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All Journal JSI: Jurnal Sistem Informasi (E-Journal) InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Jurnal Komputer Terapan Seminar Nasional Teknologi Informasi Komunikasi dan Industri ILKOM Jurnal Ilmiah IJITEE (International Journal of Information Technology and Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Technologica Jurnal Kecerdasan Buatan dan Teknologi Informasi
Warnia Nengsih
Politeknik Caltex Riau
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Other

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Journal : Jurnal Komputer Terapan

 1 
GIS berbasis Web untuk Pemetaan Lahan menggunakan Classifier Model Warnia Nengsih
Jurnal Komputer Terapan  Vol. 2 No. 1 (2016): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (414.927 KB)

Abstract

Indikator ukur perkembangan sebuah wilayah dapat dilihat dari pembangunan yang merata dari segala bidang, salahsatunya adalah pembangunan infrakstruktur. Seyogyanya pembangunan infrastruktur mempertimbangkan banyak hal, diantaranya tata letak , kemudahan akses serta peningkatan kuantitas dan kualitas yang berkelanjutan. Belum adanya sebuah sistem akurat yang memberikan informasi lahan kosong   layak bangun pada sebuah wilayah menyulitkan dinas terkait pada saat proses pengidentifikasian  dan pemantauan lahan dan pemberian ijin dalam mendirikan bangunan. Sistem  yang akan dibangun   berupa Sistem Informasi Geografis berbasis web yang memberikan informasi posisi lahan layak bangun, ukuran lahan yang tersedia serta akses lahan ke berbagai fasilitas umum yang terdekat. Sistem dikombinasikan dengan datamining menggunakan teknik k-means clustering untuk mengetahui indikasi pengelompokkan  sub wilayah-wilayah pada sebuah wilayah.
CNN Modelling Untuk Deteksi Wajah Berbasis Gender Menggunakan Python warnia nengsih
Jurnal Komputer Terapan  Vol. 6 No. 2 (2020): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.147 KB) | DOI: 10.35143/jkt.v6i2.3679

Abstract

Face detection (Face Detection) is the Utilization of Biological data (Biometrics) by identifying physical features that exist in humans. Digitalization of gender recognition as a technology to recognize human gender by distinguishing the faces of women and the faces of men based on the Extraction features. The existence of this system can be applied implementatively for automatic surveillance systems and monitoring systems or market segmentation based on demographic trends and can also be applied to restrict access to a room. This research uses Convolutional Neural Network (CNN). CNN is a type of neural network where this method can be used on image data. CNN has the ability to recognize objects in an image. In total, the dataset used has 40 attribute annotations to describe female and male images. This face detection system uses python and Keras as an open source Machine Learning library for nerve networks, developed to make the application of deep learning models. With this system provides an accuracy analysis in gender detection so that it can be developed for more implementative research. The number of images must be balanced to get good performance for modeling, each model will have a training folder, validation and test data. The number of images that are not balanced can affect the performance of the CNN model. The model is built using transfer learning from InceptionV3 where modeling can recognize gender with an accuracy of 92.6%
Co-Authors Ardiyanto Ardiyanto Ayu Putri Lestari Dini Hidayatul Qudsi Dini Nurmala Sari Hajijah Noor Istianah Muslim M. Mahrus Zein Mardhiah Fadhli, Mardhiah mutia sari zulvi Nazifa Hayati Nurmalasari, Dini Ria Anjelina Agustin Syefrida Yulina Yuli Fitrisia