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All Journal Jurnal Gaussian JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Journal of Mathematics Education and Application (JMEA) SIGMA: Jurnal Pendidikan Matematika Jurnal Sains Matematika dan Statistika AKSIOMA Jurnal Matematika Sains dan Teknologi BAREKENG: Jurnal Ilmu Matematika dan Terapan Teorema: Teori dan Riset Matematika Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jambura Journal of Mathematics Transformasi : Jurnal Pendidikan Matematika dan Matematika Variance : Journal of Statistics and Its Applications ILKOMNIKA: Journal of Computer Science and Applied Informatics Jambura Journal of Mathematics Education JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Griya Journal of Mathematics Education and Application JES-MAT (Jurnal Edukasi dan Sains Matematika) MATHunesa: Jurnal Ilmiah Matematika Research in the Mathematical and Natural Sciences Research Review: Jurnal Ilmiah Multidisiplin Milang Journal of Mathematics and Its Applications PIJAR: Jurnal Pendidikan dan Pengajaran Jurnal Riset Mahasiswa Matematika Euclid Jurnal Ilmiah Ekonomi dan Manajemen Journal of Mathematics, Computation and Statistics (JMATHCOS) Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa Limits: Journal of Mathematics and Its Applications Indonesian Journal of Computational and Applied Mathematics
Djihad Wungguli
UNIVERSITAS NEGERI GORONTALO
Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Analisis Regresi Ordinal untuk Mengetahui Faktor-Faktor yang Mempengaruhi Kepuasan Nasabah Bank BRI Pogogul Buol terhadap Kualitas Pelayanan Teller Yulianti Arbie; Djihad Wungguli; La Ode Nashar
Research Review: Jurnal Ilmiah Multidisiplin Vol. 4 No. 2 (2025): Research Review: Jurnal Ilmiah Multidisiplin (Agustus 2025 - Januari 2026)
Publisher : Transbahasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54923/researchreview.v4i2.274

Abstract

Banking is a service industry that depends heavily on customers’ trust in the services provided. Service quality is a key factor in business success, especially as technological advances continue to drive rapid innovation in banking products and services. Therefore, banks must consistently pay attention to customers’ needs and expectations and strive to fulfill them more effectively and satisfactorily than their competitors. Customer satisfaction represents an individual’s feelings after comparing the perceived performance of a service with their expectations. High levels of satisfaction are essential for maintaining a company’s market position, improving service effectiveness, and strengthening customer loyalty. This study aims (1) to determine the level of customer satisfaction with teller service quality at BRI Pogogul Buol Branch, and (2) to identify the factors that significantly influence satisfaction with teller services. A quantitative research method was applied using a questionnaire as the primary instrument. Data were collected through a Likert scale questionnaire consisting of four response options scored from 1 to 4. The instrument consisted of 27 validated items adapted from earlier instruments, and its reliability was assessed using Cronbach’s Alpha, with values above 0.70 indicating acceptable reliability. The results show that overall customer satisfaction with teller service quality at BRI Pogogul Buol is at a low or dissatisfied level. Furthermore, the analysis identifies empathy as the factor that significantly influences customers’ satisfaction with teller services. The findings highlight the importance of improving interpersonal and empathetic interactions to enhance service quality and strengthen customer trust.
Pemodelan Antrean Pelayanan KTP-El Menggunakan Switched Max-Plus Linear System Pada Berbagai Kondisi Operasional di DISDUKCAPIL Bone Bolango Alya Haja; Mohammad Rifai Katili; Djihad Wungguli
PIJAR: Jurnal Pendidikan dan Pengajaran Vol. 4 No. 3 (2026): Agustus
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/pijar.v4i3.2130

Abstract

Penelitian ini bertujuan memodelkan sistem antrean pelayanan Kartu Tanda Penduduk elektronik (KTP-el) menggunakan pendekatan Switched Max-Plus Linear System (SMPLS) guna mengevaluasi efisiensi waktu pada variasi kondisi operasional yang fluktuatif. Desain studi kasus observasional kuantitatif dengan pendekatan kejadian diskrit diaplikasikan pada alur layanan single channel-multi phase di Disdukcapil Kabupaten Bone Bolango. Data diperoleh melalui observasi terhadap 30 pemohon selama 3 hari pengamatan, yang diklasifikasikan menjadi mode sepi (4 pemohon akibat gangguan jaringan) dan mode ramai (15 pemohon akibat lonjakan kedatangan), dengan hari normal (11 pemohon) sebagai pembanding. Durasi penyelesaian layanan ditransformasikan ke dalam persamaan matriks transisi linear berbasis aljabar max-plus. Model kemudian diekspansi menjadi SMPLS yang mengintegrasikan fungsi peralihan (switching) untuk beradaptasi secara adaptif terhadap perubahan mode operasional tersebut. Validasi model dievaluasi melalui metode simulasi komputasi iteratif. Hasil analisis menunjukkan rata-rata durasi tahap pendaftaran sebesar 2,00 menit, perekaman sebesar 2,63 menit, dan pencetakan sebesar 2,27 menit. Simulasi matriks peralihan menunjukkan bahwa total waktu lintasan pelayanan meningkat dari 6,50 menit pada kondisi sepi menjadi 7,26 menit pada kondisi ramai. Lebih lanjut, kalkulasi nilai dominan (cycle time) mengidentifikasi tahap perekaman biometrik sebagai tahapan kritis yang mendominasi laju pertumbuhan waktu antrean secara keseluruhan. Anomali tingginya nilai dominan pada kondisi sepi (3,00 menit) dibandingkan kondisi ramai (2,73 menit) bukan disebabkan oleh performa operasional yang sebenarnya, melainkan akibat adanya gangguan teknis pada jaringan proxy instansi. Melalui pendekatan SMPLS, dinamika fluktuasi sistem antrean dapat direpresentasikan dalam skenario operasional yang diamati. Implikasinya, strategi peningkatan efisiensi layanan publik di instansi tersebut harus difokuskan pada percepatan penyelesaian tahap perekaman biometrik.
Development of “Stafolding”: A Computer-Based Scaffolding Interactive Learning Media to Enhance Students’ Mathematical Problem-Solving Ability Taulia Damayanti; Bertu Rianto Takaendengan; Djihad Wungguli; Karman Tambiyo; Elsa Ekaputri Utina
Jambura Journal of Mathematics Education Vol 6, No 2: September 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jmathedu.v6i2.34648

Abstract

The low level of students’ mathematical problem-solving ability remains a challenge in the learning process, particularly in statistics topics. One effective approach to address this issue is scaffolding, which provides temporary support that helps students understand problems and find solutions independently. However, in classroom settings, individualized scaffolding is often suboptimal due to the large number of students compared to the limited number of teachers and the relatively short instructional time. This study aims to develop a computer-based scaffolding interactive learning medium that is feasible and practical for enhancing students’ mathematical problem-solving ability. The research employed a Research and Development (RD) design using the ADDIE model, consisting of five stages: Analysis, Design, Development, Implementation, and Evaluation. The media were developed using Canva, Microsoft PowerPoint, and iSpring Suite, and published via GitHub Pages for online accessibility. The validation results showed a feasibility score of 91.11% from material experts and 93.33% from media experts, both categorized as excellent. The practicality tests conducted by teachers and students each obtained a score of 92%, indicating that the media are easy to use and effective in facilitating learning. Therefore, the interactive learning media “Stafolding” are considered feasible and practical to be used as a computer-based scaffolding tool in mathematics learning.
Pendekatan Hybrid VARIMA–ANN untuk Peramalan Multivariat Data Cuaca Bulanan di Provinsi Gorontalo Nur Anggraini T. Ali; Djihad Wungguli; Isran K. Hasan
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 1 April 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i1.37513

Abstract

Multivariate time series forecasting is essential for understanding the interrelationships among weather parameters. This study aims to develop a multivariate forecasting model using a hybrid Vector Autoregressive Integrated Moving Average (VARIMA)–Artificial Neural Network (ANN) approach with the backpropagation algorithm, applied to weather data from Gorontalo Province over the 2015–2023 period, including air temperature, humidity, and wind speed. The data were divided into training data (2015–2021) and testing data (2022–2023). The VARIMA model was employed to capture the linear component, while the residuals from the VARIMA model were subsequently modeled using ANN to capture nonlinear patterns. The order of the VARIMA model was determined based on the smallest Akaike Information Criterion (AIC) value, while model performance was evaluated using Mean Absolute Percentage Error (MAPE). The results indicate that the best-performing model is VARIMA(5,1,1)–ANN(18,9,3), with MAPE values of 1.32% for air temperature, 20.54% for humidity, and 21.96% for wind speed. These findings suggest that the hybrid VARIMA–ANN approach provides good forecasting performance and has the potential to serve as an alternative method for multivariate weather forecasting.   
Model Regresi Multilevel Negative Binomial Pada Kasus Kronis Filariasis di Indonesia Rizal Usman; Salmun K. Nasib; Djihad Wungguli; Siti Nurmardia Abdussamad
Jambura Journal of Probability and Statistics Vol 6, No 2 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i2.31648

Abstract

Filariasis is a contagious disease caused by infection with the parasitic worm Filaria and transmitted through the bite of an infected mosquito. Analysis of the number of chronic filariasis cases in Indonesia often faces statistical problems in the form of overdispersion and excess zero. To overcome this, a Multilevel Negative Binomial Regression model is used which is able to handle data variance that is greater than the average as well as the number of zero values in the data. The results showed that the model was effective in overcoming overdispersion and excess zero problems. Based on the parameter significance test using the Wald test, environmental variables such as the presence of unprotected wells (X4) and household proximity to waste storage (X5) have a significant effect on the number of chronic filariasis cases. In contrast, socioeconomic variables such as percentage of male population (X1), productive age population (X2), proper sanitation (X3), percentage of poor population (X6), and Human Development Index (X7) did not show a significant effect. These findings confirm that environmental factors play an important role in the spread of chronic filariasis cases in Indonesia. 
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.
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.
PENERAPAN SMOTE DAN CLUSTER-BASED UNDERSAMPLING TECHNIQUE DALAM KLASIFIKASI OPINI PUBLIK BERBASIS SUPPORT VECTOR MACHINE Dina Zulfiana Matiyeni; Djihad Wungguli; Siti Nurmardia Abdussamad
SIGMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 18 No. 1: Juni 2026
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/n8cyqc26

Abstract

Tujuan: Penelitian ini bertujuan untuk menerapkan metode hybrid yang menggabungkan SMOTE dan Cluster-Based Undersampling Technique guna mengatasi ketidakseimbangan data dalam klasifikasi sentimen terhadap Rancangan Undang-Undang Perampasan Aset menggunakan Support Vector Machine (SVM). Metode: Penelitian ini menggunakan pendekatan kuantitatif dengan rancangan eksperimental komparatif. Data dikumpulkan dari media sosial X terkait Rancangan Undang-Undang Perampasan Aset, dilanjutkan dengan preprocessing, pelabelan, ekstraksi fitur, serta pemisahan data latih dan data uji. Ketidakseimbangan data diatasi dengan menggabungkan metode SMOTE dan Cluster-Based Undersampling Technique pada data latih. Selanjutnya, klasifikasi sentimen dilakukan menggunakan Support Vector Machine (SVM). Hasil: Hasil penelitian menunjukkan bahwa model SVM tanpa penyeimbangan data menghasilkan akurasi 70,10%, presisi 62%, recall 46%, dan F1-score 47%, dengan recall kelas negatif yang sangat rendah sebesar 8%. Setelah penerapan metode resampling hybrid SMOTE dan Cluster-Based Undersampling Technique, performa model meningkat signifikan dengan akurasi 82%, presisi 84%, recall 82%, dan F1-score 82%, yang mengindikasikan bahwa metode hybrid mampu mengatasi dominasi kelas mayoritas dan meningkatkan sensitivitas model secara merata pada seluruh kelas sentimen. Simpulan: Temuan penelitian ini mengindikasikan bahwa penerapan metode SMOTE dan Cluster-Based Undersampling Technique berkontribusi signifikan dalam meningkatkan keadilan prediksi model SVM pada data yang tidak seimbang. Oleh karena itu, kombinasi kedua metode tersebut dapat dijadikan solusi yang efektif dalam pengembangan sistem klasifikasi sentimen opini publik, khususnya pada kasus dengan distribusi kelas yang tidak proporsional.
The Implementation of Random Under-Sampling and Synthetic Minority Oevrsampling Techniques to Evaluate the Performance of the Classification and Regression Tree Method Rifandi Pratama Putra Kasadi; Nurwan Nurwan; La Ode Nashar; Djihad Wungguli; Siti Nurmardia Abdussamad
Jurnal Matematika Sains dan Teknologi Vol. 26 No. 1 (2025)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v26i1.11381.2025

Abstract

Class imbalance in datasets poses a significant challenge in the application of classification models, including the Classification and Regression Tree (CART) method. This study aims to evaluate the performance of CART combined with two data balancing techniques: Random Under Sampling (RUS) and Synthetic Minority Oversampling Technique (SMOTE). The data set used in this research is the Heart Failure Clinical Records from Kaggle.com, which exhibits an imbalance where the number of deceased patients is 1,568 records (minority class) and the number of survivors is 3,432 records (majority class), with a total of 5,000 records. The RUS technique reduced the total number of records to 2,526, with each class containing 1,263 records. Conversely, after applying SMOTE, the total number of records increased to 5,474, with each class containing 2,737 records. Model performance evaluation was conducted using precision, recall, and F1-score metrics, both before and after implementing data balancing techniques. The results of the study showed that combining CART with SMOTE produced better performance in recognizing the minority class compared to RUS, achieving accuracy and F1-score of 88.203% and 88.195%, respectively. Meanwhile, RUS achieved an accuracy of 86.345% and an F1-score of 86.332%. Therefore, the use of SMOTE improved model accuracy by approximately 1.85% and F1-score by 1.86% compared to RUS. This study makes a significant contribution to improving prediction accuracy on imbalanced datasets and enriches scientific references related to the application of the CART method and data balancing techniques.
Penjadwalan Mata Pelajaran Menggunakan Metode Integer Linear Programming di SMA Negeri 1 Tilango Fitria Djafar; Muhammad Rifai Katili; Salmun K Nasib; Nurwan Nurwan; Djihad Wungguli; Armayani Arsal
Research in the Mathematical and Natural Sciences Vol. 4 No. 1 (2025): November 2024-April 2025
Publisher : Scimadly Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55657/rmns.v4i1.200

Abstract

Penjadwalan mata pelajaran secara optimal sangat penting untuk memastikan kelancaran kegiatan belajar dan mengajar. Di SMA Negeri 1 Tilango, penjadwalan yang dilakukan secara manual oleh pihak kurikulum cenderung memakan waktu yang cukup lama, sehingga sering terjadi bentrok antar mata pelajaran pada waktu yang bersamaan. Proses penjadwalan manual ini cukup sulit karena harus memenuhi semua aturan dan kebijakan sekolah yang berlaku. Untuk mengatasi tantangan tersebut, digunakan metode integer linear programming (ILP) yang dapat membantu menyusun jadwal mata pelajaran secara lebih efisien dan terstruktur. Penelitian ini bertujuan untuk menghasilkan jadwal mata pelajaran yang ideal dengan meminimalkan total bobot pelajaran, hari, dan waktu menggunakan metode ILP. Penyusunan jadwal diselesaikan dengan bantuan software Lingo 18.0. Hasil penelitian menunjukkan bahwa jadwal yang dihasilkan dengan metode ILP lebih optimal dibandingkan dengan penjadwalan manual, karena mampu memenuhi semua batasan dan kendala yang telah ditentukan oleh sekolah..
Co-Authors Adisti Dayo Agusyarif Rezka Nuha Ahmad, Rindawati Alamri, Fahima Aliwu, Randa Resvitasari Alya Haja Amanda Adityaningrum Armayani Arsal Armayani Arsal Asriadi Asriadi Asriadi Asriadi Asriadi Asriadi, Asriadi B. P. SILALAHI Bertu Rianto Takaendengan Daud, Sriwati M. Dewi Rahmawaty Isa Dina Zulfiana Matiyeni Elsa Ekaputri Utina Fenly B Mohamad Fitria Djafar Frista Delia Ghivahri Sidik Mokoagow Hanz Franklyn Bachruddin Wewengkang Hasan S. Panigoro Ibrahim, Novita Isa, Jefri N. Ismail Djakaria Ismail Saputra R. Harmain Isran K Hasan K. Hasan, Isran K. Nasib, Salmun Karina Anselia Mamonto Karman Tambiyo Karmila Mokoginta Kasim, Afrianto Pratama Kintan Sakinah Kaluku Kurniasari Abram La Ode Nashar Lailany Yahya Latif, Sintia Abdul Lindrawati Abdjul Loleh, Linda Purnama Sari Mahmud, Sri Lestari Marukai, Nur Amalia Meilan Sigar Meldawati Moh. Rifai Katili Mohamad, Rini Wahyuni Mohammad Rifai Katili Muhammad Rezky F. Payu Muhammad Rezky F. Payu Muhammad Rifai Katili Nadhilah, Farhah Ni Luh Diyani Swarningsih Ningsih, Setia Nisky I. Yahya Nisky Imansyah Yahya NISKY IMANSYAH YAHYA Novarianti Firdaus Novianita Achmad Nteseo, Sutriany Nur Anggraini T. Ali Nur Dhea Wahab Nurhayati Abbas Nurwan Nurwan Nurwan Nurwan NURWAN NURWAN Nurwan, Nurwan Nurwan, Nurwan Nur’ain Manoppo Pakaya, Desya Neydi Putri Posangi, Tiara Rahim, Delvira Masita Rahmi, Emli Resmawan Resmawan Rifandi Pratama Putra Kasadi Rizal Usman S. GURITMAN Safrudin Ismail Salmun K. Nasib Salmun K. Nasib Sartika Husain Siraj, Suaib A Siti Nurmardia Abdussamad Sri Maryam Mohungo Stella Junus Suaib A. Siraj Sutriany Nteseo Syafrudin, Marisa Tahir, Fauzia D. Taufik, Mohamad Alfiransyah Taulia Damayanti Ulfa Is. Abdul Ulfania Liputo Vidya Avianti Hadju Wahdania A.T. Ja’a Wakiden, Yuliyani Windra Tahir Yahya, Nisky Imansyah Yulianti Arbie