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Journal : Media Informatika

Membangun Sistem Informasi Pendaftaran Nikah di Kantor Urusan Agama Gamping Berbasis Web Mario Soemriyat Sengga Sae; Titik Rahmawati; Landung Sudarmana
Media Informatika Vol 20 No 3 (2021)
Publisher : P3M STMIK LIKMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.065 KB) | DOI: 10.37595/mediainfo.v20i3.78

Abstract

Pendaftaran nikah di Kantor Urusan Agama Kecamatan Gamping, calon pengantin mendaftarkan pernikahan dengan mendatangi kantor dengan menyerahkan dokumen persyaratan nikah. Pencatatan dan pengelolaan dokumen administrasi pernikahan dilakukan oleh pegawai. Setelah proses pencatatan nikah selesai maka pegawai akan melakukan penjadwalan ijab kabul. Proses terakhir yaitu pembuatan laporan pernikahan seperti buku nikah dan lainnya sehingga di saat pandemi covid  perlu adanya sistem yang dapat mengolah data pendaftaran nikah berbasis online.Sistem dibuat menggunakan bahasa pemrograman PHP dan MySQL sebagai basis data. Sistem ini juga diintegrasikan dengan framework CSS Bootstrap sehingga desain tampilannya akan bersifat responsif. Sistem ini dibangun menggunakan metode waterfall. Hasil penelitian adalah membangun sistem informasi yang dapat membantu pegawai mengolah data pendaftaran dan memberikan informasi mengenai jadwal kepada calon pengantin. Sistem ini memiliki beberapa fitur diantaranya pendaftaran nikah, unggah berkas dokumen persyaratan, jadwal nikah dan laporan pendaftaran nikah.
Simulasi Penggunaan Listrik Tarif Sosial Menggunakan Algoritma ERNN Titik Rahmawati; Landung Sudarmana; Agung Priyanto
Media Informatika Vol 21 No 3 (2022)
Publisher : P3M STMIK LIKMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (879.164 KB) | DOI: 10.37595/mediainfo.v21i3.145

Abstract

The use of electricity under the social tariff category has increased significantly each year, both purely social and commercial social use. The use of social tariff electricity is intended for public interest activities for both the lower and upper middle social strata which are oriented towards fulfilling growth and development facilities for the public interest, so that a simulation of social electricity usage is needed to map a picture of the condition of the amount of social electricity usage in the future. The research was conducted to determine the estimation of how much electricity is used by using the Elman Recurrent Neural Network (ERNN) algorithm by reducing the input dimensions. The ERNN algorithm is used to simulate network parameters formed from complex input-output relationships, so that data patterns can be found. The factors of the input dimensions of this study are demographic data, electricity usage, social customers, population, gross regional domestic product (GRDP) and industrial growth. The results showed that the ERNN algorithm is capable of simulating formed network parameters that can be used for training and validation so that the value of the network Mean Square Error (MSE) can be determined, with prediction accuracy using the Mean Absolute Percentage Error (MAPE) for forecast in sample in the forecast period of 5 years obtained an average of 0.77%, and able to know the dominant factors that influence the use of social tariff electricity.