Yayasan Prima Unggul (YPU) merupakan sekolah berbasis kewirausahaan yang ingin mewujudkan impian untuk melahirkan 10000 emterpreneur baru dari panti asuhan dan keluarga kurang mampu. Permasalahan yang dihadapi adalah kurangnya tenaga profesional untuk bidang pengembangan dan pendampingan kewirausahaan. Kegiatan ini bertujuan untuk mengadakan pelatihan tentang desain grafis menggunakan perangkat Adobe Photoshop untuk melakukan manipulasi foto bagi tim teknologi informasi Yayasan Prima Unggul tanggal 13 Maret 2014 di laboratorium komputer Kalbis Institute Jalan Pulomas Selatan Kav.22. Pulomas, Jakarta Timur. Pelatihan diberikan oleh dosen Program Studi Sistem Informasi Kalbis Institute.

<span>Image segmentation is often faced by low contrast, bad boundaries, and inhomogeneity that made it difficult to separate normal and abnormal tissue. Therefore, it takes long periodto read and diagnose brain tumor patients. The aim of this study was to applied hybrid methods to optimize segmentation process of magnetic resonance image of brain. In this study, we divide the brain tumor images with double density dual-tree complex wavelet transform (DDDTCWT), continued by convolutional neural network (CNN), and optimized by genetic algorithm (GA) with 48 combinations yielding excellent results. The F-1 score was 99.42%, with 913 images test data. The training images consist of 1397 normal MRI images and 302 tumor magnetic resonance imaging (MRI) images resized by 32 x32 pixels. The DDDTCWT transforms the input images into more detail than ordinary wavelet transforms, and the CNNs will recognize the pattern of the output images. Additionally, we applied the GA to optimize the weights and biases from the first layer of the CNNs layers. The parameters used for evaluating were dice similarity coefficient (DSC), positive present value (PPV), sensitivity, and accuracy. The result showed that the combination of DDDTCWT, CNN, and GA could be used to brain MRI images and it generated parameters value more that 95%.</span>

Pada era Revolusi Industri 4.0, teknologi terus berkembang semakin canggih seperti teknologi internet, komputasi awan, dan algoritma machine learning. Teknologi tersebut menjadi salah satu komponen penting perkembangan keilmuan di perguruan tinggi. Dengan internet, banyak sekali literasi berbasis dijital yang dapat dimanfaatkan oleh mahasiswa untuk menambah wawasan atau pengetahuannya. Tetapi sumber literasi yang beredar kurang sistematis atau urutan materi yang kurang tepat. Selain itu, materi tersebut kurang terstruktur atau kurang sesuai dengan capaian pembelajaran mata kuliah yang telah ditentukan. Ada banyak sekali materi literasi yang beredar tetapi belum dapat dipastikan kebenaran dan kevalidan dari materi literasi tersebut karena kebanyakan materi literasi tidak menyertakan sumber referensi. Kondisi seperti ini membuat mahasiswa bingung ketika mengakses materi tersebut. Mahasiswa tidak dapat memastikan tingkat kebenaran dan ketepatan dari materi tersebut. Oleh karena itu, penelitian ini mengusulkan sebuah media literasi dijital berbasis teknologi yang dapat dikustomisasi sesuai kebutuhan perguruan tinggi baik dari sisi isi, struktur maupun atribut lainnya. Hal ini berarti bahwa materi literasi yang disajikan dapat disesuaikan dengan capaian pembelajaran yang telah dirumuskan oleh institusi. Sehingga tujuan dari penelitian ini adalah pembuatan sebuah media literasi dijital yang menyajikan materi pembelajaran secara sistematis dan terstruktur bagi mahasiswa di perguruan tinggi. Sistem literasi dijital ini dibangun dengan menggabungkan metode R&D dan MDLC.

This research is intended to evaluate the development of mobile multimedia based stop drug tutorial.  This tutorial as a campaign to stop drugs, that should encourage people’s ability to integrate all information on mobile application. The tutorial focuses on how people understand about drugs and what to do if someone is drugs addicted.  Stopping drug tutorial is created using ADDIE instructional development method, and during the developing stage, it is done using Multimedia Development Life Cycle according to Luther. Subjects of the research are experts in education, visual communication and information technology in the preliminary testing. Evaluation was conducted using the analytic descriptive method on mobile multimedia evaluation method, and interpreted in a narrative way based on the research findings. The evaluation of mobile multimedia application uses combination of multimedia evaluation that is used by educationalist with ISO 9126 that was used by software developer. The research findings show that mobile multimedia stop drugs application can be used with minor revision.

Big data is defined as a very large data set (volume), velocity and variety. Big data analytics systems must be supports for parallel processing and large storage. The problem of this research is how to identify measurement metric based on big data analytics system characteristic. One device that support big data platform is Hadoop. Measurement is a process for assigning values or symbols to the attributes of an entity. The purpose of measurement is to distinguish between entities one to another. Indicator for software measurement represented with a metric. The aim of this research is to proposes some measurement metric for big data analytics system. This research using UML exactly a class diagram in system modelling to identify the measurement metric. Both of dynamic and static metric is proposed as solution to measure big data analytics system. Result for this researh are some measurement ndicator both of dynamic and static metric based on class diagram for big data analytics. CCS Concepts • Software and its engineering➝ Software creation and management • Design Software ➝ Software Design Engineering.