No abstract

Serangan Jantung adalah salah satu penyakit yang paling mematikan tercatat di dunia, terdapat jumlah kasus baru Penyakit Jantung sebanyak 43,32% serta jumlah kematian sebanyak 12,91%. Pada tahun 2013 jumlah penderita Penyakit Jantung di Indonesaia sejumlah 61.682 orang, pada umumnya jumlah penderita penyakit ini terus meningkat dikarenakan kurangnya pengetahuan atau informasi tentang penyakit jantung tersebut, oleh karena itu dibutuhkan sebuah sistem yang dapat memberikan informasi serta klasifikasi penyakit secara dini yang dapat digunakan untuk klasifikasi apabila seseorang ingin mengetahui informasi ataupun gejala awal serangan jantung. Metode naïve bayes merupakan salah satu metode yang digunakan untuk melakukan klasifikasi berdasarkan probabilitas atau kemungkinan dari data sebelumnya, selain pendekatannya sederhana metode tersebut juga dapat melakukan klasifikasi secara baik. Mekanisme pengujiannya yaitu membagi 303 data kedalam 5 subset yang akan divalidasi dengan 5-fold cross validation. Hasil akhir dari penelitian ini adalah penerapan sistem klasifikasi dengan menggunakan metode naïve bayes yang akan menghasilkan nilai rata-rata akurasi sebesar 90,61%, presisi sebesar 87,44 %, dan recall sebesar 87,95%. Kata Kunci — klasifikasi, penyakit jantung, naïve bayesClassifier Heart attack is one of the most deadly diseases recorded in the world, there are a number of new cases of heart disease as much as 43.32% and the number of deaths as much as 12.91%. In 2013 the number of sufferers of heart disease in Indonesia amounted to 61,682 people, in general the number of sufferers of this disease continues to increase due to lack of knowledge or information about heart disease, therefore we need a system that can provide information and classification of diseases early that can be used for classification if someone wants to find out information or early symptoms of a heart attack. Naïve Bayes method is one of the methods used to classify based on the probability or likelihood of previous data, in addition to a simple approach the method can also do a good classification. The testing mechanism is to divide 303 data into 5 subsets that will be validated by 5-fold cross validation. The final result of this study is the application of the classification system using the Naïve Bayes method which will produce an average accuracy value of 90.61%, a precision of 87.44%, and a recall of 87.95%. Keywords — classification, heart disease, naïve bayes

Well-designed media within a certain time limit can stimulate the emergence of an internal dialogue in students. One of the interesting media that can be used to increase students' motivation and passion for learning is Augmented Reality (AR) media. The aims of this study was to develop the Science Augmented Reality Program (SARP) media in assisting the learning process for elementary school students. This study applied the four-D method. The research data included the results of the validity and effectiveness of using the Science Augmented Reality Program (SARP) media. The research subjects in this study were fourth grade elementary school students. Validity includes the validity of learning materials, the validity of design, and the validity of learning media from two experts. Meanwhile, the effectiveness test was perceived from the results of limited trials and field trials. The product was tested on sixth grade elementary school students on natural sciences material. The results showed that the percentage of learning material validity test results was 95% with a very valid category, the percentage of learning media design validity test results was 97% with a very valid category, the percentage of learning media validity test results was 92% with a very valid category. Overall, it is concluded that the Science Augmented Reality Program media is very suitable and effective to be applied as natural science learning media in elementary schools.

Natural conditions are increasingly uncertain and difficult to predict due to changes in rainfall patterns and climate. Excessive rainfall can cause flooding which is detrimental to the agricultural sector. Flooding is a natural challenge that is often faced in the agricultural sector. This challenge is faced by most of the agricultural land in Lamongan Regency, including in Dlanggu Village. The impact of flooding on rice fields in certain locations which is increasingly widespread and intensive from year to year has caused considerable losses for farmers. The purpose of this activity is to map flood-affected agricultural land in a participatory manner with the help of the WebMap application. The method of implementing this activity includes the preparation stage, implementation stage, and monitoring and evaluation stage. The results of the activity showed that participants were very enthusiastic about this activity program, as evidenced by the positive response in the form of the presence of 96% of the training participants and active discussion activities during the socialization and training took place. After the training, the participants also expected a follow-up in the form of assistance from the service team to improve skills with WebMap applications in other fields. This activity is expected to be a solution that can be offered to provide an early warning system based on mapping so that the delivery of information about floods can be conveyed more quickly to the community, especially people who have agricultural livelihoods to be aware of flood disasters.

One automatic system for monitoring the presence of vehicles in a parking zone is an indispensable mean of an area such as services building, institutions, and other organizations, which accomodated many vehicles. A tracking record is the most important matter when the vehicle leaves the parking area. Manually, one parking officer will be needed to do the job. However, when using such an automated parking system, then this officers' job can be replaced. The vehicle license plate recording system is designed to use electronic-vision devices as a fundamental device for detecting the presence of vehicle. Vehicle license plates are detected using a digital camera which captured by the camera module on the Raspberry-Pi mini-pc microcontroller device, in addition to the detection of ultrasonic sensors that capture the position of vehicle objects. The process of reading vehicle numbers in an intelligent system of artificial neural networks to extracts each character of the license plate so that each number and letter can be recognized. Meanwhile, the detection of the ultrasonic parking sensor is a complementary confirmation indicating the presence of a vehicle object being monitored. The combination of solar power as the power supply for this automatic system is an important set-up that makes the system's electricity able to run independently. This monitoring system is prepared to help increase vehicle security automatically.