Sistem Optimalisasi Pengadaan Alat Kesehatan Menggunakan Metode Fuzzy Time Series
DOI:
https://doi.org/10.30865/mib.v7i4.6405Keywords:
Fuzzy, Control, Arrangement, Optimization, Medical DevicesAbstract
Controlling the procurement of Medical Devices is an important matter for the Pharmacy industry to pay attention to in order to win highly competitive competition, therefore an appropriate model and strategy is needed so that the number of sales can increase, the right solution is to maintain optimal stock availability. this is in line with the Regulation of the Minister of Health of the Republic of Indonesia Number 35 of 2014, concerning pharmaceutical service standards at pharmacies for pharmaceutical preparations, medical devices and consumables which includes procurement and control. The purpose of this study is to assist pharmacies in optimizing the procurement of medical devices by applying the fuzzy time series Chen model, so that they can overcome stock emptiness and over stock, besides that the pharmacy has a system that can predict the optimal number of medical device product purchases for the next period. which has an impact on the ability to control stock. The results showed that the fuzzy time series method of the Chen model has very good performance. This can be seen from the value of the accuracy of the forecasting results which is calculated using the AFER (Average Forecasting Error Rate) formula with a value of 4%. The number of medical devices that will be provided for the January 2023 period is 15 pieces.References
Menkes, Peraturan Menteri Kesehatan tentang Perubahan Kedua atas Peraturan Menteri Kesehatan Nomor 71 Tahun 2013 Tentang Pelayanan Kesehatan pada Jeminan Kesehatan Nasional. 2017.
G. A. Ayu and M. Syaripuddin, “Peranan Apoteker dalam Pelayanan Kefarmasian pada Penderita Hipertensi,†J. Kedokt. dan Kesehat., vol. 15, no. 1, p. 10, 2019, doi: 10.24853/jkk.15.1.10-21.
I. J. Thira, N. A. Mayangky, D. N. Kholifah, I. Balla, and W. Gata, “Peramalan Data Kunjungan Wisatawan Mancanegara ke Indonesia menggunakan Fuzzy Time Series,†J. Edukasi dan Penelit. Inform., vol. 5, no. 1, pp. 18–23, 2019, doi: 10.26418/jp.v5i1.31074.
Suryani Dhebys, Yunianto Dika Rizky, and P Ade Desvin Renata Paksi, “Sistem Peramalan Hasil Panen Dan Permintaan Pasar Buah Apel Menggunakan Metode Fuzzy Time Series (Studi Kasus Dinas Pertanian Kota Batu),†in Siap, 2020, pp. 458–462.
W. Widiyani, Y. Setyawan, and M. T. Jatipaningrum, “Perbandingan Metode Fuzzy Time Series-Chen Dan Weighted Fuzzy Integrated Time Series Untuk Memprediksi Data Indeks Harga Saham Gabungan,†J. Stat. Ind. dan Komputasi, vol. 7, no. 1, pp. 81–87, 2022.
V. Virgianti and S. Martha, “Penerapan Fuzzy Time Series Chen Average Based Pada Peramalan Curah Hujan,†Bul. Ilm. Math. Stat. dan Ter., vol. 10, no. 4, pp. 485–494, 2021.
E. Dulfitri Eha and Suwanda, “Pemodelan Fuzzy Time Series Cheng untuk Meramalkan Nilai Ekspor Migas di Indonesia,†Bandung Conf. Ser. Stat., vol. 3, no. 2, pp. 130–139, 2023, doi: 10.29313/bcss.v3i2.7604.
Mohammad Reza febrino, Dony Permana, Syafriandi, and Nonong Amalita, “Comparison of Forecasting Using Fuzzy Time Series Chen Model and Lee Model to Closing Price of Composite Stock Price Index,†UNP J. Stat. Data Sci., vol. 1, no. 2, pp. 74–81, 2023, doi: 10.24036/ujsds/vol1-iss2/22.
D. P. Sugumonrong and A. Handinata, “Prediksi Harga Emas Menggunakan Metode Fuzzy Time Series Model Algoritma Chen,†Informatics Eng. Res. Technol., vol. 1, no. 1, pp. 48–54, 2019.
A. Ikhsanudin, K. Imam Santoso, and S. Wahyudiono, “Metode Fuzzy Time Series Model Chen untuk Memprediksi Jumlah Kasus Aktif Covid-19 di Indonesia,†J. Transform., vol. 18, no. 1, pp. 40–53, 2022.
Y. Yehoshua, K. Kustanto, and R. T. Vulandari, “Prediksi Penjualan Produk Promo PT. Unilever, Tbk Menggunakan Metode Fuzzy Time Series,†J. Inf. J. Penelit. dan Pengabdi. Masy., vol. 6, no. 2, pp. 51–57, 2020, doi: 10.46808/informa.v6i2.184.
L. Setiyani, “Pengujian Sistem Informasi Inventory Pada Perusahaan Distributor Farmasi Menggunakan Metode Black Box Testing,†Techno Xplore J. Ilmu Komput. dan Teknol. Inf., vol. 4, no. 1, pp. 1–9, 2019, doi: 10.36805/technoxplore.v4i1.539.
G. Ngurah, M. Nata, and P. P. Yudiastra, “Fuzzy Inference System dan Fuzzy Database sebagai Kecerdasan Basis Data untuk Kontrol Stok,†J. Sist. Dan Inform., vol. 16, pp. 59–67, 2022.
J. Warmansyah and D. Hilpiah, “Penerapan metode fuzzy sugeno untuk prediksi persediaan bahan baku,†Teknois J. Ilm. Teknol. Inf. dan Sains, vol. 9, no. 2, pp. 12–20, 2019, doi: 10.36350/jbs.v9i2.58.
B. C. Kosasih and N. Setiyawati, “Sistem Pendukung Keputusan Penentuan Pemesanan Barang Menggunakan Logika Fuzzy Tsukamoto (Studi Kasus: Studio Foto Kencana),†J. Algoritm. Log. dan Komputasi, vol. 3, no. 1, pp. 215–222, 2020, doi: 10.30813/j-alu.v3i1.1935.
R. Y. Hayuningtyas and R. Sari, “Aplikasi Peramalan Alat Kesehatan Menggunakan Single Moving Average,†J. Infortech, vol. 3, no. 1, pp. 40–45, 2021, doi: 10.31294/infortech.v3i1.10397.
T. Handayani, A. H. Furqon, and S. Supriyono, “Rancang Bangun Sistem Inventori Pengendalian Stok Barang Berbasis Java Pada PT Kalibesar Artah Perkasa,†J. SITECH Sist. Inf. dan Teknol., vol. 3, no. 1, pp. 35–40, 2020, doi: 10.24176/sitech.v3i1.4884.
L. J. R. Nababan, M. I. Hutapea, R. Perangin-angin, and E. N. Purba, “Aplikasi Persediaan Obat Dan Perlengkapan Alat Medis Pada Klinik Hana Kasih,†Maj. Ilm. METHODA, vol. 12, no. 1, pp. 32–36, 2022, doi: 10.46880/methoda.vol12no1.pp32-36.
A. Nisa and K. Harefa, “Penerapan Metode Fuzzy Inference System Untuk Memprediksi Jumlah Pembelian Stok Barang (Studi Kasus: Toko Yanto Grosir),†J. Ilmu Komput. dan Pendidik., vol. 1, no. 4, pp. 939–953, 2023, [Online]. Available: https://journal.mediapublikasi.id/index.php/logic.
I. Setiadi and I. Budiarso, “Sistem Pendukung Keputusan Pengendalian Inventaris Barang Atk dengan Menggunakan Metode Fuzzy,†JRKT (Jurnal Rekayasa Komputasi Ter., vol. 03, no. 03, pp. 127–142, 2023.
K. Rodiana, B. Turnip, and M. Marbun, “Sistem Pendukung Keputusan Penentuan Jumlah Pemesanan Obat Pada Apotek Dengan Metode Fuzzy Tsukamoto,†JOISIE J. Inf. Syst. Informatics Eng., vol. 4, no. Desember, pp. 139–146, 2020.
C. Rahmad, M. F. Ramadhani, and D. Puspitasari, “Peramalan Jumlah Kedatangan Wisatawan Mancanegara Dengan Menggunakan Metode Time Invariant Fuzzy Time Series (Studi Kasus : Wisata Kabupaten Pasuruan),†J. Inform. Polinema, vol. 4, no. 3, p. 195, 2018, doi: 10.33795/jip.v4i3.206.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).