bluuebunny/crossref_metadata_2025_split huggingface dataset:
MODEL KOMBINASI ARIMA DALAM PERAMALAN HARGA MINYAK MENTAH DUNIA
Authors: Setiyowati Eka , Rusgiyono Agus , Tarno Tarno 
Published: September 2020

Oil is the most important commodity in everyday life, because oil is one of the main sources of energy that is needed for other people. Changes in crude oil prices greatly affect the economic conditions of a country. Therefore, the aim of this study is develop an appropriate model for forecasting crude oil price based on the ARIMA and its ensembles. In this study, ensemble method uses some ARIMA models to create ensemble members which are then combined with averaging and stacking techniques. The data used are the price of world crude oil period 2003-2017. The results showed that ARIMA (1,1,0) model produces the smallest RMSE values for forecasting the next thirty six months. Keywords: Ensemble, ARIMA, Averaging, Stacking, Crude Oil Price
PEMODELAN JARINGAN SYARAF TIRUAN DENGAN CASCADE FORWARD BACKPROPAGATION PADA KURS RUPIAH TERHADAP DOLAR AMERIKA SERIKAT
Authors: Wigati Ekky Rosita Singgih , Warsito Budi , Rahmawati Rita 
Published: September 2020

Neural Network Modeling (NN) is an information-processing system that has characteristics in common with human brain. Cascade Forward Neural Network (CFNN) is an artificial neural network that its architecture similar to Feed Forward Neural Network (FFNN), but there is also a direct connection from input layer and output layer. In this study, we apply CFNN in time series field. The data used isexchange rate of rupiah against US dollar period of January 1st, 2015 until December 31st, 2017. The best model was built from 1 unit input layer with input Zt-1, 4 neurons in the hidden layer, and 1 unit output layer. The activation function used are the binary sigmoid in the hidden layer and linear in the output layer. The model produces MAPE of training data equal to 0.2995% and MAPE of testing data equal to 0.1504%. After obtaining the best model, the data is foreseen for January 2018 and produce MAPE equal to0.9801%. Keywords: artificial neural network, cascade forward, exchange rate, MAPE
PERAMALAN INDEKS HARGA SAHAM GABUNGAN DENGAN METODE LOGISTIC SMOOTH TRANSITION AUTOREGRESSIVE (LSTAR)
Authors: Kresnawati Gayuh , Warsito Budi , Hoyyi Abdul 
Published: September 2020

Smooth Transition Autoregressive (STAR) Model is one of time series model used in case of data that has nonlinear tendency. STAR is an expansion of Autoregressive (AR) Model and can be used if the nonlinear test is accepted. If the transition function G(st,γ,c) is logistic, the method used is Logistic Smooth Transition Autoregressive (LSTAR). Weekly IHSG data in period of 3 January 2010 until 24 December 2017 has nonlinier tend and logistic transition function so it can be modeled with LSTAR . The result of this research with significance level of 5% is the LSTAR(1,1) model. The forecast of IHSG data for the next 15 period has Mean Absolute Percentage Error (MAPE) 2,932612%. Keywords : autoregressive, LSTAR, nonlinier, time series
ANALISIS DAMPAK SHOCK VOLUME PERDAGANGAN SAHAM PADA INDEKS HARGA SAHAM CONSUMER GOODS DENGAN STRUCTURAL VECTOR AUTOREGRESSIVE (SVAR)
Authors: Kharismawan Infan Nur , Santoso Rukun , Warsito Budi 
Published: September 2020

The stock trading in the capital market will result daily volume of trading stock that impact on stock price. One of the indicators that describes the stock price movement is stock index. There are many types of stock index, one of them is consumer goods stock index. Stock index is a sensitive economic variable affected by shock and need a restriction to form its economic model. Based on that, Structural Vector Autoregressive (SVAR) is used to describe its economic model. SVAR is formed by a stable VAR, fulfilled white noise, k-variate normal distribution. The purpose of this study are to forecast data on each variables and analyze the impact of the shock through the descriptions of variance decomposition. VAR used as the basis for SVAR is VAR(8) whose the forming variable stationary at the first different degree. Performances of forecasting SVAR using MAPE (Mean Absolute Percentage Error) for in sample data are 13.87434% (volume of trading stock) and 0.87045% (consumer goods stock index) and for out sample data are 14.22964% (volume of trading stock) and 1.76054% (consumer goods stock index). Response of consumer goods stock index to the impact of the volume of trading stock shock shown by proportion of variance decomposition tends to increase, while the shock by itself has decreased until reach its equilibrium point. Keywords:cosumer goods stock index, SVAR, variance decomposition, volume of trading stock
PERAMALAN EKSPOR NONMIGAS DENGAN VARIASI KALENDER ISLAM MENGGUNAKAN X-13-ARIMA-SEATS (Studi Kasus: Ekspor Nonmigas Periode Januari 2013 sampai Desember 2017)
Authors: Lestari Eka , Widiharih Tatik , Rahmawati Rita 
Published: September 2020

Non-oil and gas exports are one of the largest foreign exchange earners for Indonesia. Non-oil and gas exports always experience a decline in the month of Eid Al-Fitr due to delays in the delivery of export goods because the loading and unloading of goods at the port is reduced during Eid Al-Fitr. The shift of the Eid Al-Fitr month on the data will form a pattern or season with an unequal period called the moving holiday effect. The time series forecasting method that usually used the ARIMA method. Because the ARIMA method only suitable for time series data with the same seasonal period and can’t handle the moving holiday effect, the X-13-ARIMA-SEATS method used two steps. First, regARIMA modeling is a linear regression between time series data and the weight of Eid Al-Fitr and the residuals follow the ARIMA process. The weighting is based on three conditions, namely pre_holiday, post_holiday, and multiple. Second, X-12-ARIMA decomposition method for seasonal adjustments that produces trend-cycle components, seasonal, and irregular. Based on the analysis carried out on the monthly non-oil and gas export data for the period January 2013 to December 2017, the X-13-ARIMA-SEATS (1,1,0) model was obtained in the post_holiday condition as the best model. The forecasting results in 2018 show the largest decline in non-oil and gas exports in June 2018 which coincided with the Eid Al-Fitr holiday. MAPE value of 10.90% is obtained which shows that the forecasting ability is good.Keywords: time series, non-oil and gas, X-13-ARIMA-SEATS, moving holiday
COPULA FRANK PADA VALUE at RISK (VaR) PEMBENTUKAN PORTOFOLIO BIVARIAT (Studi Kasus : Saham-Saham Perusahaan yang Meraih Predikat The IDX Top Ten Blue Tahun 2017 dengan Periode Saham 20 Oktober 2014 – 28 Februari 2018)
Authors: Handini Juria Ayu , Maruddani Di Asih I , Safitri Diah 
Published: September 2020

The capital market has an important role in society to invest in financial instruments. Investors can invest in the form of a portfolio that is by combining several shares to reduce the risk that will occur. Value at Risk (VaR) is a method for estimating the worst risk of an investment. GARCH (Generalized Autoregressive Conditional Heteroscedasticity) is used to model high-volatile stock data that causes residual variance is not constant. Copula theory is a powerful tool for modeling joint distributions because it does not require normality assumptions that are difficult to fulfill in financial data. Copula Frank has a feature that can identify positive and negative dependencies. This study aims to measure the value of VaR using the Frank-GARCH copula method using stock returns data of PT Bank Rakyat Indonesia, Tbk (BBRI), PT Telekomunikasi Indonesia, Tbk (TLKM), and PT. Unilever Indonesia, Tbk (UNVR) for the period 20 October 2014 - 28 February. Bivariate portfolio pairs obtained namely TLKM and UNVR shares because they have the highest Rho Spearman residual correlation value of ρ = 0.3204. Based on the generation of data using Monte Carlo simulations, the results of the calculation of Value at Risk (VaR) of 1.40% at the 90% confidence level, 1.89% at the 95% confidence level, and 2.79% at the 99% confidence level. Keywords: Value at Risk, Frank copula, GARCH, Monte Carlo
HISTORICAL SIMULATION UNTUK MENGHITUNG VALUE AT RISK PADA PORTOFOLIO OPTIMAL BERDASARKAN SINGLE INDEX MODEL MENGGUNAKAN GUI MATLAB (Studi Kasus: Kelompok Saham JII Periode Juni - November 2017)
Authors: Nuryanto Tresno Sayekti , Prahutama Alan , Hoyyi Abdul 
Published: September 2020

The essence of investment is a placement of a number of funds at one time in hope of gaining profits in the future. One of the most traded forms of investment is stocks. When investing in stocks, investors often run the risk of loss. This loss risk can be overcome by forming a portfolio consisting of several shares. To form an optimal portfolio, investors must first determine an efficient portfolio that produces a certain level of profit with the lowest risk, or a certain level of risk with the highest level of profit. One method for determining the optimal portfolio is to use the Single Index Model method. Whereas to calculate Value at Risk (VaR) using the Historical Simulation method. In this study, researcher used data from the daily closing price of shares incorporated in the Jakarta Islamic Index (JII) stock group in the period of June - November 2017. The shares which will be used were 9 shares in the JII stock group. According to the research result, there are three stocks that go into an optimal portfolio that is SMGR, UNTR, and KLBF with the value of each of its shares respectively by 48,54%, 46,18%, and 5,28%. While the value of the Value at Risk with initial capital of Rp100.000.000, 1 day holding period and a trust level of 95% for optimal portfolio and each stock that goes into optimal portfolio amounted Rp2.090.283, Rp2.258.600, Rp3.403.000, and Rp2.564.200. Keywords: Share, Portofolio, Single Index Model, Value at Risk, Historical Simulation, JII.
PENGUKURAN KINERJA PORTOFOLIO OPTIMAL CAPITAL ASSET PRICING MODEL (CAPM) DAN ARBITRAGE PRICING THEORY (APT) (Studi Kasus : Saham-saham LQ45)
Authors: Pasaribu Dedi Baleo , Maruddani Di Asih I , Sugito Sugito 
Published: September 2020

Investing is placing money or funds in the hope of obtaining additional or specific gains on the money or funds. The capital market is one place to invest in the financial field of interest to investor. This is because the capital market gives investor the freedom to choose securities traded in the capital market in accordance with the wishes of investor. Investor are included in risk averter, that means investor will always try to avoid risk. To avoid risk, investor try to diversify their investment. Diversification concept commonly used is portfolio. To maximize the return to be earned, the investor will invest his funds into several stocks in order to earn a greater profit. Capital Asset Pricing Model (CAPM) is a balance model that describes the relation of a risk with return more simply because it uses only one variable to describe the risk. Arbitrage Pricing Theory (APT) is a balance model that used many risk variables to see the relation of risk and return. With both models will be obtained a portfolio with each constituent stock is four stocks selected from 45 stocks in the LQ45 index. To find out which portfolio is the best performed a performance analysis using the Sharpe index. From the measurement result, it is found that the best portfolio is the CAPM portfolio with composite stock is PTBA with investment weight of 0.467%, BUMI with investment weight of 12.855%, ANTM with investment weight of 53.077% and PPRO with investment weight of 33.601%. Keywords: LQ45, portfolio, Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), Sharpe Index
ANALISIS VARIANSI PADA RANCANGAN BUJUR SANGKAR YOUDEN DENGAN DUA DATA HILANG
Authors: Dewi Amalina Sari , Widiharih Tatik , Rahmawati Rita 
Published: September 2020

Youden Square Design (YSD) is an incomplete latin square design with at least one row/column which can’t run in an experiment. In this research we took 5x4 YSD (one column is not runned in an experiment). This design has a balance characteristic from a balanced incomplete block design where all treatments appears with the same number in each row. Missing data can occur in YSD. In this discussion, YSD with two missing data was used. Missing data is estimated by an iterative method then we arrange analysis of variance and LSD test. Analysis of variance with two missing data in YSD is calculated by adjusting the treatment sum of squares with it’s bias value and the total degrees of freedom and error degrees of freedom are substracted by two. LSD test is carried out if the treatment has a significant effect to the response. To clarify the discussion in YSD, example of application in the field of industry is given by observing the effect of the assembly method to the length of assembly time of X component. The assembly method has an effect to the length of assembly time of X component and if the missing data are and so the suggested assembly method is E method because it has the fastest average assembly time. Keywords: YSD, Missing Data, Analysis of Variance, LSD Test
PEMODELAN REGRESI HURDLE POISSON DALAM MENGATASI EXCESS ZEROS UNTUK KASUS PENYAKIT TETANUS NEONATORUM PADA NEONATAL DI JAWA TIMUR
Authors: Margaretha Cylvia Evasari , Ispriyanti Dwi , Widiharih Tatik 
Published: September 2020

Tetanus Neonatorum is one of the infectious diseases that occur in newborns caused by Clostridium Tetani bacteria through cuts or scratches. The number of Tetanus Neonatorum cases in East Java Province in 2017 is discrete data Poisson distribution with a proportion of zero value of 73,7 percent. The amount of zero value data can result in overdispersion where the variance is greater than the mean. To overcome this problem, Hurdle Poisson regression model is a solution. To estimation of regression parameters for Hurdle Poisson regression is using the Maximum Likelihood Estimation (MLE) method and Broyden Fletcher Goldfarb Shanno (BFGS) iteration. Hurdle Poisson regression produces predictor variables that affect the number of Tetanus Neonatorum cases in East Java Province in the logit model are the percentage of pregnant women administered the K4 program, population density per and in the truncated Poisson model are the percentage of labor assisted by health workers the percentage of pregnant women administered the K4 program, population density per with the Akaike Information Criterion (AIC) value of 78,422.Keywords: Tetanus Neonatorum, Excess Zeros, Overdispersion, Hurdle Poisson Regression
KLASIFIKASI CALON DEBITUR KREDIT PEMILIKAN RUMAH (KPR) MULTIGUNA TAKE OVER MENGGUNAKAN METODE k NEAREST NEIGHBOR DENGAN PEMBOBOTAN GLOBAL GINI DIVERSITY INDEX
Authors: Hasimah Inas , Mukid Moch. Abdul , Yasin Hasbi 
Published: September 2020

House credit (KPR) is a credit facilities for buying or other comsumptive needs with house warranty. The warranty for KPR is the house that will be purchased. The warranty for KPR multiguna take over is the house that will be owned by debtor, and then debtor is taking over KPR to another financial institution. For fulfilled the credit to prospective debtor is done by passing through the process of credit application and credit analysis. With the credit analysis, will acknowledge the ability of debtor for repay a credit. Final decision of credit application is classified into approved and refused. k Nearest Neighbor by attributes weighting using Global Gini Diversity Index is a statistical method that can be used to classify the credit decision of prospective debtor. This research use 2443 data of KPR multiguna take over’s prospective debtor in 2018 with credit decision of prospective debtor as dependent variable and four selected independent variable such as home ownership status, job, loans amount, and income. The best classification result of k-NN by Global Gini Diversity Index weighting is when using 80% training data set and 20% testing data set with k=7 obtained APER value 0,0798 and accuracy 92,02%. Keywords: KPR Multiguna Take Over, Classification, KNN by Global Gini Diversity Index weighting, Evaluation of Classification
SEGMENTASI PELANGGAN E-MONEY DENGAN MENGGUNAKAN ALGORITMA DBSCAN (DENSITY BASED SPATIAL CLUSTERING APPLICATIONS WITH NOISE) DI PROVINSI DKI JAKARTA
Authors: Rohalidyawati Windy , Rahmawati Rita , Mustafid Mustafid 
Published: September 2020

Customer segmentation is one effective way of marketing to determine the most potential target market. Increasing of E-money usage in DKI Jakarta and more banks are providing E-money products. One way to be able to compete in the global market, banks can segment customers. Determining potential customers of E-money users in DKI Jakarta can form segments by applying the DBSCAN (Density Based Spatial Clustering Application with Noise) algorithm. The quality of segments was measured by using the Silhouette Coefficient. In this study, E-money customers were grouped by reason of using the bank used, transaction activities, number of transactions, nominal balance, and frequency of top-up. The results of this study were using the density radius of 2 and minimum 3 objects that enter the density radius forming 2 segments and 17 noises. The segment quality value of 0.26. The most potential segment was the segment that has an average greater than the average of all data.
Nested PCR methods for detection Toxoplasma gondii B1 gene in Cerebrospinal Fluid of HIV patients
Authors: Halleyantoro Ryan , Andriyani Yunilda , Sari Ika Puspa , Kurniawan Agnes 
Published: September 2020

Background: Toxoplasmosis is a disease caused by infection of Toxoplasma gondii, Which may cause a life-threatening condition in immunocompromised patients, for example, Toxoplasma encephalitis (TE). It is challenging to diagnose Toxoplasma as a cause of central nervous system (CNS) infection in HIV patient, so we need an alternative method, which is a PCR detection of Toxoplasma gondii B1 gene.Objective: This research aimed to find association between PCR methods for Toxoplasma gondii B1 gene and anti-Toxoplasma IgG from cerebral spinal fluid patient HIV AIDS.Methods: A cross-sectional study was conducted to Cerebrospinal fluid (CSF) samples of HIV patients with neurological symptoms to determine Toxoplasma gondii infection using nested PCR methods for the B1 gene and detection of anti-Toxoplasma IgG.Results: 88 CSF samples from HIV patients tested using nested PCR showed 23 samples (26,1%) were positive. Serologic test for IgG Toxoplasma showed 34 samples were positive (28,6%). There was a significant correlation (p=0.000(<0.05) between PCR result and a serologic test for IgG Toxoplasma.Conclusion: Nested PCR methods to detect B1 gene increased the accuracy of diagnosis for toxoplasma encephalitis.
KAJIAN HASIL TANGKAPAN DAN TINGKAT KESEJAHTERAAN NELAYAN DI DESA AROMAREA DISTRIK KOSIWO, KABUPATEN SARUI KEPULAWAN YAPEN, PAPUA
Authors: Yapanani Ethan , Solichin Anhar , Wibowo Bambang Argo 
Published: September 2020

Nelayan Tradisional adalah nelayan yang memanfaatkan sumber daya perikanan dengan peralatan tangkap tradisional, modal usaha yang kecil, dan teknologi penangkapan yang relatif sederhana. Akibat keterbatasan teknologi, ruang gerak nelayan tradisional sangat terbatas, mereka hanya mampu beroperasi di perairan pantai. Hal ini membuat Masyarakat Aromarea Distrik Kosiwo harus memiliki pemahaman yang baik agar masalah sosial yang dihadapi dapat diatasi secara efisien dan efektif. Tujuan penelitian ini untuk mengetahui tentang hasil tangkapan dan tingkat kesejahteraan nelayan tradisional dengan alat tangkap jaring insang (gillnet). Dan mengetahui kondisi sosial dan ekonomi Masyarakat Desa Aromarea Distrik Kosiwo Papua. Penelitian ini menggunakan metode field research, tujuannya adalah mendeskripsikan secara detail tentang latar belakang, sifat serta karakter yang khas dari subyek penelitian tersebut. Metode pengambilan sampel menggunakan metode purposive sampling. Pengambilan data dilakukan di Desa Aromarea Kepulauan Yapen Papua. Data tersebut disajikan dalam bentuk tabulasi kemudian di analisis secara deskriptif, yang menghasilkan investasi atau modal, biaya total, pendapatan, dan keuntungan sehingga diperoleh tingkat kesejahteraan nelayan tradisional di Desa Aromarea. Analisis keragaan ekonomi secara undiscounted criterion menunjukkan bahwa usaha perikanan jaring gillnet di Desa Aromarea menguntungkan, efisien dan layak beroperasi dengan nilai R/C ratio sebesar 1,7 serta rentabilitas sebesar 62% dan payback period (PP) sebesar 1,6. Dan tingkat kesejahteraan nelayan jaring gillnet dengan metode Nilai Tukar Nelayan (NTN) diperoleh hasil NTN pada bulan Juli sebesar 1,4. Hal ini memberikan informasi bahwa keluarga nelayan mampu memenuhi kebutuhan sekunder atau tersiernya dan mampu menyisihkan uang untuk ditabung sebesar Rp. 829.546,00. Jadi, secara umum kehidupan nelayan mempunyai tingkat kesejahteraan cukup baik.
TINGKAT KERUSAKAN DAN KARBON MANGROVE DENGAN PENDEKATAN DATA SATELIT NDVI (NORMALIZED DIFFERENCE VEGETATION INDEX) DI DESA SIDODADI KABUPATEN PESAWARAN PROVINSI LAMPUNG
Authors: Mayuftia Rimty , Hendrarto Boedi , Hartoko Agus 
Published: September 2020

Ekosistem mangrove sebagaimana ekosistem hutan lainnya memiliki peran sebagai penyerap dan penyimpan karbon guna pengurangan kadar CO2 di udara. Hutan mangrove merupakan komponen penyusun utama dalam ekosistem mangrove. Pesisir Lampung di Desa Sidodadi, Ringgung, Kabupaten Pesawaran, Provinsi Lampung terdapat ekosistem mangrove yang masih asli dan sebagian telah dikonversi menjadi tambak udang dan pemukiman sehingga sebagian telah rusak karena alasan tersebut. Kerusakan vegetasi mangrove dapat diketahui dengan cara menggunakan kriteria yang digunakan untuk mengindikasi adanya kerusakan tegakan mangrove dengan mengunakan data citra landsat yang mencerminkan besaran nilai NDVI (Normalized Difference Vegetation Index).Penelitian ini menggunakan metode penelitian survei yang bersifat deskriptif, penelitian diarahkan untuk mendeskripsikan atau menguraikan suatu keadaan. Pengambilan data menggunakan metode purposive sampling. Variabel data utama yang dibutuhkan yaitu : Citra Satelit Landsat TM 2012 untuk dianalisis nilai digital number dengan proses dengan ER Mapper, data jenis spesies mangrove, data diameter pohon mangrove untuk data pengolahan biomassa karbon mangrove, kerapatan pohon mangrove, dan koordinat untuk analisa hubungan antara biomassa mangrove, tegakan pohon, dengan NDVI.Hasil dari penelitian ini menunjukkan bahwa tingkat kerusakan ekosistem mangrove di Pesisir Lampung, Desa Sidodadi, Kabupaten Pesawaran, Provinsi Lampung berdasarkan kriteria nilai NDVI (Normalized Difference Vegetation Index) sebesar 0,25 dan 0,378, tergolong rusak berat dan rusak sedang. Namun berdasarkan baku mutu suatu ekosistem mangrove dengan menggunakan kerapatan pohon dengan interpretasi citra menggunakan Landsat TM dengan kerapatan pohon 880 - >1100 pohon, dikategorikan sangat rapat. Biomassa karbon mangrove terkandung pada vegetasi mangrove yang ada di Pesisir Lampung, Desa Sidodadi, Kabupaten Pesawaran, Provinsi Lampung yaitu 10.694.870,18 kg/ha. Analisa hubungan antara biomassa mangrove dengan nilai NDVI memiliki hubungan yang kuat, namun hubungan pohon mangrove dengan nilai NDVI memiliki nilai hubungan yang rendah.