Aplikasi Pengenalan Budaya Jawa Tengah menggunakan Virtual Reality Berbasis Android

At this time, it is very difficult to introduce culture to students in school, and this is also involved to children do not recognizing their own culture. Many schools have so limited funds to go to museums or cultural performances, especially school which are far from the capital city. Therefore, it is necessary to make an android-based application using Virtual Reality. This writing describes about a method of designing and making Central Javanese cultural learning-application for elementary and secondary school students by utilizing technological developments, one of the fields is education. In the field of education, Virtual Reality can be used as a learning media which is able to make it more attractive. This Virtual Reality technology can be applied in regional cultural learning systems, one of this is the introduction of Central Javanese culture. The use of Virtual Reality technology is expected to be able to display objects in the form of musical instruments, traditional clothes, traditional houses, paintings and traditional weapons in virtual 3D using images which can used to be markers. This making of cultural learning application using Unity, Blender, and SketchUp. The development of this application uses the waterfall model where this method pays close attention to the design of the analysis, design, implementation and testing. With this research, it is hoped that it can help students in Central Java to get to know their culture. This application is specified for students specifically for elementary and secondary schools based on Android. This application is expected to be used as an interactive alternative media besides books, so it’s able to make students more interest on learning Central Javanese culture. This application will be made by using Unity and other assistive software and finally it will be refined with VR Box hardware to make it more real. Keywords: Virtual Reality, Unity, Budaya, Blender, SketchUp, Waterfall.

Implementasi Deep Learning Untuk Klasifikasi Citra Undertone Menggunakan Algoritma Convolutional Neural Network

The beauty of Indonesian women is distinguished by skin color, facial structure, hair color and body posture. For women today trying to look beautiful is a must. The way to make yourself look beautiful can be tricked by using make-up. But it's not that easy to use make-up because the type of make-up is differentiated based on the basic skin color, this is the problem for women in using make-up. Undertone is the basic color of the skin, there are three types of undertones, namely warm, cool and neutral. By knowing the type of undertone, it will make it easier for women to use make-up, namely to determine the appropriate shade based on the type of undertone. For this reason, a modeling of undertone image classification was made using the Convolutional Neural Network algorithm. This algorithm is claimed to be the best algorithm for solving object recognition and detection problems. The wrist vein color image dataset is required. The dataset used is 30 data per class, then preprocessing is carried out by homogenizing the image size to 64x64 pixels, then augmentation is carried out on each image by rotating and zooming. At this stage, the dataset will be divided into 3000 images which are divided into 80% training data and 20% testing data. Then it is processed through the convolution and pooling process at the feature learning stage, then the fully connected layer and classification stage where the feature learning results will be used for the classification process based on subclasses. Produces accuracy and training model values ​​reaching 98% with a loss value of 0.0214 and for accuracy from data validation it reaches 99% with a loss value of 0.0239 with model testing results of 99.5%.

Sistem Inferensi Fuzzy: Pengertian, Penerapan, dan Manfaatnya

Logika fuzzy salah satu komponen pembentuk soft computing yang digunakan sebagai cara untuk memetakan masalah dari input ke output yang diharapkan. logika fuzzy memiliki beberapa kelebihan seperti mudah dimengerti karena memiliki konsep matematis yang sederhana, fleksibel untuk digunakan, terdapat toleransi pada data-data yang tidak tepat, mampu memodelkan fungsi-fungsi non-linear yang sangat kompleks, dapat menerapkan pengalaman pakar secara langsung tanpa proses pelatihan, dapat bekerja sama dengan teknik-teknik kendali secara konvensional, dan didasarkan pada bahasa alami. Logika fuzzy memiliki banyak peran di industri seperti bidang Kesehatan, Ilmu Ekonomi, Psikolog, dan Teknologi yang dapat membantu manusia dalam memecahkan suatu masalah dalam kehidupan. Dalam penerapan logika fuzzy terdapat beberapa proses, salah satunya yaitu sistem inferensi. Sistem inferensi merupakan kerangka komputasi yang didasarkan pada teori himpunan fuzzy, aturan fuzzy berbentuk IF-THEN, dan penalaran fuzzy. Manfaat dari inferensi fuzzy yaitu sebagai alat untuk mewakili pengetahuan yang berbeda tentang suatu masalah, serta untuk memodelkan interaksi. Dengan menggunakan metode penelitian studi literatur dari beberapa sumber, ditemukan banyak produk yang dikembangkan dari logika fuzzy seperti pengambilan keputusan, penentuan atau penilaian hasil, perangkat kendali jarak jauh, alat ukur, dan sistem pakar.

Penentuan Jurusan Siswa Sekolah Menengah Atas menggunakan Metode Fuzzy Tsukamoto

According to the Regulation of the Minister of National Education (Permendiknas) Number 22 of 2006, the determination of majors is carried out at the end of the second semester of class X and the implementation of Teaching and Learning Activities (KBM) according to the program majors starts in the first semester of class XI. In fact, there are still many high school students who are confused about choosing a major in a tertiary institution and this phenomenon can be seen in high school students. There are several majors in high school programs such as Natural Sciences (IPA), Social Sciences (IPS), and Language. This research is expected to be able to determine the majors according to the abilities of the new students for the process of selecting majors and provide recommendations that help students in determining the majors in SMA using the Fuzzy Tsukamoto method. The Tsukamoto method is an extension of monotonous reasoning. In the Tsukamoto method, each consequence of the IF-THEN rules must be represented by a fuzzy set with monotonous membership functions assisted by system design using the programming language PHP, HTML, Javascript, and MySQL database, resulting in a decision making system using the fuzzy method. tsukamoto which is a useful website for determining student majors so that it can lighten the work of the school in order to help speed up and make it easier for schools to make decisions in choosing majors.

Sistem Pendukung Keputusan Prediksi Harga Rumah Kost untuk Mahasiswa IT Telkom Purwokerto Menggunakan Metode Fuzzy Tsukamoto Berbasis Web

Purwokerto City is a developing city located in the southwestern part of Central Java Province. Purwokerto is known as thecity of students in Central Java. It is not wrong if many newcomers choose to continue their studies at the favoriteuniversities in this city. One of the universities in this city is the Telkom Purwokerto Institute of Technology. With so manynewcomers who want to continue their studies in this city. Of course, you need a place to live like a boarding house. Eachboarding house has different facilities and also has varying prices, making it difficult for newcomers to choose the boardinghouse. So a decision support system is needed to help students of the Telkom Purwokerto Institute of Technology to make theright decision in predicting the price of a boarding house when choosing a boarding house according to the existing criteriaand funds using the Fuzzy Tsukamoto method.

Analisis Sentimen Masyarakat Terhadap COVID-19 Pada Media Sosial Twitter

Akhir tahun 2019 lalu dunia digemparkan oleh munculnya suatu penyakit yang disebabkan oleh virus SARS-CoV-2 yang merupakan jenis virus terbaru dari coronavirus. Penyakit ini dikenal dengan nama COVID-19. Penyebaran penyakit ini terbilang cukup luas dan cepat. Dalam waktu singkat penyakit ini mulai menyebar ke segala penjuru dunia tak terkecuali Indonesia. Dengan tingkat penyebaran yang begitu tinggi dan belum ditemukannya vaksin untuk COVID-19, menyebabkan kekacauan di tengah masyarakat. Hal ini mempengaruhi banyak sektor kehidupan masyarakat. Tak sedikit masyarakat yang aktif bersosial media dan menuliskan pendapat, opini serta pemikirannya di platform media sosial seperti Twitter. Terjadinya pandemi ini mendorong masyarakat untuk menuliskan opini, pemikiran serta pendapatnya terhadap COVID-19 pada media sosial Twitter. Dibutuhkan suatu model sentiment analysis untuk mengklasifikasi tweet masyarakat di Twitter menjadi positif dan negatif. Sentiment analysis merupakan bagian dari Natural Language Processing yang membuat sebuah sistem guna mengenali serta mengekstraksi opini dalam bentuk teks. Pada penelitian ini digunakan algoritma Naive Bayes dan K-Nearest Neighbor untuk digunakan dalam membangun model sentiment analysis terhadap tweet pengguna Twitter terhadap COVID-19. Didapatkan akurasi sebesar 85% untuk algoritma Naïve Bayes dan 82% untuk algoritma K-Nearest Neighbor pada nilai k=6, 8, dan 14.

RANCANG BANGUN SISTEM KEAMANAN RUMAH AUTENTIFIKASI FINGERPRINT BERBASIS TELEGRAM MONITORING DENGAN PENGUATAN KAMERA SEBAGAI REKAM WAJAH

Alat yang saya buat disini menjadi inovasi dimasa yang akan datang,yaitu dengan keamanan pintu di rumah,dimana ketika pemilik rumah sedang tertidur atau pun sedang menjalankan kegiatan di luar rumah,dengan adanya alat saya di sini membantu si pemilik rumah memonitoring keadaan rumah memlalui pintu,alat yang saya buat terhubung pada telegram dimana ketika data masuk akan terkirim di telegram,jika si calon autentikasi belum terdaftar maka pintu tidak akan terbuka,meminimalisir kejahatan melaui alat saya,dalam alat saya terdapat fingerprint dan camera,selain autentikasi di fingerprint alat saya juga terdapat camera yang akan mengcapture wajah siapa saja yang masuk kerumah melalui proses yang benar atau berusaha memaksa masuk melalui pintu

Hasil Klasifikasi Algoritma Backpropagation dan K-Nearest Neighbor pada Cardiovascular Disease

Cardiovascular disease adalah penyakit yang diakibatkan oleh kelainan yang terjadi pada organ jantung. Cardivascular disease dapat menyerang manusia dari usia muda hingga usia tua yang terdapat 13 faktor yang mempengaruhinya yaitu Age, Sex, Chest pain, Trestbps, Chol, Fbs, Restecg, Thalach, Exang, Oldpeak, Slope, Ca, dan Thal. Cardiovascular disease beragam jenisnya antara lain penyakit jantung koroner, gagal jantung, tekanan darah tinggi, tekanan darah rendah dan lain-lain. Oleh karena itu, penelitian ini memiliki tujuan untuk melakukan klasifikasi terhadap cardiovascular disease. Pada penelitian ini menggunakan algoritma backpropagation dan algoritma K-nearest neighbor. Langkah awal dilakukan adalah proses perhitungan euclidean distance pada K-NN untuk mencari jarak k terdekat untuk mendapatkan kategori berdasarkan frequensi terbanyak dari nilai k yang ditentukan dan mencari bobot baru untuk algoritma backpropagation untuk mendapatkan bobot baru yang digunakan untuk mendapatkan nilai yang sesuai dengan yang diharapkan. Pengujian sistem ini terdiri dari pengujian nilai akurasi dengan nilai K, pengujian K-fold X validation dan pengaruh hidden layer. Hasil dari Penelitian ini bahwa algoritma backpropagation menghasilkan nilai akurasi sebesar 64%, presisi sebesar 62%, recall sebesar 64% dan algoritma K-nearest neighbor menghasilkan nilai akurasi sebesar 66%, presisi sebesar 61% dan recall sebesar 66%. Pengaruh hidden layer terhadap algoritma backpropagation dalam mengklasifikasikan cardiovascular disease sangat besar hal ini sesuai dengan hasil dari penelitian yang telah dilakukan bahwa ketika jumlah hidden layer kecil, nilai yang dihasilkan juga kecil akan tetapi ketika jumlah hidden layernya tinggi nilai akurasinya bahkan menjadi rendah .

Pengenalan Jenis Kelamin Manusia Berbasis Suara Menggunakan MFCC dan GMM

Biometric information that exists in humans is unique from one human to another. One of the biometric data that is easily obtained is the human voice. The human voice is identic data that can differentiate between individuals. When we hear human voices directly, it is easy for our ears to tell the person who is speaking is male or female. But sometimes male voices can resemble girls and vice versa. Therefore, we propose a human voice detection system through Artificial Intelligence (AI) in machine learning. In this study, we used the Mel Frequency Cepstrum Coefficients (MFCC) method to extract human voice features and Gaussian Mixture Models (GMM) for the classification of female or male voice data. The experiment results showed that the system built was able to detect human gender through biometric voice data with an accuracy of 81.18%.

Perancangan Aplikasi Kamus Online Informatika-Indonesia Beserta Fungsinya Berbasis Web Menggunakan Metode Sequential Search

In this era of digital optimization, Information and Communication Technology is growing very rapidly. This is in line with the demands and human needs that have been actualized in various fields, such as knowledge and education. To support a learning process based on SCIENCE (Science and Technology) required several supporting aspects such as online dictionary that includes vocabulary and functions of words / terms in the FIELD of IT. One of the supporting aspects is an alternative tool in the form of media that facilitates every community in learning the terms in the field of informatics. According to pie chart data from questionnaires that the authors made, as much as 50 percent of the knowledge of the term informatics of the general public (lay people) can be said to be still very low. In contrast to the academic community such as IT Lecturers and IT Students who do master the field, although it does not close the possibility there are some IT Students who do not fully understand in their fields. The expected result of the authors in this study is the increasing knowledge, especially the general public (lay people) in studying science in the field of IT especially language and informatics terms through online disses. This Online Dictionary application will be designed website-based using sequential search method where sequential search (also called linear search) is the most simple search model performed on a data set. The Online Dictionary application will run by searching for vocabulary or terms in informatics according to the keywords they are looking for, making it easier for users to learn the language of informatics. Keywords: Website, Vocabulary, Dictionary Online, Informatics, IT, Sequential Search, Science and Technology