Heart disease can be suffered by anyone regardless of age and gender. Heart disease can be caused by many things, such as unhealthy lifestyles (smoking), as well as heredity. Low self-awareness of someone with weak heart disease to monitor their heart health regularly. To diagnose weak heart disease, this system uses the Certainy Factor method. With this method, patients can find out the results of the decision whether the patient is at risk of developing weak heart disease or heart health conditions in normal circumstances. This method can provide comparative results (and decision results) of several parameters (tested), one of which is the heart rate parameter. Therefore, the authors build a mobile application system with the concept of service and monitoring of weak heart disease named "iHeart". With this application, patients can monitor and detect weak heart disease and use various features (features) contained in the application. One of the iHeart application facilities is the GUI Chart for heart rate monitoring. This application can also accommodate the patient's heart rate history data into a database as a data storage medium. This application system uses IoT technology, which makes it easy for users or patients and practitioners to see the results of a heartbeat to find out whether a patient has a weak heart or not, in real-time via a smartphone (smartphone) without interfering with patient mobility.

Ensuring secure and private digital communication is crucial due to increasing threats like data breaches and unauthorized access. We propose a secure end-to-end encrypted chat application using Diffie–Hellman Key Exchange and AES-256 within a microservice architecture. Our system leverages Diffie–Hellman for secure key exchange and AES-256 for efficient symmetric encryption. The microservice architecture ensures scalability and modularity, reducing single points of failure. Tests confirm secure communication with low latency and high throughput. The key exchange process generates an identical shared key in real-time without transmitting a private key, ensuring encryption integrity. Messages are encrypted before transmission and can only be decrypted by the intended users, maintaining confidentiality. This approach offers a robust and scalable solution for secure messaging systems.

Ikan merupakan kelas vertebrata yang dikategorikan sebagai hewan ektotermik, artinya suhu tubuhnya berubah-ubah tergantung suhu lingkungan, hal tersebut berpengaruh terhadap tingkah laku makan ikan, saat ini sudah banyak sistem otomatisasi pakan ikan, namun sistem yang ada belum memperhatikan kondisi lingkungan, faktor yang sangat signifikan berpengaruh terhadap tingkah laku makan ikan adalah suhu air, dari permasalahan tersebut, peneliti membuat sistem otomatisasi pemberi pakan ikan lele berdasarkan suhu air menggunakan logika fuzzy sugeno. Sistem yang dibuat menggunakan metode pengembangan sistem prototype dan logika fuzzy sugeno, logika fuzzy sugeno digunakan untuk membuat aturan banyaknya pakan yang keluar berdasarkan parameter suhu air. variabel input suhu air memiliki rentang antara 0-36 oC dan variabel output jumlah pakan memiliki rentang 0-100%, hasil pengujian pada aplikasi matlab menunjukan akurasi yang tinggi, dari pengujian motor servo, didapat keluaran pakan 20 gram setiap satu kali putaran dalam waktu satu detik, pada pengujian sensor suhu air didapat selisih rata-rata 0.45 oC dengan rata-rata error 1,8%. Pada pengujian penjadwalan didapat selisih pada waktu pagi, siang dan sore hari yaitu 5 detik. Pengujian lapangan dilakukan pada kolam berukuran 4x3 meter dengan bobot ikan 600 kg, dari hasil perhitungan, kebutuhan pakan dalam satu hari yaitu 18 kg, maka sistem harus melakukan 900 kali putaran dengan waktu 15 menit untuk memenuhi kebutuhan pakan ikan dalam kolam tersebut.

Pajak Penghasilan Pasal 21 (PPh 21) adalah pajak atas penghasilan berupa gaji, upah, honorarium, tunjangan, dan pembayaran lain. Pajak diterima oleh pribadi dalam negeri dalam bentuk apa pun yang berkaitan dengan pekerjaan atau jabatan, jasa, dan kegiatan yang dilakukan oleh orang tersebut. Perhitungan pajak masih dilakukan secara manual, yang merupakan masalah yang sering muncul. Untuk mengatasi masalah ini, aplikasi PPH 21 dirancang untuk membantu pegawai dan perusahaan dalam perhitungan dan pembayaran PPH 21. Fitur utama dari aplikasi ini antara lain yaitu penghitungan PPH 21 dan generate laporan PPH 21 secara otomatis, sehingga memudahkan pengguna dalam menyediakan PPH 21 yang harus dibayarkan oleh pegawai. Penelitian ini menggunakan metode extreme programming dalam pengembangan sistemnya. Hasil dari pengujian menunjukan keberhasilan sistem pada setiap input serta ketepatan perhitungan PPH 21 dengan kondisi yang berbeda. Pada pengujian non fungsional menunjukan keberhasilan pada saat sistem digunakan pada beberapa perangkat yang berbeda dengan hasil sistem menyesuaikan ukuran layar sesuai perangkat yang digunakan (responsif).

In the era of rapid digital transformation, efficient network bandwidth allocation is vital for ensuring high-quality service and seamless network operations, particularly in environments with dynamic traffic patterns. This study proposes a novel approach to optimize bandwidth allocation using a Backpropagation Neural Network (BPNN) algorithm. The research utilizes a dataset sourced from Kaggle that has been modified to focus on prioritization during resource allocation and employs a preprocessing pipeline for consistency across network parameters. The BPNN model is trained with normalized data and evaluated using metrics such as Mean Squared Error (MSE) and R² score. The results, with an MSE of 0.1637 and an R² score of 0.9920, demonstrate high accuracy and minimal error in predicting bandwidth allocation. Furthermore, training and validation loss trends confirm the model’s convergence and effectiveness in real-time applications. The study underscores the integration of machine learning with network optimization principles, offering a robust framework for dynamic bandwidth management and resource-efficient network operations.

Key Performance Indicators (KPIs) play a crucial role in systematically evaluating employee performance. This study integrates the Simple Additive Weighting (SAW) method with Design Science Research (DSR) to develop and validate a web-based KPI assessment system for IT Support staff. This system categorizes performance into three key areas: supervisor evaluation, routine tasks, and request-based tasks. SAW is chosen due to its effectiveness in multi-criteria decision-making and the objective ranking of employees. This research presents a scalable and practical solution for performance management through a structured web-based application. A simulation utilizing Bootstrap 5.1 incorporates real-time monitoring, ticket tracking, and KPI dashboards, enhancing data visualization and reporting. The results indicate that the proposed system enhances transparency, minimizes evaluation bias, and supports objective, data-driven decision-making. By integrating SAW within a structured decision support system, this approach fosters standardized performance assessments, ensuring fairer and more consistent employee evaluations. Future work should focus on real-world implementation and empirical validation.