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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 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 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 Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) Journal of Statistics and Data Science Limits: Journal of Mathematics and Its Applications
Pepi Novianti
Program Studi Statistika, FMIPA Universitas Bengkulu
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Pelatihan Pembuatan Instalasi Biogas Sistem Kontinu Pada Kelompok Tani Harapan Maju Desa Sukasari, Air Periukan, Kabupaten Seluma, Bengkulu Eka Angasa; Ghufira; Pepi Novianti
Indonesian Journal of Community Empowerment and Service (ICOMES) Vol. 2 No. 2: December 2022
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.237 KB) | DOI: 10.33369/icomes.v2i2.24308

Abstract

Kelangkaan dan kenaikan harga LPG menyebabkan masyarakat Desa Sukasari kembali beralih ke kayu bakar untuk keperluan memasak sehari-hari. Padahal Desa Sukasari mempunyai potensi yang besar berupa limbah kotoran sapi yang dapat digunakan sebagai penghasil gás. Melihat potensi ini maka penting dilakukan pelatihan pembuatan dan pengoperasian instalasi biogás sistem kontinu pada masyarakat Desa Sukasari dengan memanfaatkan kotoran sapi. Pelatihan dilaksanakan pada Kelompok Tani Harapan Maju sebagai contoh bagi masyarakat Desa Sukasari yang lainnya. Pelatihan dilakukan dengan metode ceramah dan pembuatan langsung instalasi biogas. Kegiatan pelatihan berhasil dilaksanakan yang ditandai dengan kemampuan mitra membuat instalasi biogas dan gas yang dihasilkan telah dimanfaatkan untuk memasak. Berdasarkan informasi mitra, gas yang terbentuk dengan kapasitas digester 500 L dengan pengisian feed ±15 L/hari dapat digunakan untuk memasak selama ±0.5 jam.
The Application of Spatial Analysis and Time Series in Modeling the Frequency of Earthquake Events in Bengkulu Province Fachri Faisal; Pepi Novianti; Jose Rizal
Aceh International Journal of Science and Technology Vol 7, No 2 (2018): August 2018
Publisher : Graduate Program of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2113.633 KB) | DOI: 10.13170/aijst.7.2.8656

Abstract

This study provides an overview in combining spatial analysis and time series analysis to model the frequency of earthquake. The aim of this research is to apply the spatial statistical analysis and time series analysis in estimating semivariogram parameters for the next four steps. The data in this study is secondary data that has been validated based on sources that publish parameters of earthquake events. Looking at the characteristics of the earthquake frequency frequency data, there are spatial and time elements. The method used in this research is interpolation kriging and Autoregressive Moving Average (ARMA) model. The semivariogram models used in kriging interpolation are: Spherical, Exponential, Gaussian, and Linear. The parameters of the semivariogram model are modeled using ARMA time series analysis adjusted to the model diagnostic results. To measure of fit model is used Mean Square Error (MSE). The result of research is a suitable semivariogram model to be applied in the modeling of earthquake events is the Spherical model. While each parameter is estimated using ARMA model (2,2) with different coefficient estimation value.
Pelatihan Numerasi di SMP N 07 Kota Bengkulu sebagai Upaya Persiapan Asesmen Kompetensi Minimum Herlin Fransiska; Dyah Setyo Rini; Dian Agustina; Etis Sunandi; Pepi Novianti; Riwi Dyah Pangesti
Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat Vol. 3 No. 1 (2024): Volume 03 Nomor 01 (April 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jhp2m.v3i1.3605

Abstract

Upaya yang dilakukan pemerintah untuk meningkatkan kemampuan numerasi ialah dengan menerapkan tes Asesmen Kompetensi Minimum (AKM). Hasil wawancara terhadap satu orang guru SMP N 07 Kota Bengkulu, menunjukkan sekolah belum mempersiapkan secara khusus dalam menghadapi tes AKM. Berdasarkan hasil wawancara, siswa yang masuk SMP N 07 ialah anak warga sekitar yang yang memiliki keterbatasan kondisi sosial, ekonomi, teknologi dan kemampuan yang kurang. Untuk pembelajaran daring siswa hanya mampu menggunakan whatsapp ataupun SMS, siswa dan guru sebagian besar tidak memiliki laptop serta jaringan internet WIFI sehingga dampak pembelajaran daring sangat dirasakan oleh siswa. Siswa banyak yang belum lancar menerapkan ilmu matematika dalam soal cerita sehingga nilai matematika siswa secara keseluruhan turun saat pembelajaran daring bahkan kemampuan literasi matematika (Numerasi) sangat rendah. Kegiatan pengabdian ini diyakini dapat meningkatkan kemampuan literasi matematika dan mengurangi dampak pembelajaran daring maupun luring sistem shift karena pandemi Covid-19. Kegiatan ini akan membuat siswa menjadi melek literasi numerasi. Agar kegiatan ini menjadi efektif dan efisien maka akan digunakan beberapa rencana kegiatan seperti adanya buku saku/modul, video edukasi, penyelesaian menggunakan software matematika dan kegiatan berbentuk games. Hasil analisis pretest dan postest menggunakan uji-t menyatakan bahwa ada perbedaan yang nyata antara sebelum dan sesudah diberikan pelatihan terhadap siswa SMP N 07 Kota Bengkulu.
Binary Logistic Regression Modeling on Household Poverty Status in Bengkulu Province Sihombing, Esther Damayanti; Novianti, Pepi; Wahyuliani, Indah
Pattimura Proceeding Vol 5 No 1 (2024): Prosiding Konferensi Nasional matematika (KNM) XXII Tahun 2024
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/ppcst.knmxxiiv5i1p89-100

Abstract

Binary logistic regression is a statistical method used to analyze the relationship between one or more predictor variables and a binary or dichotomous response variable. Poverty is an issue in every province in Indonesia. One of the provinces with a relatively high poverty rate is Bengkulu Province, ranking seventh in Indonesia with a poverty rate of 14.62%. The Central Bureau of Statistics of Bengkulu Province (2023) explains that efforts to reduce poverty must involve all levels of society. Various government programs and policies in various fields such as health, social, and other areas are continuously being implemented to reduce the number of households classified as poor. Identifying the characteristics of households in Bengkulu Province by poverty status is important to study, as it serves as a reference to ensure that government programs are implemented according to the target. One method that can be used to identify household characteristics is binary logistic regression. This study aims to model the poverty status of households in Bengkulu Province using binary logistic regression and to identify the factors that influence it. The data used are social and economic household data from March 2022. The response variable used is household poverty status (poor and not poor), while the predictor variables include the ownership of toilet facilities, the source of lighting, floor area, family size, and per capita calorie consumption. Modeling is done using binary logistic regression with simultaneous and partial parameter significance tests, as well as model fit tests. The analysis results show that the factors significantly influencing household poverty status in Bengkulu Province are the ownership of toilet facilities, the source of household lighting, floor area, family size, and per capita calorie consumption. The formed binary logistic regression model has a classification accuracy of 89.98% with a sensitivity of 18.34% and a specificity of 98.61%.
Analysis of Seismic Data in Sumatra using Robust K-Means Clustering Rafflesia, Ulfasari; Rosadi, Dedi; Sari, Devni Prima; Novianti, Pepi
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.
Short-term Forecasting of Covid-19 Cases in East Java of Indonesia using NARX-NN Model Hermansah; Rosadi, Dedi; Novianti, Pepi
JINAV: Journal of Information and Visualization Vol. 4 No. 2 (2023)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav2356

Abstract

The goal of this study is to forecast short-term verified Covid-19 infections in East Java of Indonesia using the NARX-NN model. Here, the external variable used was the weather of East Java. The confirmed data for Covid-19 were obtained from the BNPB, and the weather data of East Java were obtained from the BMKG. Data from July 21st, 2020 to June 20th, 2021, were used for model formation (training data), and data from June 21st to 27th, 2021 were used for validation data. Based on the formatting model results, we can conduct a short-term forecast for three future periods (June 28th to 30th, 2021). This research evaluated the NARX-NN model using the forecasting accuracy of MAPE. The NARX-NN approach is more suitable than the NAR-NN method for predicting daily confirmed Covid-19 cases in East Java, based on the forecasting results of the NAR-NN and NARX-NN methods. The MAPE value was 0.03060 (0.03248 smaller than the MAPE value of the NAR-NN). At the conclusion of the study, the NARX-NN approach was utilized for daily forecasting of Covid-19 instances in East Java from June 28th to June 30th, 2021, namely 1039, 1072, and 1185.
ANALYSIS OF THE EXISTENCE OF THE AGRICULTURAL SECTOR IN MODELING POVERTY IN BENGKULU PROVINCE USING GAUSSIAN COPULA MARGINAL REGRESSION Nugroho, Sigit; Rini, Dyah Setyo; Novianti, Pepi; Crisdianto, Riki; Karuna, Elisabeth Evelin; Fairuzindah, Athaya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1251-1262

Abstract

Bengkulu Province ranks second in the category of the highest percentage of poor people in the Sumatra region, at 14.62% in March 2022, and sixth in Indonesia, which is undoubtedly one of the fundamental problems that requires mutual attention. The phenomenon of high poverty in Bengkulu Province is inseparable from the lives of people whose main livelihood is in the agricultural sector, especially tenant farmers. Therefore, in this study, the Copula and Gaussian Copula Marginal Regression (GCMR) methods are applied to determine how the agricultural sector affects poverty in Bengkulu Province using secondary data obtained from the Bengkulu Provincial Statistics Agency (Susenas 2022). The results show that the Copula model can identify various types of dependency between the number of poor households in each district/city in Bengkulu Province in 2022 and each of the variables, namely the Number of Agricultural Business Households , the Growth Rate of the Agricultural Sector , the Human Development Index , and the Open Unemployment Rate ( ) by considering the different characteristics of dependency such as top-tail, bottom-tail, or negative dependency. Meanwhile, the GCMR model can provide the direction of influence of the independent variables on the dependent variable Y, where it can be seen that the variables , , and have a negative influence on the variable , whie the variable has a positive impact on the variable . Therefore, in general, it can be concluded that either positive or negative dependencies identified by the Copula model can influence the resulting GCMR model by providing more profound complexity regarding the relationship between the variables analyzed.
Pengabdian Kepada Masyarakat FMIPA 2024: Desa Cantik, Desa Cinta Statistik: Visualisasi Data dengan Statistik Deskriptif di Desa Panca Mukti Kabupaten Bengkulu Tengah Susi Wijuniamurti; Nugroho, Sigit; Novianti, Pepi; Sriliana, Idhia; Dyah Pangesti, Riwi
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 | DOI: 10.36085/jpmbr.v8i1.8195

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.
ANALISIS HARGA SAHAM BANK MANDIRI MENGGUNAKAN REGRESI NONPARAMETRIK: PERBANDINGAN SPLINE TRUNCATED DAN DERET FOURIER Fadila, Risfa; Sriliana, Idhia; Hayadi, Ilham; Fhaeza, Veronnica Noer; Novianti, Pepi
Teknosains Vol 19 No 1 (2025): 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.v19i1.57387

Abstract

Saham Bank Mandiri merupakan salah satu bank terbesar di Indonesia yang masuk ke dalam Big four Bank. Harga saham Bank Mandiri tidak terhindar dari fluktuasi yang disebabkan oleh berbagai faktor ekonomi dan kebijakan pasar. Penelitian ini bertujuan untuk memahami pola pergerakan saham Bank Mandiri, menggunakan metode regresi nonparametrik dengan membandingkan metode Spline truncated dan Deret Fourier dalam memodelkan dan memprediksi harga saham Bank Mandiri. Metode Spline truncated menangkap perubahan lokal pada data dengan membaginya menjadi beberapa segmen, sedangkan Deret Fourier menggunakan fungsi sinus dan cosinus untuk mendeteksi pola periodik. Data yang digunakan pada penelitian ini meliputi harga penutupan saham BMRI bulanan, inflasi Indonesia dan BI Rate dari Januari 2021 hingga Desember 2024. Hasil penelitian menunjukkan bahwa kedua metode memiliki performa yang hampir sama. Namun, Deret Fourier sedikit lebih unggul dengan nilai R^2 sebesar 92,27% memiliki 5 titik osilasi. Penelitian ini menegaskan pentingnya model nonparametrik untuk menangkap sifat non-linier harga saham, mendorong pengembangan model yang lebih adaptif.
Analisis Asosiasi Jenis Kredit Rumah Tangga dengan Jenis Pekerjaan Utama di Provinsi Bengkulu Fairuzindah, Athaya; Marta, Rezkyan; Anjani, Retno Tri; Faeza, Veronnica Noer; Sunandi, Etis; Novianti, Pepi
Jurnal Sains Matematika dan Statistika Vol 11, No 2 (2025): JSMS Juli 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v11i2.32966

Abstract

Kredit rumah tangga di Provinsi Bengkulu berperan penting dalam mendukung kesejahteraan masyarakat, terutama dalam memenuhi kebutuhan dasar seperti perumahan, pendidikan, dan barang konsumsi. Namun tidak semua jenis pekerjaan utama memiliki kemampuan yang sama dalam memenuhi syarat pengajuan kredit. Dengan  permasalahan   tersebut  penelitian   ini   bertujuan  melihat  asosiasi jenis pekerjaan dan jenis kredit rumah tangga dengan menggunakan metode log linear 2 dimensi. Berdasarkan hasil pengujian asosiasi didapatkan hasil berupa terdapat asosiasi antara jenis pekerjaan dan kredit. Setelah melakukan pengujian dilakukan pemilihan model terbaik dengan menggunakan pengujian Goodness of fit (uji G). Berdasarkan hasil pengujian Goodness of fit (uji G) bahwa model dengan interaksi lebih baik dibandingkan model tanpa interaksi.
Co-Authors Abdul Aziz, Ali Agwil, Winalia Ahmad Ansori Mattjik Andini, Agita Anjani, Retno Tri Baki Swita 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 Ghufira Hayadi, Ilham Herlin Fransiska Hermansah I Made Sumertajaya Idhia Sriliana Jose Rizal Jose Rizal Karuna, Elisabeth Evelin Marta, Rezkyan Nur Afandi Pangesti, Riwi Dyah Rini, Dyah Setyo Riwi Dyah Pangesti Setyo Rini, Dyah Sigit Nugroho Sigit Nugroho Sihombing, Esther Damayanti Suhaimi, Alus Ahmad Sunandi, Etis Susi Wijuniamurti Swita, Baki Ulfasari Rafflesia Ulfasari Rafflesia Ulfasari Rafflesia Ulfasari Rafflesia Wahyuliani, Indah