Article Per Year (5 Year)
p-Index From 2021 - 2026
3.252
P-Index
This Author published in this journals
All Journal The Journal of Experimental Life Sciences (JELS) Jurnal EECCIS PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika Jurnal Saintek Lahan Kering Variance : Journal of Statistics and Its Applications Publik: Jurnal Manajemen Sumber Daya Manusia, Administrasi dan Pelayanan Publik Jurnal Sibermas (Sinergi Pemberdayaan Masyarakat) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS International Journal of Health, Economics, and Social Sciences (IJHESS) Griya Journal of Mathematics Education and Application Parameter: Journal of Statistics Jurnal Info Sains : Informatika dan Sains Jurnal Kolaboratif Sains Jurnal Pijar MIPA Research in the Mathematical and Natural Sciences Jurnal Riset Mahasiswa Matematika Journal of Artificial Intelligence and Digital Business Jurnal Ilmiah Ekonomi dan Manajemen Journal of Mathematics, Computation and Statistics (JMATHCOS)
Siti Nurmardia Abdussamad
Department Of Statistics, Universitas Negeri Gorontalo
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

Published : 27 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 27 Documents
Search

 1   2   3 
Partial Least Square-Path Modeling Analysis of Factors Influencing the Consumptive Behaviour of Generation Z Agustina, Melisa; Djakaria, Ismail; Abdussamad, Siti Nurmardia; Payu, Muhammad Rezky Friesta; Adityaningrum, Amanda
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.8014

Abstract

Consumptive Behaviour refers to individuals’ purchasing behaviour without considering long-term needs and financial conditions. This research presents the results of an analysis of the consumptive behaviour of Generation Z in Dungingi Sub-District, Gorontalo City, selected because it represents the second-largest Generation Z population in the city. The study used the Partial Least Square-Path Modeling (PLS-PM) method to measure factors influencing consumptive behaviour: financial literacy, fear of missing out (FOMO), and hedonistic lifestyle. The sampling technique used was purposive sampling, resulting in 378 respondents aged 17-27 years who are employed. The analysis results indicate that financial literacy and FOMO significantly influence consumptive behaviour, with FOMO being the most dominant factor. The resulting model has a value of 0,930, meaning that the three latent variables can explain 93,0% of the consumptive behaviour of Generation Z. This study is expected to provide useful insights for policymakers and related parties in adressing consumptive behaviour issues among Generation Z. Keywords: PLS-PM; Consumptive Behaviour; Generation Z
Implementation of Path Analysis for Modeling the Influence of Organizational Culture on Work Productivity Abdussamad, Siti Nurmardia; Abdussamad, Zuchri; Reza, Widya; Aqmal, Ikhlas Ul
Jurnal Pijar Mipa Vol. 19 No. 4 (2024): July 2024
Publisher : Department of Mathematics and Science Education, Faculty of Teacher Training and Education, University of Mataram. Jurnal Pijar MIPA colaborates with Perkumpulan Pendidik IPA Indonesia Wilayah Nusa Tenggara Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpm.v19i4.7037

Abstract

This research aims to determine the significant factors of organizational culture that influence employee performance productivity using a path analysis model by looking at the total direct and indirect influence of sub-variables. Path analysis can describe the magnitude of the influence and significant variables using direct and indirect influences. By adapting to this case, direct and indirect modeling is needed to see the magnitude of the influence of these sub-indicators. Research related to organizational culture has been carried out to see how much influence organizational culture and motivation have on employee performance. The result is that the greater the organizational culture and achievement motivation, the higher the influence on employee performance. This type of research uses a qualitative and quantitative approach. This research uses a questionnaire to collect data, which has been tested for validity and reliability. This research was conducted at the Gorontalo District Health Service in 2022. Respondents used in this research were 57 Gorontalo District Health Service employees. Data analysis using software R. Results of the research show that organizational culture variables and sub-variables, namely artifacts (X1), values ​​(X2), and basic assumptions (X3), significantly influence employee performance productivity (Y). The total effect is calculated using the path coefficient calculation of the significant variables. The total influence of organizational culture in the form of artifacts (X1) on employee work productivity (Y) is 72%, and the total influence of organizational culture in the form of values ​​(X2) on employee work productivity (Y) is 65%. The total influence of organizational culture is in the form of basic assumptions (X3 ) on employee work productivity (Y) of 78%. This shows that the organizational culture variable influences the most significant influence, namely basic assumptions (X3). The Gorontalo district health office can consider the results of this analysis to make further policies regarding which organizational culture priorities will be implemented to increase employee productivity to the maximum.
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.
Model Regresi Multilevel Negative Binomial Pada Kasus Kronis Filariasis di Indonesia Usman, Rizal; Nasib, Salmun K.; Wungguli, Djihad; Abdussamad, Siti Nurmardia
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. 
Penerapan Multilayer Perceptron (MLP) untuk Klasifikasi Citra Kue Karawo Berdasarkan Fitur Tekstur GLCM dan Warna HSV di Viana Cookies Ilato, Mutiara; Yahya, Lailany; Abdussamad, Siti Nurmardia
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.4243

Abstract

Kue karawo merupakan salah satu produk pangan tradisional khas Provinsi Gorontalo yang memiliki nilai budaya sekaligus potensi ekonomi. Penilaian kualitas kue karawo selama ini masih dilakukan secara visual dan manual, sehingga sangat bergantung pada subjektivitas penilai dan berisiko menimbulkan ketidakkonsistenan hasil, terutama pada proses produksi dalam jumlah besar. Penelitian ini bertujuan untuk mengklasifikasikan kualitas kue karawo secara otomatis dengan memanfaatkan citra digital dan algoritma Multilayer Perceptron (MLP). Karakteristik kualitas kue direpresentasikan melalui fitur tekstur dan warna, di mana fitur tekstur diekstraksi menggunakan Gray Level Co-occurrence Matrix (GLCM) yang meliputi energy, contrast, correlation, dan homogeneity, sedangkan fitur warna diperoleh dari model Hue, Saturation, dan Value (HSV). Data citra yang digunakan berasal dari Viana Cookies dan telah melalui tahapan praproses serta normalisasi menggunakan metode Z-score sebelum dilakukan pelatihan dan pengujian model. Evaluasi kinerja klasifikasi dilakukan menggunakan confusion matrix dengan indikator akurasi, presisi, dan recall. Hasil pengujian menunjukkan bahwa model MLP mampu memberikan kinerja yang cukup baik dengan nilai akurasi sebesar 80,72%, presisi 72,73%, dan recall 77,42%. Hasil ini menunjukkan bahwa kombinasi fitur tekstur GLCM dan warna HSV efektif digunakan dalam mengklasifikasikan kualitas kue karawo. Secara praktis, penelitian ini diharapkan dapat menjadi dasar pengembangan sistem pendukung keputusan dalam pengendalian kualitas produk kue karawo secara objektif dan efisien.
Analisis Diskriminan Pada Faktor-Faktor yang Memengaruhi Perilaku Peduli Lingkungan Masyarakat Kecamatan Pinolosian Djafar, Fikriyanto; Payu, Muhammad Rezky Friesta; Abdussamad, Siti Nurmardia
Griya Journal of Mathematics Education and Application Vol. 5 No. 4 (2025): Desember 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i4.960

Abstract

This study examines the factors that distinguish the environmental awareness behavior of the Pinolosian District community using Discriminant Analysis. The low level of environmental awareness in this region is reflected in the minimal community participation in cleanliness and waste management activities. This study aims to develop a discriminant model based on three main variables, namely attitude, subjective norms, and behavioral control, and to identify the most dominant variables in distinguishing between groups of people who do and do not engage in environmentally conscious behavior. Data were obtained from 371 respondents through a questionnaire that had been tested for validity and reliability, then analyzed using R Studio software. The results show that the discriminant function formed is statistically significant, with behavioral control as the most dominant distinguishing factor, followed by subjective norms and attitudes. The resulting classification model has an accuracy rate of 69%, which indicates a fairly good ability to categorize community environmental behavior. These findings confirm that improving environmentally conscious behavior needs to focus on strengthening the community's perception of their capabilities through the provision of supporting facilities, the reduction of structural barriers, and the strengthening of social norms as the basis for formulating environmental policies at the regional level.
Pendampingan Teknik Analisis Data dan Interpretasi Hasil untuk Penelitian Tindakan Kelas di SMP: Workshop on Data Analysis Techniques and Result Interpretation for Classroom Action Research in Junior High School Djakaria, Ismail; Isa, Dewi Rahmawaty; Adityaningrum, Amanda; Abdussamad, Siti Nurmardia; Payu, Muhammad Rezky Friesta
Jurnal Kolaboratif Sains Vol. 9 No. 1: Januari 2026
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v9i1.10570

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan kompetensi guru Sekolah Menengah Pertama (SMP) dalam menganalisis data dan menginterpretasi hasil Penelitian Tindakan Kelas (PTK) sebagai bagian dari pengembangan profesionalisme berkelanjutan. Kegiatan pengabdian ini dilaksanakan di gedung LPMP Provinsi Gorontalo dan Laboratorium Komputer FMIPA, Universitas Negeri Gorontalo, pada tanggal 10-11 Juli. Peserta kegiatan adalah guru yang tergabung dalam MGMP Matematika di Kabupaten Bone Bolango. Kegiatan pengabdian terdiri dari tiga sesi mencakup: materi dasar analisis data, pelatihan Microsoft Excel untuk statistik deskriptif, dan pengenalan SPSS untuk analisis data sistematis. Hasil pendampingan menunjukkan peningkatan dalam pemahaman dan keterampilan guru, terlihat dari kemampuan menyusun tabel distribusi frekuensi, menghitung persentase ketuntasan belajar, membuat grafik, dan menginterpretasi output SPSS dengan percaya diri. Pendampingan serupa direkomendasikan untuk dilaksanakan secara berkelanjutan dengan waktu lebih panjang.
Co-Authors Abdussamad, Siti Nurcahyati Adam, Dwi Putri Juniar Agustina, Melisa Agusyarif Rezka Nuha Alaina, Silvana Rahmayanti Armayani Arsal Asriadi Asriadi Asriadi Dewi Rahmawaty Isa Djafar, Fikriyanto Djihad Wungguli Doholio, Nadya Pratiwi effendi, Achmad Febrya Christin Handayani Buan Hasan, Nadia Kasmin Hinelo, Ikrar Prasetyo Ikhlas Ul Aqmal Ilato, Mutiara Ismail Djakaria Isran K Hasan Juriko Abdussamad Karim, Finansiya S. Abd. La Ode Nashar Lailany Yahya Lasaleng, Wahyu Pratama Marukai, Nur Amalia Naue, Siti Nurmeylisya Nikmatisni Arsad NISKY IMANSYAH YAHYA Pakaya, Desya Neydi Putri Putri Ayuningtias Mahdang Rahman, Mohamad Iswanto Rahmi, Emli Salmun K. Nasib Suci Astutik Sulista Kamah Taufik, Mohamad Alfiransyah Tiarawati, Ni Wayan Usia, Putu Ayu Indah N. Usman, Rizal Wewengkang, Hanz Franklyn Bachruddin Widya Reza Widya Reza wolah, Meitasya Zuchri Abdussamad