Judul: Application of ARIMA Model and Average-Based Fuzzy Time Series  Method on Shares Forecasting (Case Study: Close Price of PT. United Tractors Tbk Shares)
Abstrak: Terdapat beragam instrumen yang dapat digunakan untuk berinvestasi, salah satunya adalah saham. Berinvestasi dengan membeli sejumlah saham cukup berisiko karena adanya perubahan harga saham yang fluktuatif tiap waktu. Oleh karena itu, dibutuhkan metode peramalan data deret waktu sehingga pengambilan keputusan di kemudian waktu dapat dilakukan lebih akurat. Penelitian ini menerapkan model Autoregressive Integrated Moving Average (ARIMA) dan metode Fuzzy Time Series (FTS) berbasis rerata. Data yang digunakan dalam penelitian ini merupakan data harian dari harga penutupan saham PT. United Tractors Tbk periode 2 Januari 2017 – 26 Juni 2020. Peramalan pada data latih dengan metode FTS berbasis rerata menghasilkan MAPE sebesar 1,67% dan RMSE sebesar 590,528 sedangkan model ARIMA menghasilkan nilai MAPE sebesar 2,74% dan RMSE sebesar 978,491. Nilai MAPE dan RMSE pada metode FTS berbasis rerata lebih kecil dibandingkan dengan model ARIMA, sehingga dapat disimpulkan bahwa metode FTS berbasis rerata bekerja lebih baik dalam meramalkan nilai harga penutupan saham PT. United Tractors Tbk periode 2017 – 2020., There are several instruments that can be used for investment, one of them is shares. Investing by buying shares are pretty risky due to fluctuating price changes overtimes. Therefore, a time series data forecasting is needed so that future decision making can be done more accurately. This research applies Autoregressive Integrated Moving Average (ARIMA) model and average-based Fuzzy Time Series (FTS) method. The data used in this research is daily data of close price of PT. United Tractors Tbk shares start from 2 January 2017 – 26 June 2020. Forecasting on testing data with average-based FTS produces MAPE of 1,67% and RMSE of 590,528 whilst ARIMA model produces MAPE of 2,74% and RMSE of 978,491. MAPE and RMSE values in average-based FTS methods are smaller than ARIMA model, so it can be concluded that average-based FTS works better on forecasting close price of PT. United Tractors Tbk shares for period 2017 – 2020
Keyword: ARIMA, fluctuating, forecasting, Fuzzy Time Series, shares

Judul: Comparison of Autoregressive Integrated Moving Average and Average-Based Fuzzy Time Series in Forecasting Stock Closing Price (Case study: PT Adaro Energy Tbk)
Abstrak: Perkembangan pada bidang ekonomi menyebabkan kemunculan berbagai metode untuk memenuhi kebutuhan finansial. Salah satunya adalah dengan berinvestasi di pasar saham. Diperlukan metode peramalan untuk mengetahui harga masa depan dari suatu saham. Penelitian ini bertujuan melakukan peramalan harga penutupan saham dengan bantuan metode Autoregressive Integrated Moving Average (ARIMA) dan Average-Based Fuzzy Time Series (FTS). Data yang digunakan adalah data historis harga penutupan saham PT Adaro Energy Tbk periode 12 April 2021 hingga 28 April 2022. Peramalan dengan metode ARIMA menghasilkan nilai MAPE sebesar 10,75% dan RMSE sebesar 372,11 sedangkan FTS berbasis rataan menghasilkan nilai MAPE sebesar 2,74% dan RMSE sebesar 125,49. Nilai MAPE dan RMSE yang dihasilkan metode FTS berbasis rataan lebih baik dibanding ARIMA, sehingga dapat disimpulkan bahwa metode FTS berbasis rataan lebih baik daripada ARIMA dalam meramalkan harga penutupan saham PT. Adaro Energy Tbk. Peramalan 10 hari ke depan dengan metode FTS berbasis rataan menghasilkan MAPE sebesar 2,57% dan RMSE sebesar 105,92., The advances in the field of economics has made many methods of fulfilling financial needs emerge. One of those methods is investing in the stock market. Prediction methods are needed to know the future price of stocks. This study aims to forecast stock closing price using Autoregressive Integrated Moving Average (ARIMA) and Average-Based Fuzzy Time Series (FTS). The data used in this study is historical stock closing price data of PT. Adaro Energy Tbk from April 12th 2021 to April 28th 2022. Forecasting with ARIMA produced MAPE value of 10,75% and RMSE of 372,11 while forecasting with average-based FTS produced MAPE value of 2,74% and RMSE of 125,49. The values of MAPE and RMSE produced by the average-based FTS method are better than ARIMA, which indicate that average-based FTS is better than ARIMA in forecasting stock closing price of PT. Adaro Energy Tbk. A forecast of 10 days ahead using average-based FTS produced a MAPE score of 2,57% and RMSE score of 105,92.
Keyword: ARIMA, fuzzy time series, stocks, forecast

Judul: Pengembangan Bionanokomposit Film Berbasis Tapioka/Nanopartikel Perak dan Tapioka/Nanopartikel Seng Oksida dengan Plasticizer Gliserol.
Abstrak: Cassava starch can be formed into bioplastic film which is transparance as synthetic plastic films. However, pure cassava starch film has some drawbacks such as brittle, poor barrier to water vapour, sensitive to humidity and not stable during the application. The addition of nanoparticles in film was intended to increase the elongation and tensile strength, moisture stability and to provide antimicrobial activity. Meanwhile, the addition of glycerol was intended to increase the plasticity of films so they will not be easily cracked. The main purpose of this research is to elaborate the functional packaging characteristics of bionanocomposites films made from cassava starch with or without silver nanoparticles (Ag-Np) of zinc oxide nanoparticles (ZnO-Np) with glycerol as plasticizer. The addition of nanoparticles was conducted at the amount of 0%, 0,5%, and 1% by weight of the starch, whereas glycerol was used at the amount of 0% and 20% by weight of the solids (starch only or starch+nanoparticles). The value of water vapor transmission decreased significantly with the addition of Ag-Np and ZnO-Np at the concentration of 1% (from 18,0569 g/hm2 to 12,0574 g/hm2) so it enhance the water barrier of the films as packaging materials. The addition of Ag-Np and ZnO-Np at the amount of 1% with 20% of glycerol was also able to inreased the value of elongation (from 1,2% to 88,8%), but decreased the value of tensile strength (from 22,93 MPa to 4,03 MPa). The addition of glycerol gave contrary effect to the tensile strength because it produces low tensile strength values. Moreover, the results show that films made with ZnO-Np had a stronger antimicrobial activity than those made with Ag-Np for both gram positive and gram negative bacteria. In overall, it seems that the formulation of 1% ZnO-Np is the best formulation for developing bionanocomposite film based on cassava starch.
Keyword: Bionanocomposite Films, Silver Nanoparticle (Ag-Np), Zinc Oxide Nanoparticle (ZnO-Np), Cassava Starch, Antibacterial Films