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All Journal FORUM STATISTIKA DAN KOMPUTASI Teknosains: Media Informasi Sains dan Teknologi GRADIEN International Journal of Advances in Intelligent Informatics Jurnal Sains Matematika dan Statistika Jurnal Geocelebes BAREKENG: Jurnal Ilmu Matematika dan Terapan Martabe : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Bumi Raflesia Jurnal Berdaya Mandiri Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS Inferensi JINAV: Journal of Information and Visualization Journal of Applied Data Sciences Pattimura Proceeding : Conference of Science and Technology Prosiding Seminar Nasional Official Statistics Indonesian Journal of Community Empowerment and Service Aceh International Journal of Science and Technology Jurnal Sintak Multi Proximity: Jurnal Statistika Universitas Jambi Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat Journal of Statistics and Data Science
Pepi Novianti
Program Studi Statistika, FMIPA Universitas Bengkulu
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PELATIHAN ANALISIS DATA MENGGUNAKAN SPSS PADA MAHASISWA PROGRAM KEGURUAN UNIVERSITAS SWASTA DI KOTA BENGKULU Sriliana, Idhia; Dyah Pangesti, Riwi; Setyo Rini, Dyah; Novianti, Pepi; Swita, Baki; Dwi Lorenza, Kenny; Abdul Aziz, Ali
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 8, No 5 (2025): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v8i5.2135-2141

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memperluas wawasan serta meningkatkan kemampuan mahasiswa Program Studi S1 Pendidikan Biologi Universitas Muhammadiyah Bengkulu (UM Bengkulu) terhadap analisis data statistik menggunakan software SPSS. Pelatihan ini dilatarbelakangi oleh kebutuhan mahasiswa untuk memahami teknik analisis statistik yang sering kali dianggap sulit bagi mahasiswa yang tidak memiliki latar belakang ilmu statistika. Metode pelaksanaan kegiatan ini mencakup persiapan, impelemntasi, dan evaluasi, diantaranya pembuatan materi edukatif berupa modul dan poster, presentasi, demonstrasi penggunaan SPSS, serta diskusi. Hasil yang diperoleh dari pelatihan ini memperlihatkan peningkatan pemahaman dan keterampilan mahasiswa terhadap penggunaan SPSS dan interpretasi hasil analisis statistik. Evaluasi dilakukan melalui pre-test dan post-test yang memperlihatkan terdapatnya peningkatan pengetahuan serta keterampilan mahasiswa setelah mengikuti pelatihan. Kegiatan pengabdian ini diharapkan mampu berkontribusi dalam mendukung penyelesaian skripsi mahasiswa serta meningkatkan mutu penelitian di lingkungan akademik.
An Analysis of Factors Contributing to Extended Study Duration Among Students of the Faculty of Mathematics and Natural Sciences, University of Bengkulu Using Binary Logistic Regression Wahyuliani, Indah; Novianti, Pepi
Journal of Statistics and Data Science Vol. 2 No. 2 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v2i2.41287

Abstract

Logistic regression is a statistical method used to analyze the relationship between a dichotomous dependent variable and one or more independent variables, which may be numerical or categorical. In this study, binary logistic regression is applied to identify the factors influencing the study duration of students in the Faculty of Mathematics and Natural Sciences at the University of Bengkulu. These factors include both internal and external elements, such as cumulative GPA (Grade Point Average), gender, parents’ occupation, scholarship status, and university admission pathway. The results show that GPA significantly affects the length of study, with an odds ratio of 1102.13, indicating that each one-unit increase in GPA greatly increases the likelihood of graduating on time. This study suggests the use of additional statistical techniques, such as bootstrapping, to enhance parameter estimation accuracy and recommends reporting effect sizes, such as odds ratios, for a more comprehensive interpretation of the relationship between independent and dependent variables.
Comparative Analysis of SARIMA, FFNN, and Hybrid Models for Sea Surface Temperature Prediction at Enggano Island (2018–2024) Natisharevi, Raditya Janaloka; Rizal, Jose; Firdaus, Firdaus; Novianti, Pepi; Lestari, Wina Ayu
JURNAL GEOCELEBES Vol. 9 No. 2: October 2025
Publisher : Departemen Geofisika, FMIPA - Universitas Hasanuddin, Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70561/geocelebes.v9i2.46445

Abstract

Sea Surface Temperature (SST) is a key oceanographic variable that influences fish distribution and the livelihoods of coastal communities. On Enggano Island, where most residents rely on fishing, SST is critical for identifying optimal fishing grounds due to limited accessibility and high operational costs. Accurate modeling and forecasting of SST are therefore essential for effective fisheries management and sustainable resource use. This study analyzes and predicts monthly SST patterns in Enggano Island using Seasonal Autoregressive Integrated Moving Average (SARIMA), Feed Forward Neural Network (FFNN), and Hybrid SARIMA-FFNN models. SARIMA effectively captures linear trends and seasonal variations but struggles with nonlinear dynamics and requires statistical assumptions. Conversely, FFNN models nonlinear relationships without such assumptions but is less efficient in representing linear and seasonal structures. The hybrid SARIMA-FFNN combines the strengths of both approaches, integrating linear-seasonal accuracy with nonlinear adaptability. Monthly SST data from January 2018 to December 2024, covering northern, eastern, southern, and western regions of Enggano Island, were analyzed. Results show that all models achieved high predictive accuracy, with MAPE values below 10%. Based on RMSE, FFNN outperformed the other models across all regions (north: 1.173, east: 0.999, south: 1.245, west: 1.049), confirming FFNN as the most accurate model for SST prediction. Predicted SST values across the four regions exhibited only minor differences, offering fishermen flexibility in selecting fishing grounds. Sustainable fishing strategies should also consider species-specific temperature preferences and other ecological factors influencing fish distribution.
Estimation of Stunting and Wasting in Sumatra 2022 with Nadaraya-Watson Kernel and Penalized Spline Oktarina, Cinta Rizki; Nugroho, Sigit; Sriliana, Idhia; Novianti, Pepi; Sunandi, Etis; Pahlepi, Reza
Inferensi Vol 8, No 3 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i3.23330

Abstract

This study aims to estimate the prevalence of Stunting and Wasting in Sumatra in 2022 using nonparametric regression methods, specifically the Nadaraya-Watson Kernel and Penalized Spline regression models. Both models were applied to assess the relationship between these two correlated response variables and various predictor variables, such as low birth weight, sanitary facilities, poor population, and exclusive breastfeeding. The results showed that the Nadaraya-Watson Kernel regression, particularly using the Gaussian kernel, provided the best fit with minimal prediction error, as indicated by its low Generalized Cross-Validation (GCV) value of 0.024 and high R-squared values (0.9992 for Stunting and 0.9995 for Wasting). In contrast, the Epanechnikov kernel and Biweight kernel produced higher GCV values (0.110 and 0.356, respectively), indicating less optimal performance. For the Penalized Spline model, optimal parameters were determined with a smoothing parameter λ of 5 and 3 knots, which balanced model flexibility and smoothness. This research underscores the potential of nonparametric regression techniques in capturing complex relationships in health data and provides insights for improving interventions aimed at addressing child malnutrition in Indonesia.
Pemodelan log linier tiga dimensi dalam tingkat penyelesaian pendidikan di Indonesia pada tahun 2020 sampai 2023 Hayadi, Ilham; Anggraini, Ranisyah; Aria, Aurel Giovani; Sunandi, Etis; Novianti, Pepi
Teknosains Vol 20 No 1 (2026): Januari-April
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/teknosains.v20i1.51709

Abstract

Kesenjangan pendidikan di Indonesia masih menjadi isu penting yang memengaruhi berbagai kelompok demografis. Penelitian ini bertujuan untuk menganalisis hubungan antara tingkat penyelesaian pendidikan, jenis kelamin, dan tahun di Indonesia untuk periode 2020–2023 menggunakan pemodelan log-linear tiga dimensi, metode statistik untuk memodelkan frekuensi sel dalam tabel kontingensi multiarah dan mengidentifikasi efek utama dan interaksi antar variabel kategorikal. Penelitian ini didasarkan pada persistensi kesenjangan dalam penyelesaian pendidikan di berbagai kelompok demografis, khususnya berdasarkan jenis kelamin dan waktu. Data yang digunakan adalah data kategorikal tentang tingkat pendidikan, jenis kelamin, dan tahun yang dianalisis menggunakan model log-linear saturnated dan homogeneous, kemudian dibandingkan melalui nilai deviasi, uji chi-square, dan kriteria AIC. Hasil penelitian menunjukkan bahwa model saturnated merupakan model terbaik dengan nilai AIC sebesar 510,04 dan deviasi residual mendekati nol, serta terdapat interaksi tiga arah yang signifikan antara tingkat penyelesaian pendidikan, jenis kelamin, dan tahun, yang mengindikasikan bahwa ketiga variabel tersebut saling memengaruhi secara simultan. Tahun 2023 menunjukkan peningkatan yang signifikan dalam tingkat penyelesaian pendidikan, sedangkan tahun 2020 menunjukkan penurunan. Terdapat pula perbedaan pola penyelesaian pendidikan antara laki-laki dan perempuan pada setiap tingkat dan tahun.
Pengabdian Kepada Masyarakat FMIPA 2024: Desa Cantik, Desa Cinta Statistik: Visualisasi Data dengan Statistik Deskriptif di Desa Panca Mukti Kabupaten Bengkulu Tengah Susi Wijuniamurti; Sigit Nugroho; Pepi Novianti; Idhia Sriliana; Riwi Dyah Pangesti
Jurnal Pengabdian Masyarakat Bumi Rafflesia Vol. 8 No. 1 (2025): APRIL: Jurnal Pengabdian Kepada Masyarakat Bumi Raflesia
Publisher : Universitas Muhammadiyah Bengkulu

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

Abstract

Pembangunan desa dikatakan berhasil dan dapat terwujud jika masing-masing desa dapat mengenali potensi yang dimiliki. Menggali potensi desa memiliki hubungan yang erat dengan memberikan data yang akurat sehingga tugas pemerintah dalam perancangan pembangunan dapat tepat sasaran. Peran data sangat penting untuk menentukan bagaimana strategi dalam pembangunan desa. Bagi perangkat desa, meningkatkan kemampuan manajemen pengolahan data dan penggunaan data serta literasi statistik menjadi hal yang sangat penting. Penerapan teknologi akan mempermudah aparat desa dalam memahami pengolahan dan penyajian data statistik sehingga desa dapat secara mandiri mengidentifikasi potensi daerahnya. Prodi S1 Statistika, Prodi S2 Statistika dan pojok statistik Universitas Bengkulu bekerjasama dengan BPS dan mitra BPS Kabupaten Bengkulu tengah melalui program pengabdian kepada masyarakat melaksanakan kegiatan pelatihan dan pendampingan terhadap perangkat desa untuk meningkatkan kemampuan pengolahan, penganalisaan dan penyajian data statistik di bidang sektoral serta memaksimalkan penggunaan data dalam bentuk visualisasi data dengan statistik deskriptif  di Desa Panca Mukti. Kegiatan pelatihan visualisasi data dengan statistik deskriptif di Desa Panca Mukti memberikan hasil yang positif bagi masyarakat Desa Panca Mukti. Masyarakat Desa Panca Mukti, khususnya agen statistik dan perangkat desa dapat menampilkan data-data hasil survei ataupun sensus dalam bentuk diagram atau grafik yang mudah dipahami oleh semua orang. Data yang ada di Desa Panca Mukti ditampilkan di website resmi Desa Panca Mukti.
Analysis of Seismic Data in Sumatra using Robust K-Means Clustering Ulfasari Rafflesia; Dedi Rosadi; Devni Prima Sari; Pepi Novianti
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.523

Abstract

Indonesia is located within the Pacific Ring of Fire and frequently experiences significant seismic activities, rendering the region susceptible to hazards. Specifically, Sumatra is an island in the western part of the country, near the Eurasian and Indo-Australian tectonic plates. Over the past five years, an observable uptick in seismic events has been recorded in Sumatra. This research aimed to cluster the Sumatra region’s seismic data using the k-means algorithm and its extensions, including trimmed and robust sparse k-means, to determine the characteristics and patterns of seismic events. The k-means clustering algorithm operates effectively on many data but needs to work better in the presence of outliers. Meanwhile, the data identification reports the presence of outliers in the seismic data. The clustering analysis identified two main clusters, supported by multivariate and spatial outlier detection during preprocessing. The first cluster, encompassing 62% of seismic events, is located offshore near the Mentawai seismic gap, characterized by shallow depths (33–41 km) and magnitudes of 4.5–5.0 Ms. The second cluster, representing 28% of events, includes both mainland and offshore regions, associated with the Sumatran Fault system and slab deformation zones, at moderate depths (54–154 km) with magnitudes of 4.3–4.4 Ms. Rare deep-focus events exceeding depths of 214 km were identified as outliers. Evaluation using Silhouette, Davies-Bouldin, and Dunn indices determined that k=2 was the optimal number of clusters. This study contributes by integrating robust clustering methods to handle outliers, enhancing the reliability of seismic data analysis. This study demonstrates the value of applying trimmed and robust sparse k-means algorithms to improve clustering performance in regions with complex tectonic activity.
Analisis Model Log-Linier Dua Arah Kasus TBC di Kabupaten Bengkulu 2024 Fierianti, Fierianti; Marcella, Levia Dwi; Fhatiha, Shyalaisha Amani; Apriasih, Zakila; Sunandi, Etis; Novianti, Pepi
Multi Proximity: Jurnal Statistika Vol. 4 No. 2 (2025): Multiproximity
Publisher : Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/yd95kt49

Abstract

Tuberkulosis (TBC) merupakan penyakit menular yang masih menjadi ancaman global, terutama di negara berkembang seperti Indonesia. Penyakit ini tidak hanya berdampak pada kondisi fisik penderita, tetapi juga menyebabkan beban ekonomi dan sosial yang signifikan, baik bagi keluarga maupun negara. Penelitian ini bertujuan untuk menganalisis hubungan antara kabupaten/kota dan jumlah kasus TBC tahun 2024 di Provinsi Bengkulu, sekaligus menyajikan informasi dasar bagi pengambilan kebijakan kesehatan yang lebih akurat dan berbasis data. Metode yang digunakan dalam penelitian ini adalah model log-linier dua arah. Hasil penelitian menunjukkan terdapat hubungan yang signifikan antara variabel Kabupaten/Kota dan Jenis Penyakit terhadap jumlah kasus TBC di Provinsi Bengkulu tahun 2024. Distribusi kasus TBC menunjukkan bahwa beberapa kabupaten/kota seperti Kota Bengkulu, Rejang Lebong, Bengkulu Utara, dan Mukomuko memiliki angka kejadian yang relatif tinggi. Sebaliknya, daerah seperti Kaur, Bengkulu Tengah, dan Seluma memiliki jumlah kasus yang lebih rendah. Oleh karena itu, diperlukan kerja sama lintas sektor antara pemerintah daerah, tenaga kesehatan, dan masyarakat dalam memperkuat program deteksi dini, pemerataan layanan kesehatan, serta peningkatan edukasi publik guna menekan angka kejadian TBC di seluruh wilayah Provinsi Bengkulu.
Co-Authors Abdul Aziz, Ali Ahmad Ansori Mattjik Anggraini, Ranisyah Anjani, Retno Tri Apriasih, Zakila Aria, Aurel Giovani Baki Swita Cinta Rizki Oktarina Crisdianto, Riki Dedi Rosadi Devni Prima Sari Dian Agustina Dian Agustina Dian Agustina Dwi Lorenza, Kenny Dyah Pangesti, Riwi Dyah Setyo Rini Dyah Setyo Rini Dyah Setyorini Eka Angasa Etis Sunandi Fachri Faisal Fadila, Risfa Faeza, Veronnica Noer Fairuzindah, Athaya Fhaeza, Veronnica Noer Fhatiha, Shyalaisha Amani Fierianti, Fierianti Firdaus Firdaus Ghufira Hayadi, Ilham Herlin Fransiska Hermansah I Made Sumertajaya Idhia Sriliana Jose Rizal Jose Rizal Karuna, Elisabeth Evelin Lestari, Wina Ayu Marcella, Levia Dwi Marta, Rezkyan Natisharevi, Raditya Janaloka Nur Afandi Pangesti, Riwi Dyah Reza Pahlepi, Reza Riwi Dyah Pangesti Riwi Dyah Pangesti Sigit Nugroho Sigit Nugroho Sihombing, Esther Damayanti Suhaimi, Alus Ahmad Sunandi, Etis Swita, Baki Ulfasari Rafflesia Ulfasari Rafflesia Wahyuliani, Indah Wijuniamurti, Susi