Penerapan Data Mining Dalam Estimasi Harga Emas Menggunakan Algoritma Trend Moment Pada PT Victoeria Vici
DOI:
https://doi.org/10.59435/jocstec.v4i2.754Keywords:
PTVictoeriaVici, gold, Microsoft Access, Data Mining, Trend MomentAbstract
Emas merupakan salah satu jenis komoditi yang paling banyak diminati untuk tujuan investasi, karena dipandang sebagai instrumen yang lebih aman dibandingkan saham serta memiliki nilai jual yang selalu bergerak mengikuti kondisi pasar. PT Victoeria Vici, sebagai pelaku usaha perhiasan emas custom, menghadapi kendala dalam menentukan estimasi harga jual kepada pelanggan, sebab proses pengerjaan pesanan custom membutuhkan waktu hingga 14 hari, sementara harga emas bergerak fluktuatif dan tidak terstruktur setiap harinya sehingga estimasi harga menjadi tidak akurat dan tidak efektif. Berdasarkan permasalahan tersebut, penelitian ini menerapkan konsep Data Mining dengan algoritma Trend Moment untuk mengestimasi harga emas pada rentang waktu tertentu. Data yang digunakan merupakan data historis harga emas per gram pada PT Victoeria Vici periode Agustus–Oktober 2021 sebanyak 92 data. Tahapan penelitian meliputi pengumpulan data, penentuan variabel X dan Y, eliminasi untuk memperoleh nilai konstanta a dan slope b, serta penerapan persamaan Y = a + bX untuk memperoleh nilai estimasi. Hasil perhitungan menunjukkan nilai a = 720.871,725 dan b = 3,108 sehingga model estimasi mampu menghasilkan proyeksi harga emas yang mendekati pola data historis. Model ini kemudian diimplementasikan ke dalam aplikasi berbasis desktop menggunakan Microsoft Visual Basic 2010 dan basis data Microsoft Access, dilengkapi Crystal Report untuk pencetakan laporan hasil estimasi. Hasil penelitian menunjukkan bahwa algoritma Trend Moment dapat membantu PT Victoeria Vici dalam memperoleh estimasi harga emas secara lebih cepat, konsisten, dan terdokumentasi.
Gold is one of the most sought-after commodities for investment purposes, as it is regarded as a safer instrument compared to stocks and has a selling value that constantly fluctuates with market conditions. PT Victoeria Vici, a custom gold jewelry business, faces difficulty in determining the estimated selling price offered to customers because the production process for custom orders takes up to 14 days, while gold prices move in an unstructured and fluctuating manner every day, making manual price estimation inaccurate and ineffective. Based on this problem, this study applies the concept of Data Mining using the Trend Moment algorithm to estimate gold prices over a certain period of time. The data used is historical daily gold price data per gram from PT Victoeria Vici for the period of August–October 2021, consisting of 92 records. The research stages include data collection, determination of the X and Y variables, elimination to obtain the constant value a and the slope b, and the application of the equation Y = a + bX to obtain the estimated value. The calculation results show a value of a = 720,871.725 and b = 3.108, so that the estimation model is able to produce gold price projections that closely follow the pattern of historical data. This model was then implemented into a desktop-based application using Microsoft Visual Basic 2010 and a Microsoft Access database, equipped with Crystal Report for printing estimation result reports. The results show that the Trend Moment algorithm can help PT Victoeria Vici obtain gold price estimations more quickly, consistently, and in a well-documented manner.
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