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All Journal JAAKFE UNTAN ( (Jurnal Audit Dan Akuntansi Fakultas Ekonomi Universitas Tanjungpura) Sebatik Jurnal Pendidikan Akuntansi dan Keuangan Informatika Jurnal Ilmiah Manajemen Kesatuan Eksos Jurnal UNITEK Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) JCA (Jurnal Cendekia Akuntansi) Prosiding Snastikom LEBAH Journal of Innovation in Management, Accounting and Business Journal of Nursing Science Update Research Horizon Journal Global Technology Computer Jurnal Pengabdian Masyarakat ORAHUA : Jurnal Pengabdian Kepada Masyarakat Smart Humanity: Jurnal Pengabdian Masyarakat Journal of Computer Science Artificial Intelligence and Communications
Damayanti, Fera
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Penerapan Algoritma K-Nearest Neighbor Dalam Menentukan Kualitas Buah Jeruk Bali Harahap, Musbar Fandi; Damayanti, Fera; Sundari, Siti
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.7804

Abstract

Grapefruit, large orange or pomelo (Citrus maxima) could be a native Indonesian fruit plant that has high economic value. Grapefruit is spread across various regions in Indonesia and has various types of fruit such as Bali Merah, Cikoneng, Nambangan, Raja, Ratu, and Pangkep. Grapefruit (Citrus maxima) is one of three types of local citrus besides Citrus medica and Citrus reticulate. Grapefruit grows in tropical areas so that grapefruit has the potential to be cultivated in Indonesia. The quality of grapefruit is usually obtained through selection by distinguishing contrast based on the characteristics of natural materials, calculating the dosage and shape of natural materials, the shape of the tip and base of natural materials, the color and surface of grapefruit fruit. flavedo (epicarp), viscosity and color of albedo (mesocarp), color of endocarp, color and taste of vesicles or natural product tissue, odor of essential oils, number of natural products per tree and number of seeds in each natural product. Test results using the grapefruit application in data mining processing using KNN calculations. In the data testing, the precision value was obtained:0.834, Classification precision:0.860, F1:0.860, accuracy:0.861, review:0.860 and MCC:0.720 on the test data.
Determination of Fraud Diamond Theory in Detecting Fraud in Financial Reporting Wiraputra, Muhammad Rizki; Damayanti, Fera; Haryono
Research Horizon Vol. 5 No. 4 (2025): Research Horizon - August 2025
Publisher : LifeSciFi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54518/rh.5.4.2025.760

Abstract

Financial statement fraud undermines transparency and accountability in state-owned enterprises, posing significant risks to stakeholders. This study aims to examine the effectiveness of the Fraud Diamond Theory, encompassing pressure, opportunity, rationalization, and capability, in detecting such fraud in Indonesian state-owned enterprises. The research analyzes 45 annual reports from 15 state-owned enterprises between 2021 and 2023, categorized into fraud and non-fraud groups, using logistic regression with 10 independent variables. Findings indicate that only the total accrual variable, representing rationalization, significantly influences fraud detection, while the other nine variables show no notable impact. This suggests that accounting manipulation through accruals is a critical factor in fraudulent financial reporting within state-owned enterprises. The study concludes that focusing on accrual-based indicators, rather than relying solely on external pressures or governance changes, enhances fraud detection. Strengthening internal audit procedures and monitoring accrual patterns are recommended to improve financial integrity. However, the study's focus on state-owned enterprises limits its generalizability, suggesting future research should include private companies and qualitative approaches to explore contextual factors.
Penyuluhan Literasi Keuangan Digital di MIS Al-Hidayah CK Medan Purba, Bister; Iqbal, Muhammad; Tanjung, Rovidatul Hikmah; Damayanti, Fera; Bu’ulolo, Efori
Lebah Vol. 19 No. 1 (2025): September: Pengabdian
Publisher : IHSA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/lebah.v19i1.347

Abstract

Siswa sekolah dasar saat ini tumbuh di era kemajuan teknologi yang sangat cepat, sehingga mereka semakin terbiasa menggunakan internet, perangkat digital, dan berbagai aplikasi berbasis teknologi. Kondisi ini menunjukkan pentingnya memberikan edukasi sejak dini mengenai literasi keuangan digital secara bijak serta pemahaman akan risiko yang mungkin timbul dari penggunaan layanan keuangan berbasis digital. Kegiatan ini dilakukan di MIS Al-Hidayah CK Medan dengan menggunakan metode audio-visual, diskusi interaktif, dan tanya jawab sederhana dan diikuti murid kelas 5 dengan melibatkan beberapa guru MIS Al- Hidayah CK Medan. Berdasarkan hasil analisis melalui kuisioner dapat disimpulkan bahwa proses pelaksanaan kegiatan penyuluhan literasi keuangan digital ini menunjukkan hasil yang cukup signifikan dalam peningkatan pemahaman siswa MIS Al-Hidayah CK Medan terkait literasi keuangan digital. Peningkatan sebesar 42,71% dari hasil pre-test ke post-test mencerminkan bahwa penerapan metode penyuluhan yang interaktif dan  partisipatif seperti pendekatan dalam kehidupan sehari-hari, permainan interaktif, video animasi edukatif, serta diskusi mampu menciptakan suasana kegiatan yang kondusif dan mendorong keterlibatan aktif siswa. Hal ini menunjukkan bahwa pendekatan tersebut sesuai dengan karakteristik perkembangan usia anak-anak dan sangat efektif dalam membangun pondasi literasi keuangan digital sejak dini.
Pelatihan Membuat Animasi 3D Dengan SketchUp Di SMK Pantai Labu Sundari, Siti; Khairunnisa, Khairunnisa; Damayanti, Fera; Rismayanti, Rismayanti; Dewi, Arie Rafika
SMART HUMANITY : Jurnal Pengabdian Masyarakat Vol. 1 No. 2: Juni 2024
Publisher : CV. Smart Scienti

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

Abstract

Salah satu tridarma perguruan tinggi adalah pengabdian masyarakat. Kegiatan pengabdian masyarakat dilaksanakan untuk meningkatkan kualitas pendidikan dan SDM sehingga mampu bersaing di dunia kerja yang semakin berkembang pesat. SDM  berkualitas dan siap bersaing memerlukan adanya sebuah pendidikan berkualitas yang mencetak lulusan yang mempunyai daya fikir cerdas, berkompetensi dan berkepribadian baik. Untuk itu kami sebagai tim pengabdian melaksanakan pengabdian masyarakat di SMK Pantai Labu dengan topik “Pelatihan Membuat Animasi 3D Menggunakan SketchUp”. SMK Pantai Labu memerlukan ketrampilan khusus akan penguasaan teknologi agar memiliki pandangan untuk melanjutkan ke perguruan tinggi ataupun sebagai bekal di dunia kerja pasca lulus sekolah. Tujuan pelatihan ini yaitu memberikan pengetahuan kepada Siswa SMK Pantai Labu tentang teknologi animasi 3 dimensi serta cara penggunaan software SketchUp. Metode pelatihannya yaitu pengenalan animasi 3D, software SketchUp dan PreTest untuk mengetahui keminatan Siswa, pemberian materi pelatihan dan evaluasi berupa Post Test. Hasil Kegiatan Pengabdian berdasarkan posttest terdapat 47% siswa memiliki pengetahuan dan minat belajar dalam membuat animasi 3 dimensi.
A Narrative Exploring the Potential of ChatGPT: How AI Models Are Changing the Way We Interact with Technology Eka, Muhammad; Asih, Munjiat Setiani; Damayanti, Fera; Saragih, Rusmin; Supiyandi, Supiyandi
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 1 (2024): May 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i1.5

Abstract

This study explores the perceptions, attitudes, and ethical considerations surrounding the use of ChatGPT among university students. By combining quantitative and qualitative research methods, including surveys and a review of existing literature, the study examines how ChatGPT is utilized in academic settings and its impact on learning outcomes, academic integrity, and scholarly achievements. The findings suggest that ChatGPT significantly enhances students' productivity, learning experiences, and writing abilities. However, concerns regarding its potential misuse, particularly about academic integrity, plagiarism, and over-reliance on AI tools, were also identified. The research highlights the importance of establishing clear ethical guidelines and policies to regulate the use of AI in educational settings. Future research should focus on the long-term effects of ChatGPT on students' academic development and investigate strategies for promoting responsible AI usage in higher education.
Classification of Customer Credit Risk Levels Using the Random Forest Method: A Case Study on Microfinance Institutions Damayanti, Fera; Arief Budiman; Siti Sundari; Theodora MV Nainggolan
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 2 (2024): November 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i2.20

Abstract

Credit risk classification plays a crucial role in supporting financial institutions, especially microfinance institutions, in assessing the ability of customers to repay loans. This study aims to develop a credit risk classification model using the Random Forest method, which is known for its accuracy and robustness in handling classification problems. The research uses a dataset obtained from a microfinance institution consisting of various customer attributes such as income, age, loan amount, repayment history, and employment status. The dataset is preprocessed and divided into training and testing sets to evaluate model performance. The Random Forest algorithm is then applied to build a classification model that categorizes customers into three credit risk levels: low, medium, and high. The results show that the Random Forest model achieves a high level of accuracy, with a classification precision of 89%, recall of 87%, and F1-score of 88%. These findings indicate that Random Forest is an effective technique for credit risk classification and can be implemented by microfinance institutions to support better decision-making in credit approval processes. This research also highlights the potential of machine learning techniques in enhancing credit risk management and minimizing non-performing loans.
Co-Authors ., Rusliyawati Adisty, Lyanti Anisah, Nur Wafa Ardhi, Qisthi Ardimansyah Ardimansyah Arief Budiman Asih, Munjiat Setiani Aswat, Ibnu Bu’ulolo, Efori Devi Permata Sari Dewi, Arie Rafika Eka, Muhammad Elok Heniwati Espa, Vitryan Fabiola, Rivanka Wana Fariyanda, Rosan Ferrary, Melissa Franchitika, Rizky Halawa, Mariana Hamzani, Umiaty Harahap, Musbar Fandi HARYONO Ikhsan, Syarbini Indira Alifya Julianti, Erna Khairunnisa Khairunnisa Khairunnisa Khristina Yunita Margaret, Eveline Marwan, Andi MUHAMMAD FAHMI Muhammad Iqbal Musfikianty, Rindy Muzaki, Rifki Amrul Nina Febriana Dosinta Nurkhasanah Rina Puspita Pratama, Muhammad Rahmadi Purba, Bister Putra, Novrialdi Budi Raki, Endah Yuli Astuti Rismayanti Rismayanti Rismayanti Rudy Kurniawan Rusmin Saragih, Rusmin Sari, Kartika Indah Siregar, Rosyidah Siti Sundari Siti Sundari Sri Sat Titi Hamranani Supardi Supardi Supiyandi Supiyandi Surbakti, Asri Afriliany Tampubolon, Elfrans Arsendy Tanjung, Rovidatul Hikmah Theodora MV Nainggolan Tiarani, Rani Titik Susanti Vitriyan Espa Wiraputra, Muhammad Rizki Yantiana, Nella Yuniarsih, Eka