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The Relationship of Offline Learning with Discrete Mathematics Learning Interests After the Pandemic Lilia Sinta Wahyuniar; Dwi Harini; Umi Mahdiyah; Siti Rochana
Journal of Instructional Mathematics Vol. 3 No. 1 (2022): Ethics and Mathematical Ability in Online-Mediated Learning Environments
Publisher : Pendidikan Matematika STKIP Kusuma Negara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37640/jim.v3i1.1378

Abstract

This article aims to determine the relationship between offline learning and interest in learning discrete mathematics after the pandemic. The research method used is quantitative. The sampling technique in this study used purposive sampling. Data collection in this study used a questionnaire with a Likert scale of 1 to 5. The variables in this study consisted of variable X, namely offline learning and variable Y, namely interest in learning. Each variable consists of 4 indicators. The result of this research is that there is a relationship between offline learning and students' interest in learning in discrete mathematics courses of 0.801. So it can be said that the relationship between offline learning and learning interest is very strong. This is because in offline learning students can interact directly with the lecturer so that discrete mathematics material that has not been understood can be directly asked during learning. Offline learning can also encourage interest in learning so that students are more enthusiastic and enthusiastic about participating in discrete mathematics lectures.
Application of Problem-Based Learning Model to Improve Problem Solving Ability Siti Rochana; Lilia Sinta Wahyuniar; Umi Mahdiyah
Journal of Instructional Mathematics Vol. 3 No. 2 (2022): Connecting Mathematical Concepts in Learning and Solving Problems
Publisher : Pendidikan Matematika STKIP Kusuma Negara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37640/jim.v3i2.1542

Abstract

This study aims to improve the problem solving ability of class VIII junior high school students. This research was conducted after the preliminary study it was found that problem solving abilities were still relatively low. Observational shows that more than 50% of class VIII students of SMP Muhammadiyah 3 Depok have poor problem solving skills. Based on the theory put forward some expert of experts, the researchers decided to apply the problem-based learning model. This study uses classroom action research design with a target of 50% of students having a problem solving ability score above the Kriteria Ketuntasan Minimal (KKM). There are four stage of this research, namely planning, implementation, observation and reflection. The data collection technique using the test and non-test techniques. Data analysis using descriptive analysis of quantitative and qualitative analysis descriptive. From the results of the study, it was found that 77% of students had problem solving scores above the KKM. Besides that, it was found that student were able to work on the questions in a more structured manner and could better understand the questions given.
The Influence of Mathematical Logical Intelligence on Student Learning Outcomes in Linear Algebra Courses Lilia Sinta Wahyuniar; Umi Mahdiyah; Siti Rochana; Dwi Harini
Journal of Instructional Mathematics Vol. 4 No. 2 (2023): Enhancing Mathematics Learning through Innovative Pedagogies
Publisher : Pendidikan Matematika STKIP Kusuma Negara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37640/jim.v4i2.1871

Abstract

The purpose of this study was to determine the effect of mathematical logical intelligence on student learning outcomes in Linear Algebra courses. The research method used is quantitative. The sampling technique used in this study was simple random sampling. Data collection in this study used a mathematical logical intelligence test of 20 multiple choice questions and a test of student learning outcomes in linear algebra courses of 5 description questions. The variables in this study consisted of independent variables and dependent variables. The independent variable in this study is mathematical logical intelligence (X), while the dependent variable in this study is student learning outcomes in Linear Algebra courses (Y). The instrument test in this study consisted of validity test, distinguishing power, difficulty level and reliability test. The classical assumption test in this study consists of normality test and linearity test. The data analysis technique used simple linear regression. The result of this study is that there is an influence between mathematical logical intelligence on student learning outcomes in linear algebra courses of 0.527 or 53%. While the other 47% is influenced by other variables outside this study.
Pelatihan Pengolahan Bawang Merah dengan Alat Pebmo Pada Kelompok Petani Bawang Merah Di Desa Sekoto Kabupaten Kediri Indrawati, Elsanda Merita; Munawi, Hisbullah Ahlis; Suwardono, Agus; Santoso, Rachmad; Manikta, M. Dewi; Mahdiyah, Umi; Nadliroh, Kuni; Nevita, Ary Permatadeny
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 3 No 2 (2020): Volume 3 Nomor 2 Tahun 2020
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v3i2.13823

Abstract

Sekoto Village is the largest onion producer center in Kediri Regency. The aim of this service activity is to provide training on processing low quality shallots into high quality fried onion products using an Automatic Shallot Processing Machine (PEBMO) that is practical, effective and efficient. The activity material provided was about the marketing of shallots and the processing of low quality shallots starting from stripping of shallots, chopping onions, and draining oil using an Automatic Shallot Processing Machine (PEBMO). Community service activities (PKM) which include (1) observation; (2) design and provision of tools (PEBMO) to shallot farmers; (3) socialization; (4) training and practice; (5) monitoring. This activity is useful to increase the income of shallot farmers, this is because low quality shallots are processed into high-quality fried onion products with a stable selling price, so that shallot farmers will not lose if the yields produced have low quality.
Optimasi Prediksi Harga Ayam Boiler Berdasarkan Time Series Data dan Kondisi Eksisting Menggunakan Decision Tree Niswatin, Ratih Kumalasari; Setiawan, Ahmad Bagus; Mahdiyah, Umi
Nusantara of Engineering (NOE) Vol 8 No 02 (2025): Volume 8 Nomor 2 - 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/noe.v8i02.24878

Abstract

Predicting the price of boiler chicken is important in the chicken farming industry. Business actors need to have accurate price estimates as a reference in planning production and sales. However, precise and accurate price predictions can be challenging because they are influenced by various factors such as market conditions, demand, supply, and other factors. Therefore, this research was conducted to develop a boiler chicken price prediction method that can optimize prediction results by utilizing time series data and existing conditions using the Decision Tree C.45 algorithm. The aim of this research is to optimize boiler chicken price predictions based on time series data and existing conditions using the Decision Tree C.45 algorithm. By processing time series data and analyzing existing conditions, it is hoped that a more accurate prediction model can be obtained and can provide better results in predicting the price of boiler chicken. Apart from that, by implementing the Decision Tree C.45 algorithm, this research also aims to test the effectiveness of this algorithm in predicting the price of boiler chicken. The result of this research is a system that can accurately predict the price of boiler chicken, so that it can be used as an important basis for making decisions regarding determining the price of boiler chicken and inventory management.
Hybrid Ensemble Learning Sistem Keamanan Jaringan Untuk Meningkatkan Performa Deteksi Anomali Irawan, Rony Heri; Irawan, Rony Heri Irawan; Nico Adi Saputra; Umi Mahdiyah
Nusantara of Engineering (NOE) Vol 8 No 02 (2025): Volume 8 Nomor 2 - 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/noe.v8i02.25617

Abstract

Serangan siber seperti zero-day attacks dan APT menjadi tantangan serius bagi sistem deteksi intrusi jaringan, terutama yang masih mengandalkan metode berbasis tanda tangan. Penelitian ini bertujuan merancang sistem deteksi anomali jaringan berbasis hybrid ensemble learning dengan menggabungkan algoritma Isolation Forest, K-Means, dan Random Forest menggunakan metode majority voting. Proses penelitian meliputi preprocessing data, pelatihan dan evaluasi model menggunakan dataset publik CSE-CIC-IDS2018. Evaluasi dilakukan dengan metrik akurasi, precision, recall, F1-score, dan AUC. Hasil menunjukkan bahwa pendekatan hybrid ini meningkatkan akurasi deteksi hingga 99,9% dan menurunkan false positive secara signifikan dibanding pendekatan tunggal. Sistem yang diusulkan terbukti lebih adaptif dan efisien dalam mengidentifikasi berbagai pola serangan siber, serta memberikan kontribusi terhadap pengembangan teknologi keamanan jaringan yang lebih andal.
Pencarian Rongga Berpotensi Binding Site pada Protein dengan Menggunakan Support Vector Machine (SVM) Umi Mahdiyah
Limits: Journal of Mathematics and Its Applications Vol. 14 No. 2 (2017): Limits: Journal of Mathematics and Its Applications Volume 14 Nomor 2 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Bioinformatika merupakan ilmu multidisipliner yang melibatkan berbagai bidang ilmu. Salah satu aplikasi dari bioinformatika adalah dalam proses desain obat berbantuan komputer. Dalam desain obat berbantuan komputer salah satu langkah awal yang dibutuhkan adalah mencari suatu rongga pada protein, rongga tersebut nantinya untu melekat suatu ligan(partikel kecil) maupun protein yang merupakan partikel atau protein dari calon obat. Dalam penelitian ini untuk pencarian binding site digunakan metode klasifikasi dengan Support Vector Machine. Hasil dari pencarian binding site dengan metode ini menunjukkan akurasi G-Mean yang cukup tinggi yaitu 0,903 atau 90,3