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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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Implementasi Algoritma Random Forest dengan Forward Selection untuk Klasifikasi Indeks Pembangunan Manusia Posangi, Tiara; Yahya, Lailany; Wungguli, Djihad
Jambura Journal of Probability and Statistics Vol 4, No 2 (2023): 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.v4i2.18460

Abstract

Development is essentially a process of continuous change carried out to achieve better living condition. So that the benchmark for the success of a development is seen in its human development. 3 The basic dimensions that form human development are long and healthy life, knowledge, and a decent life. The indicators that represent the three dimensions are summarized in a single value, namely the Human Development Index (IPM). In 2021 the HDI figure in Indonesia is 72.29, which means it is high. However, due to the diverse geographical location of regions in Indonesia, this also influences the HDI rate in each region in Indonesia, so this study uses the Random Forest Algorithm to obtain accurate results from the HDI classification and uses Forward Selection to determine features that influence the classification. The results of the study show that the features that influence the classification are per capita spending, expected length of schooling, life expectancy, and average length of schooling, and get a final accuracy of 80%.
Penjadwalan karyawan Qmart Super Store menggunakan metode Goal Programming secara Preemptive dan Nonpreemptive Syafrudin, Marisa; Djakaria, Ismail; Nuha, Agusyarif Rezka; Wungguli, Djihad
AKSIOMA : Jurnal Matematika dan Pendidikan Matematika Vol 14, No 3 (2023): AKSIOMA: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/aks.v14i3.17005

Abstract

Penjadwalan karyawan adalah salah satu masalah organisasi yang rumit dipecahkan. Faktor yang membuat penjadwalan karyawan menjadi rumit adalah karakteristik organisasi, ketidakhadiran, serta kualifikasi dan keahlian karyawan. Karena banyaknya faktor tersebut masalah penjadwalan menjadi sangat luas dan bervariasi. Tujuan dari penelitian ini adalah untuk mengoptimalkan penjadwalan karyawan. Hasil dari penelitian ini diperoleh dengan menggunakan 2 skenario, skenario satu (Preemptive) dan skenario dua (Nonpreemptive), nilai fungsi tujuan bernilai 0 dengan solusi optimal  dan , artinya semua kendala yang dimodelkan terpenuhi sehingga penjadwalan dengan Preemptive Goal Programming dan Weighted Goal Programming dikatakan lebih optimal dibandingkan penjadwalan secara manual.
Developing a Python-Based Application for a Discrete-Time Population Dynamics Model Nadhilah, Farhah; Panigoro, Hasan S.; Arsal, Armayani; Nurwan, Nurwan; Wungguli, Djihad; Hasan, Isran K.
Indonesian Journal of Computational and Applied Mathematics Vol. 1 No. 2: June 2025
Publisher : Gammarise Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64182/indocam.v1i2.20

Abstract

Difference equation is a type of equation in mathematics that is widely used to describe certain phenomena as time changes, one of which is in the field of population dynamics. In various studies, it is explained that solving complex population dynamics models is by using numerical simulations. Along with the development of technology, computational science is used to help solve mathematical problems that are difficult to solve analytically. One of them is to use a programming language, such as Python, to help present data in a graphical form. This research aims to develop an application that presents a computational solution to a difference equation using Python. The numerical results begin by entering the equation and variable values into the application, which then automatically generates a figure according to the entered equation. The figures generated in the application include one-dimensional and two-dimensional time series, as well as a Bifurcation diagram.
STRUCTURAL EQUATION MODELING-GENERALIZED STRUCTURED COMPONENT ANALYSIS TO ANALIZING STRUCTURE OF POVERTY IN INDONESIA IN 2022 Marukai, Nur Amalia; Wungguli, Djihad; Nashar, La Ode; Nasib, Salmun K.; Asriadi, Asriadi; Abdussamad, Siti Nurmardia
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 2 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss2page167-174

Abstract

Structural Equation Modeling - Generalized Structured Component Analysis (SEM-GSCA) is a component-based method suitable for limited sample sizes. GSCA is appropriate for structural models that include variables with reflective and formative indicators. This study utilizes the Alternating Least Square (ALS) parameter estimation. Iterations in ALS are used to achieve minimal residuals. Additionally, this study employs jackknife resampling to obtain standard error estimates. This study aims to identify the poverty model structure in Indonesia and examine the relationships among poverty, human resources, economic, and health variables. The results of the structural model of poverty in Indonesia are explained as follows: the influence of human resources and economic variables on poverty is insignificant, while the health variable significantly negatively influences poverty. Furthermore, the health variable significantly influences human resources, and both human resources and health significantly influence the economy.
Sifat Fundamental Pada Granum Eulerian Suaib A. Siraj; Asriadi; Djihad Wungguli; Hasan S. Panigoro; Nurwan; Nisky I. Yahya
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 2 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Mathematical analysis has several important connections with graph theory. Although initially, they may seem like two separate branches of mathematics, there are relationship between them in several aspects, such as graphs as mathematical objects that can be analyzed using concepts from analytic mathematics. In graph theory, one often studies distance, connectivity, and paths within a graph. These can be further analyzed using analytic mathematics, such as in the structure of natural numbers. Literature studies on graph theory, especially Eulerian graphs, are interesting to explore. An Eulerian path in a graph G is a path that includes every edge of graph G exactly once. An Eulerian path is called closed if it starts and ends at the same vertex. The concept of granum theory as a generalization of undirected graphs on number structures provides a rigorous approach to graph theory and demonstrates some fundamental properties of undirected graph generalization. The focus of this study is to introduce the connectivity properties of Eulerian granum. The granum G(e,M) is called connected if for every u,v E M with u != v there exists a path subgranumG^' (e,M^' )c G(e,M)  where u,v E M^' and is called an Eulerian granum if there exists a surjective mapping O: [||E(G(e,M))|| + 1]-> M such that e(o(n),o(n+1))=1 for every n E [||E(G(e,M))||]. This property provides a deeper understanding of the structure and characteristics of Eulerian granum, which have not been fully comprehended until now.
Comparison of OPTICS and HDBSCAN Performance in Clustering Population Administration Document Ownership in Bone Bolango Regency Adisti Dayo; Djihad Wungguli; Muhammad Rezky Friesta Payu
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/s6m22g74

Abstract

Population administration is essential for public service delivery and development planning; however, disparities in population document ownership across villages remain a challenge in Bone Bolango Regency. The heterogeneous nature of the data, the presence of outliers, and variations in density patterns limit the effectiveness of classical statistical approaches in capturing the underlying distribution. Therefore, this study aims to compare two density-based clustering algorithms, Ordering Points to Identify the Clustering Structure (OPTICS) and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN), in grouping villages based on population document ownership levels. The data were obtained from the Department of Population and Civil Registration of Bone Bolango Regency in 2024 and consist of ownership records of birth certificates, identity cards, and family cards from 165 villages. Both algorithms successfully formed two main clusters representing villages with relatively high and low levels of population document ownership. Internal validation results indicate that OPTICS outperformed HDBSCAN, achieving a Silhouette Coefficient of 0.827, a Davies–Bouldin Index of 0.242, and a Calinski–Harabasz Index of 1217.425, compared to 0.787, 1.210, and 767.866, respectively, for HDBSCAN. In conclusion, OPTICS demonstrates superior capability in producing a more coherent clustering structure for population document ownership data. Therefore, the clustering results obtained using OPTICS can serve as a supporting basis for formulating policies to promote equitable population administration services.
Faktor–Faktor yang Berhubungan dengan Kejadian Underweight pada Balita dari Keluarga Petani di Kecamatan Limboto Ni Luh Diyani Swarningsih; Muhammad Rezky Friesta Payu; Amanda Adityaningrum; Rini Wahyuni Mohamad; Vidya Avianti Hadju; Djihad Wungguli; Siti Nurmardia Abdussamad
Griya Journal of Mathematics Education and Application Vol. 6 No. 2 (2026): Juni 2026
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v6i2.1050

Abstract

Masalah underweight pada balita masih menjadi tantangan kesehatan masyarakat, khususnya pada komunitas keluarga petani. Kecamatan Limboto merupakan salah satu wilayah dengan prevalensi balita underweight yang tinggi yaitu sebesar 317 kasus pada tahun 2024 dan kembali bertambah menjadi 365 kasus pada tahun 2025. Penelitian ini bertujuan untuk mengetahui hubungan antara faktor kesehatan dan sosial ekonomi dengan kejadian underweight pada balita dari keluarga petani di Kecamatan Limboto. Desain penelitian yang digunakan cross sectional dan teknik sampling purposive sampling. Data diperoleh dari kuesioner yang diisi oleh ibu atau pengasuh utama balita. Analisis data dilakukan menggunakan tabel kontingensi untuk melihat distribusi data dan uji chi-square untuk menguji hubungan antara variabel independen dan kejadian underweight. Hasil penelitian menunjukkan bahwa terdapat hubungan yang signifikan antara riwayat BBLR, riwayat ASI eksklusif, tingkat pengetahuan ibu, pola asuh, dan ketahanan pangan dengan kejadian underweight pada balita. Sementara itu, riwayat penyakit infeksi, tingkat pendidikan ibu dan pendapatan keluarga tidak menunjukkan hubungan yang signifikan. Kesimpulan penelitian ini menunjukkan bahwa faktor kesehatan dan pola pengasuhan memiliki peran penting dalam kejadian underweight pada balita dari keluarga petani, sehingga diperlukan upaya edukasi dan intervensi gizi yang lebih terarah
Model Geographically Wighted Bivariate Generalized Poisson Regression dengan Adaptive Gaussian Kernel (Studi Kasus: Jumlah Kematian Ibu dan Neonatal di Indonesia) Frista Delia; Djihad Wungguli
Research Review: Jurnal Ilmiah Multidisiplin Vol. 4 No. 1 (2025): Research Review: Jurnal Ilmiah Multidisiplin (Februari 2025 - Juli 2025)
Publisher : Transbahasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54923/researchreview.v4i1.116

Abstract

Maternal Mortality Rate (MMR) and Neonatal Mortality Rate (NMR) are important indicators in determining the level of public health in a region. Both MMR and NMR in Indonesia have decreased, but the reduction has not been significant, and the rates remind high, requiring accelerated efforts to meet the target by the end of 2024. Maternal and neonatal mortality are interrelated, at the nutrition that the baby receives during pregnancy comes from the mother’s body, meaning the mother’s health status significantly influences the health of the newborn. This study aims to identify the factors influencing maternal and neonatal mortality in Indonesia with Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method, using Adaptive Gaussian Kernel weighting. The results results indicate that the independent variables that have a significant effect on the number of maternal and neonatal deaths at each location are the percentage of health services for pregnant women in K4 (X1) and the percentage of deliveries by health workers (X2).
Perbandingan Jackknife Ridge Regression dan Principal Component Regression dalam Penanganan Kasus Multikolinearitas (Studi Kasus: Indeks Pembangunan Manusia di Indonesia) Nur’ain Manoppo; La Ode Nashar; Djihad Wungguli; Muhammad Rezky F. Payu; Siti Nurmardia Abdussamad; Salmun K. Nasib
Research Review: Jurnal Ilmiah Multidisiplin Vol. 4 No. 1 (2025): Research Review: Jurnal Ilmiah Multidisiplin (Februari 2025 - Juli 2025)
Publisher : Transbahasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54923/researchreview.v4i1.181

Abstract

According to data from Statistics Indonesia, the Human Development Index (HDI) in 2022 reached 72.91, increasing from 72.29 in the previous year. Although Indonesia’s HDI continues to improve, disparities remain among provinces, indicating that HDI distribution is still uneven. Given the importance of HDI in aregion, it is necessary to conduct statistical analysis to identify the factors that significantly influence HDI using regression analysis. In applying multiple linear regression, several classical statistical assumptions must be met, one of which is the central focus of this analysis-addressing the issue of multicollinearity. Several methods have been identified to address multicollinearity, including Jackknife Ridge Regreesion (JRR) and Principal Component Regression (PCR). This study aims to compare the effectiveness of both methods in handling multicollinearity based on Adjusted R2 and Mean Square Error (MSE) and to analyze the factors that significantly influence the HDI level in Indonesia. The data used in this study are secondary data comprising HDI and its related factors for each province in Indonesia in 2022, obtained from bps.go.id. Based on the analysis, the best model uses the JRR method, with an Adjusted R2 value of 96.7% and MSE of 0.033.
Perbandingan Fuzzy Time Series Lee dan Double Exponential Smoothing pada Permalan Garis Kemiskinan Provinsi Gorontalo Meldawati; Djihad Wungguli; Dewi Rahmawaty Isa
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.v4i2.271

Abstract

This study aims to compare the forecasting accuracy of two statistical methods, namely Fuzzy Time Series (FTS) Model Lee and Double Exponential Smoothing (DES) Holt, in predicting the poverty line in Gorontalo Province. The data used were secondary data obtained from the Central Bureau of Statistics (BPS) of Gorontalo Province for the period 2004–2024. A quantitative descriptive approach with time series analysis was applied. The analysis process involved constructing the universe of discourse, fuzzification, and defuzzification for the FTS method, as well as double smoothing with parameters α and β for the DES method. The findings revealed that the FTS Lee model achieved the highest forecasting accuracy with a Mean Absolute Percentage Error (MAPE) of 0.47%, while the DES Holt method yielded a MAPE of 2.26%. The forecasting results indicated that Gorontalo’s poverty line is projected to reach IDR 464,959.50 in 2025 and IDR 504,911.90 in 2026. These results suggest that the FTS Lee method is more effective in predicting socio-economic data characterized by high uncertainty.
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