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All Journal Pendidikan Matematika Jurnal Pelangi LEMMA: Letters Of Mathematics Education SIGMA: Jurnal Pendidikan Matematika AlphaMath: Journal of Mathematics Education Suska Journal of Mathematics Education AKSIOMA Union: Jurnal Ilmiah Pendidikan Matematika Pendas : Jurnah Ilmiah Pendidikan Dasar AXIOM : Jurnal Pendidikan dan Matematika Jurnal Cendekia : Jurnal Pendidikan Matematika JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Penelitian Pembelajaran Matematika Sekolah JURNAL PEMBELAJARAN DAN MATEMATIKA SIGMA (JPMS) Jurnal Riset Pembelajaran Matematika J-PiMat : Jurnal Pendidikan Matematika Rangkiang: Jurnal Pengabdian Pada Masyarakat Jurnal Computer Science and Information Technology (CoSciTech) Mosharafa: Jurnal Pendidikan Matematika ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Lattice Journal : Journal of Mathematics Education and Applied Pedagogy : Jurnal Pendidikan Matematika Lattice Journal : Journal of Mathematics Education and Applied Jurnal Penelitian Ilmu Pendidikan Indonesia Ar-Riyadhiyyat: Jurnal Pendidikan Matematika Jurnal Horizon Pendidikan RANGKIANG: Jurnal Pengabdian Pada Masyarakat Lemma: Letters of Mathematics Education Gudang Jurnal Multidisiplin Ilmu Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) Jnanadharma JKM: Jurnal Kemitraan Masyarakat
Ainil Mardiyah
Universitas PGRI Sumatera Barat
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Enhancing Students’ Conceptual Understanding in Mathematics through the Realistic Mathematics Education Model Amelia putri; Alfi Yunita; Ainil Mardiyah
Ar-Riyadhiyyat: Journal of Mathematics Education Vol. 6 No. 1 (2025): Ar-Riyadhiyyat: Jurnal Pendidikan Matematika
Publisher : Tadris Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47766/arriyadhiyyat.v6i1.5964

Abstract

This study investigates the effect of the Realistic Mathematics Education (RME) model on students’ conceptual understanding in mathematics within the framework of the Merdeka Curriculum. Despite curriculum reforms emphasizing student-centered learning, many classrooms remain teacher-centered, resulting in low levels of student engagement and poor conceptual understanding. This quasi-experimental study employed a one-group pretest-posttest design with a quantitative approach. The research involved students from class VIII.6 at MTsN 2 Pesisir Selatan, selected through purposive sampling. A total of four essay-type items were used in both pretest and posttest assessments, targeting three key indicators of conceptual understanding: restating concepts, applying problem-solving algorithms, and representing mathematical ideas in various forms. Data analysis involved normality and homogeneity tests, followed by a paired sample t-test to determine statistical significance. The results showed that students’ posttest scores improved significantly compared to their pretest scores, with a t-value of 18.63 exceeding the critical value at a 5% significance level. Qualitative analysis further supported the quantitative findings, as students demonstrated notable improvement across all indicators. These results suggest that the RME model effectively enhances students' conceptual understanding by fostering contextual learning, active participation, and collaborative problem-solving. The study concludes that RME is a promising instructional model that aligns well with the goals of the Merdeka Curriculum and recommends its broader implementation in mathematics education to improve learning outcomes.
Pemodelan dan Prediksi Tingkat Kemiskinan Provinsi Sumatera Barat Menggunakan Support Vector Machine Putri, Melani Septina; Junaidi, Satrio; Mardiyah, Ainil
Computer Science and Information Technology Vol 7 No 1 (2026): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v7i1.11207

Abstract

This research is motivated by the problem of poverty distribution in West Sumatra Province, which still varies between regions. The objectives of this study are to build a prediction model using the Support Vector Machine (SVM) algorithm, evaluate the model's performance, and implement the prediction results in the form of an interactive dashboard to support local government decision-making. The study uses secondary data from the Central Statistics Agency (BPS) of West Sumatra Province for the period 2015–2024, covering 19 districts/cities. The dependent variable is the percentage of poor people (P0), while the independent variables consist of seven socio-economic indicators. The method used refers to the CRISP-DM stages. In the data preparation stage, missing values are handled using median imputation, outliers are handled using winsorizing, standardization is carried out using Z-Score, and the addition of a one-period lag variable (P0_lag1). The data is divided into training data (2015–2022) and test data (2023–2024), with parameter optimization using GridSearchCV and TimeSeriesSplit. The results showed that the Support Vector Regression (SVR) model with a radial basis function (RBF) kernel provided the best performance with parameters C=1000, epsilon=0.05, and gamma=0.001. This model produced an MAE value of 0.32, RMSE of 0.36, and R² of 0.98. The implementation of the prediction results in the Streamlit dashboard for the 2025–2030 period showed a downward trend in poverty levels in most regions. This model is considered effective as a basis for planning and evaluating data-based poverty alleviation policies.
Sosialisasi Sistem Informasi Penerimaan Peserta Didik Baru (PPDB) Otomatis Menggunakan WhatsApp Bot Sebagai Layanan Customer Service 24 Jam Mardiyah, Ainil; Fadhli, Irfan; Rahmadani, Dhea Nesvira; Purnama, Desma Rita; Hanafi, Muhammad; Zikri, Fardhan
Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat Vol. 5 No. 1 (2026): Volume 05 Nomor 01 (April 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/d16et956

Abstract

Penerimaan Peserta Didik Baru (PPDB) merupakan salah satu proses penting dalam institusi pendidikan yang memerlukan sistem pelayanan informasi yang efektif dan efisien. Namun, pada praktiknya, layanan PPDB di SMKN 3 masih menghadapi kendala, seperti keterbatasan waktu pelayanan, tingginya beban kerja panitia, serta kurang optimalnya penyampaian informasi kepada calon peserta didik. Oleh karena itu, diperlukan inovasi berbasis teknologi untuk meningkatkan kualitas layanan customer service. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mensosialisasikan sistem informasi PPDB otomatis berbasis WhatsApp Bot sebagai layanan Customer Service 24 jam di SMKN 3. Metode pelaksanaan dilakukan melalui tahapan persiapan, pelaksanaan, dan evaluasi dengan pendekatan partisipatif dan aplikatif. Kegiatan meliputi penyampaian materi, demonstrasi sistem, praktik langsung, serta kuis interaktif yang disertai pemberian reward untuk meningkatkan partisipasi peserta. Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan keterampilan peserta dalam menggunakan sistem, serta respon positif terhadap penerapan WhatsApp Bot sebagai media layanan informasi. Sistem ini dinilai mampu meningkatkan efisiensi pelayanan, mempercepat respon, dan mengurangi beban kerja panitia PPDB. Dengan demikian, kegiatan ini memberikan kontribusi dalam mendukung transformasi digital layanan pendidikan.
Implementasi Sistem Informasi Berbasis Web dengan Fitur Chatbot untuk Meningkatkan Layanan Konsultasi Ainil Mardiyah; Delsi Kariman; Irfan Fadhli; Muthia Ananda; Jasril Jasril
JKM: Jurnal Kemitraan Masyarakat Volume 4 Number 2 Desember 2025
Publisher : Program Studi Pendidikan IPA Fakultas MIPA Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jkm.v4i2.78783

Abstract

The purpose of this community service activity is to help schools improve their consultation services by utilizing a web-based information system equipped with a chatbot feature. Furthermore, it also digitizes consultation data management. The program implementation consists of several stages: outreach, training, system implementation, mentoring, and evaluation. After the activity was completed, there was a significant improvement in the ability of teachers and staff to manage the digital system, increased ease of consultation for parents, and improved structured data documentation. The system used also expanded the reach of consultation services without the constraints of space and time. Furthermore, it reduced the administrative burden on teachers. This system can be applied to other schools to encourage the digital transformation of educational services.
ANALISIS KESALAHAN SISWA DALAM MENYELESAIKAN SOAL MATEMATIKA BERDASARKAN KEMAMPUAN AKADEMIK SISWA Devi Andayani; Ainil Mardiyah; Mulia Suryani
AXIOM : Jurnal Pendidikan dan Matematika Vol 11, No 1 (2022)
Publisher : State Islamic University of North Sumatra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30821/axiom.v11i1.9066

Abstract

Tujuan penelitian ini untuk mengetahui bagaimana kesalahan siswa dalam menyelesaikan soal matematika berdasarkan kemampuan akademik. Subjek dalam penelitian adalah siswa kelas XI IPA SMA PGRI 2 Padang. Jenis penelitian ini adalah penelitian deskriptif dengan pendekatan kuantitatif. Teknik pengumpulan data yang digunakan adalah tes, wawancara, dan dokumentasi, sedangkan instrumen yang digunakan berupa soal tes limit fungsi aljabar, pedoman wawancara dan dokumentasi. Hasil penelitian ini menunjukkan bahwa: siswa berkemampuan tinggi melakukan kesalahan fakta sebesar 0%; kesalahan konsep sebesar 25%; kesalahan prinsip sebesar 25%; dan kesalahan prosedural sebesar 50%, siswa berkemampuan sedang melakukan kesalahan fakta sebesar 42,86%; kesalahan konsep sebesar 42,86%; kesalahan prinsip sebesar 85,71%; kesalahan prosedural 28,57%, dan siswa berkemampuan rendah melakukan kesalahan fakta sebesar 18,18%; kesalahan konsep sebesar 72,73%; kesalahan prinsip sebesar 72,73%; kesalahan prosedural sebesar 29,22%. Penyebab siswa melakukan kesalahan adalah kurangnya ketelitian dalam menjawab soal, kurangnya pemahaman siswa tentang konsep penyelesaian limit fungsi aljabar, serta kurangnya kemampuan siswa dalam mengoperasikan bentuk aljabar.AbstractThis study aims to see students' mistakes in solving math problems based on academic ability. The subjects in the study include students of class XI (the ninth grade) of IPA SMA PGRI 2 Padang. This is a descriptive study with a quantitative approach. The data collection techniques used were tests, interviews, and documentation, while the instruments used were algebraic function limit tests, interview guidelines, and documentation. The results of this study indicate that: high-ability students made factual errors by 0%; concept errors by 25%; principal errors by 25%; and procedural errors by 50%, moderately capable students made a factual error of 42.86%; concept error of 42.86%; principle error of 85.71%; procedural errors were 28.57%, and students with low ability made factual errors of 18.18%; concept error of 72.73%; principle error of 72.73%; procedural error of 29.22%. The causes of students making mistakes are the lack of accuracy in answering questions, the lack of understanding of the concept to solve algebraic functions, and the lack of students' ability to operate algebraic forms.
Sigil software based e-module validation for class VII students on data presentation material Melisha Apriliani; Ainil Mardiyah; Ratulani Juwita
UNION : Jurnal Ilmiah Pendidikan Matematika Vol 11 No 2 (2023)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/union.v11i2.13767

Abstract

The purpose of this research is to produce an Android-based e-Module using Sigil software that is valid and practical for Class VIIA Data Presentation at SMP N 24 Padang that is valid and practical so that it can be used as a source of learning mathematics, especially data presentation material. The type of research used is development research. This research uses the Plomp model. The stages used in this development model are only stages 1 to stage 2, namely the initial investigation stage, the prototyping phase which concurrently tests the validity and practicality. The research instrument used is a validation questionnaire, a one-on-one test questionnaire that is useful for seeing the practicality of e-Modules by teachers, small group test questionnaires that are useful for seeing the practicality of e-Modules by students and interview guidelines. Based on the validator's assessment, the results of the validity of the Android-based e-Modul using the Sigil software were 90.33% with a very valid category. The final value of practicality with the teacher obtained a final score of 80% in the practical category. The final value of practicality with students was obtained 88.61% with a very practical category. Based on the results of the study, it can be concluded that the Android-based e-Module using Sigil software in Data Presentation in class VIIA SMP N 24 Padang is valid and practical for use by teachers and students.
Analisis Sentimen TikTok Shop pada Media Sosial Twitter Menggunakan Algoritma Naïve Bayes Delsi Kariman; Ainil Mardiyah; Junios Junios; Lisma Sari; Muthia Ananda; Jasril Jasril
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3096

Abstract

The progress of TikTok Shop as an e-commerce platform has generated various public responses, including both support and criticism.  Therefore, sentiment analysis is needed to determine user opinion.  The purpose of this study is to categorize Twitter users' sentiments about TikTok Shop into positive, negative, and neutral categories.  Data was collected through web scraping techniques, followed by pre-processing stages, namely case folding, tokenization, stopword removal, and stemming.  Next, features were extracted using Term Frequency-Inverse Document Frequency (TF-IDF).  The Naïve Bayes algorithm was applied to classify the sentiment in the processed tweets.  To perform the evaluation, a confusion matrix was used with accuracy, precision, recall, and F1-score metrics.  The evaluation results show that the model achieves high accuracy (0.9602). However, the model experiences problems in classifying minority classes, namely positive and negative classes, due to an unbalanced class distribution, with neutral classes dominating the dataset. These findings highlight the importance of addressing class imbalance to improve model performance in predicting positive and negative sentiment.Keywords: Sentiment Analysis; TikTok Shop; Social Media; Twitter; Naïve Bayes AbstrakKemajuan TikTok Shop sebagai platform e-commerce memunculkan berbagai tanggapan publik yang mencakup dukungan maupun kritik.  Oleh karena itu, untuk mengetahui opini pengguna diperlukan analisis sentimen.  Tujuan penelitian adalah untuk membagi sentimen pengguna Twitter tentang TikTok Shop menjadi kategori positif, negatif, dan netral.  Data dikumpulkan melalui teknik web scraping kemudian diikuti tahap pre-pemrosesan, yaitu case folding, tokenisasi, stopword removal, dan stemming.  Selanjutnya fitur diekstraksi menggunakan Term Frequency-Inverse Document Frequency (TF-IDF).  Algoritma Naïve Bayes diterapkan untuk mengklasifikasikan sentimen pada tweet yang telah diproses.  Untuk melakukan evaluasi, confusion matrix digunakan dengan metrik akurasi, precision, recall, dan F1-score.  Hasil evaluasi menunjukkan bahwa model mencapai akurasi yang tinggi (0,9602).  Namun, model mengalami masalah dalam klasifikasi kelas minoritas, yaitu kelas positif dan negatif, yang disebabkan oleh distribusi kelas yang tidak seimbang, dengan kelas netral yang mendominasi dataset.  Temuan ini menunjukkan pentingnya menangani ketidakseimbangan kelas untuk meningkatkan kinerja model dalam memprediksi sentimen positif dan negatif. 
MODEL PREDIKSI CURAH HUJAN HARIAN KOTA PADANG MENGGUNAKAN DEEP NEURAL NETWORK (DNN) Aisyah Fadri; Satrio Junaidi; Ainil Mardiyah
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 3 (2026): June 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i3.6561

Abstract

Extreme weather in coastal areas such as Kota Padang is influenced by complex topography and local atmospheric dynamics, making daily rainfall prediction a critical challenge for disaster mitigation and sectoral planning. This study aims to develop a daily rainfall prediction model using a Deep Neural Network (DNN) and evaluate its performance. The dataset consists of daily temperature, humidity, and air pressure data collected from the Automatic Weather Station (AWS) of BMKG Maritime Teluk Bayur from January 2020 to December 2024, comprising 1,823 samples after preprocessing. The research methodology follows the CRISP-DM framework, which includes six main phases. The proposed DNN architecture contains three hidden layers (128, 64, and 32 neurons) with ReLU activation and dropout regularization, enhanced by lag and rolling average features to capture temporal patterns. The model achieved an MAE of 1.79, RMSE of 17.31, and R² of 0.8972, indicating strong predictive performance. The model was deployed through a Streamlit-based interactive dashboard
Co-Authors Aisyah Fadri Alfi Yunita Alfi Yunita Alfi Yunita Ali Asmar Amelia Putri Amelia putri Anisa, Husna Anna Cesaria Annisa Pramadhany Asmar, Ali Audra Pramitha Muslim, Audra Pramitha Delsi K Delsi K Delsi K Desi Surya Tuti Desti Handika Putri Devi Andayani Dewi Ratnasari Dewi Yuliana Fitri Dona Siska E. Edimuslim Ega Meilia Puspita Eka Putriana Agustin Elmi Darwati Eva Nolisa Eva Pebri Ningsih Fadhli, Irfan Feny Seprinelfi Fitri Yulia Ningsih Fitria Maiza Gezi Afrianti Gusmanengsih Gusmanengsih Hafizah Delyana, Hafizah Hamdunah Iga Silviana Irfan Fadhli Irianti, Erika Irvani Rahmi Isra, Rilla Juni Istikhfar Istikhfar Jasril Jasril Junios Junios Karmila Karmila Lisma Sari Lita Lovia Lita Lovia Lita, Lovia Maiyuli Herni Marianto Marianto Melisa Melisa Melisha Apriliani Mella Winny Putri Minora Longgom. Nst Muhammad Hanafi Mulia Suryani Mursyida Mursyida Muthia Ananda Nadia Cahyadi Nadia Deswinda Ni Wayan Suniasih Nia Febriyani Nia Febriyani Purnama, Desma Rita Puspita, Ega M Putri Angriani Putri, Desti Handika Putri, Fauza Yolanda Putri, Melani Septina Putriardi Pratama, Lara Qori’a Nur Ustaza Radhya Yusri, Radhya Rahmadani, Dhea Nesvira Rahmadani, Nur Rahmawati, Sherli Rahmi Rahmi Rahmi, Agusti Ramadoni, Ramadoni Ratulani Juwita RATULANI JUWITA, RATULANI Rida Welita Rike Marjulisa Riri Oktafia Sari, Anggun Permata Satrio Junaidi Sefna Rismen Sherli Rahmawati Sindi Aulia Sisri Yunita Sofia Edriati Sovia Zulni SRI RAHAYU Syari, Engla Devia Tahnia Dinda Rahmadanti Ton Trisno Villia Anggraini Wasliati, Nova Winda Wulan Dari Witri Mai Darwin Yulia Haryono Zainal, Hardani Mardiana Zainal, Hardhani Mardiana Zikri, Fardhan Zulfaneti Zulfaneti Zulfitri Aima Zulma Hendra