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All Journal International Journal of Electrical and Computer Engineering Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) JOIV : International Journal on Informatics Visualization Creative Information Technology Journal Jurnal Komtika (Komputasi dan Informatika) Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Informasi Interaktif Respati Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Perangkat Lunak Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Ekonomi dan Teknik Informatika Innovative: Journal Of Social Science Research Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Komtika (Komputasi dan Informatika)
Hanif Al Fatta
Universitas Amikom Yogyakarta
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Public Health Transportation Other

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Journal : Informasi Interaktif

 1 
PEMODELAN ARSITEKTUR SISTEM INFORMASI PERIZINAN MENGGUNAKAN KERANGKA KERJA TOGAF ADM Darmanto, Darmanto; Suyanto, Mohammad; Al Fatta, Hanif
Informasi Interaktif Vol 3, No 1 (2018): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

BPPTPM regency lamandau is a public service agency in the field of licensing, non-licensing and investment, is required to provide excellent service, trusted and transparent to the community. To achieve these objectives required appropriate strategies and utilization of information technology as a supporter in the work process. The objectives of this research are to identify the needs of services and business processes and to build an integrated information system architecture to support business activities at BPPTPM Lamandau District. Limitations of variables in this study are: This study uses input data from interviews, and document analysis in the form of renstra and renja BPPTPM and other documents required. The creation of a licensing information system architecture adopts the TOGAF ADM framework from the vision architecture phase to the technology architecture, as well as other methods such as PIECES Analysis, Value Cahin, SWOT, CSF, CUR Matrix, and SOA. The output of this research is blueprint information system without making application or prototype. The result of design of information system architecture using TOGAF ADM framework on business architecture using value chain analysis obtained 10 (ten) business functional areas, 5 (five) main business functions and 5 (five) supporting business functions. While the results of application portfolio mapping based on Mc Farlan obtained 9 (Nine) future information system which contains a collection of applications as a proposal to implement. As a guide in describing blueprint of licensing information system architecture at BPPTPM regency lamandau as a whole this research using TOGAF Foundation Architecture and SOA. Keywords :EnterpriseArchitecture, TOGAF,PIESCES, Value Chain.
ANALISIS SUPPORT VECTOR MACHINE PADA PREDIKSI PRODUKSI KOMODITI PADI Nurmasani, Atik; Utami, Ema; Al Fatta, Hanif
Informasi Interaktif Vol 2, No 1 (2017): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Analysis of Support Vector Machine (SVM) implemented on prediction of production rice commodity that can help the management of rice production in Indonesia. Prediction is done with Matlab R2016A especially function of SVM Regression. The prediction results were evaluated by performance criteria such as Root Mean Squared Error (RMSE), R-Squared and Adjusted R-Squared, and also curve fitting. SVM parameters determined automatically after processing is completed. Predictions done annually, conducted from 2006 to 2015. The results of those predictions determined the value of performance to get the value of the correspondence between the predicted value and the actual value and the best prediction is illustrated by curve fitting. It also conducted comparison performance of predictions per year to determine which ones produce the best fit. Results of prediction rice commodity with SVM method showed that the best fit is prediction in 2007 with RMSE value of 1.20E+06, R-Square of 0.794 or 79.4%, Adjusted R-Square of 0788 or 78.8%, as well as curve fitting shows the level distribution predictions are optimal for the year. Keyword: SVM, regression, prediction
TEXT MINING DOKUMEN TWEET PADA TWITTER UNTUK KLASIFIKASI KARAKTER CALON KARYAWAN Saifudin, Saifudin; Kusrini, Kusrini; Fatta, Hanif Al
Informasi Interaktif Vol 5, No 1 (2020): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

Recruitment is a means to prepare as many workers as possible according to the requirements and qualifications expected by the organization. In recruitment one of the things that is calculated is the character of the prospective employee itself. Companies or organizations usually carry out psychological tests and interviews to get the character of prospective employees. This will make the recruitment process longer and require a lot of money. One way to find out a person's character can be done by looking at the publication of daily activities on various social media. In this study the classification of prospective employees is based on tweets found on twitter. The results of this study are grouping prospective employees based on their characters using the naïve bayes classifier algorithm. From the research that has been done naïve bayes classifier algorithm has an accuracy accuracy of an average of 52% by weighting using the term document frequency.Keywords: Naïve Bayes Classifier, TFIDF, Character
Co-Authors AA Sudharmawan, AA Abidarin Rosidi Agustin, Tinuk Anas, Syukron Andi Sunyoto Anggraini, Resti Kusuma Arief Setyanto Bambang Soedijono, Bambang Barnea, Samson Barnea, Samson Bayu Setiaji Christian Budi Andrianto, Christian Budi Darmanto Darmanto Ema Utami Eri Sasmita Susanto Faisal Reza Pradhana Fauji Maulana Ramlan, Fauji Maulana Fitriana, Frizka Gori, Takhamo Hasan, Nur Fitrianingsih Hidayat Hidayat I Gede Ngurah Arya Indrayasa Imam Adi Nata Kristama, El Johan Kurniasari, Iin Kusrini Kusrini Kusrini, K Kusrini, Kusrini Kusrini, Kusrini M. Suyanto, M. Maksom, Zulisman Mohammad Suyanto Muhammad Resa Arif Yudianto NABILA OPER Nurmasani, Atik Pradipta, Dody Purwidiantoro, Moch. Hari Purwoko, Agus Rahman, Aulia Tegar Risa Helilintar Safagi, Ardian Yuligar Saifudin, Saifudin Saputra, Artha Gilang Saputra, Artha Gilang Setiawan, Hendi Siti Rihastuti Sugihandono, Agus Sutanto, Yudi Suyanto, M Suyanto, M Tri Nugroho, Arief Tukan, Ewaldus Ambrosius Wijaya, Tri Amri Wira Dimuksa Zakaria, Mohd Hafiz