The increasing use of computers and the internet has resulted in an increasing trend of computer crimes. This is the reason computer security is becoming important. A computer security system should be able to provide some kind of information assurance such as confidentiality, integrity, availability, authenticity and non-repudiation of data. The method used to help meet the authenticity of information assurance is biometric-based authentication, among others, a two-dimensional (2D) face recognition system, but it can make mistakes in recognition. The intruder is also easier to enter the system if has a photo print from the user's face. To overcome these deficiencies can be use a three-dimensional (3D) face recognition system. This research did three-dimensional (3D) face recognition by not doing 3D face reconstruction. But using face data got from camera ToF i.e. distance, amplitude, and intensity from each image pixel as input data. The hypothesis was face recognition execution speed faster and similar accuracy when compared with research conducted by Zhang and Lu. The algorithm used in this research, is back propagation neural networks algorithm and Principal Component Analysis (PCA). Obtained accuracy of 95% and training time of 9728 seconds. Face recognition in this study has a lower accuracy level than previous research but faster face recognition speed.

Computer needs at work are very helpful and make easier for human to complete his work. The usageof laptops growing rapidly with increasing mobility of the community who uses laptop to run the activities. In addition, laptop continues to update its technology with the variation of the specification so that it can attract the interest of consumers, especially for students, but the variety of laptops is confusing for some users to choose. Based on a survey that has been done to the students, it concluded that laptop is 80% more interesting than desktop computer. Some students really need a recommendation system for choosing alaptop. In making a recommendation system, using TOPSIS method is the recommended one because the concept is simple, easy to understand, efficient, and have the ability to measure the relative performance of alternatives decision. According to the implementation, the recommendation system with TOPSIS method has 70% accuracy rate. Index Terms”System Recommendation, TOPSIS, Laptop, REFERENCES [1] Hendra, dkk. 2007. "Keluhan Kesehatan pada Penggunaan Laptop pada Mahasiswa FKM UI”. (pdf). Depok: Universitas Indonesia. [2] Paays, N. 2013. Rancang Bangun Meja Laptop Yang Adjustable Berdasarkan Aspek Ergonomi. Pontianak: Universitas Tanjungpura. [3] Iqbal, M. 2014. Perilaku Pembelian Laptop Oleh Mahasiswa Strata 1 Universitas Brawijaya Malang. S1 thesis. Malang: Universitas Brawijaya. [4] Setiawan, H. 2014. Rancang Bangun Aplikasi Rekomendasi Pembelian Laptop Dengan Metode Fuzzy Database Tahani Model Berbasis Web (Studi Kasus: Toko Ricky Komputer). S1 thesis. Tangerang: Universitas Multimedia Nusantara. [5] Fitriani, S. A. 2014. Perbandingan Metode Weighted Product dengan Metode Technique for Order Preference by Similarity to Ideal Solution dalam Pendukung Keputusan Perekruten Siswa/Mahasiswa Praktek Kerja Lapangan. S1 thesis. Bandung : Universitas Pendidikan Indonesia. [6] Buaton, R.2014. 15 Metode Menyelesaikan Data Mining, Sistem Pakar, dan Sistem Pendukung Keputusan (.pdf). Medan. [7] Salehah, A. 2014. Penerapan TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) Untuk Seleksi Penerimaan Beasiswa (Studi Kasus Pendaftar Beasiswa dari Fakultas MIPA di Universitas Brawijaya). S1 thesis. Malang : Universitas Brawijaya. [8] Gay, L.R. dan Diehl, P.L. (1992), Research Methods for Business and. Management, MacMillan Publishing Company, New York

Sistem Informasi Pemerintah Daerah (SIPD) adalah suatu Sistem yang mendokumentasikan, mengadministrasikan, serta mengolah data pembangunan daerah menjadi informasi yang disajikan kepada masyarakat dan sebagai bahan dalam pengambilan keputusan. Data SIPD terdiri dari 8 kelompok data, yaitu (Data Umum, Sosial Budaya, Sumber Daya Alam, Infrastruktur, Ekonomi, Keuangan daerah, Politik/hukum/Keamanan dan Insidental, serta 31 jenis data dan 2691 Elemen data. Pemerintah Kabupaten Tangerang telah bekerjasama dengan Universitas Multimedia Nusantara (UMN) untuk mengembangkan SIPD Kabupaten Tangerang. Untuk selanjutnya SIPD berbasis web tersebut telah diimplmentasikan dan berhasil dioperasionalkan oleh Tim UMN. Langkah-langkah implementasi SIPD meliputi penetapan Domain Name (nama domain internet untuk diakses oleh pengguna), hosting sistem, dan pelatihan operator. Adapun Domain Name telah diputuskan menggunakan nama URL sipd.tangerangkab.go.id. Sedangkan hosting sistem telah dilakukan pada server di Dinas Komunikasi dan Informatika Kabupaten Tangerang. Pelatihan operator telah dilakukan pada Bulan Januari 2019 dalam dua kelompok, yaitu kelompok operator dari dinas-dinas di Kabupaten Tangerang, dan kelompok operator dari kecamatan-kecamatan di Kabupaten Tangerang. Sistem Informasi Pemerintah Daerah (SIPD) adalah suatu Sistem yang mendokumentasikan, mengadministrasikan, serta mengolah data pembangunan daerah menjadi informasi yang disajikan kepada masyarakat dan sebagai bahan dalam pengambilan keputusan. Data SIPD terdiri dari 8 kelompok data, yaitu (Data Umum, Sosial Budaya, Sumber Daya Alam, Infrastruktur, Ekonomi, Keuangan daerah, Politik/hukum/Keamanan dan Insidental, serta 31 jenis data dan 2691 Elemen data. Pemerintah Kabupaten Tangerang telah bekerjasama dengan Universitas Multimedia Nusantara (UMN) untuk mengembangkan SIPD Kabupaten Tangerang. Untuk selanjutnya SIPD berbasis web tersebut telah diimplmentasikan dan berhasil dioperasionalkan oleh Tim UMN. Langkah-langkah implementasi SIPD meliputi penetapan Domain Name (nama domain internet untuk diakses oleh pengguna), hosting sistem, dan pelatihan operator. Adapun Domain Name telah diputuskan menggunakan nama URL sipd.tangerangkab.go.id. Sedangkan hosting sistem telah dilakukan pada server di Dinas Komunikasi dan Informatika Kabupaten Tangerang. Pelatihan operator telah dilakukan pada Bulan Januari 2019 dalam dua kelompok, yaitu kelompok operator dari dinas-dinas di Kabupaten Tangerang, dan kelompok operator dari kecamatan-kecamatan di Kabupaten Tangerang.

Information delivery has become a matter. Smartphone, as one of the information delivery media, has a feature called notification to be able to provide information directly to its users. UMN Bulletin, a mobile application based on Android platform, which provides information of posters of the bulletin in Universitas Multimedia Nusantara (UMN)., does not have a notification feature to give information directly to the users yet. A mobile application with notification feature cannot be separated from Human-Computer Interaction (HCI) concept. In HCI., there are two ways to get information., information delivery (push) and information access (pull). In this research., the push method will be implemented with Google Cloud Messaging (GCM)., while the pull method is given a scheduling feature with GCMNetworkManager to make information access more effective. The result from the questionnaire shows the respondents prefer that push method because of its quickness in getting a piece of new information. Besides the questionnaire result., the result of click time and click ratio also show that push method has a better value than the pull method. This means respondents' response to notifications from the push method is better than the pull method. From these results., it is concluded that the push method is more suitable to be implemented in the UMN Bulletin application.