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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI SAINSMAT Jurnal Statistika Universitas Muhammadiyah Semarang TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Matematika dan Sains Jurnal Ketahanan Nasional Journal of Information Systems Engineering and Business Intelligence Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications Zeta - Math Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Zero : Jurnal Sains, Matematika, dan Terapan Cakrawala: Jurnal Litbang Kebijakan Jurnal Aplikasi Statistika & Komputasi Statistik JCRS (Journal of Community Research and Service) JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) G-Tech : Jurnal Teknologi Terapan Inferensi Contemporary Mathematics and Applications (ConMathA) Jurnal Layanan Masyarakat (Journal of Public Service) Enthusiastic : International Journal of Applied Statistics and Data Science Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Indonesian Vocational Research Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Pengabdian Nasional (JPN) Indonesia Feelings: Journal of Counseling and Psychology Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat) Indonesian Journal of Statistics and Its Applications Limits: Journal of Mathematics and Its Applications
Nur Chamidah
Departemen Matematika, Fakultas Sains Dan Teknologi, Universitas Airlangga
Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Pemodelan Indeks Ketahanan Pangan di Indonesia Berdasarkan Pendekatan Regresi Logistik Ordinal Data Panel Efek Acak Anisa Laila Azhar; Suliyanto Suliyanto; Nur Chamidah; Elly Ana; Dita Amelia
Jurnal Ketahanan Nasional Vol 29, No 2 (2023)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jkn.86511

Abstract

ABSTRACTIndonesia is an agricultural country with the agricultural sector being an important sector in supporting food needs. Food availability that is less than necessary can lead to an unstable economy, as well as disrupt national food security. This study was conducted to model The Food Security Index (Indeks Ketahanan Pangan, IKP) and to find out what factors affect the status of food security in Indonesia.The analysis method used in this study is the logistic regression analysis of panel data with random effects. The data used in this study is secondary data related to IKP sourced from the Ministry of Agriculture and factors that are suspected to affect IKP in each province sourced from the Central Statistics Agency (Badan Pusat Statistik, BPS) from 2019 to 2021. The results of the analysis showed that statistically, the variable percentage of stunted toddlers and the variable percentage of households with access to electricity had a significant effect on the IKP. In addition, the results of the model conformity test showed that the random effect panel data logistic regression model was more in line with the classification accuracy of 50.98% when compared to the standard logistic regression with a classification accuracy of 40.80%.
Comparison Of Kernel Support Vector Machine In Stroke Risk Classification (Case Study:IFLS data) Lensa Rosdiana Safitri; Nur Chamidah; Toha Saifudin; Gaos Tipki Alpandi
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.381

Abstract

Stroke s a disability main source and main disability source to lost years of disability-adjusted life. Currently the information technology development, especially the field of machine learning has an important role in early warning of various diseases, such as strokes. One of the methods used for stroke classifying is Support Vector Machine (SVM). In this study, we aim to compare several kernel functions in SVM such as linear, radial basis function(RBF), polynomial, and sigmoid for classifying stroke risk. We determine the best kernel based on accuracy, sensitivity, and specificity values. The result of this study shows that linear kernel function gives the best performance in classifying with values of classification accuracy 99.0%, specificity 100.0%, ,and sensitivity 97.0%. Those scores are the highest scores among the other kernel , that means the linear kernel function is the best method for classifying strokes risk.
Pemodelan Jumlah Kasus Tuberkulosis pada Anak di Kota Bandung dengan Pendekatan Geographically Weighted Negative Binomial Regression Brenda Bunga Prasenda; Mohamad David Hermawan; Mutiara Aisharezka; Sufyan Ats Tsauri; Nur Chamidah
G-Tech: Jurnal Teknologi Terapan Vol 8 No 1 (2024): G-Tech, Vol. 8 No. 1 Januari 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i1.3881

Abstract

Tuberculosis (TB) is an infectious disease. According to WHO (2020), 1.5 million people die from tuberculosis and it is also the 13th largest cause of death in the world and the second largest infectious disease cause of death after COVID-19. This research aims to create a new model based on different methods, targets and time to determine the modeling of factors that influence the number of tuberculosis diseases in Bandung City using the Geographically Weight Negative Binomial Regression (GWNBR) method. The modeling in this study is known to have differences between Negative Binomial Regression and Geographically Weight Negative Binomial Regression (GWNBR) with Bojongloa Kaler having the highest cases, significantly influenced by the number of cases in adult men. This research encourages the Bandung City government to provide equitable health services, consider these factors, and evaluate policies to reduce tuberculosis cases in children aged 0-14 years, especially in adult males.
Comparison of Logistic Regression and Support Vector Machine in Predicting Stroke Risk Lensa Rosdiana Safitri; Nur Chamidah; Toha Saifudin; Mochammad Firmansyah; Gaos Tipki Alpandi
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20420

Abstract

The issue of health is the third goal of Indonesia's Sustainable Development Goals (SDGs) which is state to ensuring a healthy life and promoting prosperity for all people at all ages. One of the SDGs’s concerns is deaths caused by non-communicable diseases (NCDs) including strokes. One prevention that can be done is by making a prediction of stroke for early detection. There are various methods available which are statistical methods and machine learning methods. In this research work, we aim to compare the two methods based on statistical method and machine learning method on stroke risk prediction. The data used in this research is primary data from Universitas Airlangga Hospital (RSUA) from June until August 2023. In this research, we compare the statistical method that is Logistic Regression (LR), and the machine learning method which is Support Vector Machine(SVM). We use Phyton to analyze all methods in this research. The results show that SVM with Radial Basis Kernel is better than LR in predicting stroke risk based on three goodness criteria namely sensitivity, F-1 score and accuracy where these three goodness criteria values of SVM are greater than those of LR.
Prediksi Jumlah Penumpang Kereta Api Stasiun Surabaya Gubeng dengan Metode Monte Carlo Angga Kusuma Bayu Viargo; Toha Saifudin; Nur Chamidah
Limits: Journal of Mathematics and Its Applications Vol 20, No 3 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v20i3.16123

Abstract

Jumlah penumpang kereta api di Indonesia kembali mengalami peningkatan semenjak masa pandemi. Salah satu stasiun yang mengalami peningkatan penumpang adalah Stasiun Surabaya Gubeng. Penelitian ini bertujuan untuk mendapatkan hasil prediksi jumlah penumpang harian kereta api di Stasiun Surabaya Gubeng menggunakan metode Monte Carlo dengan pembangkit bilangan acak yang berbeda. Metode Monte Carlo merupakan metode yang menginterpretasikan hasil ketidakpastian probabilitas dari suatu proses dan menyimulasikan nilai frekuensi secara stokastik dari segala kemungkinan hasil. Pembangkit bilangan acak yang digunakan yaitu; multiplicative, mixed, dan random uniform. Tingkat keakuratan dari hasil penelitian dihitung berdasarkan nilai Mean Absolute Percentage Error (MAPE). Data dalam penelitian ini merupakan data time series diambil dari tanggal 16 Mei 2022 hingga 2 Oktober 2022 sebanyak 140 hari. Data dibagi menjadi tujuh kelompok berdasarkan nama hari sebanyak 20 data untuk setiap kelompok. Prediksi dilakukan menggunakan Monte Carlo diperoleh rata-rata nilai MAPE outsample dari setiap kelompok hari yaitu;  hari Senin sebesar 25,25%, hari Selasa sebesar 16,74%, hari Rabu sebesar 17,73%, hari Kamis sebesar 3,32%, hari Jumat sebesar 12,36%, hari Sabtu sebesar 4,88%, dan hari Minggu sebesar 2,62%. Kesimpulan akhir diperoleh bahwa hasil prediksi sangat akurat terjadi pada hari Kamis, Sabtu dan Minggu.
IMPROVING EDUCATION AND DETERMINING THE NUTRITIONAL STATUS OF TODDLERS IN REALIZING NUTRITION-CONSCIOUS FAMILIES IN BANYUWANGI USING R-SHINY Nur Chamidah; Ardi Kurniawan; Toha Saifudin; Andini Sa'idah; Ayu Widyawati; Sofia Fajrina
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 8 No. 1 (2024): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jlm.v8i1.2024.061-073

Abstract

Stunting is a condition where a child's development and growth is disturbed, which has long-term impacts, including the potential for impaired brain development due to insufficient cognitive development and a greater risk of developing chronic diseases such as diabetes, hypertension, obesity, cancer, and so on. One effort to reduce stunting rates is to increase knowledge of nutrition awareness in the family. UNAIR Statistics Study Program, participates in efforts to reduce stunting rates with community service activities (Pengmas), in the form of outreach activities regarding basic and practical knowledge in the form of workshops and training activities using R-Shiny based WEB and Android to determine the nutritional status of toddlers which can used anywhere and anytime. This community service activity was carried out in the working area of "‹"‹the Tampo Community Health Center, Banyuwangi, East Java, involving 62 female cadre representatives from 31 local posyandu. The results of this community service activity can increase knowledge regarding education and nutrition knowledge for toddlers in the context of achieving nutrition-aware families. This is proven by the results of statistical analysis of pre-test and post-test scores which conclude that there is an increase in scores from pre-test to post-test with a significance level of 5%. Based on the results of the feedback questionnaire given to participants, the posyandu cadre mother felt very satisfied with an average score of 86, gained useful knowledge, and made it easier for posyandu cadres to find out the nutritional status of toddlers.
PERAMALAN KASUS HARIAN MONKEYPOX DUNIA BERDASARKAN METODE SUPPORT VECTOR REGRESSION (SVR) Subiyanto, Marcel Laverda; Amanda, Yulia; Fachrian, Muhammad Nadhil; Afriani; Rohim, Achmad Yazid Busthomi; Chamidah, Nur
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 1 (2023): Journal of Statistical Application and Computational Statistics
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v15i1.488

Abstract

Monkeypox saat ini menjadi perhatian masyarakat global. Maka, penting untuk mengetahui perkembangan jumlah kasus monkeypox kedepannya. Pada penelitian ini dilakukan peramalan kasus harian monkeypox menggunakan metode Support Vector Regression (SVR) dengan Fungsi Kernel Radial Basis Function (RBF). Data yang digunakan adalah data sekunder berupa deret waktu harian mulai 29 Mei sampai 20 Oktober 2022. Untuk memperoleh parameter optimal pada model SVR, peneliti menggunakan algoritma grid search untuk memprediksi data testing secara akurat. Nilai RMSE pada data training dan testing sebesar 352,3 dan 809,7.
ANALYZING THE RELATIONSHIP BETWEEN FREQUENCY IN USING SOCIAL MEDIA AND THE ANXIETY LEVEL OF BODY SHAMING AND HARASSMENT VICTIMS Julianto, Agnes Happy; Putra, Mochamad Rasyid Aditya; Rahmatika, Nabila Syahfitri; Widyangga, Pressylia Aluisina Putri; Chamidah, Nur
Journal of Community Research and Service Vol 7, No 1: January 2023
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jcrs.v7i1.41142

Abstract

In this sophisticated digital era, humans are easier to connect to everything. Unfortunately, this convenience is often used for things that should not be, such as insulting other people through chatting. This makes cyberbullying rampant, especially body shaming and harassment which cause depression, anxiety, and lack of confidence. The aim of this research is analyzing the relationship between the frequency in using social media and the anxiety level as the impact of body shaming and harassment. The research method used in this research is quantitative research with a correlational method. The results of this study are there is no relationship between the frequency of using social media and the anxiety level for both victims of body shaming and harassment, but if viewed based on the results of the respondents it is found that the possibility of cyberbullying is due to the level of education of the perpetrators, attitudes, and behavior. Advice that can be given is the need of further research on the main factors that cause cyberbullying and advice for readers is to control attitudes and behavior while using social media.
Prediksi Risiko Gagal Bayar Kredit Kepemilikan Rumah dengan Pendekatan Metode Random Forest Ulandari, Kartini Putri; Chamidah, Nur; Kurniawan, Ardi
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 2 (2024): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat132630212024

Abstract

Home Ownership Credit (KPR) is a credit facility provided by banks to individual customers who want to buy or repair a house. KPR also has problems with credit payment failures. This research aims to predict the risk of fraud on home ownership loans by applying the Random Forest method. Random Forest (RF) is a method that can increase accuracy results in generating attributes for each node which is done randomly. Based on the analysis results, it was found that the model with the smallest classification error was using mtry 2 and ntree 50 using a combination of training and testing data of 60%:40%. By applying the random forest algorithm, we obtained an accuracy rate of 84.75% with an Area Under the Curve (AUC) value of 84.32%, which is included in the very good classification category.
Education of Pancasila Values to Strengthen Villages' Awareness of Harmony in Pacet Village, Mojokerto Regency, East Java Listyaningsih, Listyaningsih; Warsono, Warsono; Setyowati, Raden Roro Nanik; Sari, Maya Mustika Kartika; Adi, Agus Satmoko; Huda, Mi'rojul; Usmi, Rianda; Thohari, Habib Nihla; Chamidah, Nur
AURELIA: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Vol 4, No 1 (2025): January 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/aurelia.v4i1.4492

Abstract

In facing national problems such as intolerance and ethnic and social conflicts, Indonesia needs to re-actualize the values of Pancasila, which have been proven as a unifying solution for the nation. Pancasila, as the foundation of the state and the nation's outlook on life, plays an important role in uniting the ethnic, religious, and cultural differences in Indonesia. However, in daily practice, the values of Pancasila tend to be eroded and are more present as formal symbols than behavioral guidelines, thus triggering various disputes between residents. Therefore, the purpose of this community service activity Pancasila is intended to (1) instill Pancasila values in the Pacet Village community; (2) mentor the Pacet Village youth organization as a facilitator of harmony by utilizing social media to campaign for harmony in society. This community service activity is a collaboration between the Pancasila and Citizenship Education Study Program, Surabaya State University with the Pacet Village Government, Pacet District, Mojokerto Regency, and the Mojokerto Regency Interfaith Harmony Forum. This community service activity is a Pancasila Discussion and Creative Content Creation Training for Karang Taruna Pacet Village. The method used is socialization, which provides material about Pancasila as a unifier of the nation, ending with digital content training. Through socialization activities, national insight training, discussions with religious leaders, and training for village officials, efforts to strengthen Pancasila encourage a harmonious life amidst diversity.
Co-Authors A Meylin Abidin, Qumadha Zaenal Afriani Agus Satmoko Adi Aisharezka, Mutiara Akbar, Aditya Syarifudin Al Farizi, Muhammad Fikry Al Hasri, Ilham Maulana Alexandra, Victoria Anggia Alfinda Novi Kristanti Amadea Fitri Syaharani Amanda, Yulia Aminuyati Aminy, Aisyah Ana, Elly Ananda Dwi Andini Putri Mediani Andini Sa'idah Andriani, Putu Eka Andriani, Putu Eka Angga Kusuma Bayu Viargo Angga Kusuma Bayu Viargo Anies Yulinda W Anisa Laila Azhar Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ardiyanto, Figo Surya Aryati Aryati Auliyah, Nina Ayu Widyawati Azizah, Khansa Azzen, Fiyadika Amalia Nurizah Baihaqi, Muhammad Rizaldy Baktiar Aris Belindha Ayu Ardhani Brenda Bunga Prasenda Budi Lestari Budi Lestari Christopher Andreas D Lestari Darmawan, Kezia Eunike Dhohirrobbi, Achmad Dhyana Venosia Dhyana Venosia Diah Puspita Ningrum Diana Ulya Dita Amelia Dita Amelia, Dita Easyfa Wieldyanisa, Ezha Eko Tjahjono Elfhira Juli Safitri Fachrian, Muhammad Nadhil Faiza, Atikah Faizun, Nurin Fajrina, Sofia Andika Nur Fajrina, Sofia Andika Nur Fania, Azzahra Farida Farida Farizi, Muhammad Fikry Al Fatmawati Fatmawati Fatmawati Fatmawati Fauziah, Nathania Feevrinna Yohannes Harianto Fibryan, Muhammad Hilmi Fitri, Marfa Audilla Fitri, Marfa Audilla Gaos Tipki Alpandi Gaos Tipki Alpandi Hammami, Martha Sayyida Hariadi, Salsabila Niken Hendrawan, Ardana Tegar Herdianto, Muhammad Hendra Hidayat, Rizky Ismaul Uyun Hilma, Dzuria Hilma Qurotu Ain Horidah Horidah Huda, Mi'rojul I Nyoman Budiantara Insania Dewanty, Sanda Islamudin, Mohamad Mujahid IZZAH, NURUL Julianto, Agnes Happy Juniar, Muhammad Althof Kamiilah, Nadhira Safa Kamil, M. Aqil Zaidan Kamila, Yasmin Kinanti Hanugera Gusti Larasati, Berliani Lensa Rosdiana Safitri Lensa Rosdiana Safitri Lilik Hidayati, Lilik Listyaningsih Listyaningsih M. Fariz Fadillah Mardianto Mahadesyawardani, Arinda Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Marisa Rifada Maula, Sugha Faiz Al Maulidya, Utsna Rosalin MAYA MUSTIKA KARTIKA SARI, MAYA Mediani, Andini Putri Mediani, Andini Putri Melati Tegarina Mochammad Firmansyah Mohamad David Hermawan Muhammad Falah El Fahmi Mutiara Aisharezka N. A. Aprilianti Nadia Murbarani Naufal Ramadhan Al Akhwal Siregar Nia Saurina Nitasari, Alfi Nur Prasetyo, Juan Krisfigo Pratama, Bagas Shata Pratama, Fachriza Yosa Purnama, Titania Faisha Putra, Mochamad Rasyid Aditya Qumadha Zainal Abidin Rahayu, Rizky Dwi Kurnia Rahma, Alma Khalisa Rahmatika, Nabila Syahfitri Ramadhina, Fidela Sahda Ilona Recylia, Rien Reiza Sahawaly Rico Ramadhan, Rico Rimuljo Hendradi Riries Rulaningtyas Rizza Sulistiana Rohim, Achmad Yazid Busthomi S, Salma Bethari Andjani Sa'idah, Andini Sabrina Falasifah Salsabylla Nada Apsariny Sa’idah, Andini Sediono, Sediono Sely Novika Norrachma Septia Sari, Ni Wayan Widya Setyawan, Muhammad Daffa Bintang Setyowati, Raden Roro Nanik Shafira Salsabilla Siagian, Kimberly Maserati Siburian, Cynthia Anggelyn Siregar, Naufal Ramadhan Al Akhwal Soewignjo, Steven Sofia Fajrina Subiyanto, Marcel Laverda Sufyan Ats Tsauri Suliyanto Suryono, Alda Fuadiyah Suryono, Alda Fuadiyah Suwarno Suwarno Syavrilia Alfiatur Rakhma Syifaun Nadhiro Thohari, Habib Nihla Tiani Wahyu Utami Toha Saifudin Toha Saifudin Trias Novia L. Trisa, Nadya Lovita Hana Ulandari, Kartini Putri Ulya, Diana Umi Tri Ruhana Usmi, Rianda Valida, Hanny Wahyuli, Diana Warsono Warsono Widyangga, Pressylia Aluisina Putri Wieldyanisa, Ezha Easyfa Wulandari, Nuryuliana Yolanda Swastika Yolanda Swastika Yonani Zahrotul Azizah Zidni Ilmatun Nurrohmah