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All Journal Binus Business Review Substansi: Sumber Artikel Akuntansi Auditing dan Keuangan Vokasi Jurnal Kajian Akuntansi Journal of Applied Data Sciences
Bambang Leo Handoko, Bambang Leo
Bina Nusantara University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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The Effect of Institutional Ownership and Leverage towards Profit Management in Consumer Goods Industry Listed in BEI Handoko, Bambang Leo
Binus Business Review Vol 6, No 3 (2015): Binus Business Review
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/bbr.v6i3.951

Abstract

Earning management is usually used by the company as shortcut to make up their financial statement to fulfill some criteria for certain purpose. This research is empirical research which aimed is to examine the influence of institutional ownership and leverage to earnings management. This study takes sample from companies in the consumer goods sector at the Jakarta Stock Exchange, which were published in financial report from 2008-2011. The method of analysis of this research used multiple regression analysis. The results of this study show that (1) institutional ownership had not significant influence to earnings management sig.0,129>0,05, (2) leverage had not significant influence to earnings management sig. 0,481>0,05 and (3) simultaneously of institutional ownership and leverage had not significant influence to earnings management0,249>0,05.
Palm Oil Industry Dynamics: Assessing P/B Ratios of Indonesian Palm Oil Companies through Palm Tree Profile, Average FFB Yield, and Palm Oil Extraction Rate Hadi, Nixxen Dimitri; Handoko, Bambang Leo; Lindawati, Ang Swat Lin; Sarjono, Haryadi
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.483

Abstract

The primary objective of this paper is to explore the impact of palm tree profile (age), Fresh Fruit Bunch (FFB) yield, and Oil Extraction Rate (OER) on the Price-to-book (P/B) ratio of Indonesian palm oil companies listed on the Indonesia Stock Exchange (IDX) with return on equity (ROE) as a mediating variable. This study is important because it explores the variables that affect business valuations in a vital industry that employs more than 16 million people and generates huge export earnings, significantly supporting the Indonesian economy. Multiple linear regression is used in a quantitative analysis of secondary data gathered from the financial statements and annual reports of 15 palm oil enterprises from 2013 to 2023. The results show a strong positive relationship between OER and FFB yield with the P/B ratio, indicating that increased operational productivity and efficiency raise firm values. Specifically, the regression analysis revealed that each percentage point increase in OER is associated with a 0.1546 increase in the P/B ratio (p 0.001), and each unit increase in FFB yield contributes to a 0.1013 increase in the P/B ratio (p 0.001). On the other hand, the P/B ratio is negatively impacted by palm tree age, suggesting that older palms are less productive, with a coefficient of -0.1035 (p 0.001). The relationship between productivity ratio and valuation was also shown to be influenced by Return on Equity (ROE), which was identified as a mediating variable. The findings suggest that enhancing internal factors, such as plantation management and mill efficiency, can improve company valuation. It is recommended for future research to use larger sample sizes and longer observation periods to confirm these findings and explore additional variables.
English: - Cyntia, Calrsen; Tan, Chelsea; Handoko, Bambang Leo
SUBSTANSI Vol 9 No 1 (2025): JURNAL SUBSTANSI
Publisher : Politeknik Keuangan Negara STAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35837/subs.v9i1.3311

Abstract

The rapid development of technology in industry 4.0 today has encouraged the integration of Artificial Intelligence (AI), Internet of Things (IoT) and big data in helping the operations of various industrial sectors, especially in the start-up sector. This study aims to determine whether there are factors such as Natural Language Processing, AI-Driven data analysis, risk assessment, and electronic whistle-blowing systems that will affect the way the system detects fraud, and to determine whether these factors cause several start-up companies to use the integration of AI, NLP, and E-WBS to accelerate the fraud disclosure process. This study involved 113 employee respondents who worked in start-up companies. The results of the respondent data were processed using SMART-PLS 4.0 which involved the reliability and validity methods, discriminant, r-square adjusted, and outer loading. The results of the study showed that Natural Language Processing, AI-Driven data analysis, risk assessment, and Electronic Whistle Blowing Systems did have a positive impact or increase the accuracy of fraud disclosure in real-time, effectively and efficiently. Keyword: AI-Driven Data Analysis, Natural Language Processing, Whistle-Blowing Systems
Fraud Hexagon dalam Mendeteksi Financial Statement Fraud Perusahaan Perbankan di Indonesia Handoko, Bambang Leo
Jurnal Kajian Akuntansi Vol 5 No 2 (2021): DESEMBER 2021
Publisher : Universitas Swadaya Gunung Jati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33603/jka.v5i2.5101

Abstract

AbstractCases of fraud are increasing from year to year and the costliest type of fraud is financial statement fraud which causes substantial losses for the company and users of financial statement. The aim of this research is to analyze fraud hexagon on detecting financial statement fraud of banking companies listed in Indonesia Stock Exchange for the period 2015-2019. The research population is 46 banking companies listed in Indonesia Stock Exchange. Purposive sampling method is used on this research. The sample chosen with matching criteria is 41 companies with a total observation of 205. Logistic regression method is used to analyze data and data processing was performed with IBM SPSS 26. The research results indicated that the financial target, external pressure, ineffective monitoring, change in auditor, change in director, and frequent number of CEO’s picture do not have an effect in detecting financial statement fraud on listed banking companies. Meanwhile, collusion has an effect in detecting financial statement fraud on listed banking companies.Keywords: Fraud hexagon; Financial statement fraud; Banking company. Abstrak Kasus kecurangan mengalami peningkatan dari tahun ke tahun dan yang paling merugikan ialah kecurangan laporan keuangan serta menyebabkan kerugian bagi perusahaan dan bagi pengguna laporan keuangan. Penelitian ini bertujuan untuk menganalisis faktor-faktor fraud hexagon dalam mendeteksi financial statement fraud pada perusahaan sektor perbankan yang terdaftar di Bursa Efek Indonesia (BEI) periode 2015-2019. Populasi yang digunakan adalah 46 perusahaan sektor perbankan yang terdaftar di Bursa Efek Indonesia. Metode purposive sampling merupakan metode pengambilan sampel yang digunakan dalam penelitian ini. Sampel yang memenuhi kriteria penelitian adalah 41 perusahaan perbankan dengan total observasi adalah sebanyak 205. Metode analisis data menggunakan metode regresi logistik dengan bantuan aplikasi IBM SPSS 26 untuk melakukan pengujian data. Hasil penelitian menunjukkan bahwa financial target, external pressure, ineffective monitoring, change in auditor, change in director, dan frequent number of CEO’s picture tidak memiliki pengaruh dalam mendeteksi financial statement fraud. Sedangkan, variabel collusion memiliki pengaruh dalam mendeteksi financial statement fraud.Kata Kunci: Fraud hexagon; Kecurangan laporan keuangan; Perusahaan perbankan.
Co-Authors Ang Swat Lin Lindawati, Ang Swat Lin Cyntia, Calrsen Hadi, Nixxen Dimitri Haryadi Sarjono Tan, Chelsea