Sistem penerimaan dan pengeluaran kas di SMK Nurut Taqwa Songgon masih menggunakan cara konvensional dengan menulis secara manual di buku sehingga proses yang dilakukan kurang optimal, dan banyak sekali kendala yang dihadapi seperti kehilangan data dan butuh waktu yang cukup panjang dalam pengurusannya. Berdasarkan permasalahan yang ada, pada penelitian ini dilakukan pengembangan aplikasi yang dapat membantu pekerjaan bendahara berbasiskan web dan WhatsApp Gateway. Metode pengembangan sistem yang digunakan dalam aplikasi ini menggunakan RAD (Rapid Application Development) dan dibangun menggunakan framework Codelgniter. Hasil yang didapatkan dari penelitian ini adalah aplikasi ini dapat mempermudah bendahara dalam mengelola data tanggungan siswa dan pencatatan transaksi pengeluaran sekolah, seperti penggajian karyawan, pengelolaan pembayaran siswa dan melihat transaksi penerimaan dan pengeluaran secara keseluruhan di SMK Nurut tanpa memerlukan waktu yang panjang lagi, sedangkan untuk para wali murid dapat terbantu dalam memantau pembayaran yang dilakukan oleh anaknya melalui fitur Whatsapp Gateway. Berdasarkan pengujian yang dilakukan didapatkan bahwa semua fitur yang dikembangkan dapat berjalan sesuai dan tingkat kualitas sistem berkriteria baik dengan presentase sebesar 88.5%.
Batik is one of Indonesia's cultural heritages that is recognized around the world and has existed since the colonial era. Indonesia has a variety of different batik pattern in every Indonesia's region. It causes many ordinary people and tourists to become harder to identify and recognize the existing patterns. Banyuwangi regency itself has more than 10 batik patterns, including the Gajah Oling pattern which in the oldest batik pattern. For preserving the culture and supporting the growing tourism aspect in Banyuwangi, this study developed a system for recognizing Banyuwangi batik patterns based on digital image processing. This system is built using python language and is able to recognize three classes of Banyuwangi batik patterns, such as Gajah Oling, Kopi Pecah and other Banyuwangi batik patterns. This system proposes Gray Level Co-occurrence Matrix (GLCM) as feature extraction method and k-Nearest Neighbors (kNN) as classification method. Based on the experiments that have been carried out, the optimal accuracy is 87,5% with the K parameter of kNN is 9.
AbstrakPemeriksaan kesehatan jantung sangat penting dilakukan, mengingat jantung merupakan organ vital tubuh yang dapat mempengaruhi kinerja organ lain. Pemeriksaan jantung menggunakan sensor elektrokardiograf pada sebuah rumah sakit membutuhkan biaya yang cukup mahal. Pemeriksaan ini perlu dilakukan secara signifikan, karena banyak hal yang bisa mempengaruhi kinerja jantung. Penelitian ini merupakan penelitian pengembangan alat monitoring denyut jantung manusia menggunakan sensor AD8232 yang berfungsi untuk membaca sinyal biolistrik tubuh, dengan cara menempelkan lead atau alat penerima implus listrik jantung pada bagian tubuh yang telah ditentukan berdasarkan teori segitiga Einthoven. Selain itu, Modul MCU ESP8266 juga digunakan untuk mengontrol keluaran dan memungkinkan menjalankan sistem Internet of Things (IoT). Hasil penelitian menunjukkan bahwa perbandingan persentase rerata error antara sistem yang dikembangkan dengan alat yang digunakan di rumah sakit sebesar 1,2%. Selain itu, keberhasilan pengiriman data ke website melalui media internet sebesar 100%.
Batik cloth is one of Indonesia's most valuable cultural heritages and has been recognized by UNESCO as one of the world heritages. Many Indonesian people do not know the batik motifs of each region. Banyuwangi itself has more than 10 batik motifs, among the most famous Banyuwangi batik motifs is the Gajah Oling motif. The Banyuwangi batik motif classification system is a system built using the Python library with Python programming language. This system can recognize 7 types of Banyuwangi batik motifs, including Gajah Oling, Gedegan, Coffee Pecah, Moto Pitik, Kutah Rice, Paras Earthy and Sisikan. This system uses the convolutional neural network method and for evaluation, the confusion matrix method is used to measure the accuracy value. The research uses a CNN model with an architecture named MyCustomModel. The data used in this study were 120 images for each batik motif and the prediction results get an accuracy value of 63%.
Travel Destinations are an inseparable part of human life today. As one of the provinces with a large area, East Java is one of the most visited areas for its tourism. Many people are competing in finding information related to these tourist destinations on the internet, one of which is the Tripadvisor application. Of the many tourist attractions, several tourist attractions have different attractions and experiences each time. Tourists have widely used the Tripadvisor application in determining the location where they will visit on their vacation activities. With various features ranging from reviews and recommendations for sharing photos, TripAdvisor is one of the best applications in the inventory of tourist attractions. Of the many tourist destinations, it is necessary to analyze and evaluate both tourist attractions that have many visitors with tourist attractions that are rarely visited by both local and foreign visitors. This goal, information mining (web mining), was carried out on the TripAdvisor application to obtain information on East Java Province's popular destinations. Crawling results on the TripAdvisor website, obtained various kinds of information such as names of tourist attractions, locations, visitor reviews, photos, and ratings of these tourist attractions. Spatial Analysis, a Tourist Sentiment Analyst on tourist objects, can then be carried out. It can also be developed into the recommendation system for the best tourist attractions in East Java Province
Miniplate plays an important role as one of the implant components used as a rehabilitation device for a post-fracture finger. In this study, an analysis was carried out to determine the strength of the miniplate design made from Ti-6Al-4V titanium alloy material. Simulation and analysis were carried out using the finite element method. The given input for modeling tensile and bending loads determined von Mises stress, kinetic energy, strain energy, and internal energy. The analysis showed that uneven von Mises stress and strain distribution have occurred. The critical concentration of stresses was located at the center of the miniplate and these values were a lot lower than the yield stress of Ti-6Al-4V.
Dragon fruit is one of the favorite commodities in Banyuwangi Regency's agriculture. In 2019, this commodity had the fourth largest harvest area among other fruit commodities in Banyuwangi until it was exported to China. However, disease attacks often appeared in several dragon fruit plantations in Banyuwangi, and the identification system was still conventional. Many farmers did not know the types of disease and how to handle it, causing the quality and quantity of their crops to decline. Therefore, this study implemented two feature extraction methods. Both methods include color feature extraction using the color moments method and texture feature extraction using gray level co-occurrence matrices (GLCM). The methods used to develop a system that recognized or detected the three types of dragon fruit stem based on digital image processing using Support Vector Machine and k-Nearest Neighbors methods as comparison methods. The results obtained from this study indicated that the combination of the two proposed feature extraction methods could distinguish between stem rot, smallpox, and insect stings with an optimal accuracy score of 87.5% obtained by using Support Vector Machine as a classification method.
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