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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Riset Pembelajaran Matematika Sekolah JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA) Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Nilam Novita Sari
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Faktor Yang Berpengaruh Terhadap Kematian Bayi Baru Lahir Di Daerah Kepulauan Alor Adrianingsih, Narita Yuri; Hinadang, Elen A.; Dani, Andrea Tri Rian; Novitasari, Nilam
Jambura Journal of Probability and Statistics Vol 5, No 2 (2024): 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.v5i2.19432

Abstract

Binary logistic regression is an analysis that aims to determine the relationship between one or more predictor variables that are quantitative, qualitative, or a combination of both to a dichotomous response variable with two categories. Binary logistic regression analysis can also be applied in the health sector, especially in newborns' dead or alive status. Infant deaths in Indonesia, especially in the Alor Islands, are still widespread, which is due to several factors. In this study, several variables are thought to influence the status of the newborn, namely the newborn's weight, the baby's body length, the baby's gender, asphyxia, the mother's systolic blood pressure, and the mother's age at birth. The results of the analysis from this research showed that the factor that influences the death of newborn babies in the Alor Islands area is asphyxia. Newborn babies who experience asphyxia are 109,947 times more likely to die compared to babies who do not experience asphyxia.  
Analisis Cluster Penderita Disabilitas Mental di Provinsi Daerah Istimewa Yogyakarta Tahun 2016 Widodo, Edy; Sari, Nilam Novita; Hidayati, Irina; Yubinas, Febritista; Yuniarti, Mazna; Novyantika, Rizky Dwi
Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya 2018: Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1931.673 KB)

Abstract

Penderita disabilitas mental memiliki kedudukan dan hak yang sama dengan masyarakat non disabilitas. Provinsi DIY memiliki angka penderita disabilitas yang cukup tinggi yaitu 2406 jiwa. Untuk mengetahui tingkat disabilitas di Provinsi DIY, maka perlu dikelompokkan. Tujuan dari penelitian ini adalah mengelompokkan 78 kecamatan di Provinsi DIY menggunakan analisis cluster dengan 5 metode hirarki agglomerative, yaitu Single Linkage, Complete Linkage, Average Linkage, Ward’s, dan Centroid. Uji validitas yang digunakan untuk mengetahui metode terbaik dari kelima metode tersebut adalah koefisien korelasi cophenetic, dimana jika nilai koefisien korelasi cophenetic mendekati 1 maka solusi yang dihasilkan dari proses clustering cukup baik. Dalam penelitian ini nilai korelasi cophenetic yang tertinggi adalah pada metode average linkage sehingga dapat dikatakan metode average linkage merupakan metode cluster yang terbaik. Jumlah cluster yang ditentukan sebanyak 3 dengan hasil yaitu cluster 1 merupakan cluster dengan kategori ratarata jumlah penderita disabilitas mental dalam tingkatan ‘rendah’ dan beranggotakan 38 kecamatan, cluster 2 merupakan cluster dengan kategori rata-rata jumlah penderita disabilitas mental dalam tingkatan ‘sedang’ dan beranggotakan 27 kecamatan, cluster 3 merupakan cluster dengan kategori rata-rata jumlah penderita disabilitas mental dalam tingkatan ‘tinggi’ dan beranggotakan 13 kecamatan.
IMPLEMENTATION OF THE DBSCAN ALGORITHM FOR CLUSTERING STUNTING PREVALENCE TYPOLOGY IN WEST JAVA, CENTRAL JAVA, AND EAST JAVA REGIONS Sumargo, Bagus; Kadir, Kadir; Safariza, Dena; Asikin, Munawar; Siregar, Dania; Sari, Nilam Novita; Umbara, Danu; Hilmianto, Rizky; Kurniawan, Robert; Firmansyah, Irman
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1779-1790

Abstract

Stunting, a condition where children are malnourished for a long period, causes growth failure in children. West Java, Central Java, and East Java are the 3 provinces with the highest prevalence of stunting in 2021. This study aims to group districts/cities in these provinces based on factors that influence stunting using the DBSCAN method (there has been no previous research using this method for this case), so the typology of stunting prevalence is implied. The group results can be valuable input for policy priorities in overcoming stunting. The study used the DBSCAN (Density-Based Spatial Clustering of Application with Noise) method, which can also detect noises (outliers). The determination of eps and MinPts is based on the average value of the distance from each data to its closest neighbor. The distance obtained then was used in the KNN algorithm to determine eps and MinPts parameters. Clustering is done using standardized data and DBSCAN parameters obtained from the k-dist plot, eps is 1.92, and MinPts is 2. The validation test used is the silhouette coefficient to determine the goodness of the cluster results. The clustering results show that there are 2 clusters and 1 noise that have special characteristics related to factors that influence the prevalence of stunting. Cluster 1 consisted of 97 districts/cities and was characterized by a high percentage of infants under 6 months receiving exclusive breastfeeding and the lowest average per capita household expenditure. Cluster 2 (Bekasi City and Depok City) was characterized by the lowest percentage of households with proper health facilities and infants aged 0-59 months receiving complete immunization. The noise (high stunting prevalence) in Bandung City is characterized by the lowest percentage of households having proper sanitation.
Pemodelan Topik pada Analisis Sentimen terhadap Pendidikan Literasi Numerasi di Indonesia Menggunakan Latent Dirichlet Allocation Husnul Khotimah, Tiara; Nilam Novita Sari; Khaola Rachma Adzima; Leny Dhianti Haeruman
JURNAL RISET PEMBELAJARAN MATEMATIKA SEKOLAH Vol. 9 No. 2 (2025): Jurnal Riset Pembelajaran Matematika Sekolah
Publisher : Program Studi Pendidikan Matematika FMIPA Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jrpms.092.02

Abstract

Keterampilan literasi numerasi merepresentasikan salah satu tolak ukur vital dalam mengevaluasi standar pendidikan. Namun demikian, pencapaian literasi numerasi Indonesia masih berada pada level yang kurang memuaskan. Studi ini dirancang untuk mengkaji sentiment dan mengidentifikasi tema-tema pokok dalam persepsi publik terkait literasi numerasi berdasarkan informasi dari platform media sosial Twitter/X. Riset ini menerapkan metode kuantitatif dengan Teknik analisis sentiment dan model topik Latent Dirichlet Allocation (LDA). Data diperoleh berdasarkan unggahan Twitter/X selama periode 1 Januari hingga 31 Desember 2024. Sebanyak 691 data dikumpulkan menggunakan kata kunci terkait literasi numerasi, kemudian diklasifikasikan menjadi sentimen positif dan negatif, dilanjutkan dengan visualisasi Wordcloud, serta ekstraksi topik dengan LDA. Hasil analisis menunjukan bahwa sentimen positif lebih dominan dibandingkan dengan sentimen negatif. Sentimen negatif umumnya membahas keterbatasan pendidikan, tantangan digitalisasi pembelajaran, dan rendahnya kemampuan dasar siswa seperti membaca, menulis, dan keterampilan berhitung. Sebaliknya, sentimen positif banyak membahas mengenai apresiasi terhadap program pemerintah, pelatihan guru, serta strategi dinas pendidikan dalam peningkatan literasi numerasi. Temuan ini mengindikasikan bahwa kombinasi analisis sentimen dan LDA terbukti efektif untuk menilai persepsi masyarakat dan dapat menjadi alternatif evaluasi kebijakan pendidikan khususnya terkait literasi numerasi.
Analysis of the Lecturer’s Interest after Attending the Workshop STEM Design-Based Learning for Lecturers Adzima, Khaola Rachma; Sari, Nilam Novita; Khotimah, Tiara Husnul; Gusti, Valeria Yekti Kwasaning
JURNAL RISET PEMBELAJARAN MATEMATIKA SEKOLAH Vol. 9 No. 2 (2025): Jurnal Riset Pembelajaran Matematika Sekolah
Publisher : Program Studi Pendidikan Matematika FMIPA Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jrpms.092.01

Abstract

The STEM (Science, Technology, Engineering, and Mathematics) approach has been widely adopted in schools but remains underutilized in higher education. Lecturers often perceive STEM as difficult to implement due to complex subject matter, time constraints, and limited personal interest. This study examined whether participation in a professional development program, STEM Design-Based Learning for Lecturers, could enhance lecturer’s interest in STEM. The workshop was conducted over two weeks with 18 participants from the Faculty of Mathematics and Natural Sciences. Data were collected using pre- and post-questionnaires designed to measure lecturer’s interest in STEM. Validity and reliability tests confirmed the instrument’s quality. Since the normality assumption was not met, the Wilcoxon Signed Rank Test was applied to assess differences before and after the workshop. The results indicated a statistically significant improvement in interest (p = 0.001) with a large effect size (Cohen’s d = 1.266). Specifically, 15 of 18 lecturers reported increased interest, while two remained unchanged and one experienced a slight decrease. These findings demonstrate that structured STEM workshops can effectively foster enthusiasm and engagement among lecturers. The study highlights the importance of integrating STEM-focused professional development into higher education to support curriculum innovation and encourage broader adoption of STEM approaches in teaching.
K-Means Clustering to Classify Indonesian Provinces Based on School Participation and Socio-Economic Indicators Nilam Novita Sari; Khaola Rachma Adzima; Sahiba Sahila; Tiara Husnul Khotimah
JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM Vol. 4 No. 2 (2025): Agustus: Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrimipa.v4i2.6657

Abstract

Education serves as a fundamental pillar in national development, as it not only enhances individual capacities but also improves overall social welfare. Despite this crucial role, Indonesia continues to face disparities in both access to and quality of education among its regions, as can be seen from variations in school participation indicators and socio-economic backgrounds. To analyze these differences, this study applied the K-Means Clustering method to categorize provinces in Indonesia using six variables: School Participation Rate, Net Enrollment Rate, Gross Enrollment Rate, Poverty Rate, High School Ratio, and Teacher Ratio. To identify the most suitable number of clusters, three validation indices were utilized, namely Dunn Index, C-Index, and Davies-Bouldin Index, with cluster counts tested from three to six. The results indicated that the best clustering solution was five clusters, as reflected in the highest Dunn Index (0.1569), lowest C-Index (0.0321), and lowest Davies-Bouldin Index (0.5062). The robustness of this clustering was further supported by the ratio between within-cluster and between-cluster standard deviation (S(w)/S(b) = 0.33). Each cluster revealed unique characteristics of education and socio-economic conditions, where Cluster 4 displayed the most favorable outcomes with high participation and low poverty levels, whereas Cluster 5 highlighted the weakest performance across all observed indicators.
PENCAPAIAN SDGs: LITERASI DATA STATISTIK POTENSI DESA DI KELURAHAN KAMPUNG RAWA, JAKARTA PUSAT Bagus Sumargo; Suyono; Dian Handayani; Ria Arafiyah; Nilam Novita Sari; Vera Maya Santi
Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT - SNPPM2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Negeri Jakarta

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

Abstract

Abstrak Program Desa Cantik (Cinta Statistik) bertujuan untuk meningkatkan literasi data serta kemampuan aparat kelurahan, dan masyarakat dalam mengelola serta memanfaatkan data statistik secara mandiri dan sistematis. Sehubungan dengan hal ini, kami hadir di Kelurahan Kampung Rawa, Jakarta pusat dalam progam pengabdian kepada masyarakat. Kami sebagai civitas akademika terpanggil untuk melaksanakan Tri Dharma Perguruan Tinggi yaitu sesuai tujuan Sustainable Development Goals SDGs Nomor 4 yaitu pendidikan berkualitas dan Nomor 17 yaitu Kemitraan untuk mencapai tujuan. Pendidikan berkualitas dalam rangka memberikan literasi tentang data statistik – khususnya data PODES potensi Desa. Abstract The Beautiful Village (Love Statistics) program aims to improve data literacy and the ability of village officials and communities to manage and utilize statistical data independently and systematically. In this regard, we are present in Kampung Rawa Village, Central Jakarta, as part of a community service program. As academics, we are called to implement the Tri Dharma of Higher Education, in accordance with Sustainable Development Goals (TPB) Number 4, namely quality education, and Number 17, Partnership to Achieve Goals. Quality education aims to provide statistical data literacy—specifically PODES data regarding village potential. The statistical data literacy activity was held on July 15, 2025, with 19 participants: 2 village officials, 12 Regional Community members, and 5 Dasawisma cadres (Village Community Empowerment). The effectiveness of the training was evaluated through analysis of pre- and post-test results, which consisted of 10 statements with "Yes" and "No" answer options. The analysis was conducted using the McNemar test. The results of the pre- and post-test evaluations showed a significant increase in participant understanding, as confirmed by analysis using the McNemar test. Most participants also stated that the material presented was easy to understand, applicable, and useful for supporting data management at the sub-district level. Keywords: Beautiful Village, Village Potential, Statistical Data Literacy; McNemar; Improvements
Co-Authors Adzima, Khaola Rachma Asikin, Munawar Bagus Sumargo Bagus Sumargo, Bagus Dani, Andrea Tri Rian Dian Handayani Edy Widodo Gusti, Valeria Yekti Kwasaning Hidayati, Irina Hilmianto, Rizky Hinadang, Elen A. Irman Firmansyah Kadir Kadir Leny Dhianti Haeruman NARITA YURI ADRIANINGSIH Novyantika, Rizky Dwi Ria Arafiyah Robert Kurniawan, Robert Safariza, Dena Sahiba Sahila Siregar, Dania SUYONO Tiara Husnul Khotimah Umbara, Danu Vera Maya Santi Yubinas, Febritista Yuniarti, Mazna