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All Journal International Journal of Advances in Applied Sciences Jurnal Ilmiah Telaah Manajemen JDM (Jurnal Dinamika Manajemen) Jurnal Mahasiswa Pasca Sarjana Students´ Journal of Accounting and Banking Students´ Journal of Economic and Management Proceeding SENDI_U Jurnal Organisasi Dan Manajemen SENTRALISASI Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Jurnal GeoEkonomi International Journal of Economics, Business and Accounting Research (IJEBAR) Management Studies and Entrepreneurship Journal (MSEJ) Journal Evidence Of Law Jurnal Dinamika Akuntansi
Bambang Sudiyatno
Jl. Kendeng V Bendan Ngisor, Semarang, 50233
Humanities Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Physics Social Sciences

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Kinerja Keuangan dan Ukuran Perusahaan: Pengaruhnya Terhadap Harga Saham Sektor Teknologi di Bursa Efek Indonesia Tahun 2018 - 2022 Utami, Ratna Cahyaning; Sudiyatno, Bambang
Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Vol 7 No 2 (2024): Artikel Periode Research Juli 2024
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi Al-Washliyah Sibolga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36778/jesya.v7i2.1711

Abstract

Penelitian ini bertujuan untuk menginvestigasi faktor-faktor yang memengaruhi harga saham pada perusahaan sektor teknologi yang terdaftar di Bursa Efek Indonesia (BEI) selama periode 2018 hingga 2022. Faktor-faktor yang dianalisis meliputi Earning Per Share (EPS), Return on Assets (ROA), dan Debt to Assets Ratio (DAR), dengan ukuran perusahaan sebagai variabel kontrol. Teori yang menjadi dasar dalam penelitian ini mencakup teori sinyal (signalling theory), teori agensi (agency theory), dan teori trade-off. Sampel penelitian terdiri dari 12 perusahaan yang dipilih menggunakan metode purposive sampling. Metode analisis yang digunakan adalah analisis regresi data panel dengan menggunakan perangkat lunak Eviews 12. Hasil penelitian menunjukkan bahwa Earning Per Share (EPS) memiliki pengaruh positif dan signifikan terhadap harga saham. Namun, Return on Assets (ROA) menunjukkan pengaruh negatif yang tidak signifikan terhadap harga saham, dan Debt to Assets Ratio (DAR) tidak memiliki pengaruh signifikan terhadap harga saham. Selain itu, variabel kontrol, yaitu ukuran perusahaan (firm size), juga memengaruhi harga saham.
Does The Productivity of Companies Affected by Employee Stock Option Plans and Intellectual Capital? Puspitasari, Elen; MG Kentris Indarti; Sudiyatno, Bambang; Wahyu Meiranto
Jurnal Dinamika Akuntansi Vol. 16 No. 1 (2024)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jda.v16i1.4052

Abstract

Purposes: This study tries to identify the impact of intellectual capital and employee stock option plans on company productivity. Productivity is measured with The Malmquist Productivity Index which is intended to measure the efficiency of companies. Measurement of intellectual capital using Value Added Intellectual Capital determined by human capital efficiency, structural capital efficiency and capital employed efficiency. Methods: This research uses a quantitative approach, and data collection is carried out through secondary data. The research sample was taken from 60 companies with 180 observation data from the financial industry sector listed on the Indonesia Stock Exchange from 2019 to 2021, during the Covid-19 pandemic. The multiple regression analysis method is used to examine the relationship between intellectual capital, employee stock option plans, and company productivity. Findings: The results imply that human capital, structural capital, capital employ and employee stock option plans have impact on company productivity. Therefore, a dominant factor affecting company productivity is human resources. The implementation of share ownership schemes for employees has not been widely used in businesses that operate in the Indonesian financial industry sector. Novelty: The advantage of the Malmquist Productivity Index on the financial industry when compared to others is that it does not require assumptions of corporate behavior as applied in the Data Envelopment Analysis methods such as minimizing costs or maximizing profits. The Malmquist Productivity Index can specifically assess the productivity of each company unit. This research became very interesting because the productivity measured by the Malmquist Index in the finance industry was influenced by structural capital and human capital.
Financial distress prediction for batik small and medium enterprises credit financing based on deep learning algorithm Taryadi, Taryadi; Sudiyatno, Bambang; Basiya, Robertus; Yunianto, Era
International Journal of Advances in Applied Sciences Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i1.pp245-252

Abstract

One of the biggest obstacles that any finance provider has when evaluating a borrower's creditworthiness is the prediction of financial trouble. The credit decision-making process is made more difficult for small and medium enterprises (SMEs) due to their inherent ambiguity, which raises financing costs and lowers the chance of approval. In order to estimate a binomial classifier for predicting financial hardship using logistic regression (LR), extreme gradient boosting (XGBoost), and artificial neural network (ANN) techniques, this study examines data from batik SMEs in Pekalongan city. Financial ratios predict the first period and grow in a multi-period model based on temporal factors, credit history, and age. Financial distress is defined as a substantial obstacle to a business's capacity to pay its debts as opposed to the potential for bankruptcy. The long short-term memory (LSTM) algorithm with more variables yields the best prediction accuracy. The study's conclusion indicates that in order to guarantee the accuracy of financial distress prediction, the time at risk must be adjusted.
Co-Authors 07.250.20009 Retno Wardaningrum 08.05.51.0047 Rosida Arumbinang 10.05.51.0135 Asih Fatmawati 12.05.51.0004 Irmawati, 12.05.51.0004 12.05.51.0097 Ailsa Devina Rahmasari, 12.05.51.0097 12.05.51.0167 Titik Fauziah, 12.05.51.0167 1352020050 Sigit Widhicahyono, 1352020050 1352020090 Bambang Sudarsono, 1352020090 Agus Budi Santosa Ali Maskur AmiliaZubaidah, 14.05.52.0017 AmiliaZubaidah, 14.05.52.0017 Anindiansyah, Gladis Cahyani Nuswandari Darodjat , Tubagus Achmad Elen Puspitasari Fitiana Arumi, 12.05.51.0023 Fitiana Arumi, 12.05.51.0023 Fitika Andraini Gregorius Masdjojo Ida Nurhayati Indah Tri Forniawati Irmawati Irmawati Kusuma Putri, Galuh Lisa Agustina, Lisa MG Kentris Indarti Moch Irsad, Moch Nurhayat , Ida Olivia Dhenok Arumsari, 15.05.51.0381 Robertus Basiya Sari, Antiek Puspita Sigit Nugroho, 14.05.52.0233 Sri Nawatmi Sri Sudarsi Taryadi Taryadi Toto Suharmanto Utami, Ratna Cahyaning WAHYU MEIRANTO Yeye Susilowati Yuda Pratiwi, Elsa Yunianto, Era Zubaidah, Amilia Zubaidah, Amilia