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All Journal JURNAL EMBA : JURNAL RISET EKONOMI, MANAJEMEN, BISNIS DAN AKUNTANSI Jurnal Simetris Elkom: Jurnal Elektronika dan Komputer AKSIOMA: Jurnal Program Studi Pendidikan Matematika Aksara Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Al-Muzara'ah Jurnal Ilmiah KORPUS JURNAL PENDIDIKAN TAMBUSAI International Journal of Public Budgeting, Accounting and Finance Metalingua: Jurnal Penelitian Bahasa Agritech: Jurnal Fakultas Pertanian Universitas Muhammadiyah Purwokerto (JIML) JOURNAL OF INNOVATIVE MATHEMATICS LEARNING JURNAL PENELITIAN PERAWAT PROFESIONAL Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Akutansi Manajemen Ekonomi Kewirausahaan (JAMEK) Jurnal Pengabdian Masyarakat Bhinneka Jurnal Aplikasi Perpajakan Journal of Pharmaceutical (JOP) Cakrawala: Jurnal Ekonomi, Manajemen dan Bisnis CITAKARYA Jurnal Pengabdian Masyarakat
Windi Astuti
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Edukasi Dan Demonstrasi Senam Kaki Diabetes Mellitus Dalam Upaya Peningkatan Pengetahuan Pada Masyarakat Astuti, Windi; Begum, Nanda Sayyida; Fazri, Ahmat
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 4 (2025): Edisi Oktober - Desember
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i4.6558

Abstract

Senam kaki menjadi salah satu aktivitas fisik yang dianjurkan bagi penderita diabetes melitus karena dapat membantu melancarkan sirkulasi darah, memperkuat otot kaki, dan mencegah cedera maupun kelainan bentuk. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan pengetahuan masyarakat mengenai diabetes melitus, meliputi tanda, gejala, serta langkah pencegahannya secara tepat. Metode pelaksanaan adalah penyuluhan kesehatan, diskusi dan tanya jawab serta senam kaki diabetes. Hasil pemeriksaan gula darah sewaktu menunjukkan bahwa 9,5% peserta memiliki kadar normal (70–100 mg/dL), 61,9% dalam kategori pradiabetes (100–140 mg/dL), dan 28,5% tergolong hiperglikemia (140–200 mg/dL). Sebagian besar peserta berjenis kelamin perempuan (80,9%), berusia 51–83 tahun (38,0%), dengan tingkat pendidikan terbanyak adalah lulusan SMA (42,8%), serta jenis pekerjaan terbanyak adalah pedagang/wiraswasta (33,3%). Evaluasi melalui diskusi, sesi tanya jawab, serta praktik ulang (role play) senam kaki menunjukkan bahwa seluruh peserta (100%) memahami materi dan mampu mempraktikkan senam kaki dengan benar. Hasil ini menunjukkan bahwa kegiatan berhasil meningkatkan pengetahuan dan keterampilan masyarakat dalam mengenali serta mencegah diabetes melitus melalui pendekatan edukatif yang tepat.
Analisis Sentimen Terhadap Isu Pemblokiran Thrifting Pada Platform TikTok Menggunakan Bidirectional Long Short-Term Memory Windi Astuti; Bambang Irawan; Nur Ariesanto Ramdhan
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3361

Abstract

The development of social media platforms like TikTok has created new spaces for digital economic activities, including the practive of thrifting, which has now become a trend among the public. However, government policies that block these activities have sparked various public reactions. This study aims to analyze public sentiment regarding the issue of thrifting bans on the TikTok platform using the Bidirectional Long Short-Term Memory (Bi-LSTM) method. This method was chosen because it can understand text context from both directions, allowing it to capture deeper semantic meaning. The dataset consist of 4,000 TikTok user comments collected through a crawling process. The research stages include data preprocessing, sentiment labeling, splitting training and test data, training the Bi-LSTM model, and evaluating performance using accuracy, precision, recall, and F1-score metrics. The research results show that the Bi-LSTM model achieved an accuracy of 86.15%, with stable classification performance and minimal error rate. These findings indicate that Bi-LSTM is effective for sentiment analysis of public opinions on Indonesian language social media, particularly on context specific policy issues. Further development can be carried out by adding pre-trained embeddings or attention mechanisms to improve the model’s performance.
Financial Distress Perusahaan Transportasi Logistik ISSI: Peran Altman Z-Score dan Islamic Social Reporting Astuti, Windi
Jurnal Aplikasi Perpajakan Vol. 6 No. 2 (2025): Jurnal Aplikasi Perpajakan
Publisher : Jurnal Aplikasi Perpajakan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jap.v6i2.504

Abstract

This study aims to determine the effect of the Altman Z-Score prediction model and Islamic Social Reporting (ISR) on financial distress in transportation and logistics companies listed on the Indonesia Sharia Stock Index (ISSI). This study uses a descriptive quantitative approach with secondary data. The research population consists of all public companies engaged in the transportation and logistics sector listed on the Indonesia Sharia Stock Index (ISSI), totaling 28 companies in the period from 2020 to 2022. The research sampling method used purposive sampling, yielding 11 companies or 33 observation data. The analysis technique used in this study was multiple regression analysis. The results of this study show that both partially and simultaneously, Altman Z Score and Islamic Social Reporting (ISR) have a significant effect on Financial Distress. These two variables can explain 71% of financial distress, while the other 29% is explained by variables not mentioned in this study.
Students’ Metacognitive Errors based on Newman’s Error Types within Deep Learning Approach Astuti, Windi; Lestari, Puji; Prabawati, Mega Nur
(JIML) JOURNAL OF INNOVATIVE MATHEMATICS LEARNING Vol. 9 No. 1 (2026): VOLUME 9 NUMBER 1, MARCH 2026
Publisher : IKIP Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22460/jiml.v9i1.31027

Abstract

Students’ difficulties in solving mathematical problems are often closely related to weaknesses in metacognitive regulation, particularly in planning, monitoring, and evaluating problem-solving processes. One systematic framework to identify these difficulties is Newman’s Error Analysis, which classifies students’ errors into sequential stages of problem solving. This study aims to describe students’ metacognitive errors based on Newman’s error types in mathematics learning using a Deep Learning approach. This research employed a mixed methods approach with a sequential explanatory design, focusing on qualitative descriptive analysis. The participants consisted of three ninth-grade students from SMP Islamiyah Ciawi in the 2025/2026 academic year, selected purposively to represent high, moderate, and low levels of metacognitive ability. Data were collected through open-ended problem-solving tests on solid figures, a metacognitive questionnaire using a Likert scale, and semi-structured interviews. Data analysis was conducted by identifying students’ errors at each stage of Newman’s procedure—reading, comprehension, transformation, process skills, and encoding—and relating them to metacognitive indicators. Methodological triangulation was applied to enhance the credibility of the findings. The results indicate that students with high metacognitive ability tend to exhibit minimal errors, mainly at the encoding stage. In contrast, students with moderate and low metacognitive abilities demonstrate dominant errors at the transformation and process skills stages, with low-metacognitive students also experiencing reading and comprehension errors. These findings suggest that metacognitive regulation significantly influences the type and stage of students’ errors. In conclusion, integrating explicit metacognitive scaffolding within Deep Learning practices is essential to reduce students’ errors and enhance mathematical problem-solving performance.
Co-Authors Abdul Ghofur Agus S Suryadimulya Agus Trianto Ainun Vanat, Rifqi Andi Widodo Ariyani, Liza Azhar Maksum Azhar, Ibnu Bambang Irawan Bandu, Jumiati Begum, Nanda Sayyida Debora Paninsari Dumasari Dumasari Echa Effendy Siswanto Amir Eko Prasetyo, Wijang Faridah Faridah Fathorrahman Fathorrahman, Fathorrahman Fazri, Ahmat Firman Syah Noor Gonibala, Alfiana P. Hafsia K.N Mokodompit Hairil Akbar Hasugian, Arsita Ibnu Austrindanney Sina Azhar Imban, Putri Natasya Intan Kumalaningrum, Annisa Iskandar Muda Kuna, Moh. Rasyid Kuswardani, Anisa Linda Herawati, Linda Lubis, Andrew Satria Lubis, Muhammad Arif M Saju Feriantama, Engga M. Arifin Maman Suratman Mega Nur Prabawati, Mega Nur Mokodompit, Diva Niken Larasati Nur Ariesanto Ramdhan Nurjanah, Novi Ocky Sundari Rahardjo Petra Purnama, Davinsy Pobela, Tarisya PUJI LESTARI Putri, Puspa Mutia Syah Rahman Rahman Rini Puspa Sari, Rini Puspa Rosita, Melia Eka Rusmawati, Devita Saleh, Husna Sapto Nugroho, Wisnu Silalahi, Amlys Syahputra Sulidar Fitri Talamati, Bambang H. Watemin, Watemin Widodo, Adji Yeni Heryani