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All Journal Syntax Literate : Jurnal Ilmiah Indonesia JURNAL PENDIDIKAN TAMBUSAI Jurnal Teknik Elektro dan Komputasi (ELKOM) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Manajemen Informatika Jayakarta CKI On Spot SmartComp Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Pengabdian Nasional (JPN) Indonesia
Sri Lestari
Program Studi Sistem Informasi, St Ilmu Komputer Cipta Karya Informatika
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Journal : Journal of Computer System and Informatics (JoSYC)

 1 
Penerapan Metode Long Short-Term Memory Pada Pendataan Warga Berbasis Android Sri Lestari; Muhammad Fakhri Pratama
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.1951

Abstract

Along with technological developments, utilization in data processing both input and output become very important. Starting from inputting data manually, it proves that the use of technology is still not fully used. Data that has been processed conventionally sometimes encounters problems caused by human error. Not only that, when data must be entered into a computer, it requires additional time and when natural disasters such as floods, earthquakes, landslides occur. Census files that are still in the conventional form are likely to be damaged and will take time to re-data. This is the main reason for RT 004 RW 008 to need an efficient data collection system. The application of Optical Character Recognition (OCR) technology in this study is expected to be a solution in increasing the efficiency of the data input process. In this study, the input process is carried out in real time using the Long Short-Term Memory (LSTM) method to scan data on e-KTP. The results of testing OCR technology with the LSTM method in this study for the three experiments carried out were 1) The e-KTP detection experiment resulted in an accuracy of 100%, 2) The trial of reading 19 attributes on the e-KTP resulted in an accuracy of 98.42%, 3) Testing the error reading of the e-KTP attribute resulted in an accuracy of 93.56%. Overall, the accuracy of the LSTM method in word detection on e-KTP results in an accuracy of 92.1%. These results indicate that the application of OCR technology with the LSTM method is one of the right solutions for the data input process.
Penerapan Metode Simple Additive Weighting (SAW) Dalam Sistem Pendukung Keputusan Pemilihan Calon Peserta Pelatihan Kepemimpinan Pengawas Bagi Pejabat Struktural Sri Lestari; Yomi Kusumah
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.2161

Abstract

In the nomination of candidates for Pelatihan Kepemimpinan Pengawas (PKP), the Badan Kepegawaian dan Pengembangan Sumber Daya Manusia (BKPSDM) Kota Bekasi is still experiencing problems in determining the nominative to be dispatched. The impact of these problems is in the form of a mismatch of the nominations of potential participants with priorities that must be expedited. Therefore, it is necessary to have a system that uses a database so as to assist the leadership in making decisions to determine and determine the nominative priorities of prospective PKP participants. In this study, the authors propose the application of the Simple Additive Weighting (SAW) method. The data collection method used is the method of observation and interviews. The criteria proposed from the interview results include Age (weight: 0.35), Echelon (weight: 0.25), Group (weight: 0.2), Service Period (weight: 0.15) and Employee Work Target Value (weight: 0.05). The system development method used is the Waterfall method. The system is built using the PHP programming language with MySQL as the database. System design using Unified Modeling Language (UML) and system testing using Black-box Testing. With this decision support system, the leadership will get the results of anyone who has the right to be proposed to take part in the Training.
Co-Authors Agung Pratama Aldi Sitohang Aldino Nur Ihsan Andrian Nur Ihsan Ayuk Ambar Kusuma Bela Dina Dadang Iskandar Mulyana` Dea Noer Rachmawati Deason’s Tanduri Dhiva Andini Putri Alinur Dionta Dionta Dwi Lestari Dzaky Haidar Eka Anggraeni Eka Satria Maheswara Erno Sumantri Firza Novianto Hadi Lheena Herta Apriani Silaban Ilham Gunawan Irfan Maulana Irviani Liestian Ramadhanty Julinar Sari Hutagalung M Ainur Rofik M Ohan Joharuddin Zakaria Maharanisa Maharanisa Megawati Megawati Miftahul Jannah Ahyana Puteri Kharisha Miftahul Jannah Ahyana Puteri Kharisha Muhammad Faizal Lazuardi Muhammad Fakhri Pratama Muhammad Mufti Ramdhani Puji Kurniati Rasiban Raya Fitri Boangmanalu Sandy Rivaldiansyah Soleh Ependi Stefany Tarunajaya Sugeng Sugeng Tri Wahyudi Virginia Khoirunnisa Wahyu Hidayat Wahyu Saputro Yansen Yansen Yomi Kusumah Yuma Akbar