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All Journal Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Fourier Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Pengembangan Rekayasa dan Teknologi Jurnal Pendidikan Matematika (Kudus) J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika EIGEN MATHEMATICS JOURNAL Community Development Journal: Jurnal Pengabdian Masyarakat LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Litbang Edusaintech Fraction: Jurnal Teori dan Terapan Matematika Tepis Wiring : Jurnal Pengabdian Masyarakat Journal of Data Insights Prosiding Seminar Nasional Unimus
Prizka Rismawati Arum
Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Permodelan Jumlah Kasus Tuberkulosis Di Kabupaten Purbalingga Tahun 2022 Menggunakan Regresi Binomial Negatif: Modeling the Number of Tuberculosis Cases in Purbalingga Regency in 2022 Using Negative Binomial Regression Prizka Rismawati Arum; Indah Manfaati Nur; Amalia Jihan Syafiqoh; Hanief Rizky Utami
Journal of Data Insights Vol 1 No 2 (2023): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v1i2.273

Abstract

Menurut data dari Dinkes Purbalingga pada bulan Mei 2022 ditemukan 422 kasus TBC dan 9 diantaranya menderita TBC Multi Drug Resistant (MDR) atau kebal obat. Untuk kasus TBC MDR saat ini menjadi perhatian kusus pemerintah, hal ini karena masa penyembuhannya membutuhkan waktu yang lebih lama. Penyakit TB Paru merupakan salah satu penyebab kematian utama di Indonesia dan dunia. Selain menyerang Paru, Tuberculosis dapat menyerang organ tubuh yang lain. Jumlah orang terduga Tuberkulosis tahun 2022 sebanyak 11.324 dan orang terduga tuberkulosis yang mendapatkan pelayanan kesehatan sesuai standar sebanyak 12.072 (106,6%). Oleh karena itu, perlu dilakukan upaya untuk memodelkan jumlah kasus TBC di Kabupaten Purbalingga agar dapat memberikan informasi yang berguna dalam upaya pencegahan dan pengendalian penyakit TBC.Model regresi Poisson sering ditemukan pelanggaran asumsi overdispersi dengan memodelkan faktor-faktor yang berpengaruh terhadap kasus tuberculosis. Alternatif model yang dapat dilakukan untuk mengatasi pelanggaran asumsi overdispersi adalah Model Regresi Binomial Negatif. Berdasarkan nilai AIC diperoleh hasil pemodelan terbaik menggunakan regresi binomial negatif dengan nilai AIC sebesar 191.96 yang lebih kecil dari metode regresi Poisson.Berdasarkan uji parsial dihasilkan bahwa variabel yang berpengaruh terhadap jumlah kasus tuberculosis di Kabupaten Purbalingga adalah X2 yaitu jumlah puskesmas.
Comparison of Holt-Winters Exponential Smoothing (HWES) and Singular Spectrum Analysis (SSA) Methods in Forecasting the Number of Passengers at PT KAI in Indonesia: Perbandingan Metode Holt-Winters Exponential Smoothing (HWES) Dan Singular Spectrum Analysis (SSA) Pada Peramalan Jumlah Penumpang PT KAI di Indonesia Samikoh Ulinuha; Tiani Wahyu Utami; Prizka Rismawati Arum; Dannu Purwanto
Journal of Data Insights Vol 2 No 2 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i2.654

Abstract

Penelitian ini mengkaji penerapan dua metode peramalan, yaitu Holt Winters Exponential Smoothing (HWES) dan Singular Spectrum Analysis (SSA), dalam meramalkan jumlah penumpang di PT Kereta Api Indonesia. Hasil penelitian menunjukkan bahwa penerapan metode HWES dengan model additive menghasilkan nilai parameter pemulusan optimal dengan alpha , beta dan gamma model ini memiliki nilai MAPE sebesar 10.75%. Sementara itu, pada HWES model multiplicative menghasilkan nilai parameter pemulusan alpha , beta dan gamma , menghasilkan nilai MAPE 14.50%. Metode SSA dengan window length menghasilkan nilai MAPE 13.33%. Perbandingan nilai MAPE anatara metode HWES additive, HWES multiplicative dan SSA menunjukkan bahwa HWES additive lebih unggul dengan MAPE sebesar 10.75%. Peramalan jumlah penumpang Kereta Api Indonesia menggunakan metode terbaik Holt Winters Exponential Smoothing Additive untuk periode Januari hingga Desember 2024 memperlihatkan variasi jumlah penumpang terendah pada bulan Agustus dan tertinggi pada bulan Januari.
MODELLING SCHOOL DROPOUT RATES IN WEST JAVA PROVINCE WITH MIXED GEOGRAPHICALLY TEMPORALLY WEIGHTED REGRESSION Prizka Rismawati Arum; Endang Tri Wahyuni Maharani; Diandra Fatimahthus Zahra; Tiani Wahyu Utami
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0123-0136

Abstract

School dropout is a problem in the education sector that can hinder the progress of the quality of human resources and the competitiveness of the nation. West Java Province has the highest school dropout rates among all provinces in Indonesia. The data on school dropout rates exhibit spatial and temporal variations. Additionally, the potential differences between regions allow for the occurrence of diverse data that can be addressed locally and globally. Mixed Geographically Temporally Weighted Regression (MGTWR) is an extension of the GWR method that can produce parameters that are both local and global for each location and time. So, the objective of this research is to obtain factors that have a local and global influence on the school dropout rate in West Java Province using the Mixed Geographically Temporally Weighted Regression method. In this study, the data used includes school dropout rates in West Java Province from 2018 to 2022. The data used is sourced from the official statistical data website of the Ministry of Education, Culture, Research and Technology, and the official website of the West Java Province Central Statistics Agency. The results of the MGTWR modeling show that globally influential variables include the percentage of the poor population, population density, unemployment rate, and average length of schooling, which have local effects. Based on the MGTWR model, the Fixed Kernel Gaussian weighting function is the best model for modeling school dropout rates in regencies/cities in West Java, with an RMSE value of 0.0755 and R-squares of 92.09%.
Infografis Dampak Pandemi Covid-19 sebagai Upaya Edukasi Pemberdayaan Masyarakat Desa Katonsari Kecamatan Demak Prizka Rismawati Arum; Eko Andy Purnomo; Ali Imron; M. Al Haris; Fatkhurrokhman Fauzi; Ach Ridoi Alambara
Jurnal Pengabdian Masyarakat: Tipis Wiring Vol 1 No 2 (2022): Tepis Wiring: Jurnal Pengabdian Masyarakat
Publisher : Fakultas Ekonomi dan Bisnis Unversitas Islam Raden Rahmat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/tepiswiring.v1i2.2978

Abstract

Based on observations in the Katonsari Village, Demak District, Demak Regency, the delivery of information about Covid-19 and its impacts is still traditional, namely using text, tables or diagrams that are less attractive. Katonsari Village apparatus must have innovations in conveying information about Covid-19 and its impacts, such as new methods or media for conveying information. One of them is through infographics. Through the training, mentoring, mentoring and coaching that will be carried out, it is hoped that it will be able to make the officials of Katonsari Village, Demak District, Demak Regency more professional in utilizing IT to convey information on the impact of Covid-19 to the public through infographics. So that it can increase the awareness of the people of Katonsari Village in preventing Covid-19. This program consists of several stages which include delivering conceptual material on infographics, compiling data on the impact of Covid-19 into IT-based information, especially infographics, and socializing the results of infographics to the public.
Comparison between Average Linkage and K-Means Clustering Methods in Grouping Regencies or Cities by Open Unemployment Rate in Central Java Sarah, Albertus Dion; Supriadin, Supriadin; Widiyanti, Karin Dita; Arsusma, Jesicha Roselina; Triky, Yolan; Arum, Prizka Rismawati
Jurnal Pendidikan Matematika Vol 9, No 1 (2026): Jurnal Pendidikan Matematika (Kudus)
Publisher : Universitas Islam Negeri Sunan Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21043/jpmk.v9i1.34232

Abstract

Unemployment is a serious social and economic problem that hinders growth, including in Central Java Province. Based on the National Labor Force Survey (Sakernas), the unemployment rate in Central Java Province reached 5.96% in February 2021, an increase of 1.76% compared to February 2020. This study aims to compare two clustering methods, namely Average Linkage and K-Means Clustering, in grouping regions based on three indicators: population size, regencies/cities Minimum Wage (UMK), and labor force size. Evaluation was performed using the Silhouette Coefficient value to assess cluster quality. The analysis results indicated that the K-Means Clustering method with 2 clusters is the most optimal approach for classifying the open unemployment rate in Central Java Province. This is demonstrated by a higher Silhouette Coefficient value of 0.676 for K-Means Clustering, compared to 0.444 for the Average Linkage method. This clustering result divides the region into 2 clusters, namely the first cluster consisting of 8 regencies/cities and the second cluster comprising 27 regencies/cities. These findings are expected to assist local governments in formulating targeted unemployment mitigation policies. Pengangguran merupakan masalah sosial dan ekonomi serius yang menghambat pertumbuhan, termasuk di Provinsi Jawa Tengah. Berdasarkan Survei Angkatan Kerja Nasional (Sakernas), mencatat tingkat pengangguran di Provinsi Jawa Tengah mencapai 5.96% pada Februari 2021, atau meningkat 1,76% dibandingkan Februari 2020. Penelitian ini bertujuan membandingkan dua metode pengelompokan, yaitu Average Linkage dan K-Means Clustering, dalam mengelompokkan wilayah berdasarkan tiga indikator: jumlah penduduk, Upah Minimum Kabupaten/Kota (UMK), dan jumlah angkatan kerja. Evaluasi dilakukan menggunakan nilai Silhouette Coefficient untuk menilai kualitas cluster. Hasil analisis menunjukkan bahwa metode K-Means Clustering dengan jumlah 2 cluster merupakan pendekatan yang paling optimal dalam mengelompokkan tingkat pengangguran terbuka di Provinsi Jawa Tengah. Hal ini ditunjukkan oleh nilai Silhouette Coefficient yang lebih tinggi, yaitu 0.676 untuk K-Means Clustering, dibandingkan dengan 0.444 pada metode Average Linkage. Hasil klasterisasi ini membagi wilayah menjadi 2 cluster, yaitu cluster pertama yang terdiri dari 8 Kabupaten/Kota dan cluster kedua yang mencakup 27 Kabupaten/Kota. Temuan ini diharapkan dapat membantu pemerintah daerah dalam menyusun kebijakan penanggulangan pengangguran secara lebih tepat sasaran.
Co-Authors Ach Ridoi Alambara Agi Khoerunnisa Alfidayanti, Ina Alfisyahrina Hapsery Ali Imron Ali Imron Alwan Fadlurohman Amalia Jihan Syafiqoh Amri, Saeful Anisa Putri Arla Vatwa Lubu Aqsal Maulana Ariska Fitriyana Ningrum Arsusma, Jesicha Roselina Arya Praditya Azizah, Apipah Nur Cika Awani Ayuwida Cintadea Amanda Dwi Aryani Dannu Purwanto Dhani, Oktaviana Rahma Dheanyta Alif Shafira Diandra Fatimahthus Zahra Dominikus Leki Sogen Dwi Rahmadini Eko Andy Purnomo Elvia Nanda Sofiyanti Endang Tri Wahyuni Maharani Erlinda, Relly Evida Oktaviana Fatkhurrokhman Fauzi Fauzi, Fatkhurokhman Fenny Amalia Adani Fitriyah, Novina Indah Gautama, Rahmad Putra Hanief Rizky Utami Haris, M Al Indah Fitriyani Indah Manfaati Nur Indah Manfaati Nur Indah Sulistiya Indriani, Anita Retno ine fitriani Isna Nur Azizah Izzadin Muhamad Nur Irfan Kurnia Nur Annisa Laila Khoirun Nisa Linda Puspitasari Lisa Anggraini Lydia Nur Sa'adah M. Al Haris Miftakhul Haris Mohammad Ridwan Muhammad Saifudin Nur Mulya Asy-syifa Rahmi Nerisa Rahma Nursamsiah Nursamsiah Pratiwi, Alda Putri Prissy Nusaiba Yulisa Puspitasari, Listi Putro, Dwi Purnomo Rochdi Wasono Rochdi Wasono Samikoh Ulinuha Sarah, Albertus Dion Setyaningsih, Laras Indah Siti Mutiah Siva Alfian Sugito Sugito supriadin supriadin Supriyadin, Supriyadin Tiani Wahyu Utami Tresiani Yunitasari Triky, Yolan Velia Arni Widyasari Widiyanti, Karin Dita Wisudawati, Dinda Tri Wulandari, Anjelina Rafika Yan Nazala Bisoumi Yuciana Wilandari Yulia Fitri