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All Journal Jurnal Masyarakat Informatika Rekursif: Jurnal Informatika Jurnal Pseudocode InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal PGSD: Jurnal Ilmiah Pendidikan Guru Sekolah Dasar Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Teknik Informatika (JUTIF) These proceedings represent the work of researchers participating in The International Conference on Elementary Education (ICEE) which is being hosted by the Elementary Education Study Programme School of Postgraduate Studies, Universitas Pendidikan Dikdimas : Jurnal Pengabdian Kepada Masyarakat The Indonesian Journal of Computer Science Jurnal Abdimas Bencoolen IJIS Edu : Indonesian Journal of Integrated Science Education
Endina Putri Purwandari
Program Studi Teknik Infomatika, Fakultas Teknik, Universitas Bengkulu
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Neuroscience Nursing Public Health Social Sciences Transportation Other

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E-Worksheets Based on STEAM-PJBL with Local Coastal Wisdom to Improve Critical Thinking Skills Winarni, Endang Widi; Heryanto, Debi; Yusnia, Yusnia; Agusdianita, Neza; Purwandari, Endina Putri; Wijanarko, Andang
IJIS Edu : Indonesian Journal of Integrated Science Education Vol 8, No 1 (2026): January 2026
Publisher : UIN Fatmawati Sukarno Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29300/ijisedu.v8i1.7774

Abstract

This research aimed to investigate the influence of electronic student worksheets based on STEAM and Project-Based Learning (PjBL) with local coastal wisdom content to improve the critical thinking abilities of fifth-grade students in Group V elementary schools in Bengkulu City. This research employed a quantitative approach using a quasi-experimental method with a Matching Only Pretest-Posttest Control Group Design. The population of this study comprised all elementary schools in Group V, Bengkulu City. The sample consisted of fifth-grade students from SDN 09 and 02 Bengkulu City, selected using Cluster Random Sampling. The research instrument used was a critical thinking skills test with a pretest and posttest. The data was analysed quantitatively using descriptive statistics, prerequisite tests, and hypothesis testing. The t-test was used to test the hypothesis. The results showed that the significance value (2-tailed) was 0.000 < 0.05 at a 5% significance level. The average scores of the experimental class (80.28) and the control class (50.21) showed a significant difference between the learning outcomes of the experimental and control classes. It can be concluded that the experimental class using electronic student worksheets based on STEAM and PjBL significantly influenced the students' critical thinking abilities. In conclusion, this study found a significant influence of electronic student worksheets based on STEAM and PjBL on the critical thinking skills of fifth-grade students in Group V elementary schools in Bengkulu City.
Comparative Analysis of Machine Learning for Stroke Classification Using YOLOv11 Detection and a Radiomics-Based Two-Stage Model Manurung, Wahyu Ozorah; Ernawati, Ernawati; Oktoeberza, Widhia KZ; Andreswari, Desi; Purwandari, Endina Putri; Efendi, Rusdi
Jurnal Masyarakat Informatika Vol 17, No 1 (2026): May 2026 (Ongoing)
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.17.1.78464

Abstract

Stroke is a leading cause of disability and death worldwide, including in Indonesia. Rapid and accurate diagnosis is crucial, especially during the golden period (3–4.5 hours). CT scans are the primary imaging modality, but manual interpretation is often limited by time, subjectivity, and radiologist availability. This study proposes a two-stage model integrating YOLOv11 for lesion detection and machine learning for classification, using radiomics for feature extraction. In the first stage, YOLOv11 detects lesions and generates bounding boxes, which serve as Regions of Interest (ROIs). In the second stage, radiomics features are extracted and classified using Naïve Bayes, Support Vector Machine (SVM), and Random Forest. Results show YOLOv11 achieved an overall mAP@50 of 0.732, with the highest performance in hemorrhagic stroke (0.741). Radiomics-based classification further improves stability, achieving accuracies of 0.97–0.99 and precision, recall, and F1 scores≥0.94. Among classifiers, SVM performed best, with a test accuracy of 0.97, a false positive rate of 1.23%, total error 0.0218, generalization gap -0.0117, variance 0.0002, standard deviation 0.003635, confidence interval 0.9708 (+/-0.0073), and consistent fold accuracy between 96.5–97.5%, indicating stability without overfitting. These findings confirm that the combination of the YOLOv11 two-stage model, radiomics, and SVM provides a robust approach to support stroke diagnosis.
Penerapan Business Intelligence Menggunakan Microsoft Power BI dalam Analisis Gangguan Jaringan Massal di PT Telkom Witel Bengkulu Saragih, Eprian Travolta; Purwandari, Endina Putri; Setiawan, Yudi
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 10, No 2 (2026): InfoTekjar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v10i2.13455

Abstract

Penelitian ini bertujuan untuk menerapkan Business Intelligence (BI) dalam mengolah data gangguan jaringan massal di PT Telkom Witel Bengkulu agar terstruktur dan dapat dianalisis menggunakan Microsoft Power BI. Permasalahan utama pada penelitian ini adalah pengelolaan data gangguan jaringan yang masih dilakukan secara manual dan terpisah, sehingga data hanya berfungsi sebagai arsip administratif dan belum dimanfaatkan secara optimal untuk analisis. Kondisi ini menyebabkan sulitnya mengidentifikasi pola gangguan, penyebab utama, serta mengevaluasi efektivitas proses perbaikan secara cepat dan akurat.. Metode yang digunakan adalah deskriptif kuantitatif melalui proses Extract, Transform, Load (ETL) terhadap data sekunder periode Januari 2024 hingga Februari 2026.Hasil penelitian menunjukkan terdapat 1.054 gangguan dengan rata-rata durasi perbaikan 4,19 jam serta tingkat kepatuhan Service Level Agreement (SLA) sebesar 88% (comply) dan 12% (not comply). Hasil analisis menunjukkan bahwa gangguan didominasi oleh jenis gangguan infrastruktur kabel dengan penyebab utama berasal dari faktor eksternal, seperti force majeure dan aktivitas pihak ketiga. Pada aktivitas perbaikan, tindakan yang paling sering dilakukan adalah catu PLN up dan sambung kembali. Dashboard interaktif yang dihasilkan mampu mengidentifikasi pola gangguan dan kinerja perbaikan secara real-time, serta memberikan insight strategis bagi manajemen dalam pengambilan keputusan berbasis data. Penerapan Business Intelligence pada penelitian ini dapat meningkatkan efektivitas monitoring, evaluasi, dan pengambilan keputusan untuk mendukung peningkatan kualitas layanan jaringan.
Evaluation of the Effectiveness of Adaptive Learning Systems in Higher Education with System Usability Scale Purwandari, Endina Putri; Paryanto, Paryanto; Winarni, Endang Widi; Erlansari, Aan; Putra, Yusran Panca
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 9, No 1 (2026): Februari 2026
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v9i1.10003

Abstract

Abstract - Adaptive learning systems adapt instructional materials to students' needs through personalized learning paths, changing the layout interface, or hiding some material links. The System Usability Scale (SUS) focuses on developing a usability assessment for an adaptive education system, using an approach that asks users to evaluate web pages. This research was conducted with first-semester students in the Computer Programming subject from the Information Systems Study Program, Faculty of Engineering, University of Bengkulu. Based on the SUS calculation, the application achieved a score of 75.08. This result falls within the 68-80.3 range, placing the program product at the "Good" level. This indicates that overall user satisfaction with the adaptive online learning system is acceptable. However, there are some areas that require repairs, especially those related to inconsistent functionality and user convenience. Further study can continue to use Concurrent Think Aloud (CTA) and test scenarios for each use case to gain insight into user behavior as users interact with the application in the moment.Keywords: Evaluation; Online Learning Systems; Adaptive; System Usability Scale; Abstrak - Sistem pembelajaran daring adaptif menyesuaikan materi pembelajaran dengan kebutuhan siswa melalui jalur pembelajaran yang dipersonalisasi, mengubah tata letak antarmuka, atau menyembunyikan beberapa tautan. Metode System Usability Scale (SUS) berfokus pada pengembangan sistem penilaian kegunaan untuk sistem pendidikan daring adaptif, menggunakan pendekatan yang meminta pengguna untuk mengevaluasi halaman web. Penelitian ini dilakukan pada mahasiswa semester pertama program studi Ilmu Komputer dan Pemrograman Program Studi Sistem Informasi, Fakultas Teknik, Universitas Bengkulu. Hasil perhitungan SUS menghasilkan skor 75,08. Hasil ini berada dalam kisaran 68 hingga 80,3, menempatkan produk program pada tingkat "Baik". Ini menunjukkan bahwa kepuasan pengguna secara keseluruhan terhadap sistem pembelajaran daring adaptif dapat diterima. Namun, ada beberapa area yang perlu ditingkatkan, khususnya mengenai inkonsistensi dalam fungsionalitas dan kemudahan penggunaan. Penelitian lebih lanjut dapat menggunakan Concurrent Think Aloud (CTA) dan skenario pengujian untuk setiap kasus penggunaan untuk mendapatkan wawasan yang lebih dalam tentang perilaku pengguna saat berinteraksi dengan aplikasi.Kata kunci: Evaluasi; Sistem Pembelajaran Daring; Adaptif; System Usability Scale;
Co-Authors Aan Erlansari Abdul Muktadir, Abdul Agusdianita, Neza Ahmad, Mubarik Azmi, Yoan Leo Daimun, Daimun Dalifa, Dalifa Desi Andreswari Dianita, Meisy Endang Widi Winarni Ernawati Ernawati Harmika, Lita Harry Budi Santoso Heryanto, Debi Kasiyah Junus Lakshita, Stefanie Laksmi Manurung, Wahyu Ozorah Mochammad Yusa, Mochammad Muh Syaiful Romadhon Nabila, Nisreina Natalio, Jandri Niska Ramadani, Niska Noperman, Feri Nurul Renaningtias, Nurul Oktoeberza, Widhia KZ Paryanto Putra, Yusran Panca Rusdi Efendi Saragih, Eprian Travolta Sucipto, Sigit Syahputra, Wahyu Wijanarko, Andang Yudi Setiawan Yusnia, Yusnia Zuliuskandar, Valleryan Virgil