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All Journal Jurnal Informatika Progres Jurnal Sintak
Agung, Andi
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Mathematics

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Implementation of A Contemporary Model Between Trading Volume, Bid-Ask Spreads, And Stock Return Volatility (Case Study : The Business-27 Index) Agung, Andi; Zaqiyah, Arfatuz; Rozikin, Muhammad; Wafa, Moh. Shohibul; Nuha, Agusyarif Rezka
JURNAL SINTAK Vol. 2 No. 2 (2024): Vol. 2 No. 2 (2024): MARET 2024
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v2i2.223

Abstract

Artikel ini memuat analisis hubungan antar variabel perdagangan saham yakni volume perdagangan, bid-ask spreads, dan volatilitas return saham dalam ruang lingkup dua hipotesis utama yakni the mixture of distribution hypothesis (MDH) dan the sequential information arrival hypothesis (SIAH). Hasil perhitungan mengidentifikasi bahwa pada sebagian besar saham terdapat hubungan kontemporer positif antara volume perdagangan terhadap voltilitas return tidak cukup bukti mendukung teori MDH.
Causality Model of Trading Variables Between Trading Volume, Bid-Ask Spreads, and Stock Return Volatility (Case Study: Bisnis-27 Index) Agung, Andi; Zaqiyah, Arfatuz; Rozikin, Muhammad; Wafa, Moh. Shohibul; Nuha, Agusyarif Rezka; Sulistyono, Eko
JURNAL SINTAK Vol. 3 No. 1 (2024): SEPTEMBER 2024
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/jsintak.v3i1.317

Abstract

This research explores the causality model between trading volume, bid-ask spread, and stock return volatility in the business index-27. Utilizing historical data, Granger causality analysis is employed to determine the direction and strength of the relationships between these variables. The findings reveal significant causal relationships among trading volume, bid-ask spread, and stock return volatility. These findings offer valuable insights into understanding stock market dynamics and their implications for investment decision-making. Moreover,This article contains an analysis of the relationship between stock trading variables within the scope of two main hypothesis namely the mixture of distribution hypothesis (MDH) and the sequential information arrival hypothesis (SIAH). The calculation results identify that for most stocks there is a one way Granger causality relationship between trading volume and return volatility, which is not sufficient evidence to support the MDH theory.
PENERAPAN ALGORITMA MOBILENETV2 UNTUK KLASIFIKASI HURUF HIJAIYAH BERBASIS GESTUR TANGAN Riswan, Muh.; Wahyuni, Titin; Danuputri, Chyquitha; Habi Talib, Emil Agusalim; Faisal, Muhammad; Anas, Lukman; Agung, Andi
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.535

Abstract

The digitalization of religious education offers significant opportunities to enhance Hijaiyah letter learning, particularly for the hearing-impaired community through visual gesture recognition. This study aims to develop and evaluate a real-time web-based classification system for 28 Hijaiyah hand gestures using the MobileNetV2 architecture. The research methodology involves a quantitative approach utilizing transfer learning with a balanced dataset of augmented images. The model was trained using fine-tuning techniques and deployed on a web platform using TensorFlow.js and MediaPipe for efficient on-device inference. Experimental results demonstrate that the model achieved an overall accuracy of 84% on the independent test set, with specific classes reaching near-perfect detection in real-time scenarios, although misclassification persisted among visually similar gestures. The system effectively balances computational efficiency with classification performance, minimizing latency during user interaction. In conclusion, the implementation of MobileNetV2 facilitates a responsive and accessible educational tool, proving the viability of computer vision in creating inclusive religious learning environments without requiring complex server-side infrastructure.
Co-Authors Agusyarif Rezka Nuha Danuputri, Chyquitha Eko Sulistyono Sulistyono Emil Agus Salim Habi Talib LUKMAN ANAS Muhammad Faisal Riswan, Muh. Rozikin, Muhammad Titin Wahyuni Wafa, Moh. Shohibul Zaqiyah, Arfatuz