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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 CAUCHY: Jurnal Matematika Murni dan Aplikasi 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) 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) Jurnal Ilmiah Manajemen dan Bisnis JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) G-Tech : Jurnal Teknologi Terapan Inferensi Contemporary Mathematics and Applications (ConMathA) Jurnal Layanan Masyarakat (Journal of Public Service) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Enthusiastic : International Journal of Applied Statistics and Data Science Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Indonesian Vocational Research Journal Jurnal Pendidikan Matematika PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Pengabdian Nasional (JPN) Indonesia Feelings: Journal of Counseling and Psychology Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat) Indonesian Journal of Statistics and Its Applications Jurnal Ilmu Sosial dan Humaniora Limits: Journal of Mathematics and Its Applications Jurnal Riset Sosial Humaniora dan Pendidikan
Nur Chamidah
Departemen Matematika, Fakultas Sains Dan Teknologi, Universitas Airlangga
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry 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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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.
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.
Membangun Kesadaran Siswa Tentang Mitigasi Bencana Gempa Bumi Melalui Program Edukasi Dhohirrobbi, Achmad; Islamudin, Mohamad Mujahid; Chamidah, Nur; Amin, Saiful
Jurnal Pengabdian Nasional (JPN) Indonesia Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpni.v6i1.1142

Abstract

Indonesia is highly vulnerable to natural disasters, particularly earthquakes, due to its location at the convergence of three major tectonic plates. Every year, various disasters occur, significantly impacting communities, especially children who are the most vulnerable group. This community service program aims to improve the earthquake disaster mitigation understanding of students at Asrama Tahfidz Al Uswah Bangil through an integrated learning method that combines theory and practice. The program includes introducing earthquake signs, self-rescue actions, as well as simulations of pre-disaster, during disaster, and post-disaster earthquake responses. The earthquake simulation provides students with hands-on experience in taking correct actions during disasters. Activities are carried out by dividing students into small groups to enhance interaction, communication, and collective understanding among them. After the material presentation, a Higher Order Thinking Skills (HOTS) based quiz is conducted to assess students' comprehension of the material presented. It is hoped that the knowledge and skills gained by students through this program will help them be more prepared and vigilant in facing potential disasters. This activity also contributes to increasing public awareness of the importance of disaster mitigation in Indonesia, with the hope that students can become change agents in their communities regarding disaster preparedness.
Comparative Analysis of Local Polynomial Regression and ARIMA in Predicting Indonesian Benchmark Coal Price Mahadesyawardani, Arinda; Maulidya, Utsna Rosalin; Marbun, Barnabas Anthony Philbert; Pratama, Fachriza Yosa; Chamidah, Nur
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 19 No. 1: June 2024
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v19i1.74889

Abstract

As one of the world's biggest coal producers, it is essential for Indonesia to follow the trend of benchmark coal price fluctuations for any future possibilities. This study compared two methods of forecasting benchmark coal prices to evaluate the accuracy of the predictions used a nonparametric regression based on the local polynomial estimator and a parametric ARIMA method. Local polynomial analysis obtained a MAPE of 2.929278% using a CV method based on optimal bandwidth of 5.06 at order 2 with a cosine kernel, which means highly accurate forecasting accuracy. As for the ARIMA analysis, the data does not meet the assumption of normality, but forecasting is still continued with the best model ARIMA (1,2,1) model so that the MAPE is 12.6327%, which means good forecasting accuracy. Therefore in this study, the use of nonparametric regression methods using local polynomial estimators on data with non-normal distribution are more suitable to obtain accurate prediction results.
FORECASTING THE NUMBER OF SEARCH AND RESCUE OPERATIONS FOR SHIP ACCIDENTS IN INDONESIA USING FOURIER SERIES ANALYSIS (FSA) Recylia, Rien; Saifudin, Toha; Chamidah, Nur
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/barekengvol19iss2pp1023-1036

Abstract

As an archipelago country, Indonesia is a national and international route. This position makes high ship mobility which also increases the risk of ship accidents. To address this issue, based on these conditions, a prediction is required to forecast ship accidents in Indonesia for the upcoming period using an effective method. Through data forecasting, we can map the readiness of Basarnas resources in conducting search and rescue operations for ship accidents. Forecasting data for search and rescue operations in ship accidents is important because it can predict the quantity of needed search and rescue operations. These can be effective measures to reduce casualties in accidents of this type. This research uses the Fourier Series Analysis (FSA) method, which doesn’t require parametric assumption. Additionally, the FSA method can be used for data with unknown patterns. The data used is divided into training data and testing data. The training data used in this research is the number of search and rescue operations from January 2021 to December 2022, while the testing data is from January 2023 to December 2023. The analysis results of this study indicate that forecasting using the FSA method has a MAPE of 25.758%, which falls into the category of reasonable forecasting accuracy and with an optimal and a GCV of 166.586. The results of future predictions are in the form of a mathematical model that can be used by entering the time variable that you want to predict. The anticipated benefits of this research are to contribute to Basarnas’s planning and execution of search and rescue operations for shipwrecks, enrich academic literature on forecasting methodologies, and enhance public awareness of search and rescue operations in Indonesia
COMPARISON FORECASTING BETWEEN SINGULAR SPECTRUM ANALYSIS AND LOCAL LINEAR METHOD FOR SHIP ACCIDENT SEARCH AND RESCUE OPERATIONS IN INDONESIA Recylia, Rien; Saifudin, Toha; Chamidah, Nur; Mardianto, M. Fariz Fadillah
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/barekengvol19iss2pp1329-1340

Abstract

As a maritime country strategically located along the world's leading transportation routes, Indonesia often faces increased ship accidents. Based on the Basarnas Statistics Book, ship accidents handled by Basarnas from 2021 to 2023 increased by 3%. This condition requires an effective forecasting method to carry out SAR operations to predict ship accidents in the Indonesian region in the future and assess the readiness and needs of Basarnas resources. This study compares the forecasting results obtained using the Singular Spectrum Analysis (SSA) and the Local Linear methods. Both methods do not require parametric assumptions. The data used in this study are divided into training data and test data. This data is secondary data obtained from the Basarnas Statistics Book. The training data in this study is the number of SAR operations from January 2021 to December 2022, while the testing data is from January 2023 to December 2023. From the analysis results, it is known that the method with the smallest MAPE is the Local Linear method with a MAPE of test data of 18.67% (good forecasting category), optimal bandwidth (h) = 4.299, and CV (h) = 231.39 where bandwidth is used to determine the level of smoothness of the estimate, while the CV (h) value is used to select the optimal bandwidth that minimizes the estimation error. At the same time, the SSA method has a MAPE of 40.27% (fair forecasting category). This shows that the Local Linear method provides a more accurate forecast of the number of SAR operations related to ship accidents in Indonesia. This research contributes to the SDGs to make Basarnas an effective and accountable institution and improve the planning and decision-making process in SAR operations through accurate forecasting research is relevant to accurate forecasting.
Co-Authors A Meylin Abdul Aziz Abidin, Qumadha Zaenal Afriani Agus Satmoko Adi Ahmad Fauzi Aisharezka, Mutiara Akbar, Aditya Syarifudin Al Farizi, Muhammad Fikry Al Hasri, Ilham Maulana Alda Fuadiyah Suryono Aldawiyah, Najwa Khoir Alexandra, Victoria Anggia Alfiatur Rakhma, Syavrilia Alfinda Novi Kristanti Alpandi, Gaos Tipki Amanda, Yulia Aminuyati Aminy, Aisyah Ana, Elly Ananda Dwi Andini Putri Mediani Andriani, Putu Eka Andriani, Putu Eka Angga Kusuma Bayu Viargo Anies Yulinda W Anisa Laila Azhar Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ardiyanto, Figo Surya Ariyawan, Jovansha Aryati Aryati Aulia, Niswa Faizah Auliyah, Nina Azizah, Khansa Azzen, Fiyadika Amalia Nurizah Baihaqi, Mochamad Baihaqi, Muhammad Rizaldy Baktiar Aris Belindha Ayu Ardhani Brenda Bunga Prasenda Budi Lestari Budi Lestari Budijono, Gabriella Agnes Christopher Andreas D Lestari Darmawan, Kezia Eunike Dhohirrobbi, Achmad Dhyana Venosia Dhyana Venosia Diah Puspita Ningrum Diana Ulya Dita Amelia Dita Amelia, Dita Dzuria Hilma Qurotu Ain Hilma Easyfa Wieldyanisa, Ezha Eko Tjahjono Elfhira Juli Safitri Fachrian, Muhammad Nadhil Faiza, Atikah Faizun, Nurin Fajrina, Sofia Fajrina, Sofia Andika Nur Fakih Hamdani Fania, Azzahra Farida Farida Fatmawati Fatmawati Fatmawati Fatmawati Fauziah, Nathania Feevrinna Yohannes Harianto Fibryan, Muhammad Hilmi FIRMANSYAH, MOCHAMMAD Fitri Syaharani, Amadea Fitri, Marfa Audilla Fitri, Marfa Audilla Fizkadana, Canada Mewa Galih Yoga Santiko Gaos Tipki Alpandi Halimatuzzahro, Fitria Hammami, Martha Sayyida Hariadi, Salsabila Niken Hendrawan, Ardana Tegar Herdianto, Muhammad Hendra Hidayat, Rizky Ismaul Uyun Horidah Horidah Huda, Mi'rojul I Nyoman Budiantara Insania Dewanty, Sanda Islamudin, Mohamad Mujahid IZZAH, NURUL Januarta, R. Arya Julianto, Agnes Happy Juniar, Muhammad Althof Kamiilah, Nadhira Safa Kamil, M. Aqil Zaidan Kamila, Yasmin Kinanti Hanugera Gusti Kuni Safingah Larasati, Berliani Lensa Rosdiana Safitri Lilik Hidayati, Lilik Listyaningsih Listyaningsih M. Fariz Fadillah Mardianto Mahadesyawardani, Arinda Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Marisa Rifada Marthabakti, CitraWani Maulidya, Utsna Rosalin MAYA MUSTIKA KARTIKA SARI, MAYA Mediani, Andini Putri Mediani, Andini Putri Melati Tegarina Mohamad David Hermawan Muhammad Falah El Fahmi Muhammad Fikry Al Farizi Mutiara Aisharezka Mutiara Arlisyah Putri Utami Muzakki, Naufal N. A. Aprilianti Nadia Murbarani Nahar, Muhammad Hafidzuddin Naufal Ramadhan Al Akhwal Siregar Nia Saurina Nitasari, Alfi Nur Nur Azizah Rahayu Ningsih 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 Ramadhani, Azzah Nazhifa Wina Ramadhanti, Aulia Ramadhina, Fidela Sahda Ilona Ramadhita, Ghina 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 Safitri, Lensa Rosdiana Salsabilla, Shafira Salsabylla Nada Apsariny Sasmia Desinta Wulandari Sa’idah, Andini Sediono, Sediono Sely Novika Norrachma Septia Sari, Ni Wayan Widya Setyawan, Muhammad Daffa Bintang Setyowati, Raden Roro Nanik Siagian, Kimberly Maserati Siburian, Cynthia Anggelyn Sihite, Rivaldi Siregar, Naufal Ramadhan Al Akhwal Siti Maizul Habibah Slamet Muchsin Soewignjo, Steven Sofia Andika Nur Fajrina Subiyanto, Marcel Laverda Sufyan Ats Tsauri Sugha Faiz Al Maula Suliyanto Sunariyanto, Sunariyanto Suryono, Alda Fuadiyah Suryono, Alda Fuadiyah Suwarno Suwarno Syahputra, Bimo Okta Syifaun Nadhiro Teguh Susanto 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 Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Nuryuliana Yolanda Swastika Yolanda Swastika Yonani Zahrotul Azizah Zhafira, Azizah Atsariyyah Zidni Ilmatun Nurrohmah