PENERAPAN DATA MINING UNTUK REKOMENDASI PAKET PERNIKAHAN MENGGUNAKAN METODE ALGORITMA APRIORI
Abstract
SM Wedding Decoration is a place that provides services to take care of everything related to weddings. For example, wedding decorations, wedding organizers, and wedding planners. SM Wedding Decoration has several wedding packages that can be offered to customers. The many packages available make the bride and groom or customers confused to determine which wedding package is suitable for their wedding. The a priori algorithm method is used in this study to find recommendations for wedding packages based on existing transaction data and to improve the company's strategy and sales of other wedding packages. The Apriori algorithm is used to help computers learn patterns of association rules. This algorithm looks for a set of things that match the given criteria or sequence and has a certain frequency value. From this research, customers tend to order Photographer & Documentation and MUA → Deluxe packages more often, and these orders account for 44% of all package order transaction data. Package order transaction data for MUA→Deluxe package is 41.3%. Transaction data for the Photographer & Documentation package → Deluxe Package is 41.2%. And the transaction data for ordering the MUA → Premium Deluxe Package package is 41.3%.
References
[1] J. Sofian and H. H. Solihin, “Pembangunan Aplikasi M-Wedding Sebagai Solusi Usaha Wedding Organizer,” J. Teknol. dan Inf., vol. 8, no. 2, 2018, doi: 10.34010/jati.v8i2.1038.
[2] A. M. Muzaiyin, “ANALISIS SISTEM PELAYANAN JASA WEDDING ORGANIZER DITINJAU DARI ETIKA BISNIS ISLAM (Studi Kasus Di UD. Santoso Wedding Organizer),” Fenomena, vol. 20, no. 1, pp. 129–144, 2021, doi: 10.35719/fenomena.v20i1.56.
[3] P. Kasih, “Pemodelan Data Mining Decision Tree Dengan Classification Error Untuk Seleksi Calon Anggota Tim Paduan Suara,” Innov. Res. Informatics, vol. 1, no. 2, pp. 63–69, 2019, doi: 10.37058/innovatics.v1i2.918.
[4] J. Gladju and B. Sam, “Smart Agricultural Technology Aplikasi kerangka kerja penambangan data dan pembelajaran mesin dalam akuakultur dan perikanan : Tinjauan,” vol. 2, 2022.
[5] G. J. Yanris, “Analisis Dan Implementasi Data Mining Dalam Menganalisa Kendala Akademik Yang Sering Dikeluhkan Mahasiswa Amik Labuhanbatu (Studi Kasus : Amik Labuhanbatu),” J. Inform., vol. 4, no. 1, pp. 15–24, 2019, doi: 10.36987/informatika.v4i1.226.
[6] N. A. Sinaga and A. T. Purba, “Penerapan Algoritma C.45 Untuk Memprediksi Tingkat Kepuasan Mahasiswa Terhadap Politeknik Bisnis Indonesia,” J. TEKINKOM, vol. 4, no. 2, pp. 245–254, 2021.
[7] T. Uçar and A. Karahoca, “Benchmarking data mining approaches for traveler segmentation,” Int. J. Electr. Comput. Eng., vol. 11, no. 1, pp. 409–415, 2021, doi: 10.11591/ijece.v11i1.pp409-415.
[8] S. P. Tamba, M. D. Batubara, W. Purba, M. Sihombing, V. M. Mulia Siregar, and J. Banjarnahor, “Book data grouping in libraries using the k-means clustering method,” J. Phys. Conf. Ser., vol. 1230, p. 012074, Jul. 2019, doi: 10.1088/1742-6596/1230/1/012074.
[9] W. Purba, S. Tamba, and J. Saragih, “The effect of mining data k-means clustering toward students profile model drop out potential,” J. Phys. Conf. Ser., vol. 1007, no. 1, p. 12049, 2018, [Online]. Available: http://stacks.iop.org/1742-6596/1007/i=1/a=012049
[10] A. M. Husein, M. Harahap, S. Aisyah, W. Purba, and A. Muhazir, “The implementation of two stages clustering (k-means clustering and adaptive neuro fuzzy inference system) for prediction of medicine need based on medical data,” J. Phys. Conf. Ser., vol. 978, p. 12019, Mar. 2018, doi: 10.1088/1742-6596/978/1/012019.
[11] D. Sitanggang et al., “Diagnosing chicken diseases using fuzzy Tsukamoto web-based expert system,” IOP Conf. Ser. Mater. Sci. Eng., vol. 505, no. 1, p. 012086, Jul. 2019, doi: 10.1088/1757-899X/505/1/012086.
[12] P. Prahasti, “Data Mining Dalam Pengelompokan Jenis Dan Jumlah Pembagian Zakat Dengan Menggunakan Metode Clustering K-Means (Studi Kasus: Badan Amil Zakat Kota Bengkulu),” J. Teknol. Inf., vol. 1, no. 2, p. 211, 2018, doi: 10.36294/jurti.v1i2.298.
[13] N. Azwanti, “Combination, Pola, Apriori ANALISIS POLA BELANJA KONSUMEN MENGGUNAKAN ALGORITMA APRIORI PADA RAFFA PHOTOCOPY,” J. Teknol. Dan Open Source, vol. 2, no. 2, pp. 63–73, 2019, doi: 10.36378/jtos.v2i2.348.
[14] S. Nurajizah, “Analisa Transaksi Penjualan Obat menggunakan Algoritma Apriori,” INOVTEK Polbeng - Seri Inform., vol. 4, no. 1, p. 35, 2019, doi: 10.35314/isi.v4i1.938.
[15] Ahmad Harmain, P. Paiman, H. Kurniawan, K. Kusrini, and Dina Maulina, “Normalisasi Data Untuk Efisiensi K-Means Pada Pengelompokan Wilayah Berpotensi Kebakaran Hutan Dan Lahan Berdasarkan Sebaran Titik Panas,” Tek. Teknol. Inf. dan Multimed., vol. 2, no. 2, pp. 83–89, 2022, doi: 10.46764/teknimedia.v2i2.49.
[16] D. A. Nasution, H. H. Khotimah, and N. Chamidah, “Perbandingan Normalisasi Data untuk Klasifikasi Wine Menggunakan Algoritma K-NN,” Comput. Eng. Sci. Syst. J., vol. 4, no. 1, p. 78, 2019, doi: 10.24114/cess.v4i1.11458.
[17] S. Mulyati, B. A. Sujatmoko, T. I. M. Wira, R. Afif, and R. A. Pratama, “Normalisasi Database Dan Migrasi Database Untuk Memudahkan Manajemen Data,” Sebatik, vol. 22, no. 2, pp. 124–129, 2018, doi: 10.46984/sebatik.v22i2.319.
[18] D. - and F. Sari, “Penerapan Algoritma Apriori Terhadap Perawatan Tubuh di Kakiku,” SATIN - Sains dan Teknol. Inf., vol. 5, no. 1, pp. 51–59, 2019, doi: 10.33372/stn.v5i1.457.
[19] A. F. Lestari and M. Hafiz, “Penerapan Algoritma Apriori Pada Data Penjualan Barbar Warehouse,” INOVTEK Polbeng - Seri Inform., vol. 5, no. 1, p. 96, 2020, doi: 10.35314/isi.v5i1.1317.
[20] I. Wahyudi, S. Bahri, and P. Handayani, “Aplikasi Pembelajaran Pengenalan Budaya Indonesia,” vol. V, no. 1, pp. 135–138, 2019, doi: 10.31294/jtk.v4i2.
[21] I. Ismasari, M. Ramadhan, and W. Hadikristanto, “Analisis Tingkat Pembelian Konsumen dengan Algoritma Apriori,” J. Ilm. Intech Inf. Technol. J. UMUS, vol. 2, no. 02, 2020, doi: 10.46772/intech.v2i02.292.
[2] A. M. Muzaiyin, “ANALISIS SISTEM PELAYANAN JASA WEDDING ORGANIZER DITINJAU DARI ETIKA BISNIS ISLAM (Studi Kasus Di UD. Santoso Wedding Organizer),” Fenomena, vol. 20, no. 1, pp. 129–144, 2021, doi: 10.35719/fenomena.v20i1.56.
[3] P. Kasih, “Pemodelan Data Mining Decision Tree Dengan Classification Error Untuk Seleksi Calon Anggota Tim Paduan Suara,” Innov. Res. Informatics, vol. 1, no. 2, pp. 63–69, 2019, doi: 10.37058/innovatics.v1i2.918.
[4] J. Gladju and B. Sam, “Smart Agricultural Technology Aplikasi kerangka kerja penambangan data dan pembelajaran mesin dalam akuakultur dan perikanan : Tinjauan,” vol. 2, 2022.
[5] G. J. Yanris, “Analisis Dan Implementasi Data Mining Dalam Menganalisa Kendala Akademik Yang Sering Dikeluhkan Mahasiswa Amik Labuhanbatu (Studi Kasus : Amik Labuhanbatu),” J. Inform., vol. 4, no. 1, pp. 15–24, 2019, doi: 10.36987/informatika.v4i1.226.
[6] N. A. Sinaga and A. T. Purba, “Penerapan Algoritma C.45 Untuk Memprediksi Tingkat Kepuasan Mahasiswa Terhadap Politeknik Bisnis Indonesia,” J. TEKINKOM, vol. 4, no. 2, pp. 245–254, 2021.
[7] T. Uçar and A. Karahoca, “Benchmarking data mining approaches for traveler segmentation,” Int. J. Electr. Comput. Eng., vol. 11, no. 1, pp. 409–415, 2021, doi: 10.11591/ijece.v11i1.pp409-415.
[8] S. P. Tamba, M. D. Batubara, W. Purba, M. Sihombing, V. M. Mulia Siregar, and J. Banjarnahor, “Book data grouping in libraries using the k-means clustering method,” J. Phys. Conf. Ser., vol. 1230, p. 012074, Jul. 2019, doi: 10.1088/1742-6596/1230/1/012074.
[9] W. Purba, S. Tamba, and J. Saragih, “The effect of mining data k-means clustering toward students profile model drop out potential,” J. Phys. Conf. Ser., vol. 1007, no. 1, p. 12049, 2018, [Online]. Available: http://stacks.iop.org/1742-6596/1007/i=1/a=012049
[10] A. M. Husein, M. Harahap, S. Aisyah, W. Purba, and A. Muhazir, “The implementation of two stages clustering (k-means clustering and adaptive neuro fuzzy inference system) for prediction of medicine need based on medical data,” J. Phys. Conf. Ser., vol. 978, p. 12019, Mar. 2018, doi: 10.1088/1742-6596/978/1/012019.
[11] D. Sitanggang et al., “Diagnosing chicken diseases using fuzzy Tsukamoto web-based expert system,” IOP Conf. Ser. Mater. Sci. Eng., vol. 505, no. 1, p. 012086, Jul. 2019, doi: 10.1088/1757-899X/505/1/012086.
[12] P. Prahasti, “Data Mining Dalam Pengelompokan Jenis Dan Jumlah Pembagian Zakat Dengan Menggunakan Metode Clustering K-Means (Studi Kasus: Badan Amil Zakat Kota Bengkulu),” J. Teknol. Inf., vol. 1, no. 2, p. 211, 2018, doi: 10.36294/jurti.v1i2.298.
[13] N. Azwanti, “Combination, Pola, Apriori ANALISIS POLA BELANJA KONSUMEN MENGGUNAKAN ALGORITMA APRIORI PADA RAFFA PHOTOCOPY,” J. Teknol. Dan Open Source, vol. 2, no. 2, pp. 63–73, 2019, doi: 10.36378/jtos.v2i2.348.
[14] S. Nurajizah, “Analisa Transaksi Penjualan Obat menggunakan Algoritma Apriori,” INOVTEK Polbeng - Seri Inform., vol. 4, no. 1, p. 35, 2019, doi: 10.35314/isi.v4i1.938.
[15] Ahmad Harmain, P. Paiman, H. Kurniawan, K. Kusrini, and Dina Maulina, “Normalisasi Data Untuk Efisiensi K-Means Pada Pengelompokan Wilayah Berpotensi Kebakaran Hutan Dan Lahan Berdasarkan Sebaran Titik Panas,” Tek. Teknol. Inf. dan Multimed., vol. 2, no. 2, pp. 83–89, 2022, doi: 10.46764/teknimedia.v2i2.49.
[16] D. A. Nasution, H. H. Khotimah, and N. Chamidah, “Perbandingan Normalisasi Data untuk Klasifikasi Wine Menggunakan Algoritma K-NN,” Comput. Eng. Sci. Syst. J., vol. 4, no. 1, p. 78, 2019, doi: 10.24114/cess.v4i1.11458.
[17] S. Mulyati, B. A. Sujatmoko, T. I. M. Wira, R. Afif, and R. A. Pratama, “Normalisasi Database Dan Migrasi Database Untuk Memudahkan Manajemen Data,” Sebatik, vol. 22, no. 2, pp. 124–129, 2018, doi: 10.46984/sebatik.v22i2.319.
[18] D. - and F. Sari, “Penerapan Algoritma Apriori Terhadap Perawatan Tubuh di Kakiku,” SATIN - Sains dan Teknol. Inf., vol. 5, no. 1, pp. 51–59, 2019, doi: 10.33372/stn.v5i1.457.
[19] A. F. Lestari and M. Hafiz, “Penerapan Algoritma Apriori Pada Data Penjualan Barbar Warehouse,” INOVTEK Polbeng - Seri Inform., vol. 5, no. 1, p. 96, 2020, doi: 10.35314/isi.v5i1.1317.
[20] I. Wahyudi, S. Bahri, and P. Handayani, “Aplikasi Pembelajaran Pengenalan Budaya Indonesia,” vol. V, no. 1, pp. 135–138, 2019, doi: 10.31294/jtk.v4i2.
[21] I. Ismasari, M. Ramadhan, and W. Hadikristanto, “Analisis Tingkat Pembelian Konsumen dengan Algoritma Apriori,” J. Ilm. Intech Inf. Technol. J. UMUS, vol. 2, no. 02, 2020, doi: 10.46772/intech.v2i02.292.
Published
2022-06-30
How to Cite
SITANGGANG, Delima et al.
PENERAPAN DATA MINING UNTUK REKOMENDASI PAKET PERNIKAHAN MENGGUNAKAN METODE ALGORITMA APRIORI.
Jurnal Tekinkom (Teknik Informasi dan Komputer), [S.l.], v. 5, n. 1, p. 130-137, june 2022.
ISSN 2621-3079.
Available at: <https://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/509>. Date accessed: 18 apr. 2024.
doi: https://doi.org/10.37600/tekinkom.v5i1.509.
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