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All Journal Mimbar Sekolah Dasar Journal of Information Systems Engineering and Business Intelligence JIEET (Journal of Information Engineering and Educational Technology) Journal of Robotics and Control (JRC) Jurnal Abdi: Media Pengabdian Kepada Masyarakat ABIDUMASY : Jurnal Pengabdian kepada Masyarakat Abdimas: Papua Journal Of Community Service Journal of Informatics and Computer Science (JINACS) Jurnal Ilmiah Edutic : Pendidikan dan Informatika Ranah Research : Journal of Multidisciplinary Research and Development Journal of Emerging Information Systems and Business Intelligence (JEISBI) Journal of Education Technology and Information System
Wiyli Yustanti
Prodi Manajemen Informatika, Fakultas Teknik, Universitas Negeri Surabaya
Religion Aerospace Engineering Humanities 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 Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

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Otomatisasi Klasifikasi Tingkat Urgensi Keluhan E-Layanan Unesa Berbasis TF-IDF dan Logistic Regression Alpiana, Intan; Yustanti, Wiyli; Yamasari, Yuni
Ranah Research : Journal of Multidisciplinary Research and Development Vol. 8 No. 1 (2025): Ranah Research : Journal Of Multidisciplinary Research and Development
Publisher : Dinasti Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/rrj.v8i1.1912

Abstract

Perkembangan teknologi digital menuntut perguruan tinggi untuk menghadirkan layanan akademik yang cepat, tepat, dan responsif. Universitas Negeri Surabaya (Unesa) melalui platform E-Layanan memberikan sarana bagi civitas akademika untuk menyampaikan keluhan terkait kendala penggunaan sistem informasi dan jaringan. Namun, proses klasifikasi tingkat urgensi keluhan masih dilakukan secara manual oleh admin, yang berpotensi menyebabkan keterlambatan penanganan, inkonsistensi penilaian, serta meningkatnya beban kerja. Penelitian ini bertujuan untuk mengembangkan sistem otomatisasi klasifikasi tingkat urgensi keluhan dengan memanfaatkan Term Frequency-Inverse Document Frequency (TF-IDF) sebagai representasi fitur teks, serta Logistic Regression berbobot (class_weight) sebagai model klasifikasi utama. Dataset yang digunakan terdiri dari 79.303 keluhan, dibagi menjadi data latih (70%), validasi (15%), dan uji (15%). Evaluasi model dilakukan menggunakan metrik akurasi, presisi, recall, F1-score, dan confusion matrix. Hasil penelitian menunjukkan bahwa kombinasi TF-IDF dan Logistic Regression berbobot mampu memberikan kinerja yang baik dengan akurasi 92,54% pada data uji. Selain itu, model menunjukkan kemampuan yang tinggi dalam mendeteksi keluhan kritis secara akurat, memastikan prioritas penanganan terjaga secara optimal. Temuan ini menegaskan bahwa penerapan model berbasis pembelajaran mesin dapat meningkatkan efisiensi operasional dan konsistensi klasifikasi dibandingkan pendekatan manual. Sistem yang dikembangkan diharapkan dapat diintegrasikan lebih lanjut ke dalam platform E-Layanan Unesa, mendukung proses penanganan keluhan secara otomatis dan real-time, serta membantu administrasi fokus pada resolusi masalah yang paling mendesak.
PELATIHAN MEDIA PEMBELAJARAN MENGGUNAKAN CANVA UNTUK GURU MI AL AHMAD, KRIAN, SIDOARJO Naim Rochmawati; Yamasari, Yuni; Yustanti, WIyli; Qoiriah, Anita; Aviana, Anisah Nurul
Jurnal ABDI: Media Pengabdian Kepada Masyarakat Vol. 9 No. 1 (2023): JURNAL ABDI : Media Pengabdian Kepada masyarakat
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/abdi.v9i1.19853

Abstract

Dalam proses belajar mengajar, media pembelajaran berperan penting. Media pembelajaran yang interaktif membantu para siswa lebih mudah dalam memahami konten materi yang disampaikan para guru. Dengan kesadaran untuk meningkatkan kemampuan dalam membuat media pembelajaran agar kualitas pembelajaran semakin meningkat, para guru MI Al Ahmad, Krian, Sidoarjo, meminta pelatihan pembuatan media pembelajaran. banyak tool yang bisa digunakan, salah satunya adalah Canva. Dalam Canva, disediakan banyak fasilitas menu untuk membuat media pembelajaran yang interaktif. Untuk itu, pelatihan kali ini adalah memberikan pelatihan Canva bagi para guru MI Al Ahmad untuk meningkatkan kemampuan digital para guru MI Al Ahmad dalam membuat media pembelajaran yang interaktif. Metode kegiatan adalah dengan model ceramah dilanjutkan dengan praktikum menggunakan Canva. Hasil dari pelatihan ini adalah kemampuan para guru MI Al Ahmad dalam membuat media pembelajaran interaktif menggunakan Canva. Dari hasil evaluasi kegiatan disimpulkan bahwa pelatihan ini dapat dikatakan berhasil meskipun masih perlu penyempurnaan dalam kegiatan yang dilakukan. Hal ini diindikasikan dengan respon yang diberikan oleh guru MI Al Ahmad, sebagai peserta pelatihan, pada angket online yang dibagikan setelah selesai pelatihan.
Pelatihan Pemanfaatan Internet untuk Menunjang Kreativitas Guru dalam Penyampaian Materi secara Daring Yamasari, Yuni; Qoiriah, Anita; Yustanti, Wiyli; Rochmawati, Naim; Nurhidayat, Andi Iwan; Kurniawan, Ari
Abdimas: Papua Journal of Community Service Vol. 6 No. 1 (2024): Januari
Publisher : Lembaga Pengembangan dan Pengabdian Masyarakat Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/pjcs.v6i1.2749

Abstract

   
A Hybrid Clustering–Classification Framework for SMEs Success Level Prediction Saputra, Andika Dermawan; Yustanti, Wiyli
JIEET (Journal of Information Engineering and Educational Technology) Vol. 9 No. 2 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jieet.v9n2.p89-100

Abstract

Micro, Small, and Medium Enterprises (SMEs) are vital to economic growth, yet their complex success determinants necessitate advanced predictive modeling. This study proposes a hybrid clustering-classification framework to classify and predict SME success levels based on 22 multidimensional indicators, including financial literacy, FinTech adoption, and entrepreneurial resilience. K-Means clustering was first applied to the survey data, yielding three optimal success personas, validated by the highest Silhouette Score (0.5238). These clusters were labeled with Beginner and Conventional, Stable Digital Adopter, and Digital Innovator SMEs. These empirically derived clusters served as pseudo-labels for the classification stage. Classification algorithms were tested with and without the Synthetic Minority Oversampling Technique (SMOTE). While ensemble methods (Random Forest, LightGBM) and SVM performed well, the K-Nearest Neighbors (KNN) algorithm consistently outperformed all others, achieving the highest F1-Score (0.9324) under SMOTE implementation. The findings validate the effectiveness of the hybrid clustering-classification approach in accurately mapping and predicting SME success levels. The resulting model serves as a robust, data-driven tool for policymakers to guide targeted interventions and digital training programs, fostering sustainable SME development.
Optimizing UKT Prediction Based on Socio-Economic Features: A Multimodel Evaluation with Feature Selection Srategies Putri, Windy Chikita Cornia; Yustanti, Wiyli; Yohannes, Ervin
EDUTIC Vol 12, No 2: 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/edutic.v12i2.31828

Abstract

Determining the tuition fee group (UKT) for new students in Indonesian public universities represents a complex challenge requiring an equitable, data-driven approach. This study introduces an integrative feature selection strategy that combines five popular techniques Chi-Square, Recursive Feature Elimination (RFE), LASSO Regression, Random Forest Importance, and Exploratory Factor Analysis (EFA) to extract the most relevant attributes from 53 socioeconomic variables of prospective students at Universitas Negeri Surabaya. As a novelty, the study identifies intersecting features consistently selected by all five methods and evaluates their impact on the performance of five classification algorithms: Support Vector Machine (SVM), Decision Tree, Random Forest, K-Nearest Neighbor (KNN), and Naïve Bayes. Experimental results demonstrate a significant improvement in accuracy, with SVM increasing from 0.7550 to 0.7810. These findings confirm that integrative feature selection can optimize model performance while reducing data complexity. This study provides a replicable methodological contribution for developing transparent and adaptive classification systems based on socioeconomic data in higher education contexts.
INOVASI PEMBELAJARAN INTERAKTIF DI ERA DIGITAL: VIDEOSCRIBE JADI SOLUSI DI SDN SEMOLOWARU IV Nuryana, I Kadek Dwi; Cinthya, Monica; Yustanti, Wiyli; Devayana Putra, Cendra
ABIDUMASY Vol 7 No 2 (2026): ABIDUMASY : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/abidumasy.v7i2.12099

Abstract

The development of multimedia technology provides opportunities for teachers to deliver learning materials in a more engaging and interactive manner. However, its utilization in elementary schools remains limited, including at SDN Semolowaru IV Surabaya, which affects the quality of instructional material delivery. This community service activity aimed to enhance teachers’ competencies in developing multimedia-based learning media through training on the use of VideoScribe as a whiteboard animation tool. The program was implemented through a series of activities consisting of socialization, demonstrations, hands-on video production practice, mentoring, and evaluation. A total of 20 teachers participated in the training and were provided with a training module as a guide for further implementation. The results indicated that 87.5% of participants considered the training highly beneficial and easy to apply in classroom learning, while most participants found the materials and training methods easy to understand. The activity successfully improved teachers’ skills in producing multimedia-based learning videos and encouraged the adoption of digital learning media. These findings demonstrate that VideoScribe can serve as an effective alternative instructional medium that supports the development of more engaging learning materials and contributes to improving the quality of education in the digital era.
Co-Authors Alpiana, Intan Andi Iwan Nurhidayat ANITA QOIRIAH ARI KURNIAWAN Aulia Akbar, Rafy Aulia, Novi Rosidhatul Aviana, Anisah Nurul Ayuningtyas, Nimas Bayu Budi Prakoso Cendra Devayana Putra Cinthya, Monica Dani, Andrea Ervin Yohannes Farid Baskoro Hartanto, Unung Istopo I Gusti Putu Asto Buditjahjanto I Kadek Dwi Nuryana, I Kadek Dwi I Nyoman Budiantara IRMA FEBRIYANTI Iskandar Java, Muhammad Istianah, Eva Mohammad Akbar, Mohammad Muhammad Risalah Naufal Mutmainah Mutmainah Naim Rochmawati Nautika, Puji Septiyana Nurlyan, Reynisa Beta Prasetyo, Andhika Edo Priadana, Benny Widya Putra, Fachrian Bimantoro Putri, Windy Chikita Cornia Raden Mohamad Herdian Bhakti Rahmawati, Naim Ricky Eka Putra Rina Harimurti Rochmawati, Naim Saputra, Andika Dermawan Sifriyani, Sifriyani Suroto Suroto Syandika, Novliyan Dimas Ulfa Siti Nuraini Vebriani, Mutiara Widi Aribowo Yuni Yamasari