Kebakaran hutan tidak hanya menimbulkan kerusakan ekonomi dan ekologi, akan tetapi juga mengancam kehidupan manusia dengan pencemaran udara karena asap yang ditimbulkan.Tingginya angka kejadian ...kebakaran hutan menentukan pentingnya prediksi dilakukan. Algerian Forest Fire merupakan dataset kebakaran hutan yang digunakan dalam penelitian ini, dimana dataset ini akan diolah dengan model yang diusulkan. Dataset ini memiliki fitur-fitur yang tidak relevan dan akan mempengaruhi terhadap kinerja dari model yang diusulkan, sehingga pemilihan fitur yang relevan menggunakan Forward Selection. Metode Bagging digunakan untuk menangani ketidakseimbangan kelas yang ada pada dataset ini dan algoritma Naïve Bayes sebagai algoritma machine learning yang diimplementasikan dalam penelitian ini. Hasil akurasi terbaik adalah sebesar 98.40% pada model Naive Bayes, Bagging dan Greedy Forward Selection dan 92.63% pada model Naïve Bayes dan Bagging.
Diabetes merupakan penyakit yang mengancam kehidupan dengan pertumbuhan tercepat dan jika tidak diobati atau diindentifikasi akan menyebabkan komplikasi lain. Diabetes setiap tahunnya mengakibatkan ...kematian sebanyak 3.8 juta jiwa dan telah mempengaruhi 422 juta orang di seluruh Dunia. Dataset diabetes yang digunakan dalam penelitian ini adalah dataset publik, dataset ini akan diolah menggunakan model yang diusulkan. Dataset diabetes memiliki permasalahan seperti adanya fitur-fitur yang tidak relevan, fitur-fitur yang tidak relevan dapat menurunkan kinerja dari model yang digunakan. Seleksi fitur Greedy Forward Selection adalah seleksi fitur yang sangat efisien dan cepat dalam prosesnya. Algoritma Naïve Bayes merupakan algoritma yang mudah dan sederhana ketika diimplementasikan. Hasil penelitian menunjukkan bahwa model Naïve Bayes dan Greedy Forward Selection mendapatkan nilai akurasi tertinggi sebesar 91.73%, sedangkan model Naïve Bayes tanpa seleksi fitur Greedy Forward Selection hanya mendapat nilai akurasi sebesar 87.69%
With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as ...Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of the manufacturing process. In this study, a real-time monitoring system that utilizes IoT-based sensors, big data processing, and a hybrid prediction model is proposed. Firstly, an IoT-based sensor that collects temperature, humidity, accelerometer, and gyroscope data was developed. The characteristics of IoT-generated sensor data from the manufacturing process are: real-time, large amounts, and unstructured type. The proposed big data processing platform utilizes Apache Kafka as a message queue, Apache Storm as a real-time processing engine and MongoDB to store the sensor data from the manufacturing process. Secondly, for the proposed hybrid prediction model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based outlier detection and Random Forest classification were used to remove outlier sensor data and provide fault detection during the manufacturing process, respectively. The proposed model was evaluated and tested at an automotive manufacturing assembly line in Korea. The results showed that IoT-based sensors and the proposed big data processing system are sufficiently efficient to monitor the manufacturing process. Furthermore, the proposed hybrid prediction model has better fault prediction accuracy than other models given the sensor data as input. The proposed system is expected to support management by improving decision-making and will help prevent unexpected losses caused by faults during the manufacturing process.
This research highlights the theoretical basis and future research directions in religious tourism and related topics from 2003 to 2023. 1,689 documents from the Scopus database related to religious ...tourism and the Umrah Hajj have been analyzed using VOS viewer software. This analysis found that research on religious tourism and the Umrah pilgrimage experienced a consistent increase. The most influential countries in the research were Saudi Arabia, Indonesia, Malaysia, France, and Australia. Studies on Umrah mass gathering, respiratory viruses, preventive measures, and pilgrimage season in Hajj and Umrah religious tourism are predicted to be a significant research focus, as can be seen through keyword co-occurrence analysis. The results of this study provide a comprehensive evaluation of the religious tourism literature over a decade using bibliometric and network analysis. The results of this research can help researchers gain a deeper understanding of the study of religious tourism as a whole and determine priorities for future research.
This research aims to analyze the capital market reaction to the event study of Prabowo-Gibran's victory in the Indonesian Presidential Election by comparing the variables of stock price, stock ...return and Infobank15 stock trading volume activity in the research period 20 days before and 20 days after the announcement on March 20 2024. Including quantitative research because the data taken is secondary data sourced from idx.co.id where the population which is also a sample is 15 leading banks with good performance according to the Indonesian Stock Exchange. The research results reveal that there is no difference in the average stock price, average stock return and average TVA before and after the announcement of Prabowo-Gibran's victory.
Cabang produksi yang penting bagi negara dan/atau menguasai hajat hidup orang banyak dikuasai oleh negara. Terkait dengan penilaian mengenai cabang produksi, berada di tangan Pemerintah bersama DPR. ...Permasalahan kemudian timbul, ketika tiadanya indicator untuk melakukan penilaian yang bermuara pada penyalahgunaan kekuasaan dan berujung pada privatisasi, hingga akhirnya menciderai hak menguasai negara. Atas dasar itu, MK hadir untuk melakukan penilaian atas penilaian Pemerintah bersama DPR. Tujuan penelitian ini adalah untuk mengetahui bagaimana peran MK dalam melakukan penilaian. Penelitian ini merupakan penelitian hukum normatif. Hasil penelitian menunjukkan bahwa MK telah melakukan kewenangan ini dengan memberikan penilaiannya melalui pengujian undang-undang. Ke depan, MK harus mengeluarkan indicator cabang produksi yang dikuasai oleh negara dengan berdasar pada Pasal 33 UUD NRI 1945.
Background: The activities of traders and visitors in the market have potential hazards that pose safety and health risks. Thus, understanding the risks and the threats is a necessity.
Objective: ...This study aimed to identify hazards, analyze safety and health risks, and design risk control efforts that market managers can apply.
Methods: This research was qualitative research with an observational approach. The informants were selected purposively: the head of the Siteba Market Technical Implementation Unit, security officers, traders, and visitors at the Siteba Market, Padang City, Indonesia. The instruments used were checklists and interview guides. Risks were analyzed manually based on the AS/NZS 4360 standard matrix.
Results: The research results using the elicitation method identified ten potential safety and health hazards in Siteba Market. The safety and health risks for traders and visitors to Siteba Market consisted of seven high risks and three medium risks. Potential high risks were accidents, pickpockets, fatigue, slipping, falling, and jostling during emergencies and fires. Meanwhile, the potential risks consisted of traffic jams, indigestion, and scattered merchandise.
Conclusion: Traders and visitors were potentially exposed to safety and health. Community organizing efforts through the occupational health business post need to be activated by the health centers to carry out preventive and promotive measures for safety and health in the market.
Current technology provides an efficient way of monitoring the personal health of individuals. Bluetooth Low Energy (BLE)-based sensors can be considered as a solution for monitoring personal vital ...signs data. In this study, we propose a personalized healthcare monitoring system by utilizing a BLE-based sensor device, real-time data processing, and machine learning-based algorithms to help diabetic patients to better self-manage their chronic condition. BLEs were used to gather users' vital signs data such as blood pressure, heart rate, weight, and blood glucose (BG) from sensor nodes to smartphones, while real-time data processing was utilized to manage the large amount of continuously generated sensor data. The proposed real-time data processing utilized Apache Kafka as a streaming platform and MongoDB to store the sensor data from the patient. The results show that commercial versions of the BLE-based sensors and the proposed real-time data processing are sufficiently efficient to monitor the vital signs data of diabetic patients. Furthermore, machine learning⁻based classification methods were tested on a diabetes dataset and showed that a Multilayer Perceptron can provide early prediction of diabetes given the user's sensor data as input. The results also reveal that Long Short-Term Memory can accurately predict the future BG level based on the current sensor data. In addition, the proposed diabetes classification and BG prediction could be combined with personalized diet and physical activity suggestions in order to improve the health quality of patients and to avoid critical conditions in the future.
Angka stunting di Indonesia adalah 27,76%, angka ini jauh di atas standar WHO yaitu 20% sehingga kasus stunting di Indonesia masih tinggi. Sedangkan hasil survei Status Gizi Balita Indonesia Tahun ...2021, jumlah balita kerdil di Provinsi Banten sebanyak 294.862, angka ini juga menempatkan Propinsi Banten sebagai propinsi kelima terbesar yang memiliki balita kerdil. Tujuan pengabdian masyarakat adalah untuk meningkatkan pengetahuan masyarakat Desa Tamiang Kabupaten Tangerang tentang pencegahan stunting. Metode yang digunakan adalah memberikan pendidikan kesehatan kepada masyarakat. Dampak dari kegiatan ini adalah meningkatnya pengetahuan masyarakat tentang pencegahan stunting dengan nilai pre-test 74% dan post-test 89%. Masyarakat khususnya para ibu disarankan dapat melakukan pencegahanstunting dengan pemenuhan asupan gizi selama hamil, pada saat melahirkan dan pada anak sebelum usia 2 tahun
The classification method is part of data mining which is used to predict existing problems and also as predictions for the future. The form of dataset used in the classification method is supervised ...data. The random forest classification method is processed by forming several decision trees and then combining them to get better and more precise predictions. while a decision tree is the concept of changing a pile of data into a decision tree that presents the rules of a decision. From these two classification methods, researchers will compare the level of accuracy of predictions from both methods with the same dataset, namely the employee dataset in India, to predict the level of accuracy of employees who leave their jobs or still remain to work at their company. The number of records available is 4654 records. Of the existing data, 90% was used as training data and 10% was used as test data. From the results of testing this method, it was found that the accuracy level of the random forest method was 86.45%, while the decision tree method was 84.30% accuracy level. Then, by using the confusion matrix, you can see the magnitude of the distribution of experimental validity visually to calculate precision, recall and F1-Score. The random forest algorithm obtained precision of: 96.7%, sensitivity of: 84.7%, specificity of: 91.4%, and F1-Score of: 90.2%. Meanwhile, the decision tree algorithm obtained precision of: 95.7%, sensitivity of: 82.9%, specificity of: 88.4%, and F1-Score of: 88.8%.
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