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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Saintek Lahan Kering EKOLOGIA : Jurnal Ilmiah Ilmu Dasar dan Lingkungan Hidup BERNAS: Jurnal Pengabdian Kepada Masyarakat Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal PkM Setiadharma Jurnal Karya Abdi Masyarakat Pelita: Jurnal Pengabdian kepada Masyarakat International Journal of Applied Mathematics, Sciences, and Technology for National Defense Journal of Mathematics, Computation and Statistics (JMATHCOS) Jurnal Jendela Matematika J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Jurnal Pengabdian Masyarakat Inovatif Jurnal Pengabdian Masyarakat Inovatif
Isti Kamila
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Uncovering the potential of mining stocks: Analysis of price prediction and fundamental performance using double exponential smoothing and discounted cash flow Kamila, Isti; Mushliha; Indrawan; Azka, Muhammad; Sembiring, Brema
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528611

Abstract

The purpose of this research was to forecast the stock prices of the mining sector using the Double Exponential Smoothing method and to determine the intrinsic value of stocks using the Discounted Cash Flow method as a recommendation for investment decisions in stocks. The data used was secondary data consisting of closing prices and financial reports from 2022 to 2024 for 10 mining stocks listed on the Main Board of the Energy sector on the IDX website. Based on the results of determining the intrinsic value of the stocks using the DCF method, seven mining stock issuers were categorized as undervalued, namely ABMM, BUMI, BYAN, DEWA, GEMS, HRUM, and INDY, while three other stock issuers were categorized as overvalued, namely ADRO, DSSA, and ITMG. Based on the forecasting results using the Double Exponential Smoothing method, from the seven issuers in the undervalued category, there were two issuers, BYAN and DEWA, that have the potential to experience a price increase. The results of the stock price forecasting evaluation using MAPE show that it was categorized as very accurate with a MAPE value range of 0.6% to 3.5%.
Pemodelan Pengaruh Nilai Tukar Rupiah Terhadap Dollar Dengan Indeks Harga Saham Gabungan Kompas 100 menggunakan metode Gauss Newton Triyanto, Muhammad; Andriyati, Ani; Kamila, Isti; Rohaeti, Embay
JURNAL JENDELA MATEMATIKA Vol. 2 No. 01 (2024): Jurnal Jendela Matematika: Edisi Januari 2024
Publisher : CV. Jendela Edukasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57008/jjm.v2i01.669

Abstract

Penelitian bertujuan untuk memodelkan hubungan antara nilai tukar Rupiah terhadap Dollar dengan Indeks harga saham kompas 100. Berdasarkan informasi penelitian terdahulu bahwa hubungan nilai tukar mata uang terhadap harga saham bersifat non linier. Pemodelan regresi non linier pada penelitian ini dilakukan dengan pendekatan numerik melalui algoritma Gauss Newton. Metode Gauss Newton merupakan metode sederhana yang sangat efisien yang digunakan untuk menyelesaikan masalah pendugaan kuadrat terkecil. Metode Gauss Newton digunakan untuk menduga parameter dengan meminimalkan jumlah nilai dari suatu fungsi, dimana dalam menyelesaikannya tidak memerlukan perhitungan atau estimasi dari turunan kedua fungsi f(x) karena secara numerik lebih efektif dengan proses langsung atau iteratif. Proses pendugaan dimulai dengan fungsi f=(x,β_0,β_1 )=β_0 (1-e^(-β_1 X)) dengan dugaan awal parameter β_0=0,1 dan  β_1=1 dan JKG awal sebesar 0,000250. Pembentukan nilai awal pada iterasi pertama diperoleh β_0,1=-2,16 dan β_1,1=25,16 dengan JKG  sebesar 268,173. Perhitungan diulang secara terus menerus sampai konvergen yaitu pada iterasi ketiga. Nilai pendugaan parameter pada iterasi ketiga yaitu  β_0,3=0,0066 dan  β_1,3=216,55 dengan nilai JKG terkecil yaitu 0,001769.
Application of ARIMA (Autoregressive Integrated Moving Average) model to predict Rupiah selling exchange rate against US Dollar Afif Febriawan; Fitria Virgantari; Isti Kamila; Eduard Taganap
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 1 No. 3 (2023): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v1i3.225

Abstract

Currency is a tool in the form of money that is accepted and valid and legal as a payment and economic transactions in a country. US dollar is benchmark for world currencies, so predicting rupiah against US dollar is important. The purpose of this study is to analyze the characteristics of daily selling rate Rupiah against US Dollar, determine best model, and make predictions selling rate of Rupiah against US Dollar. Data used is daily data on selling rate of Rupiah against US Dollar 20 November 2020 - 19 January 2023 with details data training 20 November 2020 - 20 November 2022 and data testing 21 November 2022 - 19 January 2023. The model used is Autoregressive Integrated Moving Averages (ARIMA). The best model was chosen based on the smallest Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Akaike Information Criterion (AIC). From the analysis results, it is found that best model is ARIMA (2,1,2) because it has significant parameters, white-noise residuals and has smallest MSE and MAPE values. With ARIMA model (2,1,2) the forecasting results for January 20 2023 – January 31 2023 is obtained with highest selling price on January 30 2023 Rp.15,932.4 and smallest on January 20 2023 Rp.15,901.9 and the average Rp.15,919.4. Based on these results, exporters and importers can consider their business activities.
Co-Authors Afif Febriawan Amar Sumarsa Ananda Br Pelawi, Riva Andriyati, Ani Anggraeni, Fidela Ani Andriyati Azka, Muhammad Bahar, Nur Qadri Dwi Puji Ramadhani, Novira Eduard Taganap Eka Herlina Eka Herlina Embay Rohaeti Fatanah Zetafahrul, Philant Fitria Virgantari Indrawan Mawar Desember, Natalie Maya Widyastiti Maya Widyastiti, Maya Mulyati , Mushliha Prilia Ditasari Ramadhany Rumengan, Novia Rauf, Nurul Maqfirah Revi Meliyani Santoso, Eka Krisna Sara, Siti Aisah Sembiring, Brema Triyanto, Muhammad Virgantari, Fitria