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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI SAINSMAT JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Journal of Mathematics Education and Application (JMEA) PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika Jurnal Matematika: MANTIK Journal of Mathematics and Mathematics Education (JMME) JMPM: Jurnal Matematika dan Pendidikan Matematika Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jambura Journal of Mathematics Jurnal Matematika UNAND ILKOMNIKA: Journal of Computer Science and Applied Informatics ESTIMASI: Journal of Statistics and Its Application Jambura Journal of Biomathematics (JJBM) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Griya Journal of Mathematics Education and Application Journal of Science and Technology Unnes Journal of Mathematics Journal of Fundamental Mathematics and Applications (JFMA) Jurnal Riset Mahasiswa Matematika Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam Indonesian Journal of Mathematics and Applications Hexagon: Jurnal Ilmu dan Pendidikan Matematika The Indonesian Journal of Computer Science Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Amalgamasi: Journal of Mathematics and Applications Indonesian Journal of Computational and Applied Mathematics Jurnal Didaktik Matematika SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam
NISKY IMANSYAH YAHYA
Universitas Negeri Gorontalo
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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RAINBOW VERTEX-CONNECTION NUMBER ON COMB PRODUCT OPERATION OF CYCLE GRAPH (C_4) AND COMPLETE BIPARTITE GRAPH (K_(3,N)) Yahya, Nisky Imansyah; Fatmawati, Ainun; Nurwan, Nurwan; Nasib, Salmun K
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0673-0684

Abstract

Rainbow vertex-connection number is the minimum colors assignment to the vertices of the graph, such that each vertex is connected by a path whose edges have distinct colors and is denoted by . The rainbow vertex connection number can be applied to graphs resulting from operations. One of the methods to create a new graph is to perform operations between two graphs. Thus, this research uses comb product operation to determine rainbow-vertex connection number resulting from comb product operation of cycle graph and complete bipartite graph & . The research finding obtains the theorem of rainbow vertex-connection number at the graph of for while the theorem of rainbow vertex-connection number at the graph of for for .
Implementation of Graph Coloring on the Map of North Gorontalo District Using the D’Satur Algorithm and the Backtracking Algorithm Imran, Nurain; Achmad, Novianita; Asriadi, Asriadi; Yahya, Nisky Imansyah; Nasib, Salmun K.; Katili, Muh Rifai
Indonesian Journal of Mathematics and Applications Vol. 3 No. 2 (2025): Indonesian Journal of Mathematics and Applications (IJMA)
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.ijma.2025.003.02.5

Abstract

Graph Coloring is the process of assigning colors to vertices such that no adjacent vertices share the same color, using the minimal number of colors possible. This study aims to implement graph coloring to the map of North Gorontalo Regency, which consists of 11 sub-districts and 123 villages, utilizing the D’Satur and Backtracking algorithms. It also compares the algorithms in terms of the smallest chromatic number and identifies strategic points in North Gorontalo Regency, particularly in sub-districts, based on the number of adjacent vertices. The study employed a case study method to gather information, specifically the map of North Gorontalo Regency. The results demonstrate that graph coloring of the map utilizing the D’Satur algorithm produces a chromatic number of (χ = 3) for sub-districts and (χ = 5) for villages. Meanwhile, the Backtracking algorithm yields a chromatic number of (χ = 3) for districts and (χ = 4) for villages. Thus, for sub-district coloring, both algorithms yield the same chromatic number. However, the Backtracking algorithm performs better for village coloring, as it produces the smallest chromatic number. The identified strategic sub-district is Kwandang, which has the highest degree of 4.
Klasifikasi Preferensi Mahasiswa dalam Pemilihan Laptop Menggunakan Analisis Diskriminan Kernel Gaussian Meilan Sigar; Lailany Yahya; Salmun K. Nasib; Nisky Imansyah Yahya; Djihad Wungguli
Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa Vol. 3 No. 5 (2025): Oktober : Bilangan : Jurnal Ilmiah Matematika, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bilangan.v3i5.804

Abstract

Rapid developments in information technology have made laptops an essential device for students, especially those in their final year of study. Choosing the right laptop plays an important role in supporting academic productivity, such as writing theses, analyzing data, and developing software. This study aims to classify the preferences of mathematics students at Gorontalo State University in choosing laptops based on usage characteristics and factors that influence purchasing decisions. The method used is Kernel Discriminant Analysis (KDA) with a Gaussian kernel function and an optimal bandwidth of 0.8. The research data involved 268 respondents divided into training and testing data. The analysis results show that the KDA model has an accuracy rate of 60% on the training data and 52% on the testing data, which indicates the model's ability to recognize student preference patterns despite a decrease in accuracy on new data. Based on the kernel density estimation results, Acer is the most widely used laptop brand, while Zyrex and Apple are rarely chosen. The most influential factor in purchasing decisions is processor specifications, with a contribution of 35.739%, followed by brand, warranty, and price. These findings indicate that hardware characteristics are the main consideration in laptop selection, with most students choosing laptops with Intel Core i5 processors, a minimum of 8GB of RAM, and SSD storage. The results of this study can also be used by universities to provide recommendations for selecting laptops that suit students' academic needs.  
Implementation of Fuzzy Time Series Markov Chain Method using Kernel Smoothing in forecasting the Stock Price of PT. Elnusa Tbk. Mokodompit, Marcela; Nasib, Salmun K; Djakaria, Ismail; Yahya, Nisky Imansyah; Hasan, Isran K.
Indonesian Journal of Computational and Applied Mathematics Vol. 1 No. 1: February 2025
Publisher : Gammarise Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64182/indocam.v1i1.9

Abstract

This research aims to apply the Fuzzy Time Series Markov Chain combined with Kernel Smoothing in forecasting stock prices. The Kernel Smoothing technique is used to smooth stock data before the fuzzification process, resulting in more accurate predictions. The research stages include Data Smoothing, Fuzzy interval formation, Fuzzy Logical Relationship and Fuzzy Logical Relationship Group formation, and forecasting using Markov Chain Transition Matrix. Evaluation using MAPE shows a low prediction error rate, with a value of 0.005974257%, so this method is effective for volatile stock data. The implementation of this model is expected to be a reference for investors and analysts in understanding and predicting future stock price movements.
Developing Number Puzzle Learning Media for Elementary School Dyslexic Students: Single Subject Research Sumarno Ismail; Nursiya Bito; Franky Alfrits Oroh; Nisky Imansyah Yahya; Fuzi Sandra Talibo
Didaktik Matematika Vol 10, No 2 (2023): October 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jdm.v10i2.30955

Abstract

A child displaying symptoms of dyslexic learning disorders requires assistance in accurately identifying numbers, particularly those that share resemblances. This research aimed to develop media for teaching dyslexic children to help them identify numbers correctly.This research employed a development and single-subject research method.The subject was a child with symptoms of dyslexia learning disorders from primary school in Gorontalo, Indonesia. The research instruments used were observation sheets and media validation. The findings revealed that prior to engaging with the puzzle activity, the dyslexic student demonstrated the capability to identify a range of 4 to 5 numbers accurately. However, after participating in the puzzle activity, the dyslexic student exhibited an improved performance, achieving the ability to correctly recognize and recall 8 to 10 digits in both writing and memory. The number puzzle media was developed by dividing the puzzle into two parts: the part of the screen containing the complete picture and the base placing the puzzle pieces. The puzzle pieces were made by stacking several formed duplex parts, then covered with paper glued together to create a waterproof product. The puzzle focused on the numbers contrasting in color. The numbers were divided into several parts to make it easier for dyslexic students to identify models of these numbers. After conducting media testing on a dyslexic student, the analysis demonstrated a positive impact of the media on learning outcomes. This research suggests a notable improvement in the numerical identification skills of the dyslexic student
Algatika: Mathematics Private Lending Applications As An Effort To Increase Students Learning Interest In Mathematics Learning Sari, Septi Rahmita; Sidik, Amelia T. R.; Yahya, Nisky Imansyah
Journal of Mathematics and Mathematics Education Vol 11, No 1 (2021): Journal of Mathematics and Mathematics Education (JMME)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jmme.v11i1.52740

Abstract

In the era of sustainable development, education is a fundamental right for everyone. Education is a process of helping humans develop themselves so that they can face all problems with an open attitude. One way to help students clarify the concepts and understanding of mathematics that is being studied during the learning process is by using teaching aids. Teaching aids serve to facilitate the purpose of implementing learning in schools. However, the fact is that the use of mathematics teaching aids during learning at school is not yet entrenched, especially in areas far from urban areas, many of which do not have teaching aids. This directly impacts students' lack of understanding and learning experience, resulting in low student learning outcomes. This paper will introduce ALGATIKA, an application of lending mathematics teaching aids for elementary and junior high schools which can later solve these problems. The research methodology used is a qualitative descriptive method by deepening the material through literature studies. The result is that the lack of teaching aids in some schools can be overcome by the ALGATIKA application of lending mathematics teaching aids in elementary and junior high schools. Thus this application can help provide the teaching aids needed to build and improve educational facilities and provide an effective learning environment for all. It can develop students' teaching and learning processes and create higher quality education which leads to relevant and effective learning outcomes in accordance with the targets of the SDG's in education.
Energy and Laplacian Energy of Pythagorean Intuitionistic Fuzzy Graphs with Applications in Medical Diagnosis Networks Anitha Saravanakumar; Jayalakshmi Periyannan; Prasantha Bharathi Dhandapani; Nisky Imansyah Yahya
Jambura Journal of Biomathematics (JJBM) Volume 6, Issue 4: December 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v6i4.33977

Abstract

This study extends fuzzy graph energy analysis by introducing energy and Laplacian energy for Pythagorean Intuitionistic Fuzzy Graphs (PIFGs), a powerful generalization of intuitionistic fuzzy graphs capable of representing higher degrees of uncertainty. A novel connection matrix for PIFGs is defined, and new formulations for energy and Laplacian energy are established, along with sharp lower and upper bounds. Beyond theoretical contributions, the approach is applied to medical diagnosis networks, where vertices represent symptoms,  diagnostic tests,  and diseases,  and edges encode Pythagorean intuitionistic fuzzy relationships. These measures quantify both the overall strength of associations (energy) and their structural irregularity (Laplacian energy), offering interpretable indicators for diagnostic certainty or ambiguity.  The framework provides a robust mathematical basis for decision-making in biomedical contexts where data are uncertain, imprecise, or conflicting.
Implementasi Metode Bidirectional LSTM Dengan Word Embedding FastText Dalam Analisis Sentimen Ulasan Pengguna Aplikasi Maxim Hanz Franklyn Bachruddin Wewengkang; Djihad Wungguli; Nisky Imansyah Yahya; Isran K. Hasan; Siti Nurmardia Abdussamad
Jurnal Riset Mahasiswa Matematika Vol 4, No 5 (2025): Jurnal Riset Mahasiswa Matematika
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v4i5.33358

Abstract

Aplikasi transportasi online kini menjadi bagian penting dalam kehidupan masyarakat Indonesia. Maxim, sebagai salah satu penyedia layanan, perlu memahami persepsi pengguna untuk meningkatkan kualitas layanannya. Penelitian ini menerapkan metode Bidirectional Long Short-Term Memory (BiLSTM) untuk melakukan klasifikasi sentimen terhadap ulasan pengguna aplikasi Maxim di Google Play Store. Untuk memperkuat representasi kata, digunakan word embedding FastText yang mampu menangkap informasi sub-kata secara lebih baik. Data penelitian diperoleh melalui scraping menggunakan package google-play-scraper pada Python. Model BiLSTM yang dilatih dengan konfigurasi hyperparameter optimal berhasil mengklasifikasikan sentimen ulasan secara efektif, dengan hasil accuracy 94%, precision 96%, recall 95%, dan f1-score 95%. Hasil ini menunjukkan bahwa kombinasi BiLSTM dan FastText mampu mendeteksi sentimen positif dan negatif secara akurat dan seimbang, serta relevan untuk mendukung evaluasi kualitas layanan berbasis opini pengguna.
Penerapan Model ARFIMA-LSTM Menggunakan Variasi Estimasi Parameter Pembeda Dalam Meramalkan data IHPBI Trieke Nurfadilah Harun; Ismail Djakaria; Nisky Imansyah Yahya; Salmun K Nasib; Isran K Hasan
Jurnal Riset Mahasiswa Matematika Vol 4, No 5 (2025): Jurnal Riset Mahasiswa Matematika
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v4i5.33303

Abstract

Indeks Harga Perdagangan Besar Indonesia (IHPBI) merupakan indikator penting dalam mengukur perkembangan ekonomi, khususnya pada sektor pertanian yang memiliki pengaruh besar terhadap daya beli masyarakat. Fluktuasi harga di sektor ini berdampak langsung pada kesejahteraan konsumen dan produsen, sehingga diperlukan metode peramalan yang akurat. Penelitian ini bertujuan untuk meramalkan IHPBI sektor pertanian menggunakan pendekatan hybrid Autoregressive Fractionally Integrated Moving Average (ARFIMA) dan Long Short-Term Memory (LSTM), serta membandingkan performa  metode estimasi parameter pembeda terbaik. Model ARFIMA digunakan untuk menangani komponen stasioner dan pola jangka panjang melalui diferensiasi pecahan, sedangkan LSTM digunakan untuk menangkap pola nonlinier dalam data. Keterbaruan dalam penelitian ini adalah membandingkan parameter pembeda terbaik yaitu Local Whittle dan Rescaled Range Statistics dalam hybrid ARFIMA-LSTM. Hasil dari penelitian yaitu peramalan menunjukkan tren naik IHPBI sektor pertanian selama 12 bulan ke depan. Metode estimasi parameter pembeda terbaik dalam model ARFIMA adalah Rescaled Range Statistics dengan nilai sebesar 0,322. Model hybrid ini menghasilkan nilai MAPE sebesar 0,6337853%, yang menunjukkan tingkat akurasi sangat tinggi.
Prediksi Harga Emas Dunia Menggunakan Deep Learning GRU dengan Optimasi Nadam Ismail Saputra R. Harmain; Nurwan Nurwan; Isran K. Hasan; Djihad Wungguli; Nisky Imansyah Yahya
Jurnal Riset Mahasiswa Matematika Vol 4, No 6 (2025): Jurnal Riset Mahasiswa Matematika
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v4i6.36007

Abstract

Volatilitas harga emas yang tinggi menuntut adanya metode prediksi yang andal untuk mendukung pengambilan keputusan investasi. Penelitian ini mengimplementasikan algoritma Gated Recurrent Unit (GRU) berbasis deep learning yang dioptimalkan menggunakan Nesterov-Accelerated Adaptive Moment Estimation (Nadam) untuk memprediksi harga emas harian.Model terbaik diperoleh dengan nilai Mean Squared Error (MSE) sebesar 0, 00012 pada data univariat dan 0, 00027 pada data multivariat. Mean Absolute Percentage Error (MAPE) yang diperoleh masing-masing sebesar 1,107% untuk data univariat dan 1,59% untuk data multivariat. Hasil tersebut mengindikasikan bahwa model GRU dengan optimasi Nadam memiliki performa prediksi yang tinggi, baik pada data deret waktu tanpa penambahan fitur maupun dengan penambahan fitur.
Co-Authors Afifah Farhanah Akadji Akadji, Afifah Farhanah Anitha Saravanakumar Armayani Arsal Aruchamy, Pradeepa Asriadi Asriadi Asriadi Asriadi Bertu Rianto Takaendengan Cindy Aisa Putri Noor Dennynatalis Taha Dhandapani, Prasantha Bharathi Djihad Wungguli Fatmawati, Ainun Franky Alfrits Oroh Fuzi Sandra Talibo Ganesan, Gomathi Hanz Franklyn Bachruddin Wewengkang Hasan S. Panigoro Imran, Nurain Indrawati Lihawa Ismail Djakaria Ismail Saputra R. Harmain Isran K Hasan Jayalakshmi Periyannan Jusuf, Anryan K. Nasib, Salmun Karim, Finansiya S. Abd. Karina Anselia Mamonto Kasim, Afrianto Pratama Khairun Nisa Humolungo La Ode Nashar Lailany Yahya Lakisa, Narti Lakoro, Tiara Mahagaonkar, Pralahad Meilan Sigar Melisa Huntala Mohamad Rivaldi Moha Mokodompit, Marcela Muhammad Rezky F. Payu Muhammad Rifai Katili Narti Lakisa Novianita Achmad Novria Fatmawati Lakutu Nurmardia Abdussamad, Siti Nursiya Bito Nurwan Nurwan Nurwan Nurwan, Nurwan Pranata, Widya Eka Prasantha Bharathi Dhandapani Prasetyo, Deny Ardika Rahim, Delvira Masita Rahmi, Emli Randi Mooduto Randi Mooduto Rauf, Dewi Nur Angriani Resmawan Resmawan Salmun K. Nasib Salmun K. Nasib Sari, Septi Rahmita Sembiring, Rinawati Sidik, Amelia T. R. Siti Nurmardia Abdussamad Sri Lestari Mahmud Suharmin, Wandayana Nur'Amanah Sumarno Ismail Taha, Dennynatalis Tahir, Fauzia D Tahir, Fauzia D. Taufik, Mohamad Alfiransyah Trieke Nurfadilah Harun Wahdania A.T. Ja’a Zulkifli Alamtaha