Water is an essential need for human life, especially in hospitals which require a constant supply of clean water. Dr. Gunawan Mangunkusumo Regional Public Hospital, Semarang Regency, is facing problems in managing the water reservoir due to a lack of monitoring and an automatic filling system. This leads to water wastage and inconvenience.
This article discusses the design of a water level detection device prototype based on the Wemos D1 Mini microcontroller to overcome this problem.3 The system utilizes the HC-SR04 ultrasonic sensor to measure water level and display the information on an LCD and web server. The microcontroller controls the water pump automatically based on the detected water level, which is categorized into three levels: LOW, MEDIUM, and HIGH.
Test results show that the system can measure water levels accurately and control the water pump effectively.This prototype is expected to assist Dr. Gunawan Mangunkusumo Regional Public Hospital in improving water management efficiency, ensuring a sustainable supply of clean water, and reducing the workload of staff

Guava Komputer adalah toko yang menyediakan berbagai produk komputer dan laptop, termasuk laptop, desktop, aksesori, perangkat keras, dan perangkat lunak dari merek-merek terkemuka. Namun, dalam proses bisnisnya, toko ini menghadapi masalah dimana pelanggan sering kesulitan memilih laptop yang sesuai dengan kebutuhan mereka, akibat banyaknya tawaran yang diberikan oleh pegawai toko. Selain itu, pegawai juga merasa kesulitan saat melayani banyak pengunjung. Untuk mengatasi masalah ini, diterapkan sistem pendukung keputusan berbasis web menggunakan metode Analytical Hierarchy Process (AHP), yang dikembangkan dengan bahasa pemrograman PHP dan basis data MySQL. Metode AHP membantu dalam menentukan urutan alternatif dan memilih alternatif terbaik berdasarkan kriteria yang ditetapkan. Hasil penelitian ini menunjukkan bahwa sistem ini efektif membantu pelanggan menemukan laptop yang sesuai dengan kebutuhan mereka, dengan nilai tertinggi yang disarankan. Sistem ini diuji dengan skor validitas 4,63 (sangat baik) dan efektivitas 90% (sangat efektif), serta telah berhasil diuji oleh penguji internal dan eksternal, menunjukkan bahwa sistem ini bekerja sesuai harapan dan memberikan informasi yang valid dan efektif.

This research focuses on optimizing the speed of Big Data processing using Artificial Intelligence (AI) in healthcare applications. The study integrates Random Forest (RF) and Deep Learning (DL) algorithms with cloud-based computing systems to improve data processing efficiency. The dataset includes both structured data, such as Electronic Health Records (EHR), and unstructured data, like medical images. The results show that RF performs better with structured data, achieving a lower Mean Squared Error (MSE) and higher R-squared (R²) than traditional methods. Meanwhile, DL achieves superior accuracy and Area Under the Curve (AUC) in processing unstructured data. By utilizing the distributed computing power of Spark on a cloud platform, the processing speed was significantly enhanced, as demonstrated by a statistically significant reduction in processing time (p < 0.05) observed through a t-test analysis comparing Spark-based computing with traditional methods. Despite these improvements, challenges such as data privacy and infrastructure costs remain. Despite these improvements, challenges such as data privacy and infrastructure costs remain. This research provides a robust framework for real-time healthcare data analysis, highlighting its potential to improve decision-making processes and patient outcomes in medical services.

This research focuses on optimizing the speed of Big Data processing using Artificial Intelligence (AI) in healthcare applications. The study integrates Random Forest (RF) and Deep Learning (DL) algorithms with cloud-based computing systems to improve data processing efficiency. The dataset includes both structured data, such as Electronic Health Records (EHR), and unstructured data, like medical images. The results show that RF performs better with structured data, achieving a lower Mean Squared Error (MSE) and higher R-squared (R²) compared to traditional methods. Meanwhile, DL achieves superior accuracy and Area Under the Curve (AUC) in processing unstructured data. By utilizing the distributed computing power of Spark on a cloud platform, the processing speed was significantly enhanced, as demonstrated by a statistically significant reduction in processing time (p < 0.05) observed through a t-test analysis comparing Spark-based computing with traditional methods. Despite these improvements, challenges such as data privacy and infrastructure costs remain. Despite these improvements, challenges such as data privacy and infrastructure costs remain. This research provides a robust framework for real-time healthcare data analysis, highlighting its potential to improve decision-making processes and patient outcomes in medical services.

Money is a tool used to carry out buying and selling transactions and has been used by all humans in every corner of the world. This definitely makes money a basic commodity for everyone, even for people with disabilities such as the blind. The blind's limitations in seeing are a problem in terms of communication so they only rely on their sense of touch and hearing. The weakness of the blind in seeing and identifying money can cause money to be exchanged, taken wrongly, or even deceived by counterfeit money when buying and selling. Referring to this, it is necessary to have tools that can make it easier for the blind to identify the authenticity of money and the nominal value of money. The aim of this research is to design a tool that can be used to detect the authenticity of the nominal value of Rupiah banknotes. This tool uses a TCS3200-DB color sensor to detect the color of banknotes, then the microcontroller converts it into RGB data and outputs it in the form of sound output.and an ultraviolet sensor to detect the authenticity of money.The result of this research is that the system can recognize the authenticity and nominal value of moneypaper, especially rupiah. This makes it easier for users, especially the visually impaired, to carry out buying and selling transactions so they don't make mistakesto give or receive money.

The development of increasingly sophisticated pharmaceutical industry technology requires researchers to develop technology in the pharmaceutical industry that can help employees carry out their duties. As we know, technology is very helpful in providing job data in industry. Information technology can improve the quality of work in industry. One of them is about monitoring temperature and humidity in the non-sterile drug production room. This temperature and humidity is monitored by the QA ( Quality Assurance )/Quality Assurance department, which is used to see whether the temperature and humidity of the non-sterile drug production room are well conditioned.Based on the existing problems, it is necessary to have an intelligent system that can monitor temperature and humidity precisely and periodically. One of them is creating an Internet of Things (IoT) Implementation tool for Simulating Temperature and Humidity in a Non-Sterile Medicine Production Room Using an Arduino and Web Based Temperature Sensor ( LM35 ) and Humidity Sensor ( DHT 22 ). This tool will periodically detect the temperature and humidity in each non-sterile drug production room. If the temperature exceeds the maximum limit in the non-sterile drug production room, the fan will turn on to release the hot air inside. All the data that has been collected will be processed by the Arduino Uno R3 Microcontroller and will be displayed on the website as an interface . For early detection, a DC Fan appears on the website that rotates if the temperature exceeds the maximum limit. Data transmission uses ESP8266 as a wireless module .

Home is an important place for most people, where they need to keep it safe and comfortable from outside interference. Therefore, there is a need for a security system that is able to protect against these disturbances. In this study, fingerprints were used to secure the door of the house, where in the process only the registered fingerprint was allowed to open the door. In table 1 it turns out that wet, wrinkled and peeling fingerprints can still be used and read by the sensor so that concerns that fingerprints cannot be used are refuted. In table 1 it is also proven that the process of opening the door can be done with an Arduino and a fingerprint sensor

IoT technology is useful for chicken farming to control the condition of the farm concerning some problems such as odour, temperature fluctuations and feeding time system. This study used MQ135 to detect ammonia odour level, DHT11 to check room temperature, and RTC3231 to regulate feeding time. The data obtained from the sensor was sent by wemos to the fire base and MySQL to be read on android so that it can be monitored directly by the breeder. When the ammonia level is above normal it will turn on the odour fan. If  DHT11 reaches the value above 300C, it will turn on the cooling fan, and turn on the heating light when the temperature is below 250C. As RTC3231 sets the time at 07.00 and 14.00, the chicken feeder will automatically open to feed the chickens according to the time set. Table 1 and 2 show that the experiment obtained a value of 100% working well. This study succeeded in monitoring environmental conditions through Android and executing automatic feeding at the predetermined time. Thus, it can be concluded that the use of IoT technology for monitoring and feeding system automation  in chicken farms is highly recommended.

The special component of malicious software analysis is advanced malicious software analysis which implicates interested the main framework of malicious software that can be executed after executing it and aggressive malicious software investigation depend on inquisitive of the practice of malicious software after running it in a composed habitat. Advanced malicious software analysis is usually performed by contemporary anti-malicious software operating systems using signature-based analysis.
The purpose of this research is to propose also decide a DNN for the progressive identification of portable files to study the features of portable executable malicious software to minimize the occurrence of distorted likeness when aware of advanced malicious software. The model proposed in this study is a NN with a Dropout model contrary to a resolution tree model to examine how well it performs in detecting real malicious PE files. Setup-skeptic methods are used to extract features from files. The dataset is used to train the proposed approach and measure outcomes by alternative common malicious software datasets.
The results from this study illustrate that the use of simple DNNs to study PE vector elements is not only efficient but more fewer system comprehensive than the traditional interested disclosure approach. The model proposed in this study achieves an A-UC of ninety-nine point eight with ninety accurate specifics at one percent inaccurate specific on the R-OC curve. For shows that this model has the potential to complement or replace conventional anti-malicious software operating systems so for future research, it is proposed to implement this model practically.

During Covid 19 the learning process experienced very severe obstacles, one of the 03semarang Elementary School and Elementary School 01 Semarang. In this study the Android application was used to support the dance learning system where students had to learn their own dance arts at home using the Android application. From the interviews conducted as many as 66.3 % like learning with mobile phones and 72.1 % understand the theory in the Android application so that when learning with mobile phones can easily understand. But for learning the practice of dance 54.7 % does not understand it. This may be the video displayed is not suitable for elementary students so you need a suitable learning video for learning that requires movement.