An Advantage of Digital Book for Business Education in Indonesia Country

The main objective of this paper is to see the opportunity of a business education about digital book that consist of media education in Indonesia country. As we know the technology of a digital book for multimedia learning are still rare use by Indonesia educational teachers, the purpose is to determine the profit business in the future for making of digital book. The research design consisted of development design. The methodology analysis that will use in this research is SWOT (Strength, Weakness, Opportunity, Threats). The result of a research is finding that the business of digital book for learning tools in Indonesia country still open wide. Recommendations have been given on the basis of findings

Aplikasi Pengembangan Audiovisual sebagai Media Alternatif Penyampaian Materi Kuliah Multimedia Berbasis Web (Studi Kasus STMIK AMIKOM)

The use of video in learning has become commonly used in education today. With the more general use of online learning in education, it is a certainty streaming video and audio media will have a very important role in the delivery of teaching materials to students online. There have been many streaming media with the English language made by faculty or practitioners outside of IT that can be seen on youtube and various other web media but still rarely speak Indonesian media streaming. The purpose of this study is to produce course material presented by the lecturer in the form of Indonesian language streaming video uploaded to the web in order to help the students to know and learn what material has been presented by the lecturer when they can not follow the specified schedule. The target of this study were students. Activity plan consists of two activities, among others: the making of video streaming will be done by following the stages of pre-production, production and post-production and placement on the web that will be used as a medium to deliver information for the student

Image watermarking based on integer wavelet transform-singular value decomposition with variance pixels

With the era of rapid technology in multimedia, the copyright protection is very important to preserve an ownership of multimedia data. This paper proposes an image watermarking scheme based on Integer Wavelet Transform (IWT) and Singular Value Decomposition (SVD). The binary watermark is scrambled by Arnold transform before embedding watermark. Embedding locations are determined by using variance pixels. Selected blocks with the lowest variance pixels are transformed by IWT, thus the LL sub-band of 8�8 IWT is computed by using SVD. The orthogonal U matrix component of U3,1 and U4,1 are modified using certain rules by considering the watermark bits and an optimal threshold. This research reveals an optimal threshold value based on the trade-off between robustness and imperceptibility of watermarked image. In order to measure the watermarking performance, the proposed scheme is tested under various attacks. The experimental results indicate that our scheme achieves higher robustness than other scheme under different types of attack. Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved

Identifikasi Penyakit Tanaman Jagung Berdasarkan Citra Daun Menggunakan Convolutional Neural Network

Komoditas jagung di Indonesia menjadi tanaman pangan terbesar kedua setelah padi sebagai sumber karbohidrat. Namun dikarenakan keterbatasan kemampuan petani dan faktor lingkungan menyebabkan upaya penanganan tanaman jagung akibat adanya serangan organisme pengganggu tanaman menjadi terhambat. Penelitian ini mengusulkan upaya deteksi secara dini terhadap jenis penyakit pada daun tanaman jagung menggunakan metode Convolutional Neural Network (CNN) yang dikenal sebagai algoritma pembelajaran mesin berkinerja tinggi dalam mengklasifikasikan jenis penyakit tanaman ke dalam beberapa kelas seperti Blight, Common Rust, Grey Leaf Spot, dan Healthy. Selain itu, transformasi warna citra dari RGB, HSV dan Grayscale, proses segmentasi dengan Region of Interest (ROI) serta dilengkapi dengan penerapan ektraksi fitur tekstur dengan menggunakan GLCM telah mampu menghasilkan tingkat akurasi sebesar 94% dan nilai loss rate yang relatif kecil yaitu 0.1742. Hasil penelitian ini menunjukkan bahwa penggunaan metode CNN terbukti secara efisien & efektif dalam melakukan identifikasi jenis penyakit tanaman

Sentiment Analysis of BNI Mobile Application Using The K-Nearest Neighbor Algorithm (KNN) With Particle Swarm Optimization (PSO) Feature Selection

Analysis sentiment is field studies analyze opinions, sentiments, evaluations, attitudes and emotions to entity like products, services, organizations, individuals, issues, events, films and topics. Sentiment analysis first succeed used previously in various fields, such as movie ratings, service ratings, product ratings, etc. and recently This get popularity in the field economy especially on e- commerce applications. Moment This industry banking do various innovation finance that is shift their focus from banking traditional to banking based technology for fulfil need customers as well as For increase Power competitive. Mobile banking is one of them from innovation that. Response in use of this mobile banking application enter every the day with amount response as much hundreds so that response the difficult For sorted become responses included positive or including negative response. Study This using private data which is comment BNI Mobile banking application in the application laystore. Existing data Then will be done preprocessing with do a number of stages, ie started from tokenization, stemming, stopword removal and Term Frequency Inverse Document Frequency (TF-IDF) was carried out. Initial process carried out in classification is accept input comment data then the preprocessing process is carried out, then included in the classification model, method classification used is K-Nearest Neighbor with particle swarm optimization Optimization and finally is the results issued is accuracy from method used. After That researcher do optimization use one algorithm optimization namely PSO with combine with KNN or called KNN-PSO gain accuracy of 92.33% or only has an error of 7.67%. If seen from the amount of data is successful do classification as many as 277 data, in meaning only has 23 errors or missing data succeed classified with good

An Improved Image Watermarking by Modifying Selected DWT-DCT Coefficients

Digital images can be easily copied or manipulated by irresponsible persons. The right property needs to be secured and protected from illegal copies and piracy. Digital watermarking is one of the solutions to protect the intellectual property of digital images. This paper proposed the adaptive scaling factor based on selected DWT-DCT coefficients of its image content. The adaptive scaling factor was generated based on the role of selected DWT-DCT coefficients against the average value of DWT-DCT coefficients. The watermark image was embedded by using a proposed set of rules that consider the adaptive scaling factor. The experimental results showed that the proposed scheme achieved high PSNR value of 47dB, SSIM value of about 0.987 and an embedded watermark resistance to several attacks in the watermarked image

Detect Fake Reviews Using Random Forest and Support Vector Machine

With the rapid development of e-commerce, which makes it possible to buy and sell products and services online, customers are increasingly using these online shop sites to fulfill their needs. After purchase, customers write reviews about their personal experiences, feelings and emotions. Reviews of a product are the main source of information for customers to make decisions to buy or not a product. However, reviews that should be one piece of information that can be trusted by customers can actually be manipulated by the owner of the seller. Where sellers can spam reviews to increase their product ratings or bring down their competitors. Therefore this study discusses detecting fake reviews on product reviews on Tokopedia. Where the method used is the distribution post tagging feature to perform detection. By using the post tagging feature method the distribution got 856 fake reviews and 4478 genuine reviews. In the fake reviews, there were 628 reviews written with the aim of increasing product sales or brand names from store owners, while there were 228 reviews aimed at dropping their competitors or competitors. Furthermore, the classification is carried out using the random forest algorithm model and the support vector machine. By dividing the dataset for training data by 80% while 20% for data testing. Here it is known that the support vector machine gets much higher accuracy than the random forest. The support vector machine gets an accuracy of 98% while the random forest gets an accuracy of 60

An improved robust watermarking scheme using flexible scaling factor

Digital watermarking is needed to avoid piracy, forgery and illegal distribution from unauthorized people. The watermarking scheme is used to protect the ownership and copyright information in the multimedia data. A scaling factor plays an important role for balancing between invisibility and robustness for embedding watermark. However, the usage of a scaling factor may not be suitable for different selected blocks and image inputs. Flexible scaling factor is an alternative solution to obtain high robustness and invisibility in image watermarking. This research proposed a flexible scaling factor for DCT coefficients based on the image content itself. This research analyses the selected DCT coefficients against average coefficients on its block to obtain flexible scaling factor. The proposed scheme produced high invisibility with SSIM and PSNR values of 0.991 and 45dB, respectively. The proposed watermarking scheme also achieved strong resistant against noised image, filtered image and compressed image

An improved robust image watermarking by using different embedding strengths

Image watermarking technique is an alternative solution to protecting digital image copyright. This paper proposed a new embedding technique based on different embedding strengths for embedding a watermark. An image is divided into non-overlapping blocks of 8 × 8 pixels. The variance pixel value was computed for each image block. Image blocks with the highest variance value were selected for the embedding regions. Therefore, it was transformed by discrete cosine transforms (DCT). Five DCT coefficients in the middle frequency were selected and the average of selected DCT blocks was calculated to generate different embedding strengths by using a set of rules. The watermark bits were embedded by using a set of embedding rules with the proposed different embedding strengths. For an additional security, the binary watermark was scrambled by using an Arnold Transform before it was embedded. The experimental results showed that the proposed scheme achieved a higher imperceptibility than the other existing schemes. The proposed scheme achieved a watermarked image quality with a PSNR value of 46 dB. The proposed scheme also produced a high watermark extracting resistance under various attacks

Adaptive scaling factors based on the impact of selected DCT coefficients for image watermarking

Image watermarking technique aims at high imperceptibility of the embedded watermark with minimal distortion in the watermarked images. In frequency-domain, block-based Discrete Cosine Transform (DCT) is a popular method which can be improved by different scaling factors. This paper presents an adaptive scaling factor for selected DCT coefficients in image watermarking. The image blocks that have lowest pixel variances are chosen as the embedding locations. The optimal scaling factors for selected DCT coefficients on the middle frequencies are obtained by finding the best quality of images. The embedding process is performed using the obtained scaling factors. The proposed technique was investigated to verify the robustness and imperceptibility against various image-processing attacks. It is proved that our technique achieves higher robustness against noise addition, filter and compression than the existing schemes in most cases. Our technique produces greater imperceptibility than the existing schemes