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All Journal Diponegoro Journal of Accounting Jurnal Akuntansi dan Ekonomika Jurnal Indonesia Sosial Sains
Asep Rudi
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Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Energy Environmental Science Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Neuroscience Physics Social Sciences

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PENGARUH KOMPETISI PENGADAAN PUBLIK TERHADAP BELANJA PEMERINTAH (STUDI EMPIRIS PADA PUSAT LAYANAN PENGADAAN SECARA ELEKTRONIK KEMENTERIAN KEUANGAN) Asep Rudi; Haryanto Haryanto
Diponegoro Journal of Accounting Volume 2, Nomor 3, Tahun 2013
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (150.784 KB)

Abstract

This study is aimed to explore the impact of competition in public procurement on government expenditure. Using competitive bidding model adapted from previous research this study tries to analyze the effect of competition in terms of number, distance and net assets of bidders and project size on construction cost. Using data on e-tenderring process of 50 construction projects in the e-procurement unit in Ministry of Finance, linear regression analysis proves that under competitive e-tenderring process number and net assets of bidders and project size negatively effect construction cost. However, the distance of bidders has no effect on construction cost. This study also proves that those variables simultaneously effect costruction cost. This results then show that competition in public procurement negatively effects government expenditure.
Classification of Wayang Kulit Using Canny Feature Extraction and Convolutional Neural Network Algorithm Rudi, Asep; Ibnu Adam, Riza
Jurnal Indonesia Sosial Sains Vol. 6 No. 5 (2025): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v6i5.1627

Abstract

Wayang kulit is a part of Indonesian culture known to the Javanese people, but the younger generation often has difficulty recognizing the wayang characters they are looking for online because of inaccurate search results. One popular story is the Mahabharata, with the characters of the Five Pandavas: Puntadewa (Yudistira), Bima, Arjuna, Nakula, and Sadeva. Because puppet characters have similar shapes, curves, clothing, and colors, it is often difficult to distinguish and remember. This shows the need for technology to help recognize puppet characters more easily. This research aims to solve this problem by utilizing Deep Learning techniques in Computer Vision to classify puppet images. Canny's feature extraction technique and DenseNet-121 architecture are used to detect patterns in the puppet image and classify them into appropriate categories. The dataset used consisted of 1028 images divided into four categories: Arjuna, Bima, Nakula & Sadewa, and Puntadewa. The framework implemented is CRISP-DM, with the implementation using the Python 3.11 programming language, TensorFlow 2.14, and the Google Colab tool. The results of the model evaluation through the confusion matrix showed 93% accuracy, 93% precision, 93% recall, and 92% f1 score. With these results, it is hoped that technology can facilitate and increase accuracy in recognizing the character of puppet puppets.
Classification of Wayang Kulit Using Canny Feature Extraction and Convolutional Neural Network Algorithm Rudi, Asep; Ibnu Adam, Riza
Jurnal Indonesia Sosial Sains Vol. 6 No. 5 (2025): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v6i5.1627

Abstract

Wayang kulit is a part of Indonesian culture known to the Javanese people, but the younger generation often has difficulty recognizing the wayang characters they are looking for online because of inaccurate search results. One popular story is the Mahabharata, with the characters of the Five Pandavas: Puntadewa (Yudistira), Bima, Arjuna, Nakula, and Sadeva. Because puppet characters have similar shapes, curves, clothing, and colors, it is often difficult to distinguish and remember. This shows the need for technology to help recognize puppet characters more easily. This research aims to solve this problem by utilizing Deep Learning techniques in Computer Vision to classify puppet images. Canny's feature extraction technique and DenseNet-121 architecture are used to detect patterns in the puppet image and classify them into appropriate categories. The dataset used consisted of 1028 images divided into four categories: Arjuna, Bima, Nakula & Sadewa, and Puntadewa. The framework implemented is CRISP-DM, with the implementation using the Python 3.11 programming language, TensorFlow 2.14, and the Google Colab tool. The results of the model evaluation through the confusion matrix showed 93% accuracy, 93% precision, 93% recall, and 92% f1 score. With these results, it is hoped that technology can facilitate and increase accuracy in recognizing the character of puppet puppets.
Analisis Efektivitas Tata Kelola Administrasi Realisasi APBN di Kanwil DJPb Riau Tahun 2026 Sinaga, Pandu Hidayat; Ramadhan, Rian Rahmat; Zaki, Hammam; Rahayu, Norra Isnasia; Rudi, Asep
Akuntansi & Ekonomika Vol 16 No 1 (2026): Jurnal Akuntansi dan Ekonomika
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jae.v16i1.11368

Abstract

This study aims to analyze the effectiveness of administrative governance in APBN realization at the Regional Office of the Directorate General of Treasury (Kanwil DJPb) of Riau Province. The study employed a descriptive qualitative approach using in-depth interviews and document reviews as data collection techniques. The findings indicate that the administrative governance of APBN realization at the Riau Regional Office of DJPb has been implemented quite effectively, although it has not fully achieved the established performance targets. The main obstacles include coordination issues among work units, technical disruptions in the financial information system, and regulatory changes. The effectiveness of administrative governance is influenced by the quality of the reporting system, the competence of personnel, and adequate information technology support. This study recommends enhancing human resource capacity, strengthening digital infrastructure, and optimizing coordination among work units in Riau Province.
Co-Authors Haryanto Haryanto Ibnu Adam, Riza Rahayu, Norra Isnasia Ramadhan, Rian Rahmat Sinaga, Pandu Hidayat Zaki, Hammam