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All Journal Electronic Journal of Graph Theory and Applications (EJGTA) Jurnal Fourier Al-Jabar : Jurnal Pendidikan Matematika Science and Technology Indonesia Jurnal Penelitian Pendidikan IPA (JPPIPA) Limits: Journal of Mathematics and Its Applications Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Jurnal Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Pedagogy : Jurnal Pendidikan Matematika Journal of Fundamental Mathematics and Applications (JFMA) Bulletin of Applied Mathematics and Mathematics Education Prosiding Seminar Nasional Pengabdian Masyarakat Bioma : Jurnal Ilmiah Biologi
Wijayanti, Dian Eka
Universitas Ahmad Dahlan
Agriculture, Biological Sciences & Forestry Arts Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics

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Optimization of feature selection on semi-supervised data Wijayanti, Dian Eka; Afriyani, Sintia; Surono, Sugiyarto; Dewi, Deshinta Arrova
Bulletin of Applied Mathematics and Mathematics Education Vol. 4 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/bamme.v4i1.11104

Abstract

This research explores feature selection optimization in semi-supervised text data by utilizing the technique of dividing data into training and testing sets and implementing pseudo-labeling. Proportions of data division, namely 70:30, 80:20, and 90:10, were used as experiments, employing TF-IDF weighting and PSO feature selection. Pseudo-labeling was applied by assigning positive, negative, and neutral labels to the training data to enrich information in the classification model during the testing phase. The research results indicate that the linear SVM model achieved the highest accuracy with a 90:10 data division proportion with a value of 0.9051, followed by Random Forest, which had an accuracy of 0.9254. Although RBF SVM and Poly SVM yielded good results, KNN showed lower performance. These findings emphasize the importance of feature selection strategies and the use of pseudo-labeling to enhance the performance of classification models in semi-supervised text data, offering potential applications across various domains that rely on semi-supervised text analysis.
IMPLEMENTASI TEORI BILANGAN DALAM PERMAINAN KARTU UNO Andryan, Eky; Wijayanti, Dian Eka
Pedagogy: Jurnal Pendidikan Matematika Vol. 9 No. 1 (2024): Pedagogy : Jurnal Pendidikan Matematika
Publisher : Universitas Cokroaminoto Palopo

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

Abstract

Teori bilangan adalah bidang matematika yang mempelajari bilangan. Teori bilangan dapat digunakan dalam berbagai permainan kartu, salah satunya dalam permainan kartu uno, yang menggunakan lambang bilangan pada kartu-kartunya. Permainan ini dapat digunakan sebagai media pembelajaran anak-anak usia dini dalam memahami lambang bilangan, peluang menang atau kalah, dan strategi permainan. Penelitian ini menggunakan metode kombinatorika dan teori peluang dalam menganalisis aspek peluang munculnya kartu dan peluang kemenangan dalam permainan kartu uno dengan strategi tertentu. Selain mencoba eksperimen langsung bersama teman, pengumpulan data dapat menggunakan perangkat bertanding dengan komputer dan menganalisis data dari hasil turnamen-turnamen. Dengan demikian, penerapan teori bilangan dalam permainan kartu uno dapat membantu anak-anak usia dini memahami konsep bilangan. Dari hasil penelitian yang dilakukan, dapat disimpulkan bahwa setiap kartu aksi memiliki peluang muncul yang sama dalam satu set permainan. Peluang munculnya reverse card, skip card, Wild Draw card, draw +2 card, dan Wild Draw +4 card adalah sebesar 2/27 atau sekitar 7.41%.
Identification of fingerprint image with Minkowski distance algorithm approach Tulloh, Wisnu Catur Rachmad; Wijayanti, Dian Eka
Bulletin of Applied Mathematics and Mathematics Education Vol. 3 No. 2 (2023)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/bamme.v3i2.9949

Abstract

In the digital era, fingerprint identification plays a critical role in information technology administration. Various studies have been conducted to improve the fingerprint identification process, but there are still cases of identification failures that are fatal. This research discusses fingerprint identification with the Minkowski distance method. The data of fingerprints are taken from Mathematics students and the Kaggle site. Data analysis includes the steps of image retrieval, dimensioning, conversion to grayscale, pattern matching, and accuracy measurement. Results show an improvement in data accuracy with a structured approach to data capture and preprocessing. Results from primary data obtained an accuracy of 56.67% while from secondary data obtained an accuracy of 93%.
Klasifikasi penentuan status gizi balita dengan metode naive bayes Abdillah, Alfiyyah 'Ainul; Thobirin, Aris; Wijayanti, Dian Eka
Jurnal Ilmiah Matematika Vol. 11 No. 1 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jim.v11i1.30139

Abstract

Klasifikasi merupakan pengelompokan untuk memprediksi suatu kelas berdasarkan data dan data-data tersebut memiliki table atau atribut. Salah satu metode dalam klasifikasi adalah naïve bayes. Metode naïve bayes banyak digunakan dalam berbagai bidang penelitian. Pada bidang kesehatan, metode naïve bayes digunakan dalam penelitian kesehatan anak. Salah satu penelitiannya membahas tentang gizi pada bayi dibawah umur lima tahun. Pada penelitian klasifikasi status gizi balita dengan metode naive bayes digunakan untuk melakukan klasifikasi data pada kelas tertentu. Metode naive bayes diterapkan pada penelitian ini untuk mengidentifikasi data balita. Data balita tersebut kemudian dianalisis untuk pembuatan model. Setelah pembuatan model kemudian menentukan model yang terbaik. Selanjutnya, model tersebut digunakan untuk memprediksi data balita di Puskesmas Ponjong I. Hasil penelitian menunjukkan bahwa pembagian data dengan perbandingan 90% data training dan 10% data testing menghasilkan akurasi sebesar 82,14%. Model klasifikasi ini mampu memprediksi status gizi balita dengan lebih baik daripada pembagian data lainnya. Hasil prediksi menunjukkan bahwa terdapat 14 anak dengan status gizi baik, 2 anak dengan gizi kurang, dan 2 anak dengan gizi lebih. Informasi ini memiliki implikasi penting bagi puskesmas, karena puskesmas dapat melakukan perawatan dan pengawasan lebih fokus terhadap kelima balita yang diklasifikasikan memiliki masalah gizi yang buruk.
Text security by using a combination of the vigenere cipher and the rubik's cube method of size 4×4×4 Safitri, Raudhatun; Prasetyo, Puguh Wahyu; Wijayanti, Dian Eka; Arifin, Samsul; Setyawan, Fariz; Repka, Joe
Al-Jabar: Jurnal Pendidikan Matematika Vol 14 No 2 (2023): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v14i2.14276

Abstract

Background: In the current era of technology, information security is increasingly important. The growth of technology leads to a higher level of threat to the security of data and information dissemination, and cryptography is a valuable protective tool.Aim: The primary objective of this research is to enhance text security through the fusion of the Vigenere cipher and the Rubik's cube algorithm. By leveraging this novel approach, we aim to fortify the confidentiality of textual data against potential eavesdroppers and adversaries. To demonstrate the practicality of this method, we perform a simulation using the Python programming language within the Google Colab environment. Method: This study employs a qualitative research methodology supplemented by empirical simulation. The combination of the Vigenere Cipher and the Rubik's Cube algorithm in a 4×4×4 configuration is implemented to encrypt and decrypt text. The simulation is executed using the Google Colab platform, enabling a practical illustration of the encryption process.Result: The results of our research indicate the feasibility of generating ciphertext through the amalgamation of the Vigenere Cipher and the Rubik's Cube algorithm in the specified 4×4×4 configuration. The simulation conducted in Google Colab serves as concrete evidence of the effectiveness and practicality of this combined encryption method.Conclusion: In conclusion, this research offers a compelling approach to bolstering text security in the modern era of information technology. By combining the Vigenere Cipher with the Rubik's Cube algorithm in a 4×4×4 configuration, we have demonstrated the potential to significantly enhance the confidentiality of sensitive textual data. The empirical simulation conducted in Google Colab reaffirms the practicality and viability of this innovative encryption technique, highlighting its potential as a valuable tool in the realm of information security.
The Effect of Polystyrene Microplastic Exposure in the Rearing Water on Muscle Morphology of Mutiara Catfish (Clarias gariepinus Burchell, 1822) Suwartiningsih, Nurul; Aszhara, Aulia Fayzha; Marsela, Rani; Wijayanti, Dian Eka
Jurnal Penelitian Pendidikan IPA Vol 11 No 7 (2025): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i7.11537

Abstract

Polystyrene (PS) is one of the most abundant microplastics in freshwater and can accumulate in fish tissues. This study investigated the effect of PS microplastic exposure in rearing water on the abundance of microplastics in muscle, and the diameter and area of myofibers in Mutiara catfish (Clarias gariepinus). A total of 120 fish were exposed to PS microplastics at concentrations of 0, 1, 10, and 100 mg/L for 28 days. Muscle samples from the right abdomen were processed using the paraffin method and stained with hematoxylin-eosin. Microplastics were extracted using 10% KOH and observed under a stereo microscope. Myofiber diameter and area were measured with Image Raster software. Data were analyzed using the Kruskal-Wallis test. Results showed significant differences among treatments (P<0.05) for all parameters. The control group had the lowest microplastic abundance and the largest myofiber size, while the highest accumulation occurred at 100 mg/L, and the smallest myofiber diameter and area were found at 10 mg/L. Exposure to PS microplastics leads to accumulation in muscle tissue and a reduction in myofiber dimensions. These findings highlight the potential adverse impacts of microplastics on fish health and underline the importance of further studies regarding ecological and human health implications.
DETECTION OF MICROPLASTICS IN BLOOD CLAM (Tegillarca granosa) AND GREEN MUSSEL (Perna viridis) FROM BERINGHARJO MARKET, YOGYAKARTA CITY Suwartiningsih, Nurul; Lailani, Shabrina; Prabakusuma, Adhita Sri; Wijayanti, Dian Eka
BIOMA : Jurnal Ilmiah Biologi Vol. 13 No. 1 (2024): April 2024
Publisher : Prodi Pendidikan Biologi, FPMIPATI, Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/bioma.v13i1.324

Abstract

Plastic is one of the main pollutants in the ocean due to its persistent nature. Plastic in waters can be broken down into pieces <5 mm in size, called microplastics, and enter the bodies of aquatic biota such as shellfish. The objectives of this research was to analyze the abundance and identify the characteristics of microplastics in blood clam and green mussel from Pasar Beringharjo, Yogyakarta City. The method in this research is to sample shellfish from Pasar Beringharjo. The shellfish samples obtained had their meat removed and soaked in 10% KOH for 3 days. The isolation results were filtered and the microplastics obtained were observed under a light microscope to determine their abundance and characteristics. The polymers that make up microplastics are analyzed by FTIR. The abundance and characteristics of microplastics between shellfish kinds were compared using the Mann Whitney test. The results showed that the abundance of microplastics in blood clam (average 839.25 ± 144.24 microplastics/individual) was higher compared to green mussel (average 703.75 ± 159.21 microplastics/individual), but not significantly different (p>0.05). The form of microplastic that dominates in both kinds of shellfish is fragments. The most common color of microplastics found in both kinds of shellfish was black and brown. The size of microplastics in both kinds of shellfish is dominated by the range 0-100 µm. FTIR results indicate the type of nylon polymer (polyamide). Microplastics in blood clam and green mussel from Pasar Beringharjo, Yogyakarta City have almost the same abundance and characteristics.
Co-Authors Abdillah, Alfiyyah 'Ainul Abdul Rouf Alghofari Afriyani, Sintia Andryan, Eky Aris Thobirin Aris Thobirin Aris Thobirin, Aris Aszhara, Aulia Fayzha Cindy Ainun Majid Dewi, Deshinta Arrova Diari Indriati Diari Indriati Hanifah Hanifah Hidayat, Noor Lailani, Shabrina Marsela, Rani Nour, Azty Acbarrifha Puguh Wahyu Prasetyo, Puguh Repka, Joe S Slamin Safitri, Raudhatun Samsul Arifin Samsul Arifin Setyawan, Fariz Setyo Dwi Pratama Slamin Sri Handayaningsih Sugiyarto Surono, Sugiyarto Suwartiningsih, Nurul Tulloh, Wisnu Catur Rachmad Wulansari Romadlon