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All Journal Jurnal Matematika Sains dan Teknologi Jurnal Statistika dan Aplikasinya Prosiding Seminar Nasional Teknologi Industri Berkelanjutan
Andika Putri Ratnasari
Department Of Statistics, Faculty Of Mathematics And Natural Sciences, IPB University, Indonesia
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Other

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Validasi Metode Penetapan Kadar Au, Ag, Cu dalam sampel Karbon Aktif Andika Putri Ratnasari; Erlinda Ningsih
Prosiding SENASTITAN: Seminar Nasional Teknologi Industri Berkelanjutan Prosiding SENASTITAN Vol. 03 2023
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Laboratorium merupakan suatu tempat yang menghasilkan keluaran atau output berupa nilai yang valid. Untuk memperoleh nilai yang valid, suatu metode yang digunakan di Laboratorium harus tervalidasi terlebih dahulu. Validasi biasa dilakukan ketika metode pertama kali digunakan di Laboratorium atau terdapat modifikasi pada metode yang telah tervalidasi. Tujuan dari validasi ini yaitu untuk mengetahui metode awal yang digunakan berbeda nyata atau tidak berbeda nyata dengan metode yang dimodifikasi. Modifikasi yang dilakukan pada metode ini yaitu pada tahap preparasi yang seharusnya sampel activity carbon dihaluskan (pulverized) sebelum pengabuan akan tetapi tidak dihaluskan (tanpa pulverized). Metode percobaan pada validasi metode penetapan kadar Au, Ag, Cu dalam sampel karbon aktif terdiri dari 3 tahap yaitu tahap preparasi, tahap pengukuran, dan tahap pengolahan data. Hasil Analisa menunjukkan bahwa metode penetapan kadar Au, Ag, Cu dengan pulverized atau tanpa pulverized tidak berbeda nyata atau sama dengan tingkat Probabilitas 95%. Dengan demikian, metode tersebut dapat digunakan untuk analisis rutin di Laboratorium PT X.
APLIKASI MODEL ARIMA GARCH DALAM PERAMALAN DATA NILAI TUKAR RUPIAH TERHADAP DOLAR TAHUN 2017-2022 Nickyta Shavira Maharani; Yenni Angraini; Mahesa Ahmad Rahmawan; Oktaviani Aisyah Putri; Steven Kurniawan; Tias Amalia Safitri; Akbar Rizki; Wiwik Andriyani Lestari Ningsih; Nabila Ghoni Trisno Hidayatulloh; Andika Putri Ratnasari
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 1 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i1.4875.2023

Abstract

The Indonesian rupiah (IDR) exchange rate is used to gauge Indonesia's economic stability. Maintaining the IDR exchange rate's stability is critical since it has a direct impact on Indonesia's national monetary situation, particularly during the Covid-19 pandemic. Forecasting the rupiah exchange rate is important to do and is one way to assess government policy. The data series to be used here are IDR exchange rate from the Yahoo Finance. It consists of 271 data taken from August 2017 to October 2022. This study aims to use the Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) modeling method using the R-studio software and predict the IDR exchange rate. The ARIMA method describes the data based on a certain time series. ARCH-Lagrange Multiplier (ARCH-LM) was applied on the residuals of the best ARIMA model to test whetoer the data is heteroscedasticity. The testing result shows that the residual of the IDR exchange rate is heteroscedasticity. Therefore, the GARCH model can be used to handle it. The results of this study are obtained for the ARIMA(2,1,3) GARCH(3,6) model as the best and describe the actual data pattern with a mean absolute percentage error (MAPE) forecasting value is 1,99%.
Aplikasi Model ARIMA dalam Peramalan Data Harga Emas Dunia Tahun 2010-2022 Mohammad Abror Gustiansyah; Akbar Rizki; Berliana Apriyanti; Kenia Maulidia; Raffael Julio Roger Roa; Oksi Al Hadi; Nabila Ghoni Trisno Hidayatulloh; Wiwik Andriyani Lestari Ningsih; Andika Putri Ratnasari; Yenni Angraini
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07108

Abstract

Gold investment is one of the favorite investments during the Covid-19 pandemic because the price of gold is relatively volatile but shows an increasing trend. Savvy investors investing in gold need to be able to predict future opportunities. Therefore, price estimation is needed to develop a buying and selling strategy to maximize profits. The Autoregressive Integrated Moving Average (ARIMA) model is a suitable method for predicting time series data, so the best ARIMA model will be applied for forecasting world gold prices. The best ARIMA model is selected based on the Akaike Information Criterion (AIC) and Mean Absolute Percentage Error (MAPE) criteria. Monthly world gold price data for 146 periods are applied in this study and will be used to predict gold prices for the following six periods. ARIMA (0,1,1) is the best model obtained from the analysis results, with AIC and MAPE values of 1264.731 and 11.972%, respectively. Forecasting results show that world gold prices will increase for the next periods.
Co-Authors Akbar Rizki Akbar Rizki Berliana Apriyanti Erlinda Ningsih, Erlinda Kenia Maulidia Mahesa Ahmad Rahmawan Mohammad Abror Gustiansyah Nabila Ghoni Trisno Hidayatulloh Nabila Ghoni Trisno Hidayatulloh Nickyta Shavira Maharani Oksi Al Hadi Oktaviani Aisyah Putri Raffael Julio Roger Roa Steven Kurniawan Tias Amalia Safitri Wiwik Andriyani Lestari Ningsih Wiwik Andriyani Lestari Ningsih Yenni Angraini