Design and Build Applications in Total Forecasting New Students in School by Applying Non Linear Trend Method

Authors

  • Lola Eris Monika Study Program of Informatics Faculty of Computer Science Universitas Dehasen Bengkulu
  • Yupianti Yupianti Department of Informatics, Faculty of Computer Science, Universitas Dehasen Bengkulu
  • Rizka Tri Alinse Department of Informatics, Faculty of Computer Science, Universitas Dehasen Bengkulu

DOI:

https://doi.org/10.53697/jkomitek.v1i1.95

Keywords:

Forecasting, Application, Non Linear Trend Method

Abstract

SMA Muhammadiyah 1 Bengkulu City is one of the schools located in Bengkulu City, where several data processing systems still use manual systems, one of which is new student registration. Every new school year, the officer fills out the sheet of students enrolled in the school one by one in the registration book. This takes a long time when the officer wants to make a report of students registered, because they have to retype the data in the registration book into the computer. In addition, after conducting interviews, it was found that the students at SMA Muhammadiyah 1 Bengkulu City experienced a decline every academic year. The application of forecasting the number of new students at SMA Muhammadiyah 1 Bengkulu City can be used to predict the number of new students in the next academic year based on the results of the analysis on old historical data. This forecasting process is carried out through the Non-Linear Trend Method approach, so that the final forecasting result is obtained from the stages of the process that occur. It was made using the VB.Net programming language and SQL Server database which can assist the school in managing school quality assurance, in order to attract interest from prospective students to enroll in SMA Muhammadiyah 1 Bengkulu City, and can arrange school promotion strategies for prospective students. Based on the tests that have been carried out, it can be concluded that the functional application of forecasting the number of new students at SMA Muhammadiyah 1 Bengkulu City has been running properly and the application for forecasting the number of new students at the school which is able to display forecasting results in the next academic year.

References

Adjis, K. M., 2016. Penerapan 5C Dalam Pembiayaan Murabahah Di BMT Mitra Reksa Bakti. Laporan

Universitas Islam Indonesia.

Andini, T. D. A. P., 2016. Peramalan Jumlah Stok Alat Tulis Kantor di UD. Achmad Jaya Menggunakan

Metode Double Exponential Smooting.. Jurnal Ilmiah Teknologi dan Informasi ASIA (JITIKA)

Vol.10 No.1.

Enterprise, J., 2015. Pengenalan Visual Studio 2013. Jakarta: PT. Elex Media Komputindo.

Herlambang, B. A., 2015. eRancang Data Flow Diagram Sistem Pakar Penentuan Kebutuhan Gizi Bagi

Individu Normal Berbasis Web. Jurnal Informatika UPGRIS, Volume 1.

Ilyas, Marisa, F. & Purnomo, D., 2018. Implementasi Metode Trend Moment (Peramalan) Mahasiswa

Baru Universitas Widyagama Malang. Journal Of Information Technology and Computer

Science, Volume Vol.3 No.2.

KBBI, 2020. Kamus Besar Bahasa Indonesia (KBBI). [Online]

Available at: https://kbbi.web.id/

[Diakses Oktober 2020].

Kurniawan, H., 2017. Aplikasi Dalam Memprediksi Penjualan Di Toko Borobudur Menggunakan Metode

Trend Non Linear, Bengkulu: Program Studi Teknik Informatika Fakultas Ilmu Komputer

Universitas Dehasen Bengkulu.

Lubis, A., 2016. Basis Data Dasar Untuk Mahasiswa Ilmu Komputer. Yogyakarta: Deepublish.

I., 2018. Metode Trend Non Linear Untuk Forecasting Komposisi Penduduk Kabupaten

Tapanuli Tengah Menurut Jenis Kelamin Tahun 2006-2016. Jurnal Curere Vol.2 No.2 p-ISSN :

-9507.

Windari, A. & Murniati, E., 2020. Prediksi Jumlah Calon Mahasiswa Baru Tahun 2018-2022 Di Poltekes

Kemenkes Semarang. Jurnal Rekam Medis dan Informasi Kesehatan, Volume Vol.3 No.1.

Published

2021-06-29

How to Cite

Monika, L. E., Yupianti, Y., & Alinse , R. T. . (2021). Design and Build Applications in Total Forecasting New Students in School by Applying Non Linear Trend Method. Jurnal Komputer, Informasi Dan Teknologi, 1(1), 1–14. https://doi.org/10.53697/jkomitek.v1i1.95

Issue

Section

Articles

Most read articles by the same author(s)

1 2 > >> 

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.