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All Journal TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Anterior Jurnal J-SAKTI (Jurnal Sains Komputer dan Informatika) PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Bitnet: Jurnal Pendidikan Teknologi Informasi JURNAL TEKNIK Jurnal Sains Komputer dan Teknologi Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Scientific Journal of Informatics
Setio Ardy Nuswantoro
Universitas Muhammadiyah Palangkaraya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences

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Journal : Anterior Jurnal

 1 
Implementasi dan Efektivitas E-Government dalam Meminimalisasi Penyebaran Covid-19 di Era New Normal Nur Azizah; Setio Ardy Nuswantoro
Anterior Jurnal Vol 21 No 1 (2021): Anterior Jurnal
Publisher : ​Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/anterior.v21i1.2787

Abstract

Sejak kasus pertama Covid-19 di Indonesia terjadi pada 2 Maret 2020 hingga 1 Agustus 2020, telah menginfeksi 111.455 orang positif, 5.236 orang meninggal dan tingkat kesembuhan 68.975 orang. Melihat data penyebaran Covid-19 yang semakin mengkhawatirkan, penting bagi masyarakat untuk menghindari pertemuan fisik dengan kontak langsung, pertemuan publik dan padatnya penggunaan transformasi umum dalam upaya mengantisipasi masyarakat yang terinfeksi virus mematikan ini. Sejak kebijakan new normal mulai diterapkan demi menjaga kestabilan ekonomi sembari menyelamatkan kesehatan masyarakat yang berdampak pada proses penyebaran virus corona semakin tidak bisa diprediksi. Masyarakat menerapkan akselerasi kebijakan pelayanan berbasis teknologi berbasis e-government. Tujuan dari penelitian ini adalah dengan penerapan e-government di era new normal seperti saat ini menjadi pilar penting dalam mengurangi atau meminimalisasi penyebaran covid-19, dengan melembagakan hak-hak publik dalam mengetahui kinerja dan akuntabilias badan-badan publik, sehingga dapat berimbas kepada terwujudnya good governance atau tata kelola pemerintahan yang baik di setiap daerah, dimana konsep ini terdiri dari adanya transparansi, akuntabilitas, partisipasi, efektif dan efisien, responsif, dan kepastian hukum.
Algoritma Deep Learning Untuk Pengenalan Gambar Jenis Daun: Deep Learning Algorithm for Leaf Type Image Recognition Azizah, Azizah; Nuswantoro, Setio Ardy; Jaya, Firman; Razaqi, Rahmat Shofan; Ansori, Ansori
Anterior Jurnal Vol. 23 No. 3 (2024): Anterior Jurnal
Publisher : ​Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/anterior.v23i3.8199

Abstract

Image processing is a branch of informatics that deals with transforming one image into another using certain techniques. Deep learning algorithms have become one of the effective approaches to solving this problem. In this paper, we propose a deep learning algorithm that uses Convolutional Neural Networks (CNN) architecture to recognize leaf types based on a given leaf image. We outline the main steps in model development, including data pre-processing, CNN architecture selection, and model training. The experimental results show that the proposed deep learning algorithm can achieve a high level of accuracy in leaf-type image recognition. In this study, the CNN method is used to identify and classify objects in digital images, specifically leaves. The dataset used consists of 33 leaf classes, with a division of 16,500 data for training, 3,300 for validation, and 1,650 for testing. The training and validation processes were carried out in as many as 150 epochs, which resulted in the highest accuracy of 94% with the lowest loss of 0.28. While in the testing process, the accuracy value obtained reached 84%. The researched method, which integrates CNN with data augmentation and transfer learning, demonstrated superior performance with an accuracy of 94% in leaf type recognition. This outperforms other methods that rely solely on traditional CNN or do not utilize augmentation and transfer learning, which generally achieve lower accuracy rates. The combination of these techniques enables more robust feature extraction and better generalization, leading to more accurate and reliable classification results compared to other approaches.
Transformasi Digital Dan Efektivitas Belajar: Pengembangan Sistem E-Learning Sebagai Arsitektur Pedagogis Baru Di SMA Muhammadiyah 2 Palangka Raya.: Digital Transformation and Learning Effectiveness: Development of an E-Learning System as a New Pedagogical Architecture at SMA Muhammadiyah 2 Palangka Raya Miftahurrizqi; Nuswantoro, Setio Ardy
Anterior Jurnal Vol. 25 No. 1 (2026): Anterior Jurnal
Publisher : ​Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

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

Abstract

The rapid development of information technology has significantly transformed the education sector, particularly in digital-based learning processes. This study aims to develop and implement a web-based e-learning system to support blended learning at SMA Muhammadiyah 2 Palangka Raya. The research employed a Research and Development (R&D) approach using the Waterfall model, consisting of analysis, design, implementation, testing, and evaluation stages. The system was tested by 10 teachers and 60 students as primary users. The results indicate that all system functions operated effectively based on Black Box Testing, with an effectiveness rate of 88.7% (categorized as very effective) and an average student learning improvement of 15.4%. The developed e-learning system is considered user-friendly, efficient, and capable of enhancing both teaching management and learning outcomes in secondary education.
Co-Authors Achiril Haq, Muhammad Ainun Jariah Azizah Azizah Bawi, Firdana Fathul Wahid Firman Jaya Ika Safitri Windiarti Junaedi, Ahyar Miftahurrizqi Miftahurrizqi, Miftahurrizqi Muhammad Rafli Muhammad Ulfi Nur Azizah Nur Azizah Prasetya, Pahdian Bagus Putro, Hanson Prihantoro Rafii, Mohamad Rashid, Reza Athallah Razaqi, Rahmat Shofan rusita rusita Sari, Chalsi Mala Solly Aryza Supriyanto, Muhammad Ibadurrahman Arrasyid Suriansyah, S Sutami, Sutami Ulfi, Muhammad Wisne, Marga Tri Nuche Ziaurrahman, M.