results of simulations conducted during the bandwidth management application show significant improvement. The implementation effectively reduces the congestion issues in each room by providing an equal distribution of bandwidth. By using these management techniques, the IT services in the PSP Pusri Building can ensure a more stable and efficient network, improving the overall internet experience for users. This approach not only resolves existing bandwidth issues but also serves as a model for future network improvements. The study highlights the importance of careful bandwidth management in maintaining optimal network performance, especially in environments with multiple users and varying data demands.Gedung Layanan TI PSP Pusri memiliki fasilitas jaringan internet yang cukup memadai, namun pada jaringan tersebut pembagian bandwidth kurang teratur atau belum ada pemerataan bandwidth ke semua ruangan. Hal ini akan menyebabkan terjadinya perebutan antar pengguna dan menyebabkan koneksi internet menjadi lambat, karena tidak adanya batasan upload dan batasan download di setiap ruangan. Ketidakstabilan jaringan dalam hal kecepatan upload dan download sangat penting agar dapat memperlancar pengiriman data, maka diperlukan manajemen bandwidth untuk mengatasi masalah tersebut. Penelitian ini menggunakan metode action research dengan tahapan Diagnosis, Perencanaan Tindakan, Pengambilan Tindakan, Mengevaluasi, Menentukan Pembelajaran: Menganalisis hasil untuk perbaikan di masa yang akan datang. Dalam penerapan manajemen bandwidth digunakan teknik PCQ (Per Connection Queue) tree dan queue untuk mengatur aliran data berdasarkan prioritas. Berdasarkan hasil yang telah didapatkan dari simulasi penerapan manajemen bandwidth pada jaringan departemen IT service, sangat efektif untuk mengurangi masalah pada setiap ruangan dengan adanya pemerataan bandwidth in
Tongue Detection For Identification Of Syndrome Diagnosis In Heart Disease Using Convolutional Neural Network
Full text linkConvolutional Neural Network (CNN) which is one of the Deep Learning methods for Image identification and CNN models can identify images well but in this case it requires higher accuracy because the case is very crucial to determine the risk of heart disease. The initial stage in this study was the collection of tongue image data, 4836 training data and 1209 testing data. The image data used were the front, right side, left side of the tongue and under the tongue. The dataset was obtained from taking pictures using a smartphone camera centimeters above the object. The distribution of data in each class is shown in the following figure. The model from the two CNN algorithm experiments has accuracy performance. Based on the training results the model from the algorithm gets an accuracy value and Testing by identifying 20% of the total dataset as test data. The identification results are formed in a Confusion Matrix to then be poured into a classification report and obtain: train loss 0.301446, train accuracy 0.862696, test loss 0.314132 and test accuracy 0.850290 so that from the results of the tongue data test it can be concluded that the accuracy value is quite good, above 80%
Recent Developments in the Artificial Intelligence of Things (AIoT) in Assistive Technology: A Systematic Literature Review (2020–2025)
Full text linkThis systematic literature review explores the application of Artificial Intelligence of Things (AIoT) in Assistive Technology designed to support individuals with disabilities. Out of an initial 267 articles, 38 studies were selected based on inclusion criteria and quality assessment. The review identifies the dominant machine learning models used in AIoT-based assistive technology solutions. Most research focuses on visual impairments, revealing a significant gap in addressing cognitive, psychological, and degenerative disabilities. Various IoT devices such as wearables, sensors, exoskeletons, and smart wheelchairs are employed to provide adaptive, real-time, and personalized assistance. Key methodological limitations include reliance on simulated data, small sample sizes, and lack of field validation. Technical challenges such as device interoperability and accessibility also hinder implementation. These findings highlight the need for more inclusive research involving direct participation of end-users to develop effective, accessible, and scalable AIoT-based assistive technologies that enhance the quality of life for people with disabilities
Optimasi Hyperparameter Convolutional Neural Network untuk Klasifikasi Jenis Penyakit Daun Jagung menggunakan CLAHE
No full textCorn plays an important role as one of the main food sources in Indonesia and around the world. Diseases in corn plants are often visible through their leaves. However, problems arise when farmers have difficulty detecting diseases that attack corn plants, making it difficult to take appropriate action to control them. Diseases in corn plants can lead to reduced photosynthesis, disrupt agricultural productivity, and cause financial losses for farmers. Therefore, a digital approach that can detect various types of diseases in corn plants is highly needed. In recent years, the emergence of machine learning algorithms has provided support systems for classifying corn leaf diseases. This research aims to classify types of corn leaf diseases using the Optimization of Convolutional Neural Network (CNN) Method for Classifying Types of Corn Leaf Diseases Using Contrast Limited Adaptive Histogram Equalization (CLAHE). The research stages include data collection, image enhancement with CLAHE, data augmentation, data preprocessing, classification, and evaluation. The Optimization of the CNN Method for Classifying Types of Corn Leaf Diseases Using CLAHE resulted in an accuracy of 94%, indicating that this experiment is capable of classifying corn leaf diseases effectively.Jagung memiliki peran penting sebagai salah satu sumber pangan utama di Indonesia dan di seluruh Dunia. Penyakit pada tanaman jagung sering kali dapat terlihat melalui daunnya. Namun, masalah muncul ketika petani kesulitan dalam mendeteksi penyakit yang menyerang tanaman jagung, sehingga sulit untuk mengambil tindakan yang tepat untuk mengendalikannya. Penyakit pada tanaman jagung dapat mengakibatkan penurunan fotosintesis, mengganggu produktivitas pertanian, dan menyebabkan kerugian finansial bagi petani. Oleh karena itu, pendekatan digital yang dapat mendeteksi berbagai jenis penyakit pada tanaman jagung sangat diperlukan. Beberapa tahun terakhir kemunculan algoritma pembelajaran mesin menyediakan sistem dukungan untuk klasifikasi penyakit daun jagung. Penelitian ini bertujuan untuk melakukan klasifikasi jenis penyakit daun jagung menggunakan Optimasi Metode Convolutional Neural Network (CNN) untuk Klasifikasi Jenis Penyakit Daun Jagung Menggunakan Contrast Limited Adaptive Histogram Equalization (CLAHE). Tahapan penelitian berupa pengumpulan data, perbaikan citra dengan CLAHE, augmentasi data, data preprocessing, klasifikasi, dan evaluasi. Optimasi Metode CNN Untuk Klasifikasi Jenis Penyakit Daun Jagung Menggunakan CLAHE menghasilkan akurasi sebesar 94% yang menujukkan bahwa eksperimen ini mampu melakukan klasifikasi penyakit dauh jagung dengan bai
Rebuilding Public Trust in Islamic Banking Through the Utilization of Technology: Conceptual Review and Strategies
Full text linkPublic trust in Islamic banking has been a significant challenge in recent years. This is influenced by several factors such as lack of technology literature, technology distribution, cybersecurity, regulatory frameworks, customer awareness, and financial inclusion. This research aims to highlight the technology in restoring public trust in Islamic banking and present practical strategies for digital Sharia banks. This research aims to identify public trust in Islamic banking in Indonesia through technology. This research design is descriptive qualitative and the type of data used is secondary data. Sources and data were obtained from OJK websites, books, the internet, social media, journals, and other relevant digital format. Data is processed using the Python programming language. The results of this research indicate that digital literacy for Bank Hijra is less well-known among the public. From the mobile banking application, the rating of the sample banks shows a number above 4. User reviews show that the use of these applications has not yet achieved maximum customer satisfaction, as there are still complaints about data security concerns. It concluded that customer trust in digital Sharia banks has indeed increased, but there is still a need to improve data security and digital literacy, and user experience for the public
Enhancing Sundanese News Articles Classification: A Comparative Study of Models and Feature Extraction Techniques
Full text linkThis paper presents a comprehensive investigation into the classification of Sundanese news articles, focusing on the evaluation of various classification models and feature extraction methods. Using a dataset obtained from Sundanese news websites, this study conducts a systematic comparison of Naive Bayes and Logistic Regression classifiers combined with TF-IDF and Bag-of-Words feature extraction methods. The research process involves critical steps such as data preprocessing, model training, hyperparameter optimization, and performance assessment based on standard metrics, including accuracy, precision, recall, and F1-score. Results demonstrate high accuracy across all combinations, with the Logistic Regression model using Bag-of-Words feature extraction achieving the highest accuracy of 98.20%. Beyond model evaluation, the research delves into qualitative data analysis. Word clouds and TF-IDF weighting are employed to uncover prominent themes and topics within the news articles, highlighting recurring patterns in the Sundanese language. The study identifies key challenges, including the scarcity of annotated datasets for low-resource languages like Sundanese and the limitations of traditional models in capturing complex linguistic structures. Future opportunities are highlighted, such as leveraging deep learning models, including transformers, to enhance classification performance and address current limitations. Additionally, ensemble methods and domain-specific adaptations could further improve accuracy. Overall, this research contributes to advancing Sundanese language processing and provides a roadmap for future innovations in text classification and natural language processing applications