Article Per Year (5 Year)
p-Index From 2021 - 2026
4.865
P-Index
This Author published in this journals
All Journal Journal of Mechanical Engineering Education (Jurnal Pendidikan Teknik Mesin) JURNAL MEDIA INFORMATIKA BUDIDARMA RELE: Rekayasa Elektrikal dan Energi Jurnal Teknik Elektro Pendas : Jurnah Ilmiah Pendidikan Dasar KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) Jurnal Maksipreneur: Manajemen, Koperasi, dan Entrepreneurship Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA Tunas Nusantara JPM: JURNAL PENGABDIAN MASYARAKAT Journal of Social Responsibility Projects by Higher Education Forum J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Masyarakat IPTEK COMMENT: Journal of Community Empowerment Jurnal Pengabdian Masyarakat Inovasi Prosiding University Research Colloquium Journal of Computing and Informatics Research Ranah Research : Journal of Multidisciplinary Research and Development JPNM : Jurnal Pustaka Nusantara Multidisiplin Journal of Informatics, Electrical and Electronics Engineering Konsensus: Jurnal Ilmu Pertahanan, Hukum dan Ilmu Komunikasi ORAHUA : Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Multidisiplin Journal Pesona Indonesia Jurnal Cendekia Ilmiah Jurnal Pengabdian Kader Bangsa Journal of Decision Support System Research
Imam Saputra
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 51 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 51 Documents
Search

 2   3   4   5   6 
ANALISA PERBANDINGAN ALGORITMA PREFIX CODE DENGAN ALGORITMA BURROWS-WHEELER TRANSFORM DALAM KOMPRESI FILE VIDEO Hardianti, Putri Delfi; Saputra, Imam; Aripin, Soeb
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 9 No. 04 (2024): Volume 09, No. 04 Desember 2024
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v9i4.17912

Abstract

A video file is a type of file recorded or stored in a digital format that contains visual and audio data, including moving images, sound, and text. The large size of video files often causes issues in storage and data transmission, especially for long-duration videos. Storage media such as Google Drive and cloud storage are used to address storage space needs, but these solutions are often not efficient enough. Therefore, data compression techniques are required to reduce file size without losing important information. To address this issue, this research implements two data compression algorithms: Prefix Code and Burrows-Wheeler Transform. The Prefix Code algorithm uses a unique binary encoding method for each symbol in the data, while the Burrows-Wheeler Transform performs a text data transformation to produce repetitive patterns that are easier to compress. The aim of this research is to compare the effectiveness of these two algorithms in compressing video files, focusing on the parameters of Compression Ratio (CR), Ratio of Compression (RC), and Space Saving (SS). The results indicate that both algorithms are effective in compressing video files. However, a comparison between the algorithms shows significant differences in compression performance. The Prefix Code algorithm proves to be more efficient in reducing file size without compromising data quality, while the Burrows-Wheeler Transform algorithm shows advantages in maintaining data integrity during the transformation process. This analysis provides deeper insights into the effectiveness of both algorithms and can assist in choosing the most appropriate compression technique for video files.
PENGENALAN POLA BUNGA BERBASIS CITRA MENGGUNAKAN JARINGAN SARAF TIRUAN DENGAN ALGORITMA PERCEPTRON Fahrezi, Azrial; Saputra, Imam; Siregar, Annisa Fadillah
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 9 No. 04 (2024): Volume 09, Nomor 04, Desember 2024
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v9i04.18128

Abstract

Flowers are transformations of buds, including stems and leaves, with shapes and colors adapted to the plant's functions. They also serve as sites for fertilization and pollination. Flowers come in various shapes and colors, with over 250,000 flowering plant species known and classified into 350 families. Therefore, employing technology for flower pattern recognition is crucial for enhancing accuracy and efficiency. One effective method involves using Artificial Neural Networks (ANN) in conjunction with the perceptron algorithm. This algorithm has proven effective in image-based pattern recognition due to its ability to learn complex and linear patterns from image data. This study explores the use of neural networks, specifically the perceptron method, in recognizing flower patterns. The test utilizes sunflower image samples, with the perceptron algorithm applied to produce accurate and effective data in flower pattern recognition.
IMPLEMENTASI JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI TINGKAT PRODUKSI JAGUNG GILING MENGGUNAKAN METODE BACKPROPAGATION (STUDI KASUS: MIKRA MAKMUR BERSAMA) Aritonang, Reza Sri Rezeki; Saputra, Imam; Siregar, Annisa Fadillah
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 9 No. 04 (2024): Volume 09, Nomor 04, Desember 2024
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v9i04.18160

Abstract

This study aims to implement Artificial Neural Networks (ANN) to predict corn flour production levels at the agricultural company Mikra Makmur Bersama using the backpropagation learning method. As a machine learning technique, ANN has the potential to enhance prediction accuracy by effectively analyzing historical data. Data on corn flour production from 2021 to 2023 was collected from the company and used to train the ANN model with a backpropagation architecture. This process involves feedforward and backward propagation to optimize neuron weights, aiming to produce accurate and reliable predictions. The backpropagation algorithm updates weights based on prediction errors and can adapt to complex patterns in the data. The results show that the implemented ANN model successfully predicted corn flour production levels with significant accuracy, as tested with data from 2021 to 2023. This study is expected to serve as a reference for applying ANN technology in other agricultural sectors and encourage the use of advanced methods to enhance efficiency and productivity.
Fenomenal Keniasaan Masyarakat Akan Sampah Imam Saputra; Marselino Clifer Tuju; Muhammad Rizkan Abdul Aziz; Tamaulina Br.sembiring
Jurnal Ilmiah Multidisipin Vol. 2 No. 1 (2024): Jurnal Ilmiah Multidisiplin, Januari 2024
Publisher : Lumbung Pare Cendekia

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

Abstract

Sampah adalah suatu hal yang akan selalu ada dalam kehidupan sehari-hari manusia. seluruh yang memiliki aktivitas pasti akan membentuk sampah, begitu pula dengan medan krio kab. Deli Serdang. konflik dari penelitian ini ialah kurangnya pencerahan masyarakat setempat dalam membuang sampah pada tempatnya serta pengelolaan sampah yg belum dikatakan baik dan krangnya tempat pembuangan sampah pada wilayah tadi. Adapun tujuan penelitian ini untuk mengetahui mengenai keberadaan Tempat Pembuangan Sampah (TPS) di sembarang kawasan serta menganalisis dampak eksistensi TPS diwilayah tersebut. Selain dari itu juga untuk mengetahui sistem pengolahan sampah di desa tersebut. Metode penelitian yang dilakukan artinya penelitisn secara kualitatif dengan observasional deskriftif . Teknik penelitian yg dilakukan ialah dengan cara informasi lapangan lapangan serta wawancara pribadi dengan beberapa rakyat dan juga menggunakan dinas kebersihan. akibat penelitian menyatakan bahwa pengelolaan sampah pada wilayah medan krio masih kurang baik hal ini dikarenakan kurangnya pencerahan warga tersebut pada membuang sampah di tempatnya serta jua masih kurangnya tempat pembuangan sampah dan jua kurangnya kesadaran para waga pada mengelola smapah yang baik dan sahih. Adapun saran yg diberukan artinya menggunakan mengadakan sosialisasi buat menumbuhkan pencerahan para rakyat dalam mengelola sampah yg baik.
Pemanfaatan Sampah Plastik Menjadi Produk Bernilai: Studi Program Mahasiswa KKN Universitas Muhammadiyah Mataram Desa Pakuan M. Fazriansyah; Astuti, Astuti; Ranmadina Ratu Syahada; Razita Sabrina Irdani; Imam Saputra
J-CEKI : Jurnal Cendekia Ilmiah Vol. 5 No. 1: Desember 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v5i1.12433

Abstract

Permasalahan sampah plastik merupakan tantangan lingkungan global yang kian mendesak, termasuk di Indonesia yang menghasilkan jutaan ton sampah plastik setiap tahunnya. Artikel ini membahas implementasi program Plang Ecobrick oleh mahasiswa Kuliah Kerja Nyata (KKN) Universitas Muhammadiyah Mataram di Desa Pakuan, Kabupaten Lombok Barat, sebagai model pengelolaan sampah berbasis masyarakat. Penelitian ini menggunakan pendekatan kualitatif deskriptif untuk menggambarkan proses, dampak, serta tantangan pemanfaatan ecobrick sebagai solusi alternatif pengolahan sampah plastik. Hasil penelitian menunjukkan bahwa program ini mampu meningkatkan kesadaran ekologis masyarakat, mendorong perubahan perilaku dalam pengelolaan sampah, serta menciptakan produk fungsional bernilai ekonomi. Kegiatan ecobrick terbukti memperkuat kapasitas lokal melalui pelatihan partisipatif dan keterlibatan aktif warga, terutama kelompok ibu rumah tangga dan pemuda desa. Namun demikian, keberlanjutan program masih menghadapi kendala seperti rendahnya partisipasi pasca-program dan minimnya dukungan kelembagaan. Oleh karena itu, dibutuhkan penguatan kelembagaan lokal dan integrasi kebijakan desa agar inisiatif ini dapat berkembang menjadi strategi pengelolaan sampah yang mandiri, berkelanjutan, dan replikatif di wilayah lain
Analisis Sentimen Kinerja Lembaga Legislatif di Indonesia Menggunakan Algoritma Random Forest Berbasis Data Media Sosial X Saputra, Imam; Rahim, Robbi
TIN: Terapan Informatika Nusantara Vol 5 No 10 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i10.7133

Abstract

Legislative institutions such as the DPR RI are often the center of public attention and criticism on social media, particularly the X platform (formerly Twitter). The high volume of public opinion necessitates an automated classification system to monitor public perception efficiently. This study aims to analyze public sentiment towards the DPR RI in January 2025 using the Random Forest algorithm. A total of 699 tweets were collected via crawling techniques and processed through preprocessing stages including cleansing, folding, normalization, filtering, and stemming. Text features were extracted using the Term Frequency-Inverse Document Frequency (TF-IDF) method. Distribution results show a dominance of the neutral class (73.5%), followed by negative (22.2%) and positive (4.3%) sentiments. Model testing using a confusion matrix demonstrates that the Random Forest algorithm achieves high performance with an accuracy rate of 96.43%. Feature importance analysis reveals that profanity and integrity issues such as "corruption" are the primary indicators of negative sentiment. This study concludes that Random Forest is highly reliable in classifying public opinions with strong emotional polarity on social media.
Pengaruh Kebijakan Green Finance terhadap Nilai Perusahaan dengan Profitabilitas Sebagai Variabel Mediasi pada Perusahaan Manufaktur Sektor Barang Konsumsi yang Terdaftar di BEI Periode 2022–2024 Saputra, Imam; Cindiyasari, Shiwi Angelica; Muhammad, Mahatir
Jurnal Maksipreneur Vol 15 No 1 (2025)
Publisher : Universitas Proklamasi 45

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30588/jmp.v15i1.2566

Abstract

This study aims to analyze the impact of green finance policies on the business value of manufacturing companies active in the consumer goods sector and listed on the Indonesia Stock Exchange during the period 2022 to 2024. In this study, profitability is used as an intermediary variable. The analysis was performed using panel data regression and the Sobel test, with support from EViews 12 software. The results show that green finance policies can increase profitability and firm value. Furthermore, the data show that profitability contributes to increasing firm value and acts as a mediator between green finance policies and firm value. This study confirms that green finance improves financial performance and market perception while demonstrating a commitment to environmental sustainability.
Digital Signature Schemes: A Thematic Evolution from RSA/ECC to Post-Quantum and Aggregate Signatures (2015-2022) Saputra, Imam; Mesran, Mesran
Journal of Computing and Informatics Research Vol 4 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v4i1.975

Abstract

This study aims to map and quantify the thematic evolution of Digital Signature Schemes (DSS) amid the existential challenge posed by quantum computing and the increasing demand for application efficiency in Internet of Things (IoT) and Blockchain environments. Historically dominated by RSA and Elliptic Curve Cryptography (ECC), DSS now faces a significant turning point. A systematic bibliometric analysis was conducted on 2,616 documents indexed by Scopus during the 2015–2022 period, involving the analysis of Annual Scientific Production, Social Structure, and Conceptual Structure mapping using a Thematic Map. The results confirm a thematic turning point marked by a sharp acceleration in publication volume (Compound Annual Growth Rate 14.5%, peaking at 25.1% in 2020–2022), which aligns with the commencement of the Post-Quantum Cryptography (PQC) standardization process by NIST. Social structure analysis indicates a divided global role: China dominates in raw output volume, while Western countries (US, Germany, UK) act as Intellectual Hubs with the highest citation impact per document. The strongest evidence of thematic evolution is found in the Thematic Map, which empirically classifies "ECC" as a mature Motor Theme, while "Dilithium," "Lattice-based Cryptography," and "Post-Quantum Cryptography" emerge as Emerging Themes. Concurrently, "Aggregate Signature" and "Ring Signature" are identified as specialized Niche Themes. In synthesis, this study proves that the evolution of DSS is simultaneously driven by two primary factors: the external threat (quantum) and internal demands (efficiency and scalability). The findings provide a quantitative roadmap urging the global cybersecurity community to prioritize the transition to PQC standards immediately to ensure the resilience of future public key infrastructure
Peningkatan Kompetensi Guru dalam Pemanfaatan Teknologi Kecerdasan Buatan sebagai Penunjang Media Pembelajaran di Sekolah Alam Saputra, Imam; Wardayani, Wardayani; Sari, Dian Purnama; Supriyanto, Supriyanto; Hidayat, Rahmat
JPM: Jurnal Pengabdian Masyarakat Vol. 6 No. 3 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v6i3.2920

Abstract

The rapid development of Artificial Intelligence (AI) technology requires educators to possess adaptive digital literacy to enhance the quality of learning. This international community service project aims to improve the competence of teachers at Sekolah Alam Istana Hati Binjai in utilizing AI technology as a supporting instrument for learning media. The initiative was spearheaded by the ADA Research Center through strategic collaboration with Universiti Utara Malaysia (UUM), the Indonesian Institute of Technology and Business, and various other supporting higher education institutions. The method employed was Collaborative Community Engagement, featuring intensive workshops and personalized hands-on mentoring for 16 teachers across elementary, junior high, and senior high school levels. The training focused on understanding AI ethics, prompt engineering, and the creation of automated visual learning media. The results demonstrated a significant increase in the participants' digital literacy, with the average evaluation score rising from 48.5 to 86.0. All participants (100%) successfully produced digital learning media relevant to the nature school curriculum. The discussion in this article highlights that cross-country collaboration provides global motivation for local educators to adopt technology without abandoning environment-based educational philosophies. It is concluded that strengthening AI literacy for teachers is a crucial step in minimizing the digital divide and improving the efficiency of educational administration at the nature school level
Peningkatan Kreativitas Siswa SMK Melalui Pengenalan Dasar Digital Marketing Berbasis AI Siregar, Dodi; Rahayu, Sri; Saputra, Imam; Sari, Dian Purnama; Sari, Vina Winda
Jurnal Pengabdian Masyarakat Inovasi Vol. 5 No. 1 (2026): February 2026
Publisher : Sekolah Tinggi Ilmu Manajemen Sukma Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35126/jpmi.v5i1.1000

Abstract

This community service program aimed to enhance the creativity of vocational high school students through the introduction of basic artificial intelligence (AI)-based digital marketing. The implementation method included literature review, partner needs assessment, and hands-on training involving 20 participants. The results revealed a significant improvement in participants’ understanding, where initially 80% were categorized as low, but after the training, 60% were categorized as good. Satisfaction responses also indicated that most participants felt satisfied or highly satisfied with the materials and delivery methods. This program demonstrates that introducing AI-based digital marketing can serve as an effective approach to foster 21st-century skills among vocational school students. However, the limitation of this activity lies in its short duration, which restricted the coverage of advanced materials, yet it provides a strong foundation for future community service initiatives.
Co-Authors A.A. Ketut Agung Cahyawan W A.N. Afandi Abdul Karim Adiguna, Satria Agung Dwi Pradana Aguswinaya, Agung Rake Ahmad Tamrin Sikumbang Al-Adawiyah, Robiah Alfarisi Pasaribu, Ahmad Amalia, Dira Amelia Ramadhani Annisa Fadillah Siregar Anugrah, Elfira Aripriharta - Ariska, Melinda Aritonang, Reza Sri Rezeki Aryadito, Rehan Ayulia Sari Azlan Azlan, Azlan Bagaskoro, Muhammad Cahyo Berkah Mutiara Bilal Abdul Aziz Darma Taksiah Sihombing, Darma Taksiah Dendi Bianda Saputra Dian Oktarina Dian Purnamasari Dina Octavia Dito Putro Utomo Dodi Siregar Erna Verawati Fadlina Fahrezi, Azrial Fince Tinus Waruwu Ginting, Suranta Bill Fatric Gokma Lumbantoruan Guidio Leonarde Ginting Gultom, Istanto Hardianti, Putri Delfi Harianja, Chindy Lorenza Hery Sunandar Hetty Rohayani Hondro, Piter Saputra Indra Williamsyah Sinaga Ira Sagita Jariah, Nur Ainun Juwita Indah Sari Lemcia Hutajulu Lubis, Adi Mora M. Fazriansyah Maimunah, M Mariansari Mariansari Marliana Marliana, Marliana Marselino Clifer Tuju Marsya Reskiani Lole Martina Vevi Yanti Matondang, Firman MAURITZ PANDAPOTAN MARPAUNG Mesran, Mesran Muhammad Afnan Habibi Muhammad Afriansyah Muhammad Resa Arif Yudianto Muhammad Rizkan Abdul Aziz Muhammad Syahrizal Muhammad, Mahatir Nasib Marbun Nastiti, Sindy Ndruru, Eferoni Nelly Astuti Hasibuan Nur Afifah Siregar, Rizka Nur Syifa’ul Alyah Panggabean, Riski Melisa Putri Picaso Azury Sheva Putri Ramadhani, Putri Rahmat Hidayat Rahmawaty Rahmawaty Rahmawaty Raimah Handayani Harahap Ranmadina Ratu Syahada Rasyid, Irfan Razita Sabrina Irdani Ritonga, Fitri Aisyah Rivalri Kristianto Hondro Robbi Rahim Robinson Siagian, Edward Rohmat Indra Borman Sahrul Saputra Saidi Ramadan Siregar Sania Kolopaking Saputra, Febrian Eko Sari, Sri Indah Setiawan, Aditya Wahyu Shely Junian Permata Shiwi Angelica Cindiyasari Simanullang, Putri M Simanungkalit, Lidya Indah Pratama Sinurat, Sinar SRI RAHAYU Suginam Sultan Rexy Adji Suparwatini Suparwatini Surya Darma Nasution Suryanegara, Raden Kartika Satya Sussolaikah, Kelik Syafruddin Syafruddin Tamaulina Br.Sembiring Tanjung, Dewi Maulida Sari Taronisokhi Zebua Tatang Permana, Tatang Utami, Nur Indah Vina Winda Sari Wardayani Wardayani, Wardayani Yusufa, Ilham Zainun, Zainun