PENGARUH GENDER DEWAN KOMISARIS, GENDER DEWAN DIREKSI, DAN KEPEMILIKAN MANAJERIAL TERHADAP KINERJA PERUSAHAAN (Studi Empiris Pada Perusahaan yang Terdaftar di Bursa Efek Indonesia periode 2008)

Penelitian ini bertujuan untuk membuktikan pengaruh mekanisme corporate governance, diantaranya gender dewan komisaris, gender dewan direksi, dan kepemilikan manajerial terhadap kinerja perusahaan. Penelitian ini juga menambahkan ukuran perusahaan, leverage , dan umur perusahaan sebagai variabel kontrol. Penelitian ini mengammbil sampel dari Bursa Efek Indonesia tahun 2008 sehingga diperoleh 111 perusahaan sebagai dasar purposive sampling. Metode yang digunakan dalam analisis ini adalah regresi berganda. Hasil dari penelitian ini menunjukkan bahwa (1) gender dewan komisaris berpengaruh negatif terhadap kinerja perusahaan, (2) gender dewan direksi tidak berpengaruh terhadap kinerja perusahaan, dan (3) kepemilikan manajerial juga tidak berpengaruh terhadap kinerja perusahaan. Kata kunci: gender dewan komisaris, gender dewan direksi, kepemilikan manajerial, kinerja peruahaan, Tobin’s

ANALISIS EFISIENSI DUAL BANKING SYSTEM DI INDONESIA: STOCHASTIC FRONTIER ANALYSIS (SFA)

ABSTRAKPenelitian ini bertujuan untuk menganalisis perbandingan efisiensi bank konvensional dan unit usaha syariah di Indonesia tahun 2011-2016. Jenis penelitian ini adalah deskriptif kuantitatif. Objek penelitian ini adalah bank umum konvensional yang memiliki cabang unit usaha syariah di Indonesia, ada 19 bank umum konvensional dan 19 unit usaha syariah yang diteliti. Data yang digunakan dalam penelitian ini adalah data sekunder berupa laporan keuangan/laporan tahunan tahun 2011-2016. Analisis data menggunakan stochastic frontier analysis untuk mengetahui nilai efisiensi setiap objek penelitian. Pengolahan data menggunakan program Frontier 4.1. Hasil penelitian menujukkan bahwa secara keseluruhan efisiensi unit usaha syariah cukup baik namun masih kalah dari bank umum konvensional . Efisiensi unit usaha syariah unggul dibandingkan bank konvensional pada pendekatan produksi, namun nilai efisiensi unit usaha syariah rendah pada pendekatan aset dan pendekatan intermediasi. Dari keseluruhan total amatan menunjukkan bahwa bank konvensional yang efisien lebih banyak dari jumlah unit usaha syariah yang efisien.Kata Kunci: Efisiensi, Dual Banking System, Stochastic Frontier Analysis, Bank Umum Konvensional, Unit Usaha Syaria

Cross Device Federated Intrusion Detector for Early Stage Botnet Propagation in IoT

A botnet is an army of zombified computers infected with malware and controlled by malicious actors to carry out tasks such as Distributed Denial of Service (DDoS) attacks. Billions of Internet of Things (IoT) devices are primarily targeted to be infected as bots since they are configured with weak credentials or contain common vulnerabilities. Detecting botnet propagation by monitoring the network traffic is difficult as they easily blend in with regular network traffic. The traditional machine learning (ML) based Intrusion Detection System (IDS) requires the raw data to be captured and sent to the ML processor to detect intrusion. In this research, we examine the viability of a cross-device federated intrusion detection mechanism where each device runs the ML model on its data and updates the model weights to the central coordinator. This mechanism ensures the client's data is not shared with any third party, terminating privacy leakage. The model examines each data packet separately and predicts anomalies. We evaluate our proposed mechanism on a real botnet propagation dataset called MedBIoT. Overall, the proposed method produces an average accuracy of 71%, precision 78%, recall 71%, and f1-score 68%. In addition, we also examined whether any device taking part in federated learning can employ a poisoning attack on the overall system.Comment: Paper submitted to conferenc

PENGARUH GENDER DEWAN KOMISARIS, GENDER DEWAN DIREKSI, DAN KEPEMILIKAN MANAJERIAL TERHADAP KINERJA PERUSAHAA

The objective of this study is to examine the influence of corporate governance mechanisms, which are board of director’s gender, director’s gender, and managerial ownership on firm’s performance. This study also examines firm’s size, leverage, and firm’s age, as control variables, on firm’s performance. This study uses 111 listed companies’ annual reports on Indonesia Stock Exchange (BEI) year 2008. Sample in this study is selected using purposive sampling method. While multiple regression analysis is used to test the three hypotheses developed in this research. The result of this study shows that (1) board of director’s gender has negative influence on firm’s performance, (2) director’s gender does not influence the firm’s performance, and (3) managerial ownership also does not influence the firm’s performance. Keywords: board of director’s gender, director’s gender, managerial ownership, firm’s performance, Tobin’s

Cross Device Federated Intrusion Detector for Early Stage Botnet Propagation in IoT

A botnet is an army of zombified computers infected with malware and controlled by malicious actors to carry out tasks such as Distributed Denial of Service (DDoS) attacks. Billions of Internet of Things (IoT) devices are primarily targeted to be infected as bots since they are configured with weak credentials or contain common vulnerabilities. Detecting botnet propagation by monitoring the network traffic is difficult as they easily blend in with regular network traffic. The traditional machine learning (ML) based Intrusion Detection System (IDS) requires the raw data to be captured and sent to the ML processor to detect intrusion. In this research, we examine the viability of a cross-device federated intrusion detection mechanism where each device runs the ML model on its data and updates the model weights to the central coordinator. This mechanism ensures the client’s data is not shared with any third party, terminating privacy leakage. The model examines each data packet separately and predicts anomalies. We evaluate our proposed mechanism on a real botnet propagation dataset called MedBIoT. Overall, the proposed method produces an average accuracy of 71%, precision 78%, recall 71%, and f1-score 68%. In addition, we also examined whether any device taking part in federated learning can employ a poisoning attack on the overall system.</p