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All Journal Jurnal Ilmiah Dan Karya Mahasiswa Student Research Journal AR-RUMMAN: Journal of Education and Learning Evaluation
Suci Ramadhani
Universitas Negeri Medan
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Klasifikasi Tumor Otak Menggunakan Local Binary Pattern dan SVM Classifier Wahyu Ardiantito S; Stacyana Jesika Surianto; Suci Ramadhani; Willy Pramudia Ananta
Student Research Journal Vol. 1 No. 6 (2023): Desember : Student Research Journal
Publisher : Sekolah Tinggi Ilmu Administrasi (STIA) Yappi Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/srjyappi.v1i6.823

Abstract

Brain tumors are abnormal cell growths in brain tissue that can be life-threatening. This study aims to classify brain tumors to help early diagnosis. The method used is to extract features from brain MRI images using Local Binary Pattern (LBP) and then classified with Support Vector Machine (SVM). The data used were 2044 brain MRI images consisting of 3 classes namely meningioma, no tumor, and pituitary. The best results were obtained using LBP with a radius of 1 and the number of neighbors 8, while the best SVM model used the RBF kernel with a C value of 50, resulting in 88% accuracy, 86% precision, and 87% recall. It can be concluded that the combination of LBP and SVM methods is effective enough to classify brain tumor types to support early diagnosis.
Implementasi Model Machine Learning dalam Mengklasifikasi Kualitas Air Stacyana Jesika; Suci Ramadhani; Yohanna Permata Putri
Jurnal Ilmiah Dan Karya Mahasiswa Vol. 1 No. 6 (2023): DESEMBER : JURNAL ILMIAH DAN KARYA MAHASISWA
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jikma.v1i6.1162

Abstract

Water quality is an important factor in maintaining human health and environmental sustainability. Water pollution is a major problem in Indonesia, so it is important to monitor and classify water quality effectively. Implementation of machine learning models in classifying water quality can provide important benefits in the environmental and health fields. This research uses two machine learning algorithms, namely KNN and SVM, to classify water quality. The water quality data used comes from the website www.kaggle.com, which was uploaded by MsSmartyPants in 2021 with the title "Water Quality (Dataset for water quality classification)". Implementation of this machine learning model involves the steps of data collection, data pre-processing, selection of relevant attributes, algorithm selection, model training, evaluation, and model implementation for real-time water quality classification.
Pengaruh Evaluasi Pembelajaran Terhadap Peningkatan Motivasi Belajar Matematika Siswa Kelas VIII pada SMP Swasta Ar-Rahman Tiur Malasari Siregar; Hadizah Hadizah; Nasri Titania; Reni Permata Sari; Suci Ramadhani; Zavira Syalwa
AR-RUMMAN: Journal of Education and Learning Evaluation Vol 1, No 2 (2024): Desember 2024
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/arrumman.v1i2.4421

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh evaluasi pembelajaran terhadap peningkatan motivasi belajar matematika siswa kelas VIII di SMP Swasta Ar-Rahman. Pengumpulan data dilakukan melalui angket yang mencakup beberapa aspek evaluasi, seperti frekuensi pemberian evaluasi oleh guru, pemahaman siswa terhadap materi setelah evaluasi, serta dampak evaluasi terhadap motivasi belajar. Hasil penelitian menunjukkan bahwa 45,8% siswa menyatakan guru sering memberikan evaluasi setelah pembelajaran, dan 50% siswa merasa bahwa evaluasi membantu mereka memahami materi dengan lebih baik. Selain itu, 45,8% siswa menyatakan termotivasi untuk belajar lebih giat setelah evaluasi, sementara 41,7% merasa lebih percaya diri dalam menghadapi pelajaran matematika.Penelitian juga menemukan bahwa 50% siswa menyatakan guru sering menjelaskan tujuan evaluasi sebelum pelaksanaan, dan 41,7% merasa evaluasi tersebut sesuai dengan kemampuan mereka. Sebanyak 50% siswa menyatakan bahwa umpan balik dari guru setelah evaluasi jelas dan bermanfaat. Secara keseluruhan, hasil penelitian menunjukkan bahwa evaluasi pembelajaran yang konsisten dan adil dapat meningkatkan motivasi belajar siswa. Umpan balik yang relevan dan jelas juga berperan penting dalam membangun kepercayaan diri siswa terhadap kemampuan mereka dalam memahami matematika.
Co-Authors Hadizah Hadizah Nasri Titania Reni Permata Sari Stacyana Jesika Stacyana Jesika Surianto Tiur Malasari Siregar Wahyu Ardiantito S Willy Pramudia Ananta Yohanna Permata Putri Zavira Syalwa