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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Telematika : Jurnal Informatika dan Teknologi Informasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Jiko (Jurnal Informatika dan komputer) Jurnal Teknologi Terpadu bit-Tech Nusantara Science and Technology Proceedings International Journal of Data Science, Engineering, and Analytics (IJDASEA)
Muhaimin, Amri
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Transportation

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Social Media Analysis and Topic Modeling: Case Study of Stunting in Indonesia Muhaimin, Amri; Fahrudin, Tresna Maulana; Alamiyah, Syifa Syarifah; Arviani, Heidy; Kusuma, Ade; Sari, Allan Ruhui Fatmah; Lisanthoni, Angela
Telematika Vol 20 No 3 (2023): Edisi Oktober 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i3.10797

Abstract

Purpose: Stunting is a problem that currently requires special attention in Indonesia. The stunting rate in 2022 will drop to 21.6%, and for the future, the government has set a target of up to 14% in 2024. Rapid technological developments and freedom of expression on the internet produce review text data that can be analyzed for evaluation. This study analyzes the text data of Twitter users' reviews on stunting. The method used is a text-mining approach and topic modeling based on Latent Dirichlet Allocation.Design/methodology/approach: The methodology used in this study is Latent Dirichlet Allocation. The data was collected from twitter with the keyword 'stunting'. After, the data was cleaned and then modeled using the Latent Dirichlet Allocation.Findings/results: The results show that negative sentiment dominates by 60.6%, positive sentiment by 31.5%, and neutral by 7.9%. In addition, this research shows that 'children', 'decrease', 'number', 'prevention', and 'nutrition' are among the words that often appear on stunting.Originality/value/state of the art: This study uses the keyword stunting and analyzes it. Social media analytics show that the people of Indonesia are primarily aware of stunting. Also, the Latent Dirichlet Analysis can be used to create the model.
Analysis of the LQ45 Stock Portfolio Using Mean–Variance Method and Cornish–Fisher Expansion Putri, Shafira Amanda; Trimono, Trimono; Muhaimin, Amri
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3640

Abstract

Public interest in stock market investment in Indonesia has increased alongside growing awareness of financial planning and portfolio management. The LQ45 Index, consisting of stocks with high liquidity, large market capitalization, and strong fundamentals, is widely used as a benchmark for portfolio analysis. However, many portfolio studies still rely on conventional Value at Risk (VaR), which assumes normally distributed returns and may underestimate extreme losses, making it less effective in capturing tail risk. This study addresses this research gap by integrating Mean–Variance Optimization (MVO) with the Cornish–Fisher VaR approach, which incorporates skewness and kurtosis to accommodate non-normal return distributions. Daily adjusted closing price data of LQ45 stocks from January to December 2025 were obtained from Yahoo Finance, and logarithmic returns were calculated. Based on the highest Sharpe Ratios, BRPT, EXCL, and ANTM were selected as portfolio constituents. Correlation analysis shows low dependency among the selected stocks, supporting diversification, while normality tests confirm deviations from normality, justifying the use of Cornish–Fisher VaR. The optimal portfolio allocates 10.6% to BRPT, 65.5% to EXCL, and 23.9% to ANTM, producing an expected return of 65.7%, portfolio risk of 26.2%, and a Sharpe Ratio of 2.5, indicating strong risk-adjusted performance. Cornish–Fisher VaR estimates potential losses of 2.23%, 3.09%, and 5.30% at the 90%, 95%, and 99% confidence levels. These results demonstrate that combining MVO and Cornish–Fisher VaR offers a more robust framework for portfolio optimization in the Indonesian stock market.
Co-Authors Damaliana, Aviolla Terza Dwi Arman Prasetya Endah Setyowati Fahrudin, Tresna Maulana Hanif Assalmi, Fityan Heidy Arviani Kusuma, Ade Lisanthoni, Angela Maulida H, Kartika Prabowo, Hendri Putri, Shafira Amanda Rahmawati, Adinda Aulia Regita Putri Permata Sari, Allan Ruhui Fatma Sari, Allan Ruhui Fatmah Selayanti, Nabilah Sri Hidayati Suhartono Syaifullah Jauharis Saputra, Wahyu Syifa Syarifah Alamiyah Taufik, Ikbar Athallah Trimono Trimono, Trimono