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Journal : Akademika

IMPLEMENTASI ALGORITMA BACKPROPAGATION DALAM MEMPREDIKSI JUMLAH PERKAWINAN TIDAK TERCATAT DI SIANTAR MARTOBA Aldania, Desti; Parlina, Iin; Safii, Muhammad
JURNAL AKADEMIKA Vol 16 No 2 (2024): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v16i2.1222

Abstract

Pertumbuhan penduduk diikuti dengan bertambahnya masyarakat dewasa yang membuat mereka meneruskan keturunan melalui perkawinan. Di Kecamatan Siantar Martoba terungkap 91.267 warga tidak memiliki akta nikah dari Dinas Kependudukan dan Pencatatan Sipil Kota Pematangsiantar. Dibutuhkan prediksi untuk mengetahui kenaikan atau penurunan jumlah nikah sirih di Kecamatan Siantar Martoba pada tahun 2023. Metode Algoritma Backpropagation merupakan metode yang tepat untuk melakukan prediksi. Data pelatihan dimulai tahun 2017-2021 dengan target tahun 2021, data pengujian dimulai tahun 2018-2022 dengan target tahun 2022. Dalam penelitian ini, mengaplikasikan arsitektur jaringan yang diimplementasikan pada aplikasi matlab. Berdasarkan arsitektur terbaik yang dihasilkan pada penelitian ini yaitu arsitektur 4-66-1 dengan akurasi sebesar 86% dengan mean square error sebesar 0.00009995 dan epoch 1897 literations dalam waktu 34 detik untuk mencapai goal. Berdasarkan hasil penelitian ini, jumlah nikah sirih di tahun 2023 meningkat menjadi 4.366 di seluruh Kabupaten Siantar Martoba. Kata kunci: JST, Algoritma, Backpropagation, Kecerdasan Buatan, Perkawinan Tidak Tercatat Population growth is accompanied by an increase in adult society which enables them to continue their offspring through marriage. In Siantar Martoba District, it was revealed that 91,267 residents did not have a marriage certificate from the Pematangsiantar City Population and Civil Registration Service. Predictions are needed to determine the increase or decrease in the number of betel marriages in Siantar Martoba District in 2023. The Backpropagation Algorithm method is the right method for making predictions. Training data starts in 2017-2021 with a target of 2021, testing data starts in 2018-2022 with a target of 2022. In this research, the network architecture implemented in the Matlab application is applied. Based on the best architecture produced in this research, namely the 4-66-1 architecture with an accuracy of 86% with a mean square error of 0.00009995 and epoch 1897 literations in 34 seconds to achieve the goal. Based on the results of this research, the number of betel marriages in 2023 will increase to 4,366 throughout Siantar Martoba Regency. Keywords: Artificial Neural Networks, Algorithms, Backpropagation, Artificial Intelligence, Unregistered Marriages
PERANCANGAN STRATEGI VALIDASI DATA DENGAN PEMANFAATAN APLIKASI VALIDASI BERBASIS GMAPS UNTUK PRODUK INDIHOME : DESIGNING A DATA VALIDATION STRATEGY USING A VALIDATION APPLICATION BASED ON GOOGLE MAPS (GMAPS) FOR INDIHOME PRODUCTS Lumbantobing, Dedy Kristianto; Khairunnisa Sormin, Rizky; Safii, Muhammad
JURNAL AKADEMIKA Vol 16 No 2 (2024): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v16i2.1224

Abstract

Guaranteeing the accuracy and completeness of data is a critical aspect in the scope of telecommunications services. In this context, this research aims to design an effective data validation strategy through the use of a Google Maps (GMaps) based validation application in Indihome products. The design involved an approach that combined GMaps interactive map technology, the React JS framework, and the MongoDB database. Using the React JS framework, an interactive user interface has been developed to facilitate the use of validation applications. Utilization of Google Maps allows visual integration of validation data with precise geographic locations. The use of the MongoDB database supports efficient storage and management of validation data, ensuring that the data obtained meets requirements. Application testing has been carried out to ensure the effectiveness of the designed data validation strategy. The result of this research is the design of an effective data validation strategy, through the application of GMaps, React JS, and MongoDB technology. This implementation is expected to provide a more accurate, efficient and intuitive solution in ensuring data quality in Indihome services. This research can also provide benefits for technological developments in the field of data validation and the application of map concepts in user experience