Sistem Prediksi Kebutuhan Vitamin A Menggunakan Metode Fuzzy Mamdani
Abstract
The purpose of this study is to create a system that can predict the need for vitamin A in a certain period, and provide convenience to related parties to meet the needs of the vitamin. Vitamin A is the most essential nutrient, this is because food consumption is not sufficient and is still low so it must be met from the outside. In this study, the method used to predict the need for vitamin A is the fuzzy mamdani method with input variables namely stock and demand and output variables namely needs. The predictions made are based on past statistics and on the basis of the characteristics of past vitamin A consumption. To calculate the error in predicting using the mean absolute percentage error (MAPE). Analysis of system requirements built using an object approach with Unified Modeling Language (UML) tools. The results of the overall prediction obtained the highest average accuracy value of 97.93% with an average error value as small as 2.07% while the lowest average accuracy value was 92.57% with an average error value as small as 7.43%. Testing on the system obtained a 100% functional value that went well in accordance with the needs analysis that had been made, so that the system had provided predictive information on vitamin A needs for a certain period and provided convenience for related parties to fulfill these needs.
References
K. Lidia, “Peningkatan Kesehatan dengan Suplemen dan Gizi Seimbang di Era Pandemi Covid-19,” Jurnal Pengabdian Kepada Masyarakat Undana, 14(2), 63-68, 2020
G. Virgo, “Faktor-Faktor Yang Berhubungan Pemberian Vitamin A Pada Balita Di Posyandu Desa Beringin Lestari Wilayah Kerja Puskesmas Tapung Hilir 1 Kabupaten Kampar Tahun 2018,” Ners, vol. 4, no. 1, pp. 35–52, 2020
P. D. Kusumanti and N. Setyorini, “Hubungan Tingkat Pengetahuan Ibu Tentang Vitamin A Dengan Ketepatan Dalam Pemberian Vitamin A Pada Balita Di Wilayah Kerja Puskesmas Sruwohrejo Kecamatan Butuh Kabupaten Purworejo,” Komun. Kesehat., vol. 9, no. 2, pp. 29–37, 2018
F. S. D. Arianto, & P. Noviyanti, “Prediksi kasus COVID-19 di Indonesia menggunakan metode backpropagation dan fuzzy Tsukamoto,” JurTI (Jurnal Teknologi Informasi), 4(1), 120-127, 2020
S. Nurhayati and I. Immanudin, “Penerapan Logika Fuzzy Mamdani Untuk Prediksi Pengadaan Peralatan Rumah Tangga Rumah Sakit,” Komputika J. Sist. Komput., vol. 8, no. 2, pp. 81–87. 2019
C. P. P. Maibang and A. M. Husein, “Prediksi Jumlah Produksi Palm Oil Menggunakan Fuzzy Inference Sistem Mamdani,” Teknol. dan Ilmu Komput. Prima, vol. 2, no. 2, p. 19, 2019
I. Nabillah & I. Ranggadara, “Mean Absolute Percentage Error untuk Evaluasi Hasil Prediksi Komoditas Laut”. Journal of Information System. vol. 5, no. 2, 250-255, 2020
A. Hajjah & Y. N. Marlim, “Analisis Error Terhadap Peramalan Data Penjualan,” Techno.COM, vol. 20, no. 1, 1-9, 2021
A. D. W. Sumari, R. Y. A . Pratama, & O.D. Triswidrananta, “Sistem Prediksi Tingkat Kriminalitas Menggunakan Metode Triple Exponential Smoothing: Studi Kasus Pada Polres Kabupaten Probolinggo,” Jurnal Teknik Informatika Vol, 13(2), 171, 2020
B Santoso, A.I.S.Aziz, dan Zohrahayaty, “Machine Learning & Reasoning Fuzzy Logic Algoritma, Manual, Matlab, & Rapid Miner“, Deepublish, hal.3, ISBN: 9786230206726, 6230206722, 2020
A. Ikhwan, M. Badri, M. Andriani, & N. Saragih, “Analisis Tingkat Kepuasan Pelanggan Menggunakan Fuzzy Mamdani (Studi Kasus: Busrain Bakery)”. Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer), 18(2), 147-153, 2019
V. M. Nasution, G. Prakarsa, “Optimasi Produksi Barang Menggunakan Logika Fuzzy Metode Mamdani”. Jurnal Media Informatika Budidarma, 4(1), 129-135, 2020
Yulmaini, “Logika Fuzzy – Studi Kasus & Penyelesaian Menggunakan Microsoft Excel dan Matlab”, Penerbit Andi Offset: Yogyakarta, hal. 39, 2018
W. Anissudin, Y. Arkeman, I. Hermadi, & S. Sjaf, “Design a fuzzy inference system to determining superior commodities for create a village medium-term development plan,” In IOP Conference Series: Earth and Environmental Science (Vol. 335, No. 1, p. 012004). IOP Publishing, 2019
E.P. Sari, S. Setyaningsih, & H. Wijayanti, “Penerapan Metode Fuzzy Mamdani Dalam Menentukan Tingkat Keberhasilan Mengajar Berdasarkan Motivasi, Kompetensi Pedagogik, Dan Capaian Mahasiswa,” Interval Jurnal Ilmiah Matematika, 1(2), 40-49, 2021
M. Muntahanah, S. Handayani, & L. Lidia, “Penerapan Metode Fuzzy Mamdani Penentuan Strategi Belajar Siswa Pada Persiapan Ujian Nasional Berbasis Komputer (UNBK),” Pseudocode, 8(2), 108-117, 2021
L. Santya, M. Miftah, V. Mandala, S. Saepudin, & D. Gustian, “Penerapan Metode Fuzzy Mamdani Untuk Pendukung Keputusan Penentuan Jumlah Produksi Lantak Si Jimat,” Jurnal Rekayasa Teknologi Nusa Putra, 4(4), 2019
Suendri, “Implementasi Diagram UML (Unified Modelling Language) Pada Perancangan Sistem Informasi Remunerasi Dosen Dengan Database Oracle (Studi Kasus: UIN Sumatera Utara Medan),” J. Ilmu Komput. dan Inform., vol. 3, no. 1, 2018
E. Affandi and T. Syahputra, “Pemodelan Uml Manajeman Sistem Inventory,” J. Teknol. Sist. Inf. dan Sist. Komput. TGD, vol. 1, no. 2, 2018
M.D.B. Barus, & F.S. Thahirah, “Sistem Forecasting Perencanaan Produksi Dengan Metode Single Eksponensial Smoothing Pada Pt. Food Beverages Indonesia,” Nusantara: Jurnal Ilmu Pengetahuan Sosial, 9(3), 909-920, 2022
F. Liantoni, & A. Agusti, “Forecasting bitcoin using double exponential smoothing method based on mean absolute percentage error. JOIV: International Journal on Informatics Visualization, 4(2), 91-95, 2020
A. Krisma, M. Azhari, & P. P. Widagdo, “Perbandingan Metode Double Exponential Smoothing Dan Triple Exponential Smoothing Dalam Parameter Tingkat Error Mean Absolute Percentage Error (MAPE) dan Means Absolute Deviation (MAD)”. In Prosiding Seminar Nasional Ilmu Komputer dan Teknologi Informasi, vol. 4, no. 2, 2019
S. Masripah, & L. Ramayanti “Penerapan Pengujian Alpha Dan Beta Pada Aplikasi Penerimaan Siswa Baru”. Jurnal Swabumi, 8(1), 100-105, 2020
A. Rosano, "Pengujian Alpha dan Beta pada Pengembangan Sistem Internet Banking (Ibank) PT Bank Mega, Tbk." REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer 3.2, 34-40, 2019
