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All Journal Jurnal Ilmu Komputer dan Informasi JOIN (Jurnal Online Informatika) Martabe : Jurnal Pengabdian Kepada Masyarakat Edunesia : jurnal Ilmiah Pendidikan Community Empowerment Ekalaya : Jurnal Ekonomi Akuntansi
Prasetyo, Deny
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Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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The Influence of the Board of Commissioners, Institutional Ownership, and Managerial Ownership on the Firm Value of Non-Banking State-Owned Enterprises Prasetyo, Deny; Kufepaksi, Mahatma; Dalimunthe, Nindytia Puspitasari
EKALAYA : Jurnal Ekonomi Akuntansi Vol. 3 No. 1 (2025): Ekalaya : Jurnal Ekonomi Akuntansi
Publisher : CV. Kalimasada Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59966/ekalaya.v3i1.1743

Abstract

This study examines the influence of corporate governance mechanisms—specifically the Board of Commissioners, Institutional Ownership, and Managerial Ownership-on the firm value of non-banking state-owned enterprises (SOEs) listed on the Indonesia Stock Exchange from 2014 to 2023. Using a panel data regression model based on purposively selected samples of 15 firms over a ten-year period, the results indicate that while institutional and managerial ownership significantly enhance firm value, the size of the board of commissioners does not exert a statistically significant effect. The findings highlight the importance of active monitoring by institutional investors and alignment of managerial interests with shareholders in improving corporate performance. These insights contribute to understanding effective governance practices in SOEs and offer practical recommendations for policy-makers aiming to enhance transparency and accountability within Indonesian state-owned enterprises.
Short Message Service Encoding Using the Rivest-Shamir-Adleman Algorithm Prasetyo, Deny; Widianto, Eko Didik; Indasari, Ike Pratiwi
JOIN (Jurnal Online Informatika) Vol 4 No 1 (2019)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v4i1.264

Abstract

SMS (Short Message Service) is one of the data exchange features in cellphones, including Android smartphones, which are the most widely used smartphone platforms today. However, the security of the SMS is questionable because the message sent must pass through a third party frist, namely SMSC (Short Message Service Center), so that message can be tapped or misused. One of the ways to reduce this risk is to encrypt or keep the original message secret by applying the cryptography algorithm. This research is to develop a system that serves to encrypt and decrypt SMS for Android-based smartphone users. The application is created to encrypt dan decrypt SMS using the Java programming language on Android, that is applied to smartphone integrated with Android Studio and used RSA cryptography algorithm. The application can be used to encrypt and decrypt SMS using the RSA algorithm on the Android-based smartphone. This application can send an SMS with a size of 86 characters and using QR Code to exchange the public key.
Digital post-harvest transformation: Implementing IoT-based grain drying to enhance farmer welfare in Ngarum Village Mar’atullatifah, Yulaikha; Iswavigra, Dwi Utari; Wicaksono, Nicky Gilang; Prasetyo, Deny; Suyahman, Suyahman; Wicaksono, Ardy; Mursalim, Mursalim; Mahmudah, Himmatunnisak; Mustofa, Mustofa; Faruq, Muhamad; Puspasari, Novela Putri
Community Empowerment Vol 10 No 11 (2025)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Ngarum Village has a significant grain production potential of 43,459 tons per year, yet farmers face challenges with traditional drying processes that are vulnerable to sudden weather changes. This condition often leads to degraded grain quality and lower market prices. This community service program aims to increase productivity and economic value through the implementation of an Internet of Things (IoT)-based rain detection system. The methods include technical training, appropriate technology implementation, and continuous mentoring. Results indicate that IoT technology successfully maintains grain moisture at an optimal level of 14%, reduces post-harvest losses by 10%, and achieves an 80% adoption rate among farmers. Furthermore, the digitalization of farm management has increased the grain's selling price by 10%. The application of this technology has proven effective in improving post-harvest efficiency, enhancing harvest data accountability, and supporting sustainable farmer welfare.
PENERAPAN PERANGKAT LUNAK PYTHON UNTUK MENINGKATKAN KOMPETENSI ANALISIS DATA DALAM KEGIATAN RISET MAHASISWA Dwi Setiawan, Very; Utari Iswavigra, Dwi; Ulfa, Mutia; Anggiratih, Endang; Dwi Yulianto, Bagas; Praningki, Tutus; Suyahman, Suyahman; Wicaksono, Ardy; Mar'atullatifah, Yulaikha; Prasetyo, Deny; Mursalim, Mursalim
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 9, No 2 (2026): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v9i2.%p

Abstract

Perkembangan teknologi informasi menuntut mahasiswa memiliki kompetensi analisis data yang memadai untuk mendukung kegiatan riset akademik. Namun, kenyataannya masih banyak mahasiswa yang mengalami keterbatasan dalam pemanfaatan perangkat lunak analisis data berbasis komputasi dan cenderung bergantung pada aplikasi spreadsheet sederhana. Kegiatan Pengabdian kepada Masyarakat ini bertujuan untuk meningkatkan kompetensi analisis data mahasiswa melalui penerapan perangkat lunak Python dalam kegiatan riset. Pelatihan dilaksanakan di Universitas Islam Batik Surakarta melalui kolaborasi antara Program Studi Teknik Industri Universitas Batik Surakarta dan Program Studi Teknik Industri Universitas Nahdlatul Ulama Jepara. Metode yang digunakan adalah pelatihan berbasis praktik langsung (hands-on training) yang meliputi pengenalan dasar pemrograman Python, pengolahan dan preprocessing data, serta visualisasi data penelitian menggunakan pustaka Pandas, NumPy, Matplotlib, dan Seaborn. Evaluasi kegiatan dilakukan melalui pre-test dan post-test untuk mengukur peningkatan kompetensi peserta. Hasil evaluasi menunjukkan peningkatan yang signifikan pada seluruh aspek kompetensi, termasuk pemahaman konsep dasar Python, kemampuan pengolahan dan pembersihan data, keterampilan visualisasi data, serta pemanfaatan Python dalam penyusunan laporan penelitian. Peningkatan nilai post-test yang lebih tinggi dibandingkan pre-test mengindikasikan bahwa pendekatan pelatihan yang diterapkan efektif dalam meningkatkan literasi komputasional dan kualitas analisis data mahasiswa. Kegiatan ini berkontribusi positif terhadap peningkatan mutu riset mahasiswa serta mendorong pemanfaatan perangkat lunak open-source dalam lingkungan akademik. Pelatihan ini juga berpotensi menjadi model Pengabdian kepada Masyarakat yang berkelanjutan dalam pengembangan kompetensi analisis data di perguruan tinggi.
Traditional Batik Pattern Recognition with MobileNetV2 and Sampling-Based Hyperparameter Optimization Suyahman; Saut Parulian, Onesinus; Prasetyo, Deny; Anwar Fauzi, Muhammad
Jurnal Ilmu Komputer dan Informasi Vol. 19 No. 1 (2026): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Informatio
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21609/jiki.v19i1.1597

Abstract

Batik holds significant cultural value in Indonesia, reflecting the nation's historical and artistic heritage through its intricate patterns. Preserving these designs is essential for maintaining cultural identity and supporting artistic and economic communities. With the advancement of technology, deep learning has emerged as an effective approach for recognizing and classifying batik patterns. Convolutional Neural Networks (CNNs), particularly MobileNetV2, are widely recognized for their efficiency and accuracy in image classification. However, the performance of deep learning models is highly influenced by hyperparameter selection, which remains a challenging task. This study investigates the effectiveness of MobileNetV2 in classifying traditional Indonesian batik motifs, including Kawung, Mega Mendung, Parang, and Truntum, by applying different hyperparameter optimization methods such as Treestructured Parzen Estimator (TPE), Gaussian Process Sampler (GPS), Grid Search, and Random Search. The experimental results show that TPE achieved the best overall performance with a test accuracy of 91.94% and an F1 score of 92.09%. GPS and Grid Search obtained identical test accuracy of 90.83% with F1 scores of 90.89% and 90.87%, respectively, while Random Search produced the lowest performance with an accuracy of 88.61% and F1 score of 88.61%. These findings highlight the importance of structured hyperparameter optimization, particularly TPE, in enhancing the robustness of CNN-based batik classification. The results provide valuable insights for the development of automated batik pattern recognition systems that support cultural heritage preservation and related image classification applications.
Principal Innovation in Managing Budgetary Autonomy: Evidence from a Narrative Review Using the Saber Framework Shofiyah, Faridatus; Sumarni, Sri; Saputro, Ardiyan Eko; Puspitasari, Vinda; Prasetyo, Deny
Edunesia : Jurnal Ilmiah Pendidikan Vol. 7 No. 2 (2026)
Publisher : Research, Training and Philanthropy Institution Natural Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51276/edu.v7i2.1642

Abstract

Vocational education in Indonesia has transformed the implementation of budgetary autonomy in vocational high schools (SMKs), requiring principals to manage resources strategically and accountably. However, most studies emphasise administrative compliance with funding regulations, and few synthesize principals' innovation within the School Autonomy and Accountability (SABER) framework. This study analyses principals' innovation strategies in managing SMK budgetary autonomy via a narrative literature review. Twelve articles (2022–2025) were thematically synthesized. Findings show three dominant innovation patterns: revenue diversification through internal business units such as BLUD and teaching factories; financing efficiency via strategic industry partnerships; and strengthened accountability through digital internal control systems. These innovations suggest that effective budgetary autonomy depends less on funding magnitude and more on principals' entrepreneurial leadership capacity to balance autonomy with strict accountability. The study contributes a conceptual synthesis of SABER in vocational contexts and recommends capacity-building for principals and adaptive regulatory measures to support innovation, particularly in remote and resource-constrained settings, for wider validation.
Co-Authors Anggiratih, Endang Anwar Fauzi, Muhammad Bagas Dwi Yulianto Dalimunthe, Nindytia Puspitasari Eko Didik Widianto Faruq, Muhamad Indasari, Ike Pratiwi Iswavigra, Dwi Utari Mahatma Kufepaksi Mahmudah, Himmatunnisak Mar'atullatifah, Yulaikha Mar’atullatifah, Yulaikha Mursalim Mursalim Mustofa Mustofa Puspasari, Novela Putri Puspitasari, Vinda Saputro, Ardiyan Eko Saut Parulian, Onesinus setiawan, very dwi Shofiyah, Faridatus Sri Sumarni Suyahman Suyahman ulfa, mutia Utari Iswavigra, Dwi Wicaksono, Ardy Wicaksono, Nicky Gilang