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Model of Corporate Value Improvement Through Investment Opportunity in Manufacturing Company Sector Faozi, Imam; Ghoniyah, Nunung
International Research Journal of Business Studies Vol. 12 No. 2 (2019): August-November 2019
Publisher : Universitas Prasetiya Mulya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21632/irjbs.12.2.185-196

Abstract

This study aims to analyze the significance of the direct and indirect effect of institutional ownership (INST), profitability (ROI), funding policy (DER), and dividend policy (Tobin’s Q) through investment opportunity (MV/BVE). The research data used 21 samples of manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the 2012-2016 period. Data analysis used path analysis with the help of EViews 9 and Sobel test to know the effect of investment opportunity as an intervening variable. The interpretation findings of the first line analysis model show that Profitability directly affects positively and significantly on Corporate Value. Whereas, based on second-line analysis model, Funding Policy and Dividend Policy indirectly have significant effects on Corporate Value through Investment Opportunity variable. Simultaneously, all independent variables affect 97.45% of Investment Opportunities and amounted to 97.97% of Corporate Value through Investment Opportunities.
Pelatihan Manajemen Keuangan dan Penguatan Kelembagaan Kelompok Ternak Salehawati, Nurul; Dewi, Meita Puspa; Faozi, Imam; Rozaq, Abdul; Jazuli, Ahmad
PASAI : Jurnal Pengabdian kepada Masyarakat Vol. 1 No. 2 (2022): December
Publisher : Yayasan Pendidikan Mitra Mandiri Aceh(YPMMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58477/pasai.v1i2.51

Abstract

This activity aims to provide training and understanding to livestock groups, so thet can record financial adminitrastion books in accordance with financial accounting standards and institusional reinforcement. This activity was held in two places, namely The Bendosari Livestock Group and The Plosokerep Livestock Grup. In this training, the methods used are observation of discussions with livestock groups about what activities have been carried out in financial recording and institutional strengthening of groups, presentation of material by means of presentations and video playback, the practice of manual financial recording, and use of the Android SME-Financial Accounting Application. The results of this training activity are: (1) socialization activities for institutional strengthening; and the practice of manual financial recording and using applications smoothly, (2) Having the awareness that each group member has a role in strengthening group institutions, (3) Having awareness of the importance of recording every financial transaction and documenting financial transaction notes, (4) Manual recording can be done either by hand or with the SME-Finance Accounting application, and (5) Understand the importance of keeping personal and business transactions separate
Implementasi Deteksi Jenis Tanaman Herbal Dengan Model Klasifikasi Gambar Menggunakan Teachable Machine Putri, Amanda Titania; Safira, Ola; Yulianti, Amelia; Faozi, Imam; Setiawan, Retno Agus
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2025 Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2025)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v4i1.1373

Abstract

Herbal plants are a source of natural ingredients widely used in traditional medicine and alternative therapies. However, the process of identifying herbal plant types is still often done manually, potentially leading to errors, especially for the general public. The aim of this research is to implement an intelligent system capable of classifying herbal plant types based on leaf images, thereby helping to identify herbal plants independently while providing educational value. The research utilizes an image dataset of several types of herbal plant leaves that were processed and trained using Google Teachable Machine. This platform facilitates training machine learning models through an image-based approach without requiring complex programming knowledge. The dataset is divided into several classes according to the type of herbal plant, and the training process is carried out by varying parameters such as epoch, batch size, and learning rate to obtain the most optimal configuration. The results of this research create a web-based intelligent system application that can effectively classify herbal plant images, provide educational information to users, and can be further developed into a practical tool for herbal plant identification. The research also highlights several challenges, such as the need for a sufficiently large and diverse dataset, variations in lighting conditions and image backgrounds, and the model's ability to perform consistently under real-world conditions.