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The advancement of information technology has had a significant impact across various sectors, including healthcare. The digitalization of healthcare services has become a solution to improve efficiency, effectiveness, and accessibility for the public. Puskesmas Selindung still uses a manual patient registration system, which leads to several issues such as long queues, extended waiting times, and the risk of lost or damaged patient records. Based on visit data, the number of patients coming to Puskesmas Selindung has increased each year. Therefore, a digital queue system is needed to optimize the patient registration process. This research aims to analyze and design an Android-based patient registration queue application to improve service efficiency at Puskesmas Selindung. The research methods include system requirements analysis, user interface design, and the development of core features to support the online patient registration process. The implementation of this application is expected to reduce long queues, speed up administrative processes, and make it easier for patients to access healthcare services more effectively and accurately. With this Android-based system, the quality of healthcare services at Puskesmas Selindung is expected to improve significantly.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring.

The election of the OSIS chairman at SMK Al-Ikhlas Losari often influences subjectivity, so a goal-oriented system is needed to select the best candidate. This study applies the WASPAS method in a Decision Support System to broadcast OSIS chairman candidates based on criteria such as attendance, integrity, academic achievement, and health. Data were collected through observation, interviews, and literature studies, then processed using Microsoft Excel. The results of the WASPAS calculation yield a Qi preference value, which determines the ranking of candidates transparently. This system reduces subjectivity, increases efficiency, and ensures the selection of competent leaders, supporting the OSIS vision.

Indoor air quality plays a vital role in public health, especially since people spend about 90% of their time indoors. Poor indoor air quality, often caused by chemical, physical, and biological pollutants, can severely impact health, comfort, and productivity. To tackle this issue, a robust air quality monitoring and control system was designed, featuring an ESP32 microcontroller paired with sensors such as the GP2Y1010AU0F dust sensor, MQ-7 carbon monoxide sensor, and MQ-2 smoke sensor, along with a fan to enhance air circulation. This system is capable of detecting air quality issues and taking corrective action. The ESP32 module, integrated with the Internet of Things (IoT) technology, enables real-time transmission of sensor data to a web server for continuous monitoring and prompt response. Researchers have made significant progress in creating an effective, system-based solution to improve and maintain indoor air quality

This paper presents the design and implementation of an automatic Virgin Coconut Oil (VCO) making device using an Arduino Uno microcontroller. Virgin Coconut Oil has gained popularity due to its health benefits and versatile uses in various industries. The traditional process of making VCO involves manual effort and precise timing, which can be tedious and inconsistent. The proposed automated system aims to streamline the VCO production process by integrating sensors, actuators, and a microcontroller to achieve precise control and monitoring of the process variables. The Arduino Uno microcontroller serves as the central unit for data acquisition, processing, and control, facilitating automation through programmed logic. Key components of the automated VCO maker include temperature sensors for monitoring heating stages, a motor for stirring, and relays for controlling heating elements. The system utilizes feedback loops to maintain optimal conditions during each phase of VCO production, ensuring reproducibility and quality. The design also emphasizes user-friendly operation, with an interface that provides real-time feedback on process parameters and allows manual intervention if necessary. Safety features are incorporated to prevent overheating and ensure operational reliability. Overall, the developed automatic VCO maker offers a practical solution to enhance the efficiency and consistency of VCO production, catering to both small-scale producers and commercial enterprises in the food and cosmetic industries

According to the Jakarta Air Quality Index (AQI US) 12 July 2023, 200 indicates unhealthy air quality with an index value between 151 and 200. This figure even shows that Jakarta is currently the second most polluted city in Southeast Asia. (CNN Indonesia., 2023). This incident gave rise to responses from the public which were expressed via social media Twitter. From this incident, sentiment analysis was carried out regarding Jakarta's air quality. The amount of data used for this research was 500 tweet data. The results of the positive and negative sentiment analysis show that negative sentiment appears more frequently than positive sentiment with a percentage of 7% positive sentiment and 14% negative sentiment, by using the Rstudio application. This method uses the naïve Bayes classifier. Data division in the dataset with training data 1:499 and test data 1:476. It was found that the results of the Accuracy, Precision, Recall, and F1-Score values were Accuracy 87.50%, Precision 87.50 Recall 93.33%, and F1-Score 82.35%.       

The design of the POSKESDES health service system for tanjung miring village was carried out so that the use of information technology was used as a tool to increase productivity for POSKESDES for tanjung miring village. The method used in this study is a qualitative descriptive method, which means carefully recording various phenomena that are seen and heard and read via interviews or field notes, photos, videos, personal documentation, notes and memos and so on. The results of this research are to help manage information about POSKESDES so that it can help the surrounding community. Can assist POSKESDES in terms of disseminating information about the latest activities and the latest information at POSKESDES in tanjung miring village and can assist in the patient service process.

Along with the development of technology, the use of computers as a tool really needs to be used, especially in the health sector. The Prabumulih City General Hospital is the only hospital owned by the Prabumulih City Government and is a first-level referral. The patient registration process at the Prabumulih City Hospital is still direct, by means of the patient/patient's guardian coming directly to the health service facility, then the patient is given a registration queue number, then the patient waits for a call according to the queue number, after the queue number is called, the officer will ask the type of patient new or old, poly patient purposes, outpatient or inpatient care, private payments or BPJS, after that the officer enters patient data to create a queue number for patient care in order to get health services. In this regard, it is necessary to have an application system for patient administration so that new patients can register online through the internet network, making it easy for old patients to check personal data, view doctor schedules, take queues and others.

In the era of the new normal, maintaining health and hygiene has become critically important, especially in preventing the spread of viruses. One effective way to achieve this is through regular handwashing. Schools are particularly susceptible to the transmission of viruses and bacteria, which is why it's crucial to implement an effective hand sanitizer system. However, the use of conventional hand sanitizer bottles that require manual pressing or opening still carries the risk of virus transmission. Therefore, there is a need for the development of an automatic hand sanitizer system to reduce the risk of virus transmission. This research aims to design an Arduino-based automatic hand sanitizer system at SD Kanisius Genuk. The automatic hand sanitizer system utilizes an ultrasonic sensor to detect the distance between an object, in this case, a hand, and the hand sanitizer. When the hand approaches within a certain distance, the hand sanitizer fluid is dispensed automatically through a mini 5V pump. Additionally, the device features a liquid level sensor that provides information about the hand sanitizer fluid level via an LCD screen. The theoretical significance of this research lies in enriching knowledge about programming using the C++ programming language in designing an automatic hand sanitizer system. Furthermore, the research is expected to enhance creativity, innovation, and knowledge development in response to technological advancements. The practical benefits of this research include facilitating students, teachers, and guests at SD Kanisius Genuk in using the automatic hand sanitizer, thus reducing the risk of virus transmission. Additionally, this research can serve as a reference for universities and contribute to the field of human resource management knowledge.

Rossama Pratama Clinic is one of the health service providers for the community, which is located on Street Taman RT/RW 01/03 Sukajadi Village, East Prabumulih District, Prabumulih City, South Sumatra Province. The lack of information conveyed to the public has resulted in a lack of public knowledge about the Rossama Prabumulih Clinic Pratama Prabumulih because the information administration system carried out at this clinic is still manual, namely people who want to know about the latest information about the clinic must come directly so that it is more effective and efficient, because take a lot of time to arrive at the clinic. Therefore, the researcher will create a web informationsystem for the Rossama Pratama Clinic which will be accessed via a browser using the PHP programming language with the help of UML design to help design the system that will be created. The method of developing the system is using the Waterfall method. With this website, hopefully it will help people save time when they want to go to the clinic or seek treatment from home.

Pulmonary Hospital dr. Ario Wirawan Salatiga is a health service institution that organizes plenary health. In the era of the Covid-19 pandemic, dr. Ario Wirawan experienced a significant increase so that during administration the patient experienced a long waiting time. The preparation of this research aims to develop an independent registration system so that it can manage long and ineffective queues. This self-registration platform system uses a web-based FIFO (First in First Out) algorithm. The system development stage is the analysis, design, design and testing stage. The method for developing an independent registration platform system uses the prototype method according to needs. While the coding stage of this system was built using the Python programming language with the PostgreSQL database. With the existence of an independent registration platform system, it is hoped that the hospital and patients can be facilitated in the examination registration process and managing patient data at the Pulmonary Hospital dr. Ario Wirawan Salatiga.  Keywords: FIFO, Automated Pavement System

Teeth are one of human‘s organs that feeds on food. As an organ, the tooth definitely can be attacked by some disease. There are many cases of dental disease that occur from dental diseases common to people to chronic dental diseases that can be dangerous. The low level of public concern about dental disease is a problem faced today. Evidenced by the small number of people who diligently consult with dentists about the health of their teeth. An alternative option is needed that can make it easier for people to be able to consult or diagnose dental health and disease without having to see a doctor of dental health. Therefore, in this essay an expert system was created to provide alternative choices for people. This expert system was created with the php hypertext preprocessor programming language. Using the forward chaining method as a tracking method. The purpose of making this expert system is to be able to be a substitute for a dental expert so that people can already do the diagnosis of dental disease anywhere and anytime.

Arzara company is a company engaged in the garment sector, the development of the company affects the level of production of goods, so that in order to balance the production needs, it must increase the number of employee needs. The problem that often occurs in Arzara's company is the lack of professionalism of the company's employees, resulting in unilateral termination of employment. Termination of employment of employees of course will also affect the amount of production of goods. The SAW method or often called Simple Additive Weighting is an algorithmic method used for decision making, using certain criteria as the weight of the assessment in decision support. In making employee admission decisions using the SAW method using several criteria, which include expertise (skills), work experience, age, gender, education, health, talent, character, temperament, character, general knowledge tests, psychological tests. By using the PHP programming language, it can be used to assist the company to perform valid recruitment of employees . Applications that have been made can be used as a tool for decision makers while remaining based on a decision support system that is more effective in selecting employee admissions using the SAW ( Simple Additive Weighting ) method . 

Diabetes is a serious chronic disease that occurs because the pancreas does not produce enough insulin (a hormone that regulates blood sugar or glucose), or when the body cannot effectively use the insulin it produces. WHO data shows that the incidence of non-communicable diseases in 2004 reached 48 , 30% is slightly higher than the incidence rate of infectious diseases, namely 47.50% [1]. According to the Ministry of Health in 2012 diabetes caused 1.5 million deaths. Some Indonesian people, this disease is better known as diabetes or blood sugar. This research was developed through secondary data processing from the Pima Indians Diabetes Dataset health database which was taken from the Kaggle dataset and can be accessed through https://www.kaggle.com/uciml/pima-indians-diabetes-database. Where the data itself consists of 768 records with several medical predictor variables (Pregnancies, Glucose, Blood Pressure, Skin Thickness, Insulin, BMI, Diabetes Pedigree Function, Age and Outcome). Then the data will be processed using the Particle Swarm Optimization (PSO) feature selection to increase the accuracy value and the Naive Bayes algorithm to determine the accuracy results of the diagnosis of diabetes. From the results of research that has been done for the accuracy of the classification algorithm Naive Bayes is 74.61%, while the accuracy of the classification algorithm with Particle Swarm Optimization is 77.34% with an accuracy difference of 2.73%. So it can be concluded that the application of the Particle Swarm Optimization technique is able to select attributes in the Naive Bayes Algorithm, and can produce a better level of diabetes diagnosis accuracy than using only the individual method, namely the Naive Bayes algorithm. Keywords: Diabetes, Particle Swarm Optimization, Naive Bayes Algorithm

Recent technological developments determine humans to be creative in creating tools that implement technology in it with the aim of facilitating human tasks in daily activities. Inappropriate use of fertilizers can cause losses, both losses on fertilizer, on plants, as well as on the soil and the environment around fertilization. Losses on plants such as unhealthy plant growth and susceptible to disease pests, plant yields are not as expected or low. From the background above, the writer found an idea to create a system or tool that can help farmers in determining the dose of Nitrogen fertilizer in their rice plants, through the storage of the dosage data of each land. The user did five scans, from each scan producing RGB values, each RGB value from five samples was then matched with the BWD dose color indicator. The sample dose results are then sent by the NodeMcu microcontroller to the webserver database. Based on the assessment of the test conducted by 10 Users by Gapoktan Farmers Group of Tosari Kendal Village, the total value of 372 that has been averaged to be 37.2 is between 31 - 40 which is classified in the category of "Very Valid or Very Effective".

In all section of inventory management, including inventory management in a hospital, minimize cost and ideal inventory accommodation against demand has always been a primary goal (Varghese, 2012). Nearly a third of the operational success of a hospital is in the field of medical supplies. In its usual way, inventory  management in hospitals using the approach to the demand usage, the characteristics of the item and the estimate of the demand. The model presented in this study accommodates that common approach which use a combination of inventory safety stock limit, Economic Order Quantity, and reorder point in a information system dashboard that capable to provide quick and easy information about the condition of inventory management. The result of the system are used for the hospital pharmaceutical inventory management in integration with the INACBGs  to optimize the inventory performance.  

PT. Vermindo Utama Semarang having its address at Jl. Pawiyatan Luhur Number 25 Semarang is a company engaged in the distribution and production of goods, especially health products. PT. Vermindo Utama Semarang has dozens of Salesmen and a leader. PT. Vermindo Utama Semarang carries out the process of buying and selling wholesale with various customers, the majority of whom are Pharmacies and supermarkets. In running its business, PT. Vermindo Utama Semarang still sells conventionally by using salesmen. And the marketing area still covers Central Java and East Java. Based on the problems above, the writer wants to propose a web-based booking system design to be considered in helping in the promotion of goods from PT. Vermindo Utama Semarang. Application Order System PT. Vermindo Utama Semarang by using PHP and MySql database. Making this application is expected to be one of the efforts that can be done to overcome the problems that often occur so as to increase the effectiveness of work which will certainly affect the quality of service to customers.