Penentuan Harga Tandan Buah Segar (TBS) Kelapa Sawit Menggunakan Metode Fuzzy Logic


Amriana Amriana(1); Anita Ahmad Kasim(2); Maghfirat Maghfirat(3*);

(1) Universitas Tadulako
(2) Universitas Tadulako
(3) Universitas Tadulako
(*) Corresponding Author

  

Abstract


The purpose of this study is to create a system for determining the price of oil palm fresh fruit bunches using the Fuzzy Logic method. Oil palm plantations are plantations that have natural resources that can generate large profits, which are used as cooking oil and much more. Palm oil FFB consists of Crude Palm Oil (CPO), which is fruit flesh oil and Palm Kernel (PK), which is the kernel of palm oil. This research makes the system use 5 input variables that is CPO price, IKS price, K Index, CPO Rendemen and IKS Rendemen, and one output variable which is the price of oil palm FFB. This system uses the Fuzzy Logic method because in this study there is fuzzy that can be determined, namely the price of oil palm-based TBS. This system uses 100 data to request using MAPE so that a percentage value is 85.75%. While the average value of the difference between the actual data and the results of the fuzzy Mamdani data is 17852 with an average percentage of errors of the fuzzy Mamdani data is 14.25%. The result of this system is the variable price of oil palm FFB output based on 5 variable inputs. The Mamdani Fuzzy Logic method determines the outcome of an uncertain value. Fuzzy logic starts from the formation of fuzzy sets, then implications, then rules, and then defuzzification.

Keywords


Determination; Price; Fresh Fruit Bunches; Palm Oil; Fuzzy Logic

  
     

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Digital Object Identifier

doi  https://doi.org/10.33096/ilkom.v12i3.619.%25p
  

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References


Afrizon, “Pertumbuhan Bibit Kelapa Sawit (Elaeis guineensis Jacq.) Dengan Pemberian Pupuk Organik dan Anorganik,” AGRITEPA, vol. III, no. 2, pp. 95–105, 2017.

I. R. Purba, Irsal, and Meiriani, “Hubungan Fraksi Kematangan Buah dan Ketinggian Tandan terhadap Jumlah Buah Memberondol pada Panen Kelapa Sawit (Elaeis guineensis Jacq) di Kebun Rambutan PTPN III,” J. Agroekoteknologi FP USU, vol. 5, no. 2, pp. 315–328, 2017.

Republik Indonesia, “Peraturan Menteri Pertanian Nomor 01 Tahun 2018 Tentang Pedoman Penetapan Harga Pembelian Tandan Buah Segar Kelapa Sawit.pdf.” pp. 1–26, 2018.

R. E. Caraka, H. Yasin, and A. W. Basyiruddin, “Peramalan Crude Palm Oil ( CPO ) Menggunakan Support Vector Regression Kernel Radial Basis,” J. Mat., vol. 7, no. 1, pp. 43–57, 2017.

S. Andriyani and N. Sitohang, “Implementasi Metode Backpropagation Untuk Prediksi Harga Juanl Kelapa Sawit Berdasarkan Kualitas Buah,” JURTEKSI (Jurnal Teknol. dan Sist. Informasi), vol. IV, no. 2, pp. 155–164, 2018.

D. Rahayu, R. C. Wihandika, and R. S. Perdana, “Implementasi Metode Backpropagation Untuk Klasifikasi Kenaikan Harga Minyak Kelapa Sawit,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 4, pp. 1547–1552, 2018.

H. Aini, Haviluddin, E. Budiman, M. Wati, and N. Puspitasari, “Prediksi Produksi Minyak Kelapa Sawit Menggunakan Metode Backpropagation Neural Network,” Sains, Apl. Komputasi dan Teknol. Inf., vol. 1, no. 1, pp. 24–33, 2019.

D. L. Rahakbauw, F. J. Rianekuay, and Y. A. Lesnussa, “Penerapan Metode Fuzzy Mamdani Untuk Memprediksi Jumlah Produksi Karet (Studi Kasus: Data Persediaan Dan Permintaan Produksi Karet Pada Ptp Nusantara Xiv (Persero) Kebun Awaya, Teluk Elpaputih, Maluku-Indonesia),” J. Ilm. Mat. Dan Terap., vol. 16, no. 1, pp. 51–59, 2019.

S. Y. Nababan and M. Harahap, “Implementasi Metode Tsukamoto Pada Analisis Prediksi Hasil,” J. Penelit. Tek. Inform., vol. 3, no. 1, pp. 1–10, 2020.

G. Tendra, “Implementasi Fuzzy Logic Mamdani Untuk Menentukan Kelayakan Calon Anggota Tamtama (CATAM) Tentara Negara Indonesia Angkatan Darat (TNI-AD),” J. PI-Cache, vol. 5, no. 1, pp. 1–11, 2016.

M. Abrori and A. H. Prihamayu, “Aplikasi Logika Fuzzy Metode Mamdani Dalam Pengambilan Keputusan Penentuan Jumlah Produksi,” Kaunia, vol. XI, no. 2, pp. 91–99, 2015.

A. R. Wardani, Y. N. Nasution, and F. D. T. Amijaya, “Aplikasi Logika Fuzzy Dalam Mengoptimalkan Produksi Minyak Kelapa Sawit Di PT. Waru Kaltim Plantation Menggunakan Metode Mamdani,” Inform. Mulawarman J. Ilm. Ilmu Komput., vol. 12, no. 2, p. 94, 2017.

M. Yusida, D. Kartini, A. Farmandi, R. A. Nugroho, and Muliadi, “Implementasi Fuzzy Tsukamoto Dalam Penentuan Kesesuaian Lahan Untuk Tanaman Karet Dan Kelapa Sawit,” Klik - Kumpul. J. Ilmu Komput., vol. 4, no. 2, p. 233, 2017.

A. Bahroini, A. Farmadi, and R. A. Nugroho, “Prediksi Permintaan Produk Mie Instan Dengan Metode Fuzzy Takagi-Sugeno,” Klik - Kumpul. J. Ilmu Komput., vol. 3, no. 2, pp. 220–230, 2016.

M. Destiningrum and Q. J. Adrian, “Sistem Informasi Penjadwalan Dokter Berbasis Web Dengan Menggunakan Framework Codeigniter (Studi Kasus: Rumah Sawit Yukum Medical Centre),” J. TEKNOINFO, vol. 11, no. 2, pp. 30–37, 2017.

B. Prasetyo, T. J. Pattiasina, and A. N. Soetarmono, “Perancangan dan Pembuatan Sistem Informasi Gudang ( Studi Kasus : PT . PLN ( Persero ) Area Surabaya Barat ),” Teknika, vol. 4, no. 1, pp. 12–16, 2015.

B. Putro, M. T. Furqon, and S. H. Wijoyo, “Prediksi Jumlah Kebutuhan Pemakaian Air Menggunakan Metode Exponential Smoothing ( Studi Kasus : PDAM Kota Malang ),” J. Pengemb. Teknol. Inf. dan Ilmu Komput. Univ. Brawijaya, vol. 2, no. 11, pp. 4679–4686, 2018.


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