Judul: Nonparametric Regression  Spline Truncated Modelling on External Factors Affecting Stock Prices
Abstrak: Saham adalah salah satu instrumen investasi yang diminati investor. Akan tetapi, harga saham bergerak cepat dan fluktuatif. Pergerakan harga saham dipengaruhi oleh banyak faktor di antaranya adalah inflasi, suku bunga, dan kurs USD, yang merupakan faktor eksternal di luar perusahaan. Penelitian ini bertujuan membuat model pengaruh inflasi, suku bunga, dan kurs USD terhadap harga saham menggunakan data longitudinal. Model dibuat menggunakan regresi nonparametrik spline truncated. Data yang digunakan dalam penelitian ini terdiri dari dua emiten, yaitu PT. Astra Agro Lestari (AALI) dan PT. Perusahaan Perkebunan London Sumatra (LSIP). Data dipisahkan menjadi dua sampel, yaitu data in sample dimulai dari Januari 2017 – Desember 2020 yang digunakan untuk membuat model dan data out sample dimulai dari Januari 2021 – Desember 2021 untuk diprediksi. Metode MAPE digunakan sebagai alat pengukur kinerja prediksi. Hasil penelitian menunjukkan model terbaik untuk saham AALI memiliki tiga titik knot dan memiliki nilai MAPE sebesar 17,27%. Model terbaik untuk saham LSIP memiliki tiga titik knot dan memiliki nilai MAPE sebesar 13,42%., Stock is one of investment instruments that an investor has an interest in. However, stocks move fast and fluctuate. The movement of the stock price is influenced by many factors including inflation, interest rate and USD exchange rate which are external factors outside the company. This manuscript aims to create a model for influence of inflation, interest rate, and USD exchange rate on stock prices uses longitudinal data. The models were obtained by using nonparametric regression spline truncated. The data consisted of stocks from two companies, namely PT. Astra Agro Lestari (AALI) and PT. Perusahaan Perkebunan London Sumatra (LSIP). The data were split into two sub-samples which were “in sample” data from January 2017 – December 2020 that were used to generate the models and “out sample” data from January 2021 – December 2021 that were used in predictions. MAPE was used as measurement of predictive performance. The results show that the best model for AALI has three knot points and has a MAPE value of 17,27%. The best model for LSIP has three knots and has a MAPE value of 13,42%.
Keyword: data longitudinal, regresi nonparametrik spline truncated, saham, longitudinal data, nonparametric regression spline truncated, stock

Judul: Stock Price Modelling in the Banking Sector Using Multivariable B-Spline Regression
Abstrak: Laporan keuangan perusahaan biasanya digunakan oleh investor sebagai pertimbangan dalam membeli saham. Di dalam laporan keuangan terdapat rasio keuangan yang menggambarkan kondisi perusahaan. Penelitian ini bertujuan untuk membangun model persamaan regresi terbaik dari rasio keuangan yang berpengaruh terhadap pergerakan harga saham. Sampel yang digunakan adalah laporan keuangan 4 perusahan perbankan yang tercatat di Bursa Efek Indonesia (BEI) periode 2018 hingga 2022. Variabel bebas yang digunakan dalam penelitian ini adalah debt to equity ratio (DER) dan earning per share (EPS) sedangkan variabel terikat yang digunakan adalah harga saham. Penelitian ini menggunakan metode analisis regresi non parametrik yaitu regresi B-Spline. Hasil penelitian menunjukkan model harga saham terbaik dipilih dengan kombinasi empat titik knot dan jumlah orde lima., Company financial reports are typically utilized by investors as a consideration when purchasing stocks. Within financial reports, there are financial ratios that depict the company's condition. This research aims to construct the best regression equation model from influential financial ratios on stock price movements. The sample consists of financial reports from four banking companies listed on the Indonesia Stock Exchange (IDX) from 2018 to 2022. The independent variables in this study are the debt-to-equity ratio (DER) and earnings per share (EPS), while the dependent variable is the stock price. This research employs the non-parametric regression analysis method, namely B-Spline regression. The research results indicate that the best stock price model is selected with a combination of four knot points and a fifth order.
Keyword: debt to equity ratio, earning per share, harga saham, orde, regresi b-spline, titik knot, b-spline regression, stock price, knot points, order

Judul: Detoxification of Cassava’s Acid Hydrolyzate by Activated Carbon Method for Bioethanol Production
Abstrak: Cassava is one of natural resources for carbohydrate that also available for bioethanol production. Starch and fibers hydrolysis maybe conducted on acid condition. The restriction in acid hydrolysis is 5-hydroxymethyl furfural (HMF) and furfural formation, which inhibit yeast fermentation. This study applied two stages of detoxification, which are overliming and activated carbon adsorption methods for lowering HMF and furfural concentrations. In order to obtain tolerable amount in sugar solution, detoxification by activated carbon adsorption was done by concentration of 1%, 2.5%, 5% and 10% and duration of contact are 30 45 and 60 minutes. The results showed that overliming method decreased HMF and furfural concentrations 34.38% and 60.81%, respectively. Overliming followed by 5% activated carbon adsorption for 30 minutes produced the best sugar solution which has a lower HMF and furfural concentrations by 72.03% and 89.11%, respectively. Adsorption constants of HMF and furfural by 5% activated carbon were 0.044 g/min and 3,7 x 10-5 g/min, respectively. The concentration of ethanol produced was 5.00% (b/v) or 63.22% higher than obtained from detoxification by neutralization (NH4OH) which produced ethanol only 3.06%.
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