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Dalam memulai pengembangan perangkat lunak, salah satu poin terpentingadalah menentukan arsitektur teknologi sesuai dengan analisa kebutuhan produk.Sehingga nantinya dapat berjalan selaras bersamaan dengan visi produk tersebut.Namun, seiring berjalannya waktu dengan user dan data yang semakin bertambahperlu ada perombakan arsitektur kembali, dengan membangun pondasi yang lebihkokoh. Hal ini dialami oleh perusahaan startup sosial Campaign.com.Campaign.com merupakan sebuah aplikasi untuk mengambil aksi sosial yang dapatmenyalurkan donasi dari sponsor. Desain sistem yang dibangun di campaign.commasih menggunakan arsitektur monolitik. Antarmuka pengguna, pemrosesanlogika, dan akses data digabungkan menjadi satu program dan ditempatkan dalamsatu basis data. Namun hal ini membuat aplikasi sering mengalami bugs dan serverdowntime. Dengan masalah yang sedang dihadapi ini penulis mencoba melakukaneksperimen dengan merancang dan menganalisa sistem arsitektur backend. Tujuanyang ingin dicapai dari perancangan arsitektur ini adalah mendeskripsikan prosespenyederhanaan dari sebuah sistem arsitektur backend microservice agar mudahdalam pemeliharaan sistem dan penggunaan algoritma Docker yang akan membuatsistem menjadi efisien terhadap penulisan kode.

Pulse Coupled Neural Network (PCNN) is claimed as a third generation neural network. PCNN has wide purpose in image processing such as segmentation, feature extraction, sharpening etc. Not like another neural network architecture, PCNN do not need training. The only weaknes point of PCNN is parameter tune due to seven parameters in its five equations. In this research we proposed a novel method for segmentation based on modified PCNN. In order to evaluate the proposed method, we processed L Band Multipolarisation Synthetic Apperture Radar Image. The Results showed all area extracted both by using PCNN and ICM-PCNN from the SAR image are match to the groundtruth. There fore the proposed method is work properly.Copyright © 2017 International Journal of Artificial Intelegence Research.All rights reserved.

As the IT operation in the other Enterprise, the implementation of IT in Higher Education has to be directed and aligned with organizational strategy and program. The strategic alignment is one of five IT Governance focus areas. This paper presents the results, discussions and recommendations of IT Governance in Higher Education self assessment which is performed by COBIT 4.1 framework. The assessment is performed to IT Governance implementation in Mercu Buana University as a case study. The study result shows that the implementation of IT Governance in the university is still in the first stage of its development. Based on these results and some evidences collected, the study proposes some improvements such: it is needed to provide IT master plan, data and process custodian settlements must be performed, and the setup of such organizational structure which has capabilities enough to coordinate and deal with process / data owner and key user to drive University's IT Governance. 

This paper proposed a texture's feature of gray-level co-occurrence matrix (GLCM) as a calibrator of the sea wave height. Texture in Synthetic Aperture Radar (SAR) images represent the surface roughness of the sea or the wave height. As an archipelago country which has 70% sea of entire region, Indonesia needs and must have early warning system to provide transportation and fisherman safety circumvent the accident. Object of research are the P band full polarization Synthetic Aperture Radar (SAR) image acquired from coastal of East Kalimantan. These polarization are; horizontal-horizontal, horizontal-vertical, vertical-horizontal and vertical-vertical. Extraction of feature is done under observation angle 0° and adjacent pixels is 1. The results showed homogeneity is a consistent and toughest feature in horizontally-vertically polarization and vertical-vertical polarization and this feature can be used as a calibrator.

The features texture in the textured images could be extracted by using grey level co-occurence matrix (GLCM). GLCM was a such kind of good descriptor for textured images, which has two variables in observation window such as angle and distance of pixels. This research observed the results of features texture for four different observation angle in the window of GLCM such as 0°, 45°, 90° and 135°. The object in this reserach was the textured image of macroscopic jati wood (Tectona grandy), a such kind of good wood from Indonesian forest. The extracted texture features were contrast, correlation, energy and homogeneity. The results showed that contrast had a biggest value in direction of 45°, the other features correlation, energy and homogeneity had the biggest value both in direction of 0°.