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International Journal of Business, Economics and
Social Development
Vol. 6, No. 1, pp. 68-72, 2025
e-ISSN 2722-1156
p-ISSN 27722-1164
Analysis of Financial Distress in Telecommunication Companies in
Indonesia Using the Ohlson O-Score and Zmijewski Methods
Ayyinah Nur Bayyinah1*
1Universitas Padjajaran, Sumedang, Indonesia
Corresponding author email: ayyinah21001@mail.unpad.ac.id
Abstract
Currently, major telecommunication sub-sector companies in Indonesia are experiencing rapid growth and have become dominant
players in the market. However, not all telecommunication companies are profitable, as some dominant subsidiaries have
experienced declining profits or losses, potentially leading to financial distress. Financial distress is a condition where a company
is unable to meet its current obligations, such as trade payables, tax liabilities, and short-term debts. This study aims to analyze
and evaluate the accuracy of the Ohlson O-Score and Zmijewski methods in detecting financial distress in telecommunication
companies in Indonesia. The data used in this study are historical financial data from several telecommunication companies listed
on the Indonesia Stock Exchange. The results show that the Ohlson O-Score is effective in early detection of potential financial
distress, while the Zmijewski method is more effective in evaluating companies already in critical financial conditions.
Keywords: financial distress, bankruptcy prediction, Zmijewski, Ohlson O-Score, telecommunication.
1. Introduction.
The telecommunication sub-sector in Indonesia has seen significant growth, with several companies dominating the
market. However, not all telecommunication companies are profitable, as some dominant subsidiaries have
experienced declining profits or losses. Intense competition in price wars, where operators offer data tariffs below
production costs, has led to an unhealthy industry, particularly in the mobile sector. The drastic increase in traffic is
not proportional to revenue, and this loss-making practice threatens the financial condition of operators, potentially
leading to financial distress (Winaya et al., 2020).
According Manalu et al. (2017) financial distress occurs when a company is unable to meet its current obligations,
such as trade payables, tax liabilities, and short-term debts. If not addressed properly, this condition can lead to
bankruptcy, reducing the company's value and investor confidence. Therefore, it is crucial for companies to detect
potential financial distress early. Various financial models and indicators, such as the Ohlson O-Score and Zmijewski
models, can be used to analyze and predict bankruptcy risk.
The Ohlson O-Score method, developed by James Ohlson in 1980, uses logistic regression to predict bankruptcy. It
incorporates various independent variables from financial statements, such as liquidity, profitability, and solvency
ratios, which are believed to influence the probability of bankruptcy. Similarly, the Zmijewski Model, developed by
Edward Zmijewski in 1984, uses variables like profitability, liquidity, and capital structure to identify bankruptcy risk.
The Zmijewski Model is known for its simplicity and ability to provide a clear picture of a company's financial health.
Hudaya et al. (2024) used the Zmijewski X-Score and Ohlson O-Score models to analyze bankruptcy potential in
companies with special notations on the Indonesia Stock Exchange (IDX). The results showed that the Zmijewski
model detected 60 out of 154 companies at risk of bankruptcy, while the Ohlson model identified 34 companies with
similar potential. The study also revealed that companies with certain notations, such as E, B, Y, D, and S, had a
higher risk of bankruptcy, serving as a warning for investors.
Winaya et al. (2020), expanded the analysis to the telecommunication sector using the Altman Z-Score and
Zmijewski models for the period 2016-2018. Their study found that some telecommunication companies faced
financial distress due to unhealthy price competition, significantly squeezing profit margins. Additionally, the
differing results between the two models highlight the importance of considering various analytical approaches for a
more accurate assessment of bankruptcy risk.
Manalu et al. (2017) compared three bankruptcy prediction models-Altman Z-Score, Springate, and Zmijewski—in
the food and beverage sector. Their results showed that all three models could predict bankruptcy potential well,
Bayyinah / International Journal of Business, Economics and Social Development, Vol. 6, No. 1, pp. 68-72, 2025 69
although the predictions varied depending on the financial ratios used. This study emphasizes the importance of
selecting a model that fits the specific characteristics of the company being analyzed.
Table 1. Research Gap
Author
Method
Zmijewski
Ohlson O-Score
Telecommunication
Companies
Manalu et al.,
2017
Altman,
Springate, and
Zmijewski
Yes
No
No
Winaya et al.,
2020
Altman, and
Zmijewski
Yes
No
Yes
Hudaya et al.,
2024
Zmijewski, and
Ohlson
Yes
Yes
No
This research
Zmijewski, and
Ohlson
Yes
Yes
Yes
Based on previous research, both the Zmijewski and Ohlson models have been widely used to predict financial
distress, but studies focusing on the telecommunication sector in Indonesia are still limited. Therefore, this study
focuses on analyzing and comparing the Ohlson O-Score and Zmijewski methods in detecting financial distress in
Indonesian telecommunication companies. Using historical financial data from several telecommunication companies
listed on the Indonesia Stock Exchange, this study aims to evaluate the accuracy of both methods in predicting
bankruptcy risk over a specific period. Additionally, the results are expected to provide insights for
telecommunication company management and investors in taking appropriate strategic steps to anticipate financial
distress risks.
2. Literature Review
2.1. Financial Statements
According to Munawir, as cited in Dharma et al. (2023) financial statements are the results of the accounting
process and can be used to communicate financial data to stakeholders. Financial statements are essential for
measuring a company's performance and progress. Prihadi (2019) states that financial statements generally consist of
four types: the balance sheet, income statement, cash flow statement, and statement of changes in equity. These
statements can be used for financial analysis.
Financial statement analysis is the process of studying financial data to understand a company's financial position,
operational results, and progress. This is done by examining relationships and trends in financial statements. Thus,
financial statement analysis can serve as a basis for decision-making by stakeholders (Riswan & Kesuma, 2014).
Financial statement analysis uses financial ratios, which allow financial managers and stakeholders to quickly assess a
company's financial health. Ratio analysis links elements of the balance sheet and income statement to evaluate a
company's effectiveness and efficiency (Orniati, 2009). According to Prayitno in Dharma et al. (2023), there are four
types of financial ratios:
1. Liquidity ratios, which measure a company's ability to meet short-term obligations.
2. Solvency ratios, which measure a company's ability to meet long-term obligations.
3. Profitability ratios, which explain how a company calculates profit using all its resources.
2.2. Financial Statements
According to Manalu et al. (2017), financial distress occurs when a company is unable to meet its current
obligations, such as trade payables, tax liabilities, and short-term debts. There are five types of financial distress:
economic failure, business failure, technical insolvency, insolvency in bankruptcy, and legal bankruptcy.
Dwijayanti (2010) states that financial distress can occur in any company and may be a sign of impending
bankruptcy. If a company experiences financial distress, management must take action to address the issue and
prevent bankruptcy. There are three main reasons why companies experience financial distress and subsequently go
bankrupt:
(a) Neoclassical model: Financial distress occurs due to improper allocation of resources for operational activities.
(b) Financial model: Financial distress results from liquidity constraints, even if asset allocation is correct, leading to
short-term bankruptcy despite long-term survival potential.
Bayyinah / International Journal of Business, Economics and Social Development, Vol. 6, No. 1, pp. 68-72, 2025 70
(c) Corporate governance model: Financial distress arises from poor asset management and inefficient financial
structures, causing the company to go out of the market.
3. Materials and Methods
3.1. Materials
This study predicts bankruptcy in 15 telecommunication companies in Indonesia, including PT. Bali Towerindo
Sentra Tbk, PT. Smartfren Telecom Tbk, PT. Gihon Telekomunikasi Indonesia Tbk, PT. Indosat Ooredoo Hutchison
Tbk, PT. Sinergi Inti Andalan Prima Tbk, PT. First Media Tbk, PT. Ketrosden Triasmitra Tbk, PT. Mora Telematika
Indonesia Tbk, PT. Dayamitra Telekomunikasi Tbk, PT. Remala Abadi Tbk, PT. Sarana Menara Nusantara Tbk, PT.
Tower Bersama Infrastructure Tbk, PT. Visi Telekomunikasi Infrastruktur Tbk, PT. Telkom Indonesia (Persero) Tbk,
and PT. XL Axiata Tbk. The data used are secondary data from the companies' 2023 financial reports, obtained from
their official websites. The analysis was conducted using Microsoft Excel to calculate the required values for both the
Ohlson O-Score and Zmijewski methods.
3.2. Methods
3.2.1. Ohlson O-Score
Hudaya et al. (2024) explain that James Ohlson developed the O-Score model in 1980 to predict bankruptcy using
logistic regression. The model incorporates nine independent variables, and the equation is as follows:
(1)
Log (total assets to GNP price-level index)
Total liabilities to total assets
Working capital to total assets
Current liabilities to current assets
1 if total liabilities exceeds total assets, 0 otherwise
Net income to total assets
Funds provided by operations to total liabilities
1 if net income was negative for the last two years, 0 otherwise
, where is net income for the most recent period
The cutoff value from this equation is classified into two conditions:
Bankrupt :
Non-bankrupt :
3.2.2. Zmijewski
The Zmijewski Model, developed by Zmijewski in 1984, uses ratio analysis to predict bankruptcy by measuring
performance, leverage, and liquidity. The model is calculated using the following equation (Hudaya et al., 2024).
(2)
A company is considered to be in financial distress or at high risk of bankruptcy if the B score is greater than 0. If
the B score is less than 0, the company is considered non-financial distressed, indicating a low risk of bankruptcy.
4. Results and Discussion
The results of this study are presented in the form of ratios derived from the analysis of annual financial reports for
2023 from 15 telecommunication companies in Indonesia. Two methods were used: the Ohlson O-Score with nine
independent variables and the Zmijewski method with three independent variables.
Bayyinah / International Journal of Business, Economics and Social Development, Vol. 6, No. 1, pp. 68-72, 2025 71
Table 2. Calculation Using the Ohlson O-Score Method
Company Code
O-Score
Description
BALI
3,97647
Financial Distress
FREN
4,43564
Financial Distress
GHON
3,16496
Financial Distress
ISAT
4,27358
Financial Distress
INET
-0,1117
Non-Financial Distress
KBLV
9,41572
Financial Distress
KETR
3,38928
Financial Distress
MORA
3,21522
Financial Distress
MTEL
2,55839
Financial Distress
DATA
3,05947
Financial Distress
SMN
5,07172
Financial Distress
TBIG
4,70792
Financial Distress
TLKM
2,24280
Financial Distress
GOLD
1,24261
Financial Distress
EXCL
2,00446
Financial Distress
Based on the O-Score calculation results presented in Table 1, it is evident that only one company falls into the
non-financial distress category, while the other 14 companies are categorized as financial distress. The company
classified as non-financial distressed is PT. Sinergi Inti Andalan Prima Tbk (INET). This company has an O-Score
value of -0.1117, which is below the threshold of 0.38. The negative value indicates that the company has a very low
probability of facing bankruptcy, reflecting its strong financial health. In other words, PT. Sinergi Inti Andalan Prima
Tbk has successfully maintained stable financial conditions and effectively managed critical factors such as
profitability, leverage, liquidity, and operational efficiency.
On the other hand, the remaining 14 companies have O-Score values exceeding 0.38, indicating that they fall into
the financial distress category, with a potential risk of bankruptcy in the future. Among these 14 companies, PT. First
Media Tbk (KBLV) has the highest O-Score, suggesting that it has a higher likelihood of bankruptcy compared to the
others. The high O-Score value of PT. First Media Tbk reflects significant financial issues, particularly in areas such
as low profitability, high debt levels, and inefficient operational management. These factors contribute to the
company's vulnerability to financial instability and potential bankruptcy.
Table 3. Calculation Using the Zmijewski Method
Company Code
B Score
Description
BALI
-1,32182
Non-Financial Distress
FREN
-0,57496
Non-Financial Distress
GHON
-2,43510
Non-Financial Distress
INDOSAT
-0,46397
Non-Financial Distress
INET
-4,11449
Non-Financial Distress
KBLV
4,98738
Financial Distress
KETROSDEN
-1,36090
Non-Financial Distress
MORA
-1,45822
Non-Financial Distress
MTEL
-2,16307
Non-Financial Distress
REMALA
-2,95494
Non-Financial Distress
SMN
-0,19360
Non-Financial Distress
TBIG
-0,25693
Non-Financial Distress
TLKM
-2,21700
Non-Financial Distress
VTI
-3,96307
Non-Financial Distress
XL
-2,64445
Non-Financial Distress
In contrast to the Ohlson O-Score method, which identified only one company in the non-financial distress
category and 14 companies in the financial distress category, the results of the Zmijewski method show that 14
Bayyinah / International Journal of Business, Economics and Social Development, Vol. 6, No. 1, pp. 68-72, 2025 72
companies fall into the non-financial distress category, while only one company is categorized as financial distress, as
presented in Table 2. Based on the calculations, the smallest B score is held by PT. Sinergi Inti Andalan Prima Tbk
(INET) with a value of -4.04318. This indicates that the company has the healthiest financial condition compared to
the others. This financial health reflects the company's ability to manage its finances effectively, including high
profitability, controlled debt levels, and strong liquidity.
Additionally, the Zmijewski method results reveal that only one company, PT. First Media Tbk (KBLV), has a B-
Score greater than 0, placing it in the financial distress category. This indicates a high risk of bankruptcy. The
company's financial condition reflects significant issues, necessitating strategic actions from management to improve
financial management.
A comparison between the Ohlson O-Score and Zmijewski methods shows that the two approaches yield
significantly different results. In the Ohlson O-Score method, PT. First Media Tbk has the most negative O-Score,
classifying it as the company with the best financial condition. This aligns with the Zmijewski method, which also
categorizes the company as non-financial distressed. However, the difference lies in the number of companies
identified as bankrupt or financially distressed. The Ohlson O-Score method identified 14 companies as financially
distressed, while the Zmijewski method identified only one company in this category. This discrepancy is due to the
number of variables and the approaches used in each method. The Ohlson O-Score incorporates more variables,
including external factors such as the Gross National Product (GNP), making it more sensitive to changes in
macroeconomic conditions. Therefore, the Ohlson O-Score is more suitable as an early detection tool for predicting
bankruptcy potential. On the other hand, the Zmijewski method is simpler and more effective in identifying
companies already in critical financial conditions or at significant risk of bankruptcy. By understanding the strengths
of each method, their use can be tailored to specific analytical needs.
5. Conclussion
Based on the calculations using both the Ohlson O-Score and Zmijewski methods, only one company, PT. First
Media Tbk, is at high risk of bankruptcy. This reflects the company's poor financial condition, requiring strategic
management actions to improve financial management.
However, there is a significant difference in the results between the two methods. The Ohlson O-Score identified
14 companies as financial distressed and one as non-financial distressed, while the Zmijewski method identified only
one company as financial distressed and 14 as non-financial distressed. This difference is due to the number of
variables and approaches used in each method. The Ohlson O-Score, with more variables including external factors
like GNP, is more suitable for early detection of bankruptcy risk. In contrast, the Zmijewski method, with its simpler
approach, is more effective in evaluating companies already in critical financial conditions. Understanding the
strengths of each method allows for their application based on specific analytical needs.
References
Dharma, B., Ramadhani, Y., & Reitandi, R. (2023). The Importance of Financial Statements in Assessing Company Performance.
El-Mujtama: Journal of Community Service, 4(1), 137–143. https://doi.org/10.47467/elmujtama.v4i1.3209
Hudaya, R., Kartikasari, N., Suryantara, A. B., & Sukma, P. (2024). Bankruptcy Potential in Companies with Special Notations
Using Zmijewski X-Score and Ohlson O-Score Models. Research, Economics, Accounting, and Taxation (REKAN), 5(1),
15–40. https://doi.org/10.30812/rekan.v5i1.3650
Manalu, S., Octavianus, R. J. N., & Kalmadara, G. S. S. (2017). Financial distress analysis with altman z-score approach and
zmijewski x-score on shipping service company. Jurnal Aplikasi Manajemen, 15(4), 677-682.
Orniati, Y. (2009). Financial Statements as a Tool to Assess Financial Performance, 14(3), 206.
Riswan, R., & Kesuma, Y. F. (2014). Financial Statement Analysis as a Basis for Assessing the Financial Performance of PT.
Budi Satria Wahana Motor. Journal of Accounting and Finance, 5(1). https://doi.org/10.36448/jak.v5i1.449
Winaya, G. Y., Rm, K. M., Ayu, I. G., Budiasih, N., & Wiratmaja, I. D. N. (2020). Analysis of Altman Z-Score and Zmijewski
Bankruptcy Prediction in Telecommunication Sub-Sectors Registered in Indonesia Stock Exchange in 2016-2018. 1, 313–
322.
