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All Journal JURNAL PENDIDIKAN TAMBUSAI JEKKP (JURNAL EKONOMI, KEUANGAN DAN KEBIJAKAN PUBLIK) INVENTION: Journal Research and Education Studies Mudabbir: Journal Research and Education Studies Media Farmasi Indonesia Journal Of Safety and Health Worksheet : Jurnal Akuntansi Coreid Journal
Aulia, Citra
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Economics, Econometrics & Finance Education Health Professions Immunology & microbiology Medicine & Pharmacology Public Health Social Sciences Other

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Pemahaman Konsep Barisan Aritmatika Malay, Irvan; Aulia, Citra; Nainggolan, Eva Elisa S; Cahyadi, Taufik Nur
Jurnal Pendidikan Tambusai Vol. 10 No. 1 (2026)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v10i1.36557

Abstract

Pemahaman konsep barisan aritmatika memiliki peranan penting dalam pembelajaran matematika karena membantu peserta didik memahami keteraturan pola bilangan serta hubungan antar suku secara runtut. Materi barisan aritmatika tidak hanya menuntut kemampuan menggunakan rumus, tetapi juga pemahaman terhadap konsep dasar, seperti suku pertama, beda, dan suku ke-n, beserta penerapannya dalam berbagai permasalahan. Peserta didik yang memiliki pemahaman konsep yang baik umumnya mampu menjelaskan kembali konsep barisan aritmatika dengan bahasanya sendiri, mengaitkannya dengan situasi sehari-hari, serta menyelesaikan permasalahan matematika secara logis. Sebaliknya, peserta didik yang kurang memahami konsep cenderung hanya menghafal rumus, sehingga sering mengalami kesalahan dalam proses penalaran dan penyelesaian soal. Oleh karena itu, pembelajaran barisan aritmatika perlu dirancang secara lebih bermakna dengan menekankan pemahaman konsep, proses berpikir, dan penerapan dalam kehidupan nyata agar penguasaan konsep dapat berlangsung secara optimal dan berkelanjutan.
Short Message Spam Classification using Decision Tree, Naive Bayes, and Logistic Regression Aulia, Citra; Dinah, Azalia Fathimah; Zahratunnisa, Dzilan Nazira; Efendi, Rofik
CoreID Journal Vol. 3 No. 3 (2025): November 2025
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v3i3.146

Abstract

The increasing use of Short Message Service (SMS) in digital communication has been accompanied by a rise in spam messages, which threaten user convenience and information security. This study presents a comparative analysis of three classical machine learning algorithms—Decision Tree, Naïve Bayes, and Logistic Regression—for SMS spam classification. The research follows the CRISP-DM methodology, including data collection, understanding, preparation, modeling, and evaluation. The dataset used is the SMS Spam Collection (A More Diverse Dataset) from Kaggle, comprising 5,574 SMS messages labeled as spam or ham. Text preprocessing is performed through cleaning operations and feature extraction using the Term Frequency–Inverse Document Frequency (TF-IDF) method. The models are evaluated using accuracy, precision, recall, F1-score, and Area Under the Curve (AUC) metrics. Experimental results indicate that Logistic Regression achieves the most balanced performance, with an accuracy of 97.13%, precision of 99.23%, recall of 80.75%, F1-score of 89.04%, and an AUC of 98.72%. Naïve Bayes demonstrates high efficiency and perfect precision but lower recall, while Decision Tree offers interpretability with comparatively lower classification performance. The results suggest that Logistic Regression is the most suitable model for lightweight and reliable SMS spam detection systems, balancing accuracy and misclassification risk. This study provides practical insights for implementing efficient spam filtering solutions and serves as a reference for future research in text classification and natural language processing, particularly for short-message communication.
Co-Authors Al Zahwa, Afitzka Anja, Eka Suci Barus, Muhammad Joni Cahyadi, Taufik Nur Dinah, Azalia Fathimah Elfayetti Elfayetti Elsa Kardiana Elviani, Sri Fitriani, Fitrianti Hamida, Novelia Harefa, Meilinda Suriani Haza, Suci Amaliah Hesti Wulan, Hesti Hutauruk, Mutiara Cristeofani Kautsar, M. Anas Lubis, Farida Khairani Lumbangaol, Riski Fanni Malay, Irvan Muftih, Anisa Nainggolan, Eva Elisa S Nurmala Berutu Pirnama Widagdo, Dian Purba, Tondang Raja P. Rahmadayanti, Rahmadayanti Rahmah, Mawaddah Ramadona Simbolon Rofik Efendi Simaremare, Ermas Simarmata, Claudia G.N. Siregar, Kholila Yuli Yanti Siregar, Risbue Syukri Hidayat Yunazar Manjang Zahratunnisa, Dzilan Nazira Zahwa, Afitzka Al