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All Journal Technologia: Jurnal Ilmiah Balance Vocation Accounting Journal Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) International Journal of Social Service and Research International Journal of Science and Society (IJSOC) Indonesian Journal of Multidisciplinary Science Jurnal Ekonomi dan Bisnis Digital (MINISTAL) East Asian Journal of Multidisciplinary Research (EAJMR) Indonesian Journal of Business Analytics (IJBA) Formosa Journal of Multidisciplinary Research (FJMR) Journal Research of Social Science, Economics, and Management Asian Journal of Social and Humanities Informasi interaktif : jurnal informatika dan teknologi informasi
I Gusti Agung Musa Budidarma Budidarma
Bunda Mulia University Jakarta, Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Public Health Social Sciences

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Studi Kasus Feature Engineering Untuk Data Teks: Perbandingan Label Encoding dan One-Hot Encoding Pada Metode Linear Regresi Cevi Herdian; Ahya Kamila; I Gusti Agung Musa Budidarma
Technologia : Jurnal Ilmiah Vol 15 No 1 (2024): Technologia (Januari)
Publisher : Fakultas Teknologi Informasi, Universitas Islam Kalimantan Muhammad Arsyad Al Banjari, di bawah koordinasi UPT Publikasi dan Pengelolaan Jurnal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v15i1.13457

Abstract

Di dalam pemodelan pembelajaran mesin (Machine Learning), data terbagi menjadi jenis data numerik dan jenis data teks. Tetapi Machine Learning lebih cenderung efektif dalam mengenali pola pada jenis data numerik karena algoritma Machine Learning, terutama yang berbasis statistik dan matematika, dirancang untuk memproses dan menganalisis data numerik. Sehingga bentuk data teks harus dirubah ke dalam bentuk data numerik yang merupakan bagian dari Feature Engineering. Pada penelitian ini, peneliti membanding sebuah hasil akurasi dari prediksi Machine Learning yaitu linear regresi pada teks label data yang telah dilakukan perubahan menjadi numerik dengan metode Feature engineering Label Encoding dan juga Feature Engineering One-Hot Encoding. Pada penelitian ini didapatkan hasil R-Square untuk Label Encoding 0.54 dan R-Squared untuk One-Hot Encoding 0.85 (hasil One-Hot Encoding lebih baik). Sehingga tentu saja yang harus dipilih untuk model yang dibuat adalah Feature Engineering One-Hot Encoding. Untuk kedepannya bisa dilakukan pengujian dengan metode lain untuk merubah data teks menjadi numerik seperti Bags of Words (BoW), Term Frequency-Inverse Document Frequency (TF-IDF), dan yang lainnya.
The Effect of Board Gender Diversity, Board Size, and Capital Structure on Firm Performance Moderated by Institutional Ownership Jennifer Wirawan; I Gusti Agung Musa Budidarma
Dinasti International Journal of Economics, Finance & Accounting Vol. 5 No. 3 (2024): Dinasti International Journal of Economics, Finance & Accounting (July - August
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v5i3.3134

Abstract

The aim of this study was to examine the effect of board gender diversity, board size, and capital structure on firm performance in energy sector companies listed on the Indonesian Stock Exchange for the 2021–2023 period, which was moderated by institutional ownership. This study employed a purposive sampling technique, with a total sample size of 93 companies’ data. The data were analyzed using the SPSS program, specifically through moderated regression analysis. The results showed that board gender diversity and capital structure had no effect on firm performance, whereas board size had a negative effect. In addition, institutional ownership moderated the effect of board size and capital structure on firm performance; on the contrary, it did not moderate the effect of board gender diversity on firm performance.
The Effect Of Intellectual Capital Towards Firm’s Financial Performance, Moderating Effect Of Firm Reputation Clara Angela; I Gusti Agung Musa Budidarma
Dinasti International Journal of Economics, Finance & Accounting Vol. 5 No. 3 (2024): Dinasti International Journal of Economics, Finance & Accounting (July - August
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v5i3.3172

Abstract

This study aims to analyze the impact of intellectual capital on the financial performance of companies in Indonesia, considering the moderating effects of corporate reputation as presented by Fortune 100 Indonesia list. Intellectual capital, which includes employee capital and structural capital, is considered an important asset that can enhance a company's financial performance. The study uses secondary data from the annual reports of companies listed on the Fortune 100 and Indonesia Stock Exchange for the period of 2020 to 2022. The analysis method employed is data panel regression analysis, and purposive sampling is used in forming the sample. The results of regression analysis shows support for the significant impact of intellectual capital towards financial performance, urging Indonesian firms to maintain their intellectual capital well. On the other hand, firm size may also be inspected as independent variable instead of moderator.
Co-Authors Agung Stefanus Kembau Ahya Radiatul Kamila Angela, Clara Anggawikara, Sherly Cevi Herdian Clara Angela Eirene Virginia Budikasi Gebrill Kimberly Pendong Herdian, Cevi Jennifer Wirawan Jesslyn, Claresta Laras Puri Asih Lee-Anne C Johennesse M. Primastuti Dyah Shintawati Melody Natashia Sandiputri Priskilia Wuwancong Jacob Sheren Laura Lasaru Stefanie Valencia Kezia Kalengkian Tampinongkol, Felliks Feiters Veronicha Veronicha Veronicha, Veronicha Vianty Adella Santo Wirawan, Jennifer Yuansi Ester Tumilaar Yuli Andriyani