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The performance of the Indonesian National Team (Timnas) in the 2026 World Cup qualifications has triggered massive and diverse responses on social media, particularly on platform X. This study aims to identify and classify public sentiment regarding Timnas Indonesia's performance into positive, negative, and neutral categories using a data mining approach. Text data was processed through pre-processing stages, term weighting using TF-IDF, and the application of the Synthetic Minority Over-sampling Technique (SMOTE) to address significant class distribution imbalance. The classification algorithm employed was Multinomial Naïve Bayes. Model performance evaluation was conducted by comparing two training-testing data split scenarios: 90:10 and 80:20 ratios. The results indicate that public opinion is dominated by negative sentiment at 73.2%, reflecting public disappointment. In terms of model performance, the 90:10 ratio scenario yielded the best accuracy of 80%, outperforming the 80:20 ratio which recorded an accuracy of 75%. These findings demonstrate that combining Multinomial Naïve Bayes with the SMOTE technique is effective in handling imbalanced text data and is capable of accurately mapping public perception.

Abstrak  - Coal handling system berfungsi menangani pekerjaan mulai dari pembongkaran batu bara dari kapal/tongkang (unloading area) yang dipindahkan ke conveyor - conveyor, penimbunan/penyimpanan di stock area, ataupun pengisian ke bunker yang digunakan untuk pembakaran di boiler. Dalam proses pembongkaran tersebut tidak boleh terjadi penyumbatan / plugging terutama pada chute conveyor, maka dari itu diperlukan sensor proteksi untuk mencegah hal tersebut. Sensor lama yang digunakan yaitu berjenis Tilt Switch yang selama pemakaian tidak efektif karena banyak masalah sehingga dilakukan pemeliharaan, akibatnya dilakukan penggantian menggunakan sensor berjenis MBD (Microwave Beam Detector). Dari analisa setelah penggantian menggunakan sensor MBD, permasalahan penyumbatan chute berkurang dapat dilihat dari frekuensi pemeliharaan yang semakin berkurang.

The management of service centers at the Indonesian Rede Cross (PMI) in East Jakarta is still conducted manually, which slows down service processes and increases the likelihood of data processing erorrs. This research aims to design a Java-based application to automate patient registration, admission, handling, emergency services, available ambulance data, and the preparation of reports as quickly as possible. The application was developed using the Java programming language with a prototype model approach in software development. Testing results indicate that this application successfully enhances the efficiency and accuracy of PMI East Jakarta’s operations, particularly in managing data related to patients, actions, personnel, and ambulance availability. It is hoped that this application can be integrated with other PMI regions to establish a more structured and connected service management system.

This research aims to design and simulate a DC motor speed control system using integral state feedback (KISF) control. This control is designed to maintain DC motor speed stability with high accuracy despite disturbances or load changes. The research stages include mathematical modeling of the DC motor, PID control design, integral state feedback control design, simulation implementation and simulation results analysis. The show that althought integral state feedback control has a rise time 273.501 ms, slightly slower than PID 197.604 ms, integral state feedback compensates with higher slew rate of change 6.540 V/ms compared to PID 4.344 V/ms. Integral state feedback offers greater flexibility through pole placement values with Ackerman’s formula J3 = [-12 -100 -600], indicating that this system has good capability in responding to input changes, thus maintaining motor speed stably and efficiently. This indicates that integral state feedback control is superior in system adaptation and handling complex dynamics.

Starting from the development of medical technology that is increasingly sophisticated and rapidly growing,researchers conduct medical research, namely about patient infusion handling services. In handling patient infusion, currently it is still manual which is carried out by nurses / medical personnel. Infusion handling services for patients still have shortcomings, namely the process of monitoring and replacing infusion fluids which are often late. If the problem is not treated quickly, it can lead to problems, namely the presence of air embolism in the blood vessels (the entry of foreign objects into the blood vessels, for example air). From that problem, the researchers made a new innovation in medical technology in handling infusions automatically and based on IoT. In this study, the smart online infusion device that has been made has good features and is very effective in handling infusions. This device has 3 main functions, namely: it can monitor the remaining infusion, it can change the infusion fluid automatically and it can indicate a blocked patient's infusion. This device already has a method for processing data with fuzzy logic. Media monitoring has been supported by a website that can be controlled remotely and in real time. Tests have been carried out and the effectiveness of the system is found to have an error rate of 0.2% - 0.7% and has an accuracy of 98%. Thus this tool can be used in terms of handling patient infusion automatically.

Management of medical actions carried out in handling patients who are ODP (people under monitoring), OTG (asymptomatic people), PDP (patient under monitoring) and positive Covid-19 patients is carried out based on assumptions, such as self-isolation, hospitalization, or special treatments in the ICU (Intensive Care Unit) room. The condition of the body in each patient is different, a patient may have same symptoms but the treatment is different, especially in elderly patients. Many problems occur in determining medical action because the patient's body condition is different. Therefore, it needs to be appointed as a research. The research method used in this study was Nive Bayes algorithm with supporting application Rapid Miner. It was applied to carry out the process of testing on patient data as much as 500 data, 25 variables or patient symptoms and 3 outputs as a form of medical action. Based on the results of the analysis carried out in this study, prediction of medical actions for ODP, PDP, OTG and positive Covid-19 patients were obtained by comparing training data with testing data using Rapid Miner application. It resulted that an accuracy rate of 76.00% was obtained

The use of information, media and communication technology has changed both the behavior of society and human civilization globally. The development of hospitals in Karawang is increasingly mushrooming, as well as the increasing number of degenerative diseases such as hypertension and diabetes, the increasing prevalence of chronic kidney disease. So it requires the handling of renal replacement therapy (Renal Replacement Therapy) because it is increasingly needed for cases of acute and chronic renal failure. The purpose of this research is to build an integrated and controlled information system that can simplify the patient administration process and reduce the effectiveness of the patient's time for dialysis. The methodology that the authors use in this study includes methods of identification and system design. System identification includes identification of the organization, running systems, and problem identification. The problems faced at this time in the Hemodialysis Installation. Patient data is not the same between patients who are served by hemodialysis (dialysis) and those in the application report, the transaction value for using tools and materials is sometimes empty or there is no transaction value in the application, it will cause losses to the customer. hospital. It is hoped that this system can eliminate the problems that have been happening so far.

The recruitment of new mechanics at Mataram Sakti is no longer through the training process at the head office, but new mechanics are placed at the dealership accompanied by the chief mechanic as a supervisor, with the aim of providing training to new mechanics in order to be able to service or periodically repair Yamaha products especially the latest motorbikes namely Yamaha NMAX, because of the flurry sometimes the mechanical head is not in place so that when the mechanic is experiencing problems it cannot directly ask the mechanical head causing the handling of repairs to be less effective and efficient. One way to overcome this is to create a web-based expert system application with a forward chaining method so that the chief mechanic can transfer the knowledge he has into the computer. Forward chaining method is a search technique that starts with known facts and then matches these facts with the IF part of the IF-Then rules, so that conclusions can be drawn. This expert system was built using supporting software including, Macromedia Dreamweaver MX, PHP script language, MySQL database and WAMP server. The expert system for diagnosing damage to Yamaha NMAX motorcycles using the forward chaining method can be used as a new mechanical learning media in diagnosing damage to NMAX motorcycles and as a means of chief mechanics transferring their knowledge.