Article Per Year (5 Year)
p-Index From 2020 - 2025
1.452
P-Index
This Author published in this journals
All Journal EKONOMIS : Journal of Economics and Business J-MAS (Jurnal Manajemen dan Sains) JURNAL LENTERA BISNIS Jurnal Disrupsi Bisnis
Rahman Amrullah Suwaidi
Universitas Pembangunan Nasional "Veteran" Jawa Timur
Economics, Econometrics & Finance Social Sciences

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : JURNAL LENTERA BISNIS

 1 
ANALISIS NILAI PERUSAHAAN PADA PERUSAHAAN SEKTOR PROPERTIES DAN REAL ESTATE DI BEI Anessya Anggia Savitri; Rahman Amrullah Suwaidi
JURNAL LENTERA BISNIS Vol. 13 No. 3 (2024): JURNAL LENTERA BISNIS, SEPTEMBER 2024
Publisher : POLITEKNIK LP3I JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34127/jrlab.v13i3.1201

Abstract

Industrial development during the transformation period as a policy of every business entity whose existence is urgent for the welfare of all audiences and economic growth, with the principle of building an independent and ever-growing economy. The observation is intended to analyze the impact of profitability, liquidity, solvency, and activity ratio variables on company value in the property and real estate sector listed on the IDX for the period 2020-2022. The observation has a population of 85 companies in the property and real estate sector listed on the IDX. The purposive sampling technique was used to take samples in the observation. The sample obtained from this technique was 64 companies. The analysis method for programming observation data is multiple linear regression processed with SPSS. The research indicates that starting from liquidity, solvency, and activity ratio there is a match with the company's value, while profitability is the opposite.
ANALISIS DETERMINAN HARGA SAHAM BASIC MATERIALS TAHUN 2018-2022 Delia Septy Dwi Sucahyo; Rahman Amrullah Suwaidi
JURNAL LENTERA BISNIS Vol. 13 No. 3 (2024): JURNAL LENTERA BISNIS, SEPTEMBER 2024
Publisher : POLITEKNIK LP3I JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34127/jrlab.v13i3.1203

Abstract

The research intends to evaluate the impact of leverage ratios, market ratios, and dividend policies on stock prices. All basic materials companies on the Indonesian Stock Exchange until 2022 constitute the research population, then using a purposive sampling method the sample can finally be determined, namely 15 basic materials companies on the Indonesian Stock Exchange during the period 2018 to 2022. Data was collected through documentation techniques referring to annual financial data and historical stock price data and analyzed using multiple regression techniques using SPSS data processing tools. The results of the analysis show that the leverage ratio has no effect on stock prices, while the market ratio and dividend policy have a significant effect on stock prices.
ANALISIS KOMPARATIF MODEL PREDIKSI FINANCIAL DISTRESS PADA PERUSAHAAN SUB-SEKTOR TEKSTIL DAN GARMEN YANG TERDAFTAR DI BURSA EFEK INDONESIA M Indra Fauzi; Rahman Amrullah Suwaidi
JURNAL LENTERA BISNIS Vol. 14 No. 2 (2025): JURNAL LENTERA BISNIS, MEI 2025
Publisher : POLITEKNIK LP3I JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34127/jrlab.v14i2.1540

Abstract

Financial distress is a condition in which a company experiences a decline in financial performance, marked by decreasing profits and even potential losses. This study aims to identify the most accurate model in predicting financial distress in the textile and garment sub-sector in Indonesia. This study uses secondary data, collected from the companies’ financial statements published on the Indonesia Stock Exchange website and the respective company websites. The population in this study includes textile and garment sub-sector companies listed on the Indonesia Stock Exchange for the period 2019–2023, totaling 23 issuers. The sample was selected using purposive sampling, resulting in 20 companies being used as the research sample. This study compares the scores of four financial distress prediction models using statistical techniques, and evaluates the models’ accuracy by considering both the level of accuracy and error rate. The results show that the Springate model is the most accurate prediction model, with an accuracy rate of 95% and an error rate of 5%. Therefore, companies—especially those in the textile and garment sub-sector listed on the Indonesia Stock Exchange—can use the Springate model to predict financial distress. The researcher suggests that future studies consider using other models such as Ohlson, Taffler, or Internal Growth to enrich perspectives.
Co-Authors Alivka Maulida Anniza Anessya Anggia Savitri Delia Septy Dwi Sucahyo Dinda Krisna Sri Puji Astutik M Indra Fauzi Muhammad Riza Saifullah Trixie Ridasiena Ariosafira