JMAI (Jurnal Multimedia & Artificial Intelligence) <h3>JMAI atau Jurnal Multimedia and Artificial Intelligent mengundang peneliti untuk mempublikasikan hasil karya penelitiannya. JMAI mengundang tulisan dengan fokus tema 5 bidang :</h3> <p>1. Artificial Intelligent dan implementasinya</p> <p>2. Computer vision and pattern recognition</p> <p>3. Multimedia</p> <p>4. Expert system</p> <p>5. Big Data and Data analysis</p> <p>Paper yang disubmit ditulis dalam bahasa indonesia dan abstrak dua bahasa inggris dan indonesia serta melalui proses review minimal 1 nasional reviewer.</p> <p>Terbit setiap Februari dan Agustus</p> LPPM Universitas Mercu Buana Yogyakarta en-US JMAI (Jurnal Multimedia & Artificial Intelligence) 2580-2593 Evaluation of Academic Information System of Mercu Buana University Yogyakarta Using UTAUT2 One form of the adoption of the College Information Technology (IT) is Academic Information System (SIA) at the University of Mercu Buana Yogyakarta (UMB Yogyakarta). After a few improvements in 2016 and 2017, Directorat ICT felt need to conduct a SIA evaluation with the intention to know the level of admission of students in the use of SIA in Yogyakarta UMB to be the cornerstone in Next development. One of the suitable models for the evaluation of the user's acceptance of technology is a model developed by Venkatesh et al in 2012 which was named the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The test equipment used in this research is SPSS for validity testing and realibility testing, as well as SmartPLS for final tests. Based on the results of the analysis, this study has eight conclusions of the ten accepted hypotheses. Further intentions of student behaviour and behaviour in the use of SIA are medium or moderate category. Further intentions of student behaviour and behaviour in the use of SIA are medium or moderate category. Keywords: SIA UMB Yogyakarta; UTAUT2; SPSS; SmartPLS; Validity; Reliability. DAVID HADIANSYAH ##submission.copyrightStatement## 2020-04-21 2020-04-21 4 1 1 12 10.26486/jmai.v4i1.108 M Model RGB, CV, Indeks R, Indeks G, Indeks B, HSI Dan Metode Wavelet Daubechies Untuk Identifikasi Jenis Daging Sapi Untuk Mendapatkan Kualitas Daging Terbaik This image identification application can adjust to the current needs of the community in choosing the type of beef. Unfortunately, this development has not been used optimally to choose the type of beef. This is because the quality of beef is not good enough. This paper proposes a solution by calculating the values of R, G and B on each image of the flesh, then normalizing the process to get the index value R, index G and index B and the conversion process from the RGB model to the HSI model to obtain the value of Hue, Saturation and Intensity. The purpose of this study is to provide the best quality beef. This research uses RGB, CV, R Index, G Index, B Index, HIS wavelet daubechies method. This research contributes to the provision of beef-sorting services. Kiswanto Kiswanto fitriyanti fitriyanti Benny Wijaya ##submission.copyrightStatement## 2020-04-21 2020-04-21 4 1 13 20 10.26486/jmai.v4i1.110 Application of Steganography for Inserting Text Messages in Digital Images Using the Least Significant Bit Method The development of digital media (Internet, electronic mail, and so on) gas data is already common, along with such developments, crimes in the field of information technology and telecommunication increasingly occur. Digital data commonly used is digital imagery, digital imagery that is transmitted through the media can be important data, so there is a problem arises how to secure digital imagery is confidential. One ofhis ways is steganography. The goal in this study inserts text messages using a steganography technique with the Least Significant Bit method on the digital Image media. The Least Significant Bit Method performs the insertion of a text message into a digital image by changing the value of the pixel to 8 bits then taking the leading 4 bits to be inserted at 4 the last bit at 8 bit pixels, the process of inserting a text message on digital imagery will be divided into three layers namely layer Red, layer Green, layer Blue . Once the digital image is saved, the extract process is aimed at retrieving text messages that are already stored in the digital image. In this test there are two images used that image size 325x325 pixels and image size 473x354 pixels each image is performed three times the insertion of text messages different number of characters ranging from three words to one paragraph. The image encryption process that becomes the container is not significantly different from the original, for image description results that have been inserted in a hidden text message can be returned with a change in the pixel value that does not alter the image Significant. Nasrullah Akbar Ramadhani Indah Susilawati ##submission.copyrightStatement## 2020-04-21 2020-04-21 4 1 21 27 10.26486/jmai.v4i1.99 association rule Implementation of Data Mining to Determine Book Placement Recommendation Based on Lending Pattern Using Association Rule Library book lending data is increasing, thus a processing to make the lending transaction record data into information is required to help library visitor find books by finding relation with book borrowed at the same time. The relation of borrowed book item was found by analyzing library book lending data from 2014 to March 2019. The data was cleaned to select the attributes of id member, book code, book title and inconsistent writing, then the data was grouped into one single transaction during book lending in the library and transformed into tabular data to calculate the itemset of books borrowed at the same time. Association rules were made using data which had been grouped and transformed into one tabular data transaction during lending, resulting in 2225 transaction data with 0.01 support and confidence by putting the limit of 50 association rules with the highest role being lending communication science book with psychology book with support x confidence of 8.17% Yusuf Nawawi ##submission.copyrightStatement## 2020-04-21 2020-04-21 4 1 28 33 10.26486/jmai.v4i1.105 Prototype Design of Login Security Using Face Biometrics With the Eigenface Method Login security is a major problem when using a device that is connected in an outside network or internet network. Therefore a data security using face biometrics is performed. Eigenface is a face recognition method based on the Principal Component Analysis (PCA) algorithm. In short the process is that the image is represented in a combined vector which is made into a single matrix. From this single matrix, we will extract a main feature that will distinguish between one face image and another face image. In using the biometric login system this face is the user registering to the system then the user's face will be trained so that the user will be recognized by the system for login purposes. When a user logs in, the user's face data will be processed in real time and matched with the data in the database so that if the data match, the user will successfully log in. The standard face distance from the webcam is 50-60 cm, while the minimum exposure level of the face that can be recognized is 5 lux, and the angle of the face that the system can still recognize is 40 °. sugeng widodo ##submission.copyrightStatement## 2020-04-21 2020-04-21 4 1 34 41 10.26486/jmai.v4i1.102