PENERAPAN METODE MAUT PADA PEMILIHAN BIMBINGAN INTENSIF TERBAIK DI PEMATANGSIANTAR

 (*)Yolanda Agustina Situmorang Mail (STIKOM Tunas Bangsa, Pematangsiantar, Medan, —)
 Nurhafidah Dalimunthe (STIKOM Tunas Bangsa, Pematangsiantar, Medan, —)
 Iin Parlina (STIKOM Tunas Bangsa, Pematangsiantar, Medan, —)
 Muhammad Ridwan Lubis (STIKOM Tunas Bangsa, Pematangsiantar, Medan, —)

(*) Corresponding Author

Abstract

Education is a sector that greatly determines the quality of a nation. The failure of education has implications for the failure of a nation, the success of education also automatically brings the success of a nation. In the world of education, it should pay attention to the elements of education, which include: students, educators, software, management, facilities and infrastructure and stake holders. Assets needed in education are human resources that are quality. Quality resources can be from students, the community, as well as from educators. In education, there is a level of education which starts from kindergarten, elementary school, junior high school, high school and university. Higher education is the education unit of higher education providers. Higher education students are called students, while college educators are called lecturers. According to the type, universities are divided into two, namely; state universities and private universities. Among students who want to go to college, many of the students want to go to state universities. So that many students and parents make their children for intensive guidance so that they can be accepted at the desired state universities. Intensive guidance is a learning aid activity for students or students that aims to make students achieve optimal learning achievement.

Keywords: Education, Higher Education, Intensive Guidance

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References

A. P. Windarto, “Penerapan Data Mining Pada Ekspor Buah-Buahan Menurut Negara Tujuan Menggunakan K-Means Clustering,” Techno.COM, vol. 16, no. 4, pp. 348–357, 2017.

M. G. Sadewo, A. P. Windarto, and D. Hartama, “PENERAPAN DATAMINING PADA POPULASI DAGING AYAM RAS PEDAGING DI INDONESIA BERDASARKAN PROVINSI MENGGUNAKAN K-MEANS CLUSTERING,” InfoTekJar (Jurnal Nas. Inform. dan Teknol. Jaringan), vol. 2, no. 1, pp. 60–67, 2017.

A. P. Windarto, “Implementation of Data Mining on Rice Imports by Major Country of Origin Using Algorithm Using K-Means Clustering Method,” Int. J. Artif. Intell. Res., vol. 1, no. 2, pp. 26–33, 2017.

Sumijan, A. P. Windarto, A. Muhammad, and Budiharjo, “Implementation of Neural Networks in Predicting the Understanding Level of Students Subject,” Int. J. Softw. Eng. Its Appl., vol. 10, no. 10, pp. 189–204, 2016.

M. N. H. Siregar, “Neural Network Analysis With Backpropogation In Predicting Human Development Index ( HDI ) Component by Regency / City In North Sumatera,” I n t e r n a t i o n a l Jo u r n a l O f I n f o r m a t i o n S yst e m T e c h n o l ogy, vol. 1, no. 1, pp. 22–33, 2017.

Solikhun, A. P. Windarto, Handrizal, and M.Fauzan, “Jaringan Saraf Tiruan Dalam Memprediksi Sukuk Negara Ritel Berdasarkan Kelompok Profesi Dengan Backpropogation Dalam Mendorong Laju Pertumbuhan Ekonomi,” Kumpul. J. Ilmu Komput., vol. 4, no. 2, pp. 184–197, 2017.

A. P. Windarto, L. S. Dewi, and D. Hartama, “Implementation of Artificial Intelligence in Predicting the Value of Indonesian Oil and Gas Exports With BP Algorithm,” Int. J. Recent Trends Eng. Res., vol. 3, no. 10, pp. 1–12, 2017.

A. P. Windarto, “IMPLEMENTASI JST DALAM MENENTUKAN KELAYAKAN NASABAH PINJAMAN KUR PADA BANK MANDIRI MIKRO SERBELAWAN DENGAN METODE BACKPROPOGATION,” J-SAKTI (Jurnal Sains Komput. dan Inform., vol. 1, no. 1, pp. 12–23, 2017.

A. Putrama and A. P. Windarto, “Analisis dalam menentukan produk bri syariah terbaik berdasarkan dana pihak ketiga menggunakan ahp,” CESS (Journal Comput. Eng. Syst. Sci., vol. 3, no. 1, pp. 60–64, 2018.

P. P. P. A. N. W. F. I. R. H. Zer and A. P. Windarto, “Analisis Pemilihan Rekomendasi Produk Terbaik Prudential Berdasarkan Jenis Asuransi Jiwa Berjangka Untuk Kecelakaan Menggunakan Metode Analytic Hierarchy Process ( Ahp ),” CESS (Journal Comput. Eng. Syst. Sci., vol. 3, no. 1, pp. 78–82, 2018.

D. R. Sari, A. P. Windarto, D. Hartama, and S. Solikhun, “Sistem Pendukung Keputusan untuk Rekomendasi Kelulusan Sidang Skripsi Menggunakan Metode AHP-TOPSIS,” J. Teknol. dan Sist. Komput., vol. 6, no. 1, p. 1, 2018.

A. P. Windarto, “Penilaian Prestasi Kerja Karyawan PTPN III Pematangsiantar Dengan Metode Simple Additive Weighting (SAW),” J. Ris. Sist. Inf. Dan Tek. Inform., vol. 2, no. ISSN 2527-5771, pp. 84–95, 2017.

T. Imandasari and A. P. Windarto, “Sistem Pendukung Keputusan dalam Merekomendasikan Unit Terbaik di PDAM Tirta Lihou Menggunakan Metode Promethee,” J. Teknol. dan Sist. Komput., vol. 5, no. 4, p. 159, 2017.

S. M. Lubuklinggau, “Elmayati , Azari Taher RANCANG BANGUN DASHBOARD SISTEM INFORMASI SEBARAN DATA PENDUDUK BERBASIS WEB MOBILE ( STUDI KASUS DINAS KEPENDUDUKAN DAN CATATAN SIPIL KOTA LUBUKLINGGAU ) Elmayati , Azari Taher,” vol. 2, no. 2, pp. 93–101, 2017.

R. Jannah, “Aplikasi Penerimaan Karyawan dengan Metode Multi Attribute Utility Theory Riadhil Jannah.”

A. Baihaqi and K. Pengantar, “MEMBANGUN APLIKASI PENGOLAHAN DATA PEGAWAI DAN KENAIKAN PANGKAT REGIONAL DENGAN METODE MULTI-ATTRIBUTE UTILITY THEORY ( MAUT ) DI PT . KERETA API ( PERSERO ),” 2009.

A. N. W. M. (Universitas M. Surakarta), “PENENTUAN PRIORITAS PENGURANGAN LIMBAH DENGAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) DAN TECHNIQUE OF ORDER PREFERENCE BY SIMILIARY TO IDEAL SOLUTION (TOPSIS),” 2017.

F. F. Harryanto and S. Hansun, “Penerapan Algoritma C4 . 5 untuk Memprediksi Penerimaan Calon Pegawai Baru di PT WISE,” Jatisi, vol. 3, no. 2, pp. 95–103, 2017.

S. Nugroho, “SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI OBJEK WISATA DI KABUPATEN GROBOGAN MENGGUNAKAN METODE PROFILE MATCHING Satrio.”

T. La, R. Electre, and L. Marlinda, “SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN TEMPAT WISATA YOGYAKARTA MENGGUNAKAN METODE ELimination Et Choix,” no. November, pp. 1–7, 2016.

R. A. S. Ulya Anisatur Rosyidah, M.Kom, “SISTEM PENDUKUNG KEPUTUSAN UNTUK PENERIMAAN KARYAWAN PT PLN JEMBER MENGGUNAKAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT),” no. 1210652011, 2017.

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