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All Journal Jurnal Ilmu Pertanian Indonesia FORUM STATISTIKA DAN KOMPUTASI Media Statistika Disease Prevention and Public Health Journal JURNAL PETERNAKAN Sosioinforma JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics BAREKENG: Jurnal Ilmu Matematika dan Terapan J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jambura Journal of Mathematics ComTech: Computer, Mathematics and Engineering Applications J-ADIMAS (Jurnal Pengabdian kepada Masyarakat) JURNAL AKUNTANSI KEUANGAN DAN MANAJEMEN Jurnal Pendidikan dan Kebudayaan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Natural Xplore: Journal of Statistics Jurnal Pengabdian Masyarakat dan Lingkungan PRAGMATIS Jurnal Manajemen dan Bisnis Jurnal Medika Veterinaria Scientific Journal of Informatics Indonesian Journal of Statistics and Its Applications Jurnal Info Kesehatan
Indahwati
Department Of Statistics, Faculty Of Mathematics And Natural Science, IPB University, Bogor, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Veterinary Other

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KLASIFIKASI TINGKAT PENGANGGURAN TERBUKA DI PULAU JAWA MENGGUNAKAN REGRESI LOGISTIK ORDINAL Indah, Yunna Mentari; Fitrianto, Anwar; Erfiani, Erfiani; Indahwati, Indahwati; Aliu, Muftih Alwi
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i2.629

Abstract

Unemployment is one of the indicators for measuring the economic conditions of a region. It is also a social and economic problem in many countries, including Indonesia, especially in areas with a density of economic activity, such as Java Island. The purpose of this study was to classify and analyze the factors that affect the open unemployment rate in cities and regions on Java Island, which are categorized as low, medium, and high. The research method used in this study was ordinal logistic regression analysis. The data source comes from the BPS website in 2023 with four predictor variables: population size, labor force participation rate, average years of schooling, and gross regional domestic product at constant prices. The research results show that the variables population size and labor force participation rate had a significant effect on the open unemployment rate, while the variables average years of schooling and gross regional domestic product at constant prices did not have a significant effect on the open unemployment rate with the accuracy of the ordinal logistic model is 77.27%.
ANALISIS FAKTOR YANG MEMPENGARUHI INDEKS PEMBANGUNAN MANUSIA DI INDONESIA MENGGUNAKAN MODEL REGRESI LOGISTIK BINER Vitona, Desi; Erfiani, Erfiani; Indahwati, Indahwati; Fitrianto, Anwar; Aliu, Mufthi Alwi
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i2.634

Abstract

The primary tool for assessing the extent of human development progress in a country is the Human Development Index (HDI). There are three components of Indonesia's Human Development Index (HDI). The method used to characterize the quality of human existence is based on these foundational aspects of HDI. The three elements include the role of economic advancement in human progress, as well as health, knowledge, and a decent standard of living. The objective of this research is to conduct binary logistic regression modeling to identify the key aspects that influence the Human Development Index of Regencies and Cities in Indonesia. If the response variable is binary and the predictor factors consist of one or more continuous or categorical variables, binary logistic regression is the statistical technique used to model the categorical response variable. The research results indicate that the percentage of Life Expectancy (X1), Average Length of Schooling (X2), Expected Years of Schooling (X3), and Per Capita Expenditure (X4), both partially and simultaneously, are independent variables that have the most significant impact on HDI at a real level of α = 5%. A balanced accuracy rating of 91.83% was achieved from the model evaluation, indicating that the model is useful
MODEL KLASIFIKASI REGRESI LOGISTIK BINER UNTUK LAPORAN MASYARAKAT DI OMBUDSMAN REPUBLIK INDONESIA Daswati, Oktaviyani; Indahwati, Indahwati; Erfiani, Erfiani; Fitrianto, Anwar; Aliu, Muftih Alwi
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i2.702

Abstract

A classification model is needed to predict data into the right class according to the pattern of previous data. Binary Logistic Regression can be used in building classification models, even though the independent variables are categorical scale data. Through binary logistic regression, it can also be seen which category of independent variables influences the response variable. Public complaint reports at the Ombudsman of the Republic of Indonesia are classified into reports that found maladministration and not. The Binary Logistic Regression model with several categorical independent variables related to the public complaint reports data applied resulted in a classification model with an overall classification accuracy of 66.08% and a sensitivity of 75.31% in estimating the presence of maladministration findings in the submitted public complaint reports. Based on the 95% confidence level of the model, it is known that the factors that influence the occurrence of maladministration are the Group of Reportees, the Substance of the Report, the Method of Submission, the Request for Confidentiality, and the Location of the Inspection Office. This model can be used as a reference to reduce the incidence of maladministration cases in public service providers by focusing socialization and education on categories that have a real influence on each of these factors
Prevalence and Risk Factors of Scabies in Cats at Koiverde Petcare Clinic during 2022 Kamil, Farid Ikram; Narindria, Yasmin Nadhiva; Notodiputro, Khairil Anwar; Indahwati, Indahwati; Mualifah, Laily Nissa; Putra, Stefanus Morgan Setyadi Perdana
Jurnal Medika Veterinaria Vol 18, No 2 (2024): J. Med.Vet
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21157/j.med.vet..v18i2.38993

Abstract

Scabies is a skin disease caused by Sarcoptes scabiei or Notoedres cati mites in the corneum layer of the skin. This case study aimed to determine the prevalence and risk factors affecting the incidence of scabies in cats. Medical record data were obtained from Koiverde Petcare clinic from January to December 2022. The data obtained were then processed with binary logistic regression analysis and Odds Ratio (OR) using Minitab 19 for Windows software. OR value of the risk factors of breeds, sex and age were evaluated. Based on the results of the study, the prevalence rate of scabies in January-December 2022 period at the Koiverde Petcare clinic was 2.84%. The breeds most at risk of being infected with scabies was the Himalayan breed (X16), the sex most at risk of being infected was male (X21), and the age of the cat most at risk of being infected with scabies was the young age of the cat.
Future Prospect Versus Past Performance Menjelang Pemilihan Umum tahun 2024 Indahwati, Indahwati; Agustini , Ni Ketut Yulia
Jurnal Akuntansi, Keuangan, dan Manajemen Vol. 6 No. 1 (2024): Desember
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/jakman.v6i1.3351

Abstract

Purpose: This study aims to determine whether what investors actually expect between future prospects or past performance is related to the certainty and policy of market rules and the upcoming government to provide an overview of decision-making for management and investors. Research methodology: The research variables in this study were operational decisions, strategic decisions, financial performance, and company value as proxies for future prospects and past performance. Factor analysis and multiple linear regression were used for analysis. The population in this study includes companies listed on the Indonesia Stock Exchange. The sample was obtained using the purposive sampling method with the criteria of companies in the industry that were directly affected by the election on a quarterly basis, namely the 3rd and 4th quarters of 2023, and as many as 49 companies with 69 analysis units were obtained. Results: The results show that the three variables–operational decisions (DSO), strategic decisions (growth), and financial performance (ROA)–have a significant effect on the company's value (P/E) ahead of the 2024 elections. Research implications: Investors look more at future prospects by examining operational decisions, strategic decisions, and the company's financial performance. Limitations: The lack of data and the analysis techniques used were very simple. Contributions: This study reveals how operational, strategic, and financial performance decisions affect the value of companies in Indonesia ahead of the 2024 elections. Using regression analysis, this study identifies key factors such as Days Sales Outstanding (DSO), growth (growth), and Return on Assets (ROA) as determinants of company value. These findings provide practical insights for managers and investors, as well as theoretical contributions, by adding the political economy context to the analysis of company values.
Comparison of SARIMA and BES for Forecasting Red Chili Production Agustina, Titin; Fitrianto, Anwar; Indahwati, Indahwati
Jurnal Ilmu Pertanian Indonesia Vol. 30 No. 2 (2025): Jurnal Ilmu Pertanian Indonesia
Publisher : Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18343/jipi.30.2.333

Abstract

The goal of this study is to compare the performance of Seasonal Autoregressive Integrated Moving Average (SARIMA) and Bagging Exponential Smoothing (BES) models for forecasting red chili production. The secondary data used in this study came from BPS-Statistics Indonesia and the Ministry of Agriculture. The data include monthly national-level red chili production from January 2013 to December 2021. Data is analyzed using time series approaches such as SARIMA and BES. The performance of both systems was compared, and production forecasts were created using the best model. According to the research findings, for this dataset, the SARIMA (1,1,1)(0,1,1)12 technique outperforms the BES method since it has lower MAPE and RMSE values, 7.06 and 95,473, respectively. The best model was then applied to anticipate red chili production from January to December 2022, resulting in a highly accurate MAPE of 5.39. Keywords: Bagging Exponential Smoothing, red chili production, SARIMA
Membangun Minat dan Jiwa Kewirausahaan Pada Siswa SMK Kartini Surabaya Agustini, Ni Ketut Yulia; Indahwati, Indahwati; Kholidiah, Kholidiah
Jurnal Pengabdian Masyarakat dan Lingkungan (JPML) Vol 3 No 2 (2025): Jurnal Pengabdian Masyarakat dan Lingkungan (JPML)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/jpml.v3i2.9085

Abstract

Building interest and entrepreneurial spirit in the younger generation is not easy, the perception that entrepreneurship is not an attractive or profitable career choice is one of the obstacles in building interest and developing an entrepreneurial spirit among young people, this perception causes young people's interest in entrepreneurship to still be very low. This service aims to provide entrepreneurship training in order to build economic independence for students at Vocational High School SMK Kartini 7 Surabaya. Generation Z is a generation that is expected to be able to contribute to participating in encouraging economic development and improving welfare, improving welfare starts for themselves, family, friends and the surrounding community. Inability to see business opportunities, lack of ideas or concepts, lack of knowledge and skills, fear of failure, inability to manage and face risks, lack of self-confidence, lack of support from people around them, all of these are factors that hinder the growth of interest and entrepreneurial spirit among the younger generation. For this reason, efforts are needed to overcome these obstacles, through entrepreneurship training. Entrepreneurship training aims to foster interest and build an entrepreneurial spirit among vocational school students and build awareness that entrepreneurship is very important to increase potential and self-development, build an independent, creative and innovative spirit, a tough generation that does not give up easily.
IDENTIFIKASI KARAKTERISTIK ANAK PUTUS SEKOLAH DI JAWA BARAT DENGAN REGRESI LOGISTIK Tina Aris Perhati; . Indahwati; Budi Susetyo
Indonesian Journal of Statistics and Applications Vol 1 No 1 (2017)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v1i1.51

Abstract

School dropouts are the problem in education which is the condition of children who do not have the opportunity to complete their education that they couldnt obtain degree certificate due to certain factors. Based on SUSENAS 2013, there is 2.15% of children aged 7-15 years old in West Java who dropped out of school. Three aspects that have great potential on the incidence of school dropouts are characteristic of social, economy, and demography. This study uses logistic regression analysis to determine the effect of school dropouts by the three aspects. The results of logistic regression analysis at 5% significance level indicates that the characteristics of social, economy, and demography that have significant effect on the incidence of school dropouts are the low education of household head, more than four household members, less than the poverty line household expenditure per capita, residence location in urban areas, and boys. The resulting model is sufficientfor estimation with the sensitivity value of 70.20% and the area under the ROC curve of 76.42%. Keywords: logistic regression, ROC curve, school children, sensitivity.
COMPARISON OF K-MEANS CLUSTERING METHOD AND K-MEDOIDS ON TWITTER DATA Cahyani Oktarina; Khairil Anwar Notodiputro; Indahwati Indahwati
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i1.599

Abstract

The presidential election is one of the political events that occur in Indonesia once in five years. Public satisfaction and dissatisfaction with political issues have led to an increase in the number of political opinion tweets. The purpose of this study is to examine the performance of the k-means and k-medoids method in the Twitter data and to tweet about the presidential election in 2019. The data used in this study are primary data taken from Muhyi's research, then mining the text against data obtained. Because this data has been processed by Muhyi to analyze the electability of the 2019 presidential candidate pairs, for this journal needs a preprocessing was carried out to analyze the tendency of tweets to side with the candidate pairs of one or two. The difference in the pre-processing of this research with previous research is that there is a cleaning of duplicate data and normalizing. The results of this study indicate that the optimal number of clusters resulting from the k-means method and the k-medoid method are different.
EVALUASI KINERJA METODE CLUSTER ENSEMBLE DAN LATENT CLASS CLUSTERING PADA PEUBAH CAMPURAN Debora Chrisinta; I Made Sumertajaya; Indahwati Indahwati
Indonesian Journal of Statistics and Applications Vol 4 No 3 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i3.630

Abstract

Most of the traditional clustering algorithms are designed to focus either on numeric data or on categorical data. The collected data in the real-world often contain both numeric and categorical attributes. It is difficult for applying traditional clustering algorithms directly to these kinds of data. So, the paper aims to show the best method based on the cluster ensemble and latent class clustering approach for mixed data. Cluster ensemble is a method to combine different clustering results from two sub-datasets: the categorical and numerical variables. Then, clustering algorithms are designed for numerical and categorical datasets that are employed to produce corresponding clusters. On the other side, latent class clustering is a model-based clustering used for any type of data. The numbers of clusters base on the estimation of the probability model used. The best clustering method recommends LCC, which provides higher accuracy and the smallest standard deviation ratio. However, both LCC and cluster ensemble methods produce evaluation values that are not much different as the application method used potential village data in Bengkulu Province for clustering.
Co-Authors A. A., Muftih Aditya Ramadhan Agus Mohamad Soleh Agustini , Ni Ketut Yulia Agustini, Ni Ketut Yulia Aji Hamim Wigena Akbar Rizki Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amelia, Reni Amin, Yudi Fathul Anang Kurnia Anik Djuraidah Antonius Benny Setyawan Ari Handayani Arie Anggreyani Aristawidya, Rafika Assyifa Lala Pratiwi Hamid Aunuddin . Bagus Sartono Budi Susetyo Cahyani Oktarina Chrisinta, Debora Daswati, Oktaviyani Dea Fisyahri Akhilah Putri Dian Kusumaningrum Erfiani Erfiani Erfiani Erfiani Erfiani Etis Sunandi Farit Mochamad Afendi Farit Mohamad Afendi Fatimah Fatimah Fira Nurahmah Al Aminy Fitrianto, Anwar Fulazzaky, Tahira Ghina Fauziah Hanifa Izzati Hari Wijayanto Harismahyanti A., Andi Hasanah, Lailatul I Gusti Putu Purnaba I Made Sumertajaya Iin Maena Indah, Yunna Mentari Irawan Irawan Jaya, Eddy Santosa Julianti, Elisa D Kamil, Farid Ikram Karunia, Nia Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Kholidiah, Kholidiah Khusnia Nurul Khikmah Kusman Sadik Latifah, Leli Lestari, Nila Lili Puspita Rahayu Miranti, Ita Miranti, Ita Mohammad Masjkur Mualifah, Laily Nissa Mualifah, Laily Nissa Atul Muhammad Nur Aidi Naima Rakhsyanda Narindria, Yasmin Nadhiva Nurul Fadhilah Panjaitan, Intan Juliana Puput Cahya Ambarwati Putra, Stefanus Morgan Setyadi Perdana Putri, Christiana Anggraeni Ramdani, Indri Rasyid, Baharun Ray Sastri Regan, Regan Reni Amelia Reni Amelia Reza, Charolina Therezia Rifki Hamdani Rindy Anggun Pertiwi Salvina Salvina Silmi Annisa Rizki Manaf Siti Hafsah Siwi Haryu Pramesti Tahira Fulazzaky Tina Aris Perhati Titin Agustina Titin Suhartini Titin Suhartini, Titin Utami Dyah Syafitri Vera Maya Santi Vitona, Desi Wahyudi Setyo Yenni Angraini Yuniarty, Titin Zulkarnain, Rizky _ Aunuddin