This study's goal is to ascertain the connection between liquidity ratio (CR), asset management (TATO), capital structure (DAR) and firm size on financial performance, The  property & real estate firms that were listed between 2019 and 2023 on the Indonesia Stock Exchange (IDX). The study's sample, which was 52 companies in a period of (5) periods with a total of 260 data. The multiple regression analysis is used in this study method with the type of panel data with the Random Effect Model (REM) method. According to the study's findings that asset management has a favorably and significantly effect on financial performance, capital structure has a negatively and significantly effect on financial performance, but liquidity ratio and firm size have no effect on financial performance.

Cyberloafing behavior is a form of withdrawal deviance in the workplace which is increasingly surfacing along with technological developments. Cyberloafing behavior not only has a positive impact but also has a negative impact on the company. To maximize the positive impact and minimize the negative impact, this research has an urgency to examine predictors that can explain the occurrence of cyberloafing behavior. The study was conducted using employees from various companies in various industries as research samples. The results of this study indicate that cyberloafing behavior is explained by role ambiguity, role conflict and role overload.

Kualitas produk bimbingan di sebabkan beberapa faktor yang juga merupakan elemen kinerja dosen juga diantaranya lulusan dosen, bidang keahlian, mata kuliah yang diajar, jumlah mahasiswa lulusan. Penentuan dosen bimbingan pada setiap topik tugas akhir yang dilakukan prodi manajemen selama ini masih berdasarkan satu variabel saja yaitu lulusan dosen, belum ada variabel pertimbangan lain seperti yang tersebut diatas. Perlu dilakukan klasifikasi kinerja dosen yang meliputi lulusan dosen, bidang keahlian, mata kuliah yang diajar, jumlah mahasiswa lulusan terhadap ploting topik bimbingan tugas akhir mahasiswa. Hasil klasifikasi mampu memberikan dukungan keputusan dalam menentukan dosen-dosen yang berkompeten pada setiap jenis topik tugas akhir.