Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

3.448

P-Index

This Author published in this journals

All Journal Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Media Statistika MATEMATIKA SAINS DAN MATEMATIKA Jurnal Ilmu Dasar Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Indonesian Journal of Applied Statistics Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan

Dwi Ispriyanti

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 3131513

Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Transportation Other

Published : 113 Documents Claim Missing Document

Claim Missing Document

Articles

Title

5 6 7 8 9

EXPECTED SHORTFALL PADA PORTOFOLIO OPTIMAL DENGAN METODE SINGLE INDEX MODEL (Studi Kasus pada Saham IDX30) Eis Kartika Dewi; Dwi Ispriyanti; Agus Rusgiyono
Jurnal Gaussian Vol 10, No 2 (2021): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v10i2.30947

Stock investment is a commitment to a number of funds in marketable securities which shows proof of ownership of a company with the aim of obtaining profits in the future. For obtaining optimal returns from stock investments, investors are expected to form optimal portfolios. The optimal portfolio formation using the Single Index Model is based on the observation that a stock fluctuates in the direction of the market price. It shows that most stocks tend to experience price increases if the market share price rises, and vice versa. Selection of optimal portfolio-forming stocks on IDX30 using the Single Index Model method produces 4 stocks, that are BRPT (Barito Pacific Tbk.) with weight 31.134%, ICBP (Indofood CBP Sukses Makmur Tbk.) 17.138%, BBCA (Bank Central Asia Tbk.) 51.331% and SMGR (Semen Indonesia (Persero) Tbk.) 0.397%. Every investment must have a risk, for that investors need to calculate the possible risks that occur before investing. To calculate risk, Expected Shortfall (ES) is used as a measure of risk that is better than Value at Risk (VaR) because ES fulfill the subadditivity. At the 95% confidence level, the ES value is 23.063% while the VaR value is 10.829%. This means that the biggest possible risk that an optimal portfolio investor will receive using the Single Index Model for the next five weeks is 23.063%.Keywords : Portfolio, Single Index Model, Expected Shortfall, Value at Risk.

PERAMALAN HARGA MINYAK MENTAH DUNIA MENGGUNAKAN METODE RADIAL BASIS FUNCTION NEURAL NETWORK Rahafattri Ariya Fauzannissa; Hasbi Yasin; Dwi Ispriyanti
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Oil is the most important commodity in everyday life, because oil is one of the main source of energy that is needed for the people. Changes in crude oil prices greatly affect the economic conditions of a country. To forecast crude oil prices, the past data of the crude oil that is the time series data will be studied so that will produce crude oil price forecast in the future. Model of Radial Basis Function Neural Network is suitable for large-scale data processing, because this model does not require the use of all data input and has a total processing time of rapid system. This model has a network architecture in the form of input layer, hidden layer and output layer. Analysis conducted on the data as much as 1286 taken as 100 the data thus obtained value of 0.9145 MSE training and training MAPE value of 0.74%, while for the testing of 4.2739 MSE and MAPE testing value is 1.63%. Based on the results of forecasting, crude oil prices on July 29, 2015 until August 2, 2015 at USD $ 55.91 per barrel. Keywords: Radial Basis Function Neural Network (RBFNN), Time Series, Crude Oil, MSE, MAPE, Forcasting

PEMODELAN PENGELUARAN PER KAPITA DAN PERSENTASE PENDUDUK MISKIN DI JAWA TENGAH MENGGUNAKAN REGRESI BIRESPON SPLINE TRUNCATED Merinda Pangestikasari; Rita Rahmawati; Dwi Ispriyanti
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The Central Bureau of Statistics states that the average per capita spending (Y1) of Central Java Community in 2016 is around 27.808 rupiah per day. This value is still considered low, because it covers all the needs of an individual's life. The low expenditure per capita indicates the low level of welfare. Another indicator that can be used to measure community welfare is the percentage of poverty (Y2). Through this variable can be known how proportion of people who still difficult to meet their needs. Many factors are suspected to affect welfare, one of which is the average variable of school length (X). This study aims to get the best model and know the goodness of the model. Approach is done by nonparametric regression that is regres biresponse spline truncated. Nonparametric approach is done when data function does not show certain pattern. The best spline truncated biresponse model is highly dependent on determining the order and location of the optimal knot point that has a minimum Mean Square Error (MSE) value. In this study, the best model is obtained when order of Y1 is 2 and order of Y2 is 2 with five knots. The location of the knot point obtained is 7,05; 7,17; 7,32; 9,82 and 10,29 with MSE value of 662634,2. The goodness of the model is measured based on R-Square and MAPE, R-Square=43,21%, means the variance of response variables that can be explained by the predictor variable are 43,21% while the rest is influenced by other variables and MAPE=14,25%. Based on the value of MAPE can be said that the model had a good performance. Keywords: Welfare, Expenditure, Percentage of Povery, Birespon Spline, Truncated, MSE

ESTIMASI VALUE AT RISK PORTOFOLIO SAHAM MENGGUNAKAN METODE GARCH-COPULA (Studi Kasus : Harga Penutupan Saham Harian Unilever Indonesia dan Kimia Farma Periode 1 Januari 2013- 31 Desember 2016) Lingga Bayu Prasetya; Dwi Ispriyanti; Alan Prahutama
Jurnal Gaussian Vol 7, No 4 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v7i4.28867

Any investment in the stock market will earn returns accompanied by risks. Return and risk has a mutual correlation that equilibrium. The formation of a portfolio is intended to provide a lower risk or with the same risk but provide a higher return. Value at Risk (VaR) is a instrument to analyze risk management. Time series model used in stock return data that it has not normal distribution and heteroscedastisicity is Generalized Autoregressive Conditional Heteroscedasticity (GARCH). GARCH-Copula is a combined method of GARCH and Copula. The Copula method is used in joint distribution modeling because it does not require the assumption of normality of the data and can capture tail dependence between each variable. This research uses return data from stock closing prices of Unilever Indonesia and Kimia Farma period January 1, 2013 until December 31, 2016. Copula model is selected based on the highest likelihood log value is Copula Clayton. Value at Risk estimates of Unilever Indonesia and Kimia Farma's stock portfolio on the same weight were performed using Monte Carlo simulation with backtesting of 30 days period data at 95% confidence level. Keywords : Stock, Risk, Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Copula, Value at Risk

PEMODELAN FUNGSI TRANSFER DENGAN DETEKSI OUTLIER UNTUK MEMPREDIKSI NILAI INFLASI BERDASARKAN BI RATE (Studi Kasus BI Rate dan Inflasi Periode Januari 2006 sampai Juli 2016) Firda Dinny Islami; Abdul Hoyyi; Dwi Ispriyanti
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation control is one of the important things in managing a country besides economic growth. Inflation received special attention in the economy of Indonesia. Every time there is a distortion in the society, politic or economic development, people always relate it to inflation. Low and stable inflation is a stimulator of economic growth. Inflation is also the final target in the monetary policy framework so the need for a central bank role to determine the policy direction. The BI Rate is one of the variables capable of controlling inflation. This study aims to forecast inflation based on the BI Rate using the transfer function model with outlier detection. The transfer function model depends on the parameters b, r, and s. The result of the analysis has been obtained the transfer function model with the value of b = 1, r = 0, s = 1 and the noise series ARMA (2,0). The addition of 16 outliers on the model yielded the best model with the AIC value is -868,56. The forecasting results show that the value of inflation has fluctuated, where in September 2016 it has decreased and then increased until December 2016.Keywords : Inflation, BI Rate, transfer function, outlier detection, AIC

IMPLEMENTASI ALGORITMA FUZZY C-MEANS DAN FUZZY POSSIBILISTICS C-MEANS UNTUK KLASTERISASI DATA TWEETS PADA AKUN TWITTER TOKOPEDIA Ghina Nabila Saputro Putri; Dwi Ispriyanti; Tatik Widiharih
Jurnal Gaussian Vol 11, No 1 (2022): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v11i1.33996

Social media has become the most popular media, which can be accessed by young to old age. Twitter became one of the effective media and the familiar one used by the public, thus making the company make Twitter one of the promotional tools, one of which is Tokopedia. The research aims to group tweets uploaded by @tokopedia Twitter accounts based on the type of tweets content that gets a lot of retweets and likes by followers of @tokopedia. Application of text mining to cluster tweets on the @tokopedia Twitter account using Fuzzy C-Means and Fuzzy Possibilistic C-Means algorithms that viewed the accuracy comparison of both methods used the Modified Partition Coefficient (MPC) cluster validity. The clustering process was carried out five times by the number of clusters ranging from 3 to 7 clusters. The results of the study showed the Fuzzy C-Means method is a better method compared to the Fuzzy Possibilistic C-Means method in clustering data tweets, with the number of clusters formed is 4. The content type formed is related to promo, discount, cashback, prize quizzes, and event promotions organized by Tokopedia. Content with the highest average number of retweets and likes is about automotive deals, sports tools, and merchandise offerings. So, that PT Tokopedia can use this content type as a tool for advertising on Twitter because it gets more likes by followers of @tokopedia.Keywords: Data Tweets, Clustering, Fuzzy C-Means, Fuzzy Possibilistics C-Means, Modified Partition Coefficient.

PERBANDINGAN ARIMA DENGAN FUZZY AUTOREGRESSIVE (FAR) DALAM PERAMALAN INTERVAL HARGA PENUTUPAN SAHAM (Studi Kasus pada Jakarta Composite Index) Muhammad Fitri Lutfi Anshari; Dwi Ispriyanti; Yuciana Wilandari
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The capital market is one of the most popular investment option today. In capital market, stock price prediction is an important issue for investors, so needed a good forecasting method as a basic for decision-making for the transaction. One of the most popular forecasting method is ARIMA, but this method still uses the concept that measurement error which is obtained from the difference between the observed values with estimated values. To resolve the error in modeling, Fuzzy Autoregressive was developed, it is a model combination of Fuzzy Regression and Autoregressive (AR). This method gives results in interval forecasting, thus providing information to decision makers regarding the best and worst situation that may occur. This paper discusses the application of Fuzzy Autoregressive forecasting interval for the Jakarta Composite Index and compare it with the ARIMA prediction interval. The result of this study is Fuzzy Autoregressive interval is narrower than the ARIMA 95% significance rate

PERAMALAN DINAMIS PRODUKSI PADI DI JAWA TENGAH MENGGUNAKAN METODE KOYCK DAN ALMON Firdha Rahmatika Pratami; Sudarno Sudarno; Dwi Ispriyanti
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Paddy is one of the staple crops that have strategic value and has a great influence in economic, environmental, social and political. Almost of Indonesia's population consumes rice every day. Because of that, need models to determine or predict the amount of paddy production in Central Java for the future. Because the data used is the historical data, there will be a regression analysis that takes into account the time. If the regression model include not only the value of the independent variable X at this time, but also the value of the past (lagged), this model called a distributed-lag model. The methods used in determining the equation of distributed-lag are Koyck and Almon method. Koyck method used to determine the estimated dynamic model of distributed-lag time difference (lag) is unknown. Almon method used to determine the estimated dynamic model of distributed-lag time difference (lag) is known. Selection of the best model is using Mean Absolut Percentage Error criteria. According the result of the analysis, using Almon model has better result than Koyck Model.Keyword: Paddy, Distributed-lag model, Koyck, Almon

PEMODELAN HARGA SAHAM DENGAN GEOMETRIC BROWNIAN MOTION DAN VALUE AT RISK PT CIPUTRA DEVELOPMENT Tbk Trimono Trimono; Di Asih I Maruddani; Dwi Ispriyanti
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Financial sector investment is an activity that attracts a lot of public interest. One of them is investing funds in purchasing company’s shares. Profit received from stock investment activity can be seen from the value of stock returns. While, if the previous stock returns Normal distribution, the future stock price can be predicted by Geometric Brownian Motion Method. Based on the stock price prediction, can also be measured an estimated value of the investment risk. The result of data processing shows that the stock price prediction of PT. Ciputra Development Tbk period December 1, 2016 untuk January 31, 2017, has very good accuracy, based on the value of MAPE 1.98191%. Further, Value at Risk Method of Monte Carlo Simulation with α = 5% significance level was used to measure the share investment risk of PT.Ciputra Development Tbk. Thus, this method is only useful if it can be used to predict accurately. Therefore, backtesting is needed. Based on the processing obtained data, backtesting generates the value of violation ratio at 0, it means that at significance level α = 5%, Value at Risk Method of Monte Carlo Simulation can be used at all levels of probability violation.. Keywords : Geometric Brownian Motion, Risk, Value at Risk, Backtesting

PERBANDINGAN MODEL REGRESI BINOMIAL NEGATIF DENGAN MODEL GEOGRAPHICALLY WEIGHTED POISSON REGRESSION (GWPR) (Studi kasus : Angka Kematian Ibu di Provinsi Jawa Timur Tahun 2011) M. Ali Ma'sum; Suparti Suparti; Dwi Ispriyanti
Jurnal Gaussian Vol 2, No 3 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Maternal mortality rate is one of the crucial problems of death in Indonesia. Maternal deaths in East Java province is likely to increase so that the role of data and information are very important. Negative Binomial Regression is a model that can be used to address the problem overdispersion. While the method of spatial attention factor for type discrete data is Geographically Weighted Poisson Regression Model (GWPR). This study was conducted on the comparison between the Negative Binomial Regression and GWPR to discuss the factors that influence maternal mortality rate in the province of East Java. Indicators that affect maternal mortality include maternal health services. Maternal health services such as antenatal care, obstetric complications treated, Aid deliveries by skilled health care child birth, and neonatal health care services handled neonatal complications. The results of testing the suitability of model shows that there is no influence of spatial factors on maternal mortality rate in the province of East Java. Based on Negative Binomial Regression derived variable number of puerperal women who received vitamin A significantly affect maternal mortality rate, while for GWPR is divided into six clusters districts/cities by same significant variables. From the comparison value of AIC was found that GWPR better to analyzing Maternal mortality in East Java because it has the smallest value of AIC

Co-Authors A Rusgiyono Abdul Hoyyi Agus Rusgiyono Agustinus Salomo Parsaulian Ain Hafidita Ajeng Dwi Rizkia Alan Prahutama Alan Prahutama Alvi Waldira Ana Kartikawati Anisa Septi Rahmawati Anjan Setyo Wahyudi Annisa Ayu Wulandari Arief Rachman Hakim Arkadina Prismatika Noviandini Taryono Arya Despa Ihsanuddin Arya Huda Arrasyid Atika Elsadining Tyas Aulia Ikhsan Avia Enggar Tyasti Azizah Mulia Mawarni Berta Elvionita Fitriani Bitoria Rosa Niashinta Budi Warsito Budi Warsito Cylvia Evasari Margaretha Dedi Nugraha Di Asih I Maruddani Di Asih I Maruddani Diah Safitri Diah Safitri Diah Wulandari Dita Ruliana Dwi Rahmayani, Dwi Dyan Anggun Krismala Dydaestury Jalarno Eis Kartika Dewi Endah Fauziyah Erna Sulistianingsih Erna Sulistio Evi Yulia Handaningrum Fadhilla Atansa Tamardina Firda Dinny Islami Firdha Rahmatika Pratami Fithroh Oktavi Awalullaili Gandhes Linggar Winanti Gera Rozalia Ghina Nabila Saputro Putri Hanifah Nur Aini Hasbi Yasin Hasbi Yasin Henny Widayanti, Henny Ilham Maggri Imam Desla Siena Innosensia Adella Irawati Tamara Iut Tri Utami Jesica, Haniela Puja Kishatini Kishartini Lifana Nugraeni Lingga Bayu Prasetya M. Ali Ma'sum Marlia Aide Revani Masfuhurrizqi Iman Maulida Azkiya, Maulida Maulida Najwa, Maulida Merinda Pangestikasari Moch. Abdul Mukid Moch. Abdul Mukid Muhammad Fitri Lutfi Anshari Muhammad Rosyid Abdurrahman Muhammad Zidan Eka Atmaja Mustafid Mustafid Mustafid Mustafid Nanci Rajagukguk, Nanci Nandang Fahmi Jalaludin Malik Nida Adelia Nidaul Khoir Nova Nova Noviana Nurhayati Nurwihda Safrida Umami Oka Afranda Pandu Anggara Pritha Sekar Wijayanti Puput Ramadhani Pusphita Anna Octaviani Puspita Kartikasari Putri Fajar Utami Rafida Zahro Hasibuan Rahafattri Ariya Fauzannissa Rahmah Merdekawaty Rahmaniar, Ratna Rany Wahyuningtias Ratih Nurmalasari, Ratih Ratna Pratiwi Ria Sutitis Rio Tongaril Simarmata Riszki Bella Primasari Rita Rahmawati Rita Rahmawati Riza Adi Priantoro Riza Fahlevi Sa'adah, Alfi Faridatus Sania Anisa Farah Setiani Setiani Sherly Candraningtyas Sindy Saputri Sisca Agustin Diani Budiman Sri Maya Sari Damanik Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suhendra, Muhammad Arif Suparti Suparti Suparti Suparti Suparti, S. Suryaningrum, Fahlevi Syilfi Syilfi Sylvi Natalia P P Tarno Tarno Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Tatik Widiharih Tiani Wahyu Utami Triastuti Wuryandari Triastuti Wuryandari Trimono Trimono Ulya Tsaniya Umiyatun Muthohiroh Warsito Budi Yani Puspita Kristiani Yashmine Noor Islami Yuciana Wilandari Yuciana Wilandari

Title Search

Found 85 Documents Search Journal : Jurnal Gaussian

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 85 Documents
Search
Journal : Jurnal Gaussian