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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.
Sentiment Analysis of Tokopedia Customer Reviews using IndoBERT and SMOTE for Class Imbalance Handling Saputra, Imam; Mesran, Mesran; Ginting, Guidio Leonarde
Journal of Computer System and Informatics (JoSYC) Vol 7 No 1 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v7i1.8748

Abstract

Sentiment analysis in the Indonesian e-commerce sector faces significant challenges due to the informal nature of language and severe class imbalance, where neutral reviews are often underrepresented. This research proposes a hybrid framework combining the deep semantic capabilities of IndoBERT with the Synthetic Minority Over-sampling Technique (SMOTE) to improve classification fairness. Using a dataset of Tokopedia customer reviews, this study compares a baseline model against a balanced model using SMOTE on 768-dimensional IndoBERT features. The experimental results reveal that while the baseline model achieved a high overall accuracy of 83%, it suffered from an "accuracy paradox," exhibiting a dismal recall of only 0.07 for the neutral class. Upon implementing SMOTE, the neutral class recall surged to 0.29, marking a significant 314% improvement in minority class detection. Although overall accuracy slightly decreased to 81%, the Macro Average F1-Score increased from 0.61 to 0.65, proving that the model is more robust and objectively reliable across all sentiment polarities. This study demonstrates that sacrificing marginal accuracy for improved minority sensitivity is vital for providing accurate business intelligence in the digital marketplace. These findings provide a robust roadmap for developing more equitable automated sentiment analysis systems in Indonesia.
Co-Authors A.A. Ketut Agung Cahyawan W A.N. Afandi Abdul Karim Adiguna, Satria Afriansyah, Muhammad Agung Dwi Pradana Aguswinaya, Agung Rake Ahmad Tamrin Sikumbang Al-Adawiyah, Robiah Alfarisi Pasaribu, Ahmad Amalia, Dira Amelia Ramadhani, Amelia Annisa Fadillah Siregar Anugrah, Elfira Aripriharta - Ariska, Melinda Aritonang, Reza Sri Rezeki Aryadito, Rehan Astuti - Ayulia Sari Azlan Azlan, Azlan Bagaskoro, Muhammad Cahyo Bilal Abdul Aziz Darma Taksiah Sihombing, Darma Taksiah 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 Guidio Leonarde Ginting Gultom, Istanto Hardianti, Putri Delfi Harianja, Chindy Lorenza Hery Sunandar Hetty Rohayani Hondro, Piter Saputra Indra Williamsyah Sinaga Jariah, Nur Ainun Kolopaking, Sania Lemcia Hutajulu Lole, Marsya Reskiani Lubis, Adi Mora M. Fazriansyah Maimunah, M Mariansari, Mariansari Marliana Marliana, Marliana Marselino Clifer Tuju Matondang, Firman MAURITZ PANDAPOTAN MARPAUNG Mesran, Mesran Muhammad Afnan Habibi Muhammad Resa Arif Yudianto Muhammad Rizkan Abdul Aziz Muhammad Syahrizal Muhammad, Mahatir Mutiara, Berkah Nasib Marbun Nastiti, Sindy Ndruru, Eferoni Nelly Astuti Hasibuan Nur Afifah Siregar, Rizka Nur Syifa’ul Alyah Oktarina, Dian Panggabean, Riski Melisa Permata, Shely Junian Pohan, Ferdi 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 Sagita, Ira Sahrul Saputra Saidi Ramadan Siregar Saputra, Dendi Bianda Saputra, Febrian Eko Sari, Juwita Indah Sari, Sri Indah Setiawan, Aditya Wahyu Sheva, Putri Picaso Azury Shiwi Angelica Cindiyasari Simanullang, Putri M Simanungkalit, Lidya Indah Pratama Sinurat, Sinar SRI RAHAYU Suginam Sultan Rexy Adji Suparwatini, Suparwatini Supriyanto Supriyanto Surya Darma Nasution Suryanegara, Raden Kartika Satya Sussolaikah, Kelik Syafruddin Syafruddin Tamaulina Br.Sembiring Tanjung, Dewi Maulida Sari Taronisokhi Zebua Tatang Permana, Tatang Tua, Rahmat Utami, Nur Indah Vina Winda Sari Wardayani Wardayani, Wardayani Yanti, Martina Vevi Yusufa, Ilham Zainun, Zainun