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All Journal Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika Wikrama Parahita : Jurnal Pengabdian Masyarakat JURNAL ILMIAH INFORMATIKA Journal Information System Development MATAPPA: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika UNIKA Santo Thomas Computer Based Information System Journal Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Jurnal Tekinkom (Teknik Informasi dan Komputer) MEANS (Media Informasi Analisa dan Sistem) Akrab Juara : Jurnal Ilmu-ilmu Sosial Innovation in Research of Informatics (INNOVATICS) Ar-Rasyid: Jurnal Pendidikan Agama Islam Journal Automation Computer Information System (JACIS) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Puan Indonesia Jurnal Sains Informatika Terapan (JSIT) Engineering and Technology International Journal (EATIJ) Jurnal PADI (Pengabdian mAsyarakat Dosen Indonesia) Jurnal Desain dan Analisis Teknologi JURSIMA Jurnal Sistem Informasi dan Manajemen Hanif Journal of Information Systems Applied Information Technology and Computer Science (AICOMS) Computer & Science Industrial Engineering Journal Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK) Tsabit
Simanjuntak, Pastima
Universitas Putera Batam
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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PELATIHAN PEMANFAATAN GENERATIVE ARTIFICIAL INTELLIGENCE UNTUK LITERASI DIGITAL MAHASISWA STIDKI AL-AZIZ BATAM Pastima Simanjuntak; Rika Harman; Yohanni Syahra; Herman Yuliansyah; Imam Riadi
PUAN INDONESIA Vol. 8 No. 1 (2026): Jurnal PUAN Indonesia Vol. 8 No. 1 Juli 2026
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v8i1.516

Abstract

The development of Generative Artificial Intelligence (AI) presents significant opportunities to support digital literacy and creativity in higher education. However, utilization of this technology among students still faces challenges, including limited understanding, technical skills, and ethical awareness. This community service activity was conducted on January 31, 2026, at STIDKI Al-Aziz Batam, involving 18 student participants from two study programs. The activity employed an educative-participatory approach comprising material presentations, interactive discussions, and hands-on practice sessions. Post-training evaluation was conducted using a Likert-scale questionnaire (scale 1-5) covering three dimensions: conceptual understanding, perceived benefits, and participant satisfaction. Results showed a mean score of 4.21 out of 5 (84.2%) for conceptual understanding of Generative AI, a mean perceived benefit score of 4.35 (87.0%), and an overall satisfaction score of 4.40 (88.0%). Furthermore, 88.9% of participants (16 of 18) met the minimum understanding threshold (score >= 4). These findings demonstrate that structured, practice based training significantly enhances students digital literacy competence and ethical awareness of AI use. The activity provides a tangible contribution to strengthening students digital capacities and is relevant for sustainable development.
Predicting Non-Performing Loan Levels Using XGBoost and Explainable Data Mining Pastima Simanjuntak; Rika Harman
Hanif Journal of Information Systems Vol. 3 No. 2 (2026): February Edition
Publisher : Ilmu Bersama Center

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

Abstract

Non-Performing Loans (NPLs) represent one of the most critical indicators in assessing the stability and financial health of banking institutions. An increasing NPL ratio may negatively affect profitability, liquidity, and overall banking performance, making accurate prediction models essential for effective credit risk management. This study proposes a predictive framework for estimating Non-Performing Loan levels using the Extreme Gradient Boosting (XGBoost) algorithm combined with Explainable Data Mining techniques. The dataset consists of historical banking and financial indicators that influence loan repayment behavior. Data preprocessing stages include data cleaning, feature selection, normalization, and handling of missing values to improve model performance. The XGBoost model was employed due to its ability to handle complex nonlinear relationships and high-dimensional data efficiently. To enhance model transparency and interpretability, Explainable Data Mining techniques based on SHapley Additive exPlanations (SHAP) were applied to identify the contribution and importance of individual features affecting NPL predictions. Experimental results demonstrate that the proposed XGBoost model achieves high predictive performance, outperforming conventional machine learning approaches in terms of accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). Furthermore, the explainability analysis reveals the most influential factors contributing to NPL levels, providing valuable insights for financial institutions and policymakers in developing proactive risk mitigation strategies. The findings indicate that integrating XGBoost with Explainable Data Mining not only improves prediction accuracy but also enhances the interpretability and trustworthiness of credit risk assessment models. This approach can support data-driven decision-making processes and strengthen the sustainability of banking operations in increasingly complex financial environments.
Analisis Komparatif Support Vector Machine dan Random Forest untuk Deteksi Email Phishing Indah Purnama Sari; Oris Krianto Sulaiman; Dicky Apdilah; Pastima Simanjuntak
Applied Information Technology and Computer Science (AICOMS) Vol 4 No 2 (2025)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v4i2.1806

Abstract

Information and communication technology has rapidly advanced, bringing significant changes to daily life. With these advancements, access to information has become faster and easier; however, this convenience also introduces challenges, particularly concerning personal data security. One common cybercrime is email phishing, where attackers use malicious links to encrypt user data or devices and demand a ransom to restore access. Phishing emails often resemble official messages from trusted sources, making recipients unaware of the potential threat. To minimize such risks, technology can be utilized to automatically classify phishing emails. This study focuses on developing a machine learning model for automatic phishing email classification. The dataset used consists of 18,650 emails, including 11,322 non-phishing and 7,328 phishing emails. The proposed models employ two algorithms: Support Vector Machine (SVM) and Random Forest. To optimize performance, hyperparameter tuning was conducted using GridSearchCV. The experimental results demonstrate that the SVM algorithm achieved an accuracy of 97.27%, while the Random Forest algorithm achieved 96.51%. These findings indicate that the developed models can effectively support efforts to anticipate and mitigate phishing email threats..
Rancang Bangun Website Promosi Produk Industri Menggunakan QR Code Berbasis Augmented Reality Garry Johannes; Pastima Simanjuntak
Journal Automation Computer Information System Vol. 6 No. 1 (2026): Mei
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jacis.v6i1.166

Abstract

Keterbatasan media promosi konvensional dalam menyajikan informasi teknis dan fungsional produk industri secara komprehensif menjadi kendala dalam strategi pemasaran digital, sebagaimana dialami oleh PT Gunung Mas Perkasa Abadi yang masih mengandalkan katalog dua dimensi serta penjelasan verbal dari tim sales pada interaksi Business-to-Business (B2B). Penelitian ini bertujuan untuk merancang dan mengembangkan prototipe sistem informasi promosi berbasis website yang mengintegrasikan teknologi Web-based Augmented Reality (Web-AR) dengan Quick Response (QR) Code guna menampilkan lima produk prioritas perusahaan dalam bentuk model 3D interaktif. Pengembangan sistem dilakukan menggunakan metode Multimedia Development Life Cycle (MDLC) yang meliputi tahap concept, design, material collecting, assembly, testing, dan distribution, dengan memanfaatkan aset yang bersumber dari data produk perusahaan. Sistem dikembangkan berbasis browser untuk meningkatkan aksesibilitas pengguna tanpa memerlukan instalasi aplikasi tambahan. Hasil pengujian teknis menunjukkan bahwa seluruh fungsi utama sistem berjalan sesuai dengan spesifikasi yang dirancang. Teknologi Web-AR mampu mentransformasikan representasi produk dua dimensi menjadi objek tiga dimensi interaktif secara real-time, sementara QR Code berfungsi sebagai media akses yang cepat dan akurat. Temuan ini mengindikasikan bahwa integrasi QR Code dan Web-AR secara teknis dapat diimplementasikan sebagai mekanisme penyampaian informasi promosi yang terintegrasi. Namun demikian, klaim keberhasilan penelitian ini dibatasi pada aspek fungsionalitas dan kelayakan teknis sistem, tanpa mencakup pengukuran efektivitas promosi, persepsi pengguna, maupun dampaknya terhadap peningkatan penjualan
SOSIALISASI DAN PELATIHAN SAFETY HOUSE PADA WARGA DI RT 04 RW 13 KELURAHAN TANJUNG RIAU KOTA BATAM Sri Zetli; Pastima Simanjuntak; Erlin Elisa; Koko Handoko; Neni Marlina Br Purba
PUAN INDONESIA Vol. 7 No. 2 (2026): Jurnal Puan Indonesia Vol 7 No 2 januari 2026
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v7i2.483

Abstract

Occupational Safety and Health (OSH) is not only important in industrial or office environments, but also in households that have the potential for accidents and health problems. One group that is vulnerable to these risks is housewives, who carry out daily activities at home. The lack of understanding of safety principles at home (safety house) has the potential to cause accidents, such as burns while cooking, slipping while washing, or exposure to household cleaning chemicals. This Community Service Activity (PKM) was carried out in RT 04 RW 13, Tanjung Riau Village, with the aim of increasing housewives' knowledge and awareness regarding the implementation of K3 at home. The methods used were socialization, interactive counseling, and group discussions on the concept of safety house and practices for preventing household accidents. The results of the activity showed an increase in participants' understanding of the importance of risk management at home, as demonstrated by increased enthusiasm, critical questions, and awareness to apply simple preventive measures in daily activities. Thus, this program made a real contribution to building a culture of safety at the household level, especially for housewives as the front line in maintaining the safety and health of their families.
Co-Authors Abimayu, Fajri Adam, Steffi Ade Novit Syahputra Akhmad Jayadi Alex Alfandianto Alfisyahri, Suciani Anggara, Kevin Asnawati Axl Bhernov Azwanti, Nurul brantaricke Cecep Sugianto Dalimunthe, Hery Fadly Daris Purba David Pranata Desrini Ningsih Dewa Kurniawan Nusantoro Dewi Kartika Sari Dicky Apdilah Dicky Prayoga Eko Suharyanto, Cosmas Elisa, Erlin Ellbert Hutabri, Ellbert Fajrin, Alfannisa Annurrullah Febry harlian hasibuan Ferdy Santoni Fernandes, Fadli Garry Johannes Gulo, Michael Joakson Gultom, Mitha Serlina Handoko, Koko Handoko, Koko Hendra Suprapto Hendri Kremer Herman Yuliansyah Humairani, Ayunda Annisa Imam Asyarie Imam Riadi Indah Purnama Sari Indra, Yanto Kang, Jetlie Khairiyah, Riri Kho, Willy Kie, Kennard Koko, Koko Handoko Kurnia Cahyana, Muhammad Angga Lase, Devi Chrisman Liska sumarni Manurung, Sesi Susanti Marubah Siringo, Anggiat Maslan, Andi MAULI SIAGIAN Muhammat Rasid Ridho Nanito Nasruji, Nasruji Nurma Dhona Handayani Nurma Dhona Handayani Nurma Dhona Handayani, Nurma Oris Krianto Sulaiman Pangaribuan, Hotma Pardede, Uly Prayoga, Dicky Prima, Elsa Adam Alvin Priska Napitu Purba, Neni Marlina BR Realize, Realize Rika Harman Rika Harman Riri Khairiyah RONI Rosida V Nainggolan RR. Ella Evrita Hestiandari Sianturi, Apoan Toni Corline Sibarani, Sarina Sihombing, Joel Simatupang, Enjelina Siska Damayanti Sitohang, Sunarsan Sri Zetli Sri Zetli Suhaili Suharyanto, Cosmas Eko Suprapto, Hendra Suratman Syastra, Muhammad Taufik Tampubolon, Dumayanti Tarigan, Armando Muhsirada Teddy Santya Toni, Toni Vernando, Veron Wasiman Wasiman Wasiman, Wasiman Yanto, Indra Yanto Yohanni Syahra Yohanni Syahra Zara Tania Rahmadi Zetli, Sri Zetly, Sri