Article Per Year (5 Year)
p-Index From 2021 - 2026
1.633
P-Index
This Author published in this journals
All Journal Media Statistika Jurnal Ilmu Dasar Jurnal Gaussian Jurnal Kajian Akuntansi Indonesian Journal of Applied Statistics Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Di Asih I Maruddani
Jurusan Statistika FSM UNDIP
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science Mathematics Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
PEMBENTUKAN PORTOFOLIO OPTIMAL DENGAN METODE MEDIAN VARIANCE PADA SAHAM JAKARTA ISLAMIC INDEX (JII) SEKTOR CONSUMER GOODS Faadillah, Muhamad Nabil; Maruddani, Di Asih I; Hakim, Arief Rachman
Jurnal Gaussian Vol 12, No 4 (2023): 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.12.4.487-498

Abstract

Investment is an activity to place owned assets or funds in a product hoping that there will be profits in the future. This case study was conducted by calculating the optimal portfolio using the median variance and calculating Value at Risk (VaR) using the historical simulation method. Median Variance in portfolio optimization is more suitable to be used as an investment guide because the method is not fixated on the normality distribution of the data. The data used is the Jakarta Islamic Index (JII) daily stock price data for 1 year period, which start from April 23th 2021 until April 23th 2022. The stock price used in this research is the closing price data each day during the period. The return data is used to find the weight using Median Variance method so that an optimal portfolio is formed. it is known that the Value at Risk with a confidence level of 95% and the next 1-day time period is -0,024088232 or -2,41% by investing 1% of the funds into UNVR.JK shares., by 58 % to shares of ICBP.JK, by 57% to shares of INDF.JK, by 1% to shares of JPFA.JK, and the last -17% to KLBF.JK shares is 2.41%. 
Perbandingan Kriteria Kataoka Safety First dan Mean Varians dalam Pembentukan Portofolio Saham Optimal Siswanah, Emy; Abdurakhman, Abdurakhman; Maruddani, Di Asih I
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 2 August 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i2.32846

Abstract

The Markowitz Mean-Variance Portfolio and the Kataoka Safety-First criterion share similarities, as both serve as risk-control methods and suitable for risk-averse investors. This study compares these two approaches in constructing an optimal portfolio and evaluates their respective performances. The findings indicate that the portfolio weights derived from both methods are positive. Empirical evidence suggests that the expected return of the Kataoka Safety-First portfolio is consistently higher than that of the Mean-Variance method. However, this greater return is accompanied by a higher level of risk. Furthermore, the Sharpe and Treynor indices for the Kataoka Safety-First portfolio surpass those of the Mean-Variance method across both portfolio variations analyzed. These results confirm that the Kataoka Safety-First portfolio demonstrates superior performance compared to the Mean-Variance approach. Therefore, the Kataoka Safety-First criterion presents itself as a viable strategy for constructing an optimal portfolio tailored to risk-averse investors.
Integrasi Data Envelopment Analysis dan Analisis Rasio Keuangan untuk Penilaian Efisiensi Perusahaan IDXBUMN20 Astuti, Tutut Dewi; Maruddani, Di Asih I
Jurnal Kajian Akuntansi Vol 8 No 2 (2024): DECEMBER 2024: Article in Progress
Publisher : Universitas Swadaya Gunung Jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jka.v8i2.11037

Abstract

Corporate efficiency is a critical indicator for assessing the performance of state-owned enterprises (SOEs) listed on the Indonesia Stock Exchange (IDX). In the era of global competition, SOEs are required to optimize resources to achieve sustainable financial performance. One of the widely applied approaches for measuring relative efficiency among firms is Data Envelopment Analysis (DEA), which can be integrated with financial ratio analysis to provide a comprehensive assessment. This study aims to evaluate the efficiency of IDX BUMN20 companies by integrating DEA and financial ratio analysis. The input variables consist of Debt to Equity Ratio (DER), Price Earning Ratio (PER), and stock return volatility, while the output variables include Return on Assets (ROA), Return on Equity (ROE), Price to Book Value (PBV), Dividend Yield (DY), and Earnings per Share (EPS). The DEA CCR model was employed to estimate the efficiency scores of each company. The findings indicate that several firms such as PTBA, BMRI, BJBR, AGRO, and TLKM achieved an efficiency score of 1.00, suggesting full efficiency. In contrast, companies such as SMGR and BBNI recorded scores below 0.40, indicating significant inefficiency. This study concludes that DEA combined with financial ratio analysis serves as an effective tool for performance evaluation and provides managerial insights for improving efficiency in underperforming companies.
Seleksi Saham Papan Utama Berbasis Rasio Keuangan dan Expected Shortfall Menggunakan Promethee Serta Evaluasi Sharpe Ratio Maruddani, Di Asih I; Rahmawati, Rita
Jurnal Kajian Akuntansi Vol 9 No 1 (2025): JUNI 2025
Publisher : Universitas Swadaya Gunung Jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jka.v9i1.11881

Abstract

The development of the Indonesian capital market requires stock selection methods that can comprehensively integrate financial statement information and market risk. Conventional approaches that rely on a single indicator are considered insufficient to capture the complexity of stock performance and risk. This study aims to select stocks in the Indonesian Main Board Index using the PROMETHEE method based on financial ratios and Expected Shortfall, and to evaluate risk–return efficiency using the Sharpe Ratio. This research adopts a quantitative approach using financial statement data for 2024 and daily stock price data from January 1 to December 31, 2025. The variables include liquidity, profitability, solvency, bankruptcy risk, stock return, and 95% Expected Shortfall. The results show that PROMETHEE is able to generate systematic stock rankings based on multi-criteria dominance, where stocks with the highest net flow exhibit better fundamental performance and lower extreme risk. However, further analysis reveals that stocks with the highest PROMETHEE rankings do not necessarily have the highest Sharpe Ratios, indicating differences in evaluation dimensions between the two methods. This study concludes that a two-stage approach PROMETHEE as an initial screening tool and the Sharpe Ratio as a subsequent evaluation provides more comprehensive insights for investment decision-making.
Pemodelan Data Time Series Menggunakan Pendekatan Regresi Polinomial Lokal Pada Data Harga Saham MDKA Fauzi, Febrian Adri Nur; Santoso, Rukun; Maruddani, Di Asih I
Indonesian Journal of Applied Statistics Vol 6, No 2 (2023)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v6i2.80118

Abstract

Investment is an important way to manage finances for profit. One of the most popular investments in Indonesia is buying and selling shares. In addition to getting profits, they also have risks.  Therefore, analyzing stock prices before buying and selling is an important key in stock investing. Investors should buy stocks at a low price and sell them at a high price. One of the methods used is parametric regression analysis, but it has assumptions that must be met. A more flexible alternative is local polynomial regression without any particular assumptions. PT Merdeka Copper Gold Tbk with MDKA stock code is a company engaged in the mining and industrialization of gold, silver, and other associated minerals. The study of modeling the lowest daily price of MDKA shares using local polynomial regression showed excellent results. The high coefficient of determination exceeding 67% on the in-sample data indicates strong model performance, and the Mean Absolute Percentage Error (MAPE) value on the out-of-sample data is less than 10%, ensuring excellent model accuracy.Keywords: local polynomial regression; MDKA shares; time series
Co-Authors Abdul Hoyyi Abdurakhman Abdurakhman Ari Purbowati Arief Rachman Hakim Danang Chandra Pradana, Danang Chandra Emy Siswanah Faadillah, Muhamad Nabil Fauzi, Febrian Adri Nur Hasbi Yasin Mas'ad, Mas'ad Rita Rahmawati Rokhma Al Anisah Rukun Santoso Samosir, Jessika Aurora Sinambela, Nadiyah Hafidah Sudarno Sudarno Sugito - Tarno Tarno Trimono, Trimono Tutut Dewi Astuti Utami, Rianti Siswi Yuciana Wilandari Yulia Agnis Sutarno