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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.
MODELLING MATHEMATICS LEARNING OUTCOMES USING A MULTIPREDICTOR SEMIPARAMETRIC REGRESSION APPROACH BASED ON SPLINE ESTIMATOR Purnama, Titania Faisha; Chamidah, Nur; Saifudin, Toha
JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) Vol 11, No 1 (2025)
Publisher : Universitas Bhinneka PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jp2m.v11i1.6999

Abstract

Education is one of the points of Indonesia's SDGs which is stated in goal number 4. Mathematics is one of the subjects that contributes to the realizing national education goals. In the independent curriculum, the success of the learning process at school can be seen from the criteria for achieving learning objectives. In this article, we analyzed students’ mathematics learning outcomes using a multi predictor semiparametric regression approach and interpreted the results with Spline estimator. The results shows that the differences between the types of classes greatly influence outcomes in learning mathematics, where social classes experienced a decrease of 2.435 percent compared to science classes. To increase outcomes in learning mathematics, the percentage of learning motivation must be more than 88 percent. Apart from that, high or low IQ cannot determine whether students’ mathematics learning outcomes. Furthermore, by combining linear and nonlinear components in the model effectively, the overall accuracy based on the MAPE value is 7.87 percent, so that the model can be predict the actual value high accurately. Thus, the multi predictor semiparametric regression approach based on spline estimator can explain the mathematics learning outcomes model very well.
Prediction and Analysis of The Number of ARI Cases based on PM2.5 Concentration with Co-Kriging Approach Chamidah, Nur; Andriani, Putu Eka; Fitri, Marfa Audilla; Fajrina, Sofia Andika Nur; Suryono, Alda Fuadiyah; Alexandra, Victoria Anggia
Inferensi Vol 8, No 1 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i1.20512

Abstract

Air quality significantly impacts global environmental health, influencing both human well-being and climate change. According to the World Health Organization (WHO), air pollution is one of the most substantial environmental threats to human health, with Indonesia experiencing particularly severe air quality issues. The World Air Quality Report ranks Indonesia 14th globally and 1st in Southeast Asia for poor air quality, with a notable increase in PM2.5 concentrations to 37.1 µg/m³ in 2023. Major sources of pollution include coal-fired power plants, motor vehicles, forest fires, and agricultural activities. In urban areas like Surabaya, PM2.5 levels have risen, contributing to high incidences of Acute Respiratory Infections (ARI). Spatial analysis reveals a correlation between PM2.5 levels and ARI cases, with spatial regression and co-kriging methods offering accurate estimation models. This study utilizes co-kriging, incorporating PM2.5 data from nine districts in Surabaya, to estimate ARI cases. The Exponential semivariogram model provided the most accurate predictions, with a MAPE value of 5.11%. The highest estimated ARI cases were in the Kenjeran district, highlighting the need for targeted interventions. Future research should expand observation points and consider additional influencing factors such as weather, population density, and socioeconomic conditions to enhance prediction accuracy and support effective public health strategies.
MODELING OF THE PERCENTAGE OF AIDS SUFFERERS IN EAST JAVA PROVINCE WITH NONPARAMETRIC REGRESSION APPROACH BASED ON SPLINE TRUNCATED ESTIMATOR Nadia Murbarani; Yolanda Swastika; Ananda Dwi; Baktiar Aris; Nur Chamidah
Indonesian Journal of Statistics and Applications Vol 3 No 2 (2019)
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.v3i2.209

Abstract

Acquired Immune Deficiency Syndrome (AIDS) is a set of symptoms and infection or a syndrome that arise due to damage to the human immune system. AIDS is a health problem that often occurs in developing countries, including in Indonesia. East Java Province was ranked first in the highest number of AIDS sufferers in Indonesia ever reported from 1987-2016 as many as 16,911 people out of a total of 86,780 people. In order to overcome AIDS cases, it is necessary to know the factors that influence it. Data on the percentage of AIDS sufferers and their predictor variables have irregular data patterns or do not match in certain patterns, then the method that can solve these problems is by using the nonparametric regression based on spline truncated estimator. A spline truncated estimator is a segmented polynomial function that has better flexibility because there are knot points indicating changes in data behaviour patterns. The data that used in this study is a secondary data in 2016 obtained from the East Java Provincial Health Office. The results showed that the determination coefficient (R2) based on the best model of 93.84%. This shows that the variables of health facilities, blood donors, health workers, condom users, and residents of 25-29 years are able to explain 93.84% of the percentage of AIDS sufferers in East Java Province in 2016.
COMPARISON OF LEAST SQUARE SPLINE AND ARIMA MODELS FOR PREDICTING INDONESIA COMPOSITE INDEX Fitriyah, Any Tsalasatul; Chamidah, Nur; Saifudin, Toha
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2169-2178

Abstract

The Indonesian Composite Index (ICI) reflects Indonesia's economic growth. ICI predictions are significant considerations for investors when making investment decisions. Two approaches can be used to predict ICI: parametric and nonparametric approaches. Therefore, this study compares parametric and nonparametric approaches to predict ICI. In its application, the parametric approach requires several assumptions to be met, such as linearity. This differs from analysis with a nonparametric approach that does not require certain assumptions. The parametric approach in this study uses the ARIMA model. ARIMA is widely used to predict time series data. In the nonparametric approach, in this study, we used nonparametric regression based on the least square spline. Spline is chosen because it can handle data that tends to fluctuate by placing knot points when data changes occur. In this study, ICI monthly data obtained from the website investing.com was used. Investing.com is a website that financial analysts often use as a data source to monitor world economic conditions, including the ICI. The Mean Absolute Percentage Error (MAPE) value is determined to assess the accuracy of the prediction. The study results indicate that the analysis with ARIMA cannot meet the assumptions, so ARIMA modeling cannot be continued. Different results were obtained in nonparametric regression modeling based on the least square spline estimator. Prediction of ICI using nonparametric regression based on the least square spline estimator has a MAPE value of 2.613% (less than 10%), which means the model is a highly accurate prediction, meaning modeling using nonparametric regression based on the least square spline estimator is better than the ARIMA model for predicting ICI.
Peran Mahasiswa dalam Memanfaatkan Teknologi pada Program Asistensi Mengajar di EL DE’OT Private Course Darmawan, Kezia Eunike; Chamidah, Nur
Jurnal Teknologi Informasi untuk Masyarakat Vol. 3 No. 1 (2025): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v3i1.30229

Abstract

The Teaching Assistance Program is one of the implementations of the Merdeka Belajar Kampus Merdeka (MBKM) program, which aims to provide opportunities for students to participate in teaching and deepening their knowledge by becoming teachers, facilitators, tutors, trainers, or mentors in educational institutions within the community. This article documents the implementation of the Teaching Assistance Program by students of Universitas Airlangga at EL DE'OT Private Course. The students play the role of teaching assistants, creating teaching materials and being directly involved in the teaching and learning process in a non-formal institution in the form of private tutoring. In its implementation, students learn how to prepare teaching materials and teach using various teaching approaches, including fun learning, interactive PowerPoint, and exercises. It can be concluded that the program's objectives were successfully achieved, and the program provided various positive impacts for the students, the learners, and EL DE'OT Private Course as the institution where the teaching assistance took place. The students gained teaching experience, the learners acquired knowledge, and the institution involved obtained learning materials that could be used in the future.
Optimalisasi Analisis Harga Komoditas Daging dan Telur Ayam di Jawa Timur dengan Pendekatan Regresi Semiparametrik Chamidah, Nur; Kurniawan, Ardi; Hendradi, Rimuljo; Fatmawati; Kristanti, Alfinda Novi; Siregar, Naufal Ramadhan Al Akhwal; Wulandari, Nuryuliana; Aminy, Aisyah; Herdianto, Muhammad Hendra
Cakrawala Vol. 19 No. 1: Juni 2025
Publisher : Badan Riset dan Inovasi Daerah Provinsi Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32781/cakrawala.v19i1.759

Abstract

Fluktuasi harga yang terlalu tinggi pada komoditas pangan strategis seperti telur dan daging ayam telah menjadi permasalahan krusial, diantaranya disebabkan oleh harga pakan dan tingkat konsumsi masyarakat. Hal ini berdampak pada turunnya daya beli dan kesulitan akses pangan terutama bagi rumah tangga berpendapatan rendah yang mengandalkan kedua komoditas ini sebagai sumber protein utama. Oleh sebab itu, penelitian ini bertujuan untuk menganalisis pengaruh harga jagung sebagai bahan baku pakan ternak dan jumlah penduduk sebagai gambaran tingkat konsumsi masyarakat terhadap harga telur ayam dan harga daging ayam pada 38 Kabupaten/Kota di Jawa Timur tahun 2023 dengan menggunakan data sekunder yang diperoleh melalui aplikasi SISKAPERBAPO dan Badan Pusat Statistik Provinsi Jawa Timur. Metode yang digunakan adalah regresi semiparametrik birespon linear lokal. Hasil analisis menunjukkan bahwa model prediksi memiliki tingkat akurasi sangat tinggi, dengan nilai MAPE sebesar 1,103% untuk harga telur ayam dan 4,474% untuk harga daging ayam. Penelitian ini penting karena dapat menjadi dasar pengambilan kebijakan dalam upaya stabilisasi harga oleh pemerintah daerah maupun pelaku industri perunggasan di Jawa Timur.
Prediksi Harga Emas dan Nilai Tukar Rupiah dengan Pendekatan Estimator Deret Fourier Birespon Wahyuli, Diana; Chamidah, Nur; Saifudin, Toha; Herdianto, Muhammad Hendra
Cakrawala Vol. 19 No. 1: Juni 2025
Publisher : Badan Riset dan Inovasi Daerah Provinsi Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32781/cakrawala.v19i1.777

Abstract

Harga emas dan nilai tukar merupakan indikator ekonomi penting yang berdampak signifikan pada stabilitas ekonomi dan kebijakan moneter. Prediksi yang akurat dibutuhkan untuk mendukung pencapaian Sustainable Development Goals (SDGs) 8: Pekerjaan Layak dan Pertumbuhan Ekonomi, terutama dalam menjaga stabilitas pasar keuangan dan pengambilan keputusan berbasis data. Penelitian ini bertujuan untuk memprediksi harga emas dan nilai tukar menggunakan regresi nonparametrik birespon berbasis estimator deret Fourier. Metode ini dipilih karena fleksibilitasnya dalam menangkap pola tanpa asumsi bentuk fungsional tertentu. Data yang digunakan adalah data bulanan harga emas dan nilai tukar di Indonesia yang dibagi menjadi 80% insampel dan 20% outsampel selama periode Januari 2016 hingga Desember 2024, di mana satu variabel prediktor digunakan untuk memodelkan dua respon secara simultan. Model dievaluasi menggunakan Mean Absolute Percentage Error (MAPE), dengan hasil sangat akurat, sebesar 1,31%. Model ini mendukung strategi investasi dan kebijakan ekonomi di sektor keuangan.
Subjective Well-being of Tarim Women: A Study of Asceticism in the Novel Bidadari Bumi Nur Chamidah
Feelings: Journal of Counseling and Psychology Vol. 2 No. 2 (2025)
Publisher : Penerbit Hellow Pustaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61166/feelings.v2i2.60

Abstract

This research examines the subjective well-being of Tarim women reflected in the novel Bidadari Bumi by Halimah Alaydrus by using the approach of Ed Diener's subjective well-being theory and Max Weber's concept of asceticism. Using descriptive qualitative research method, this study aims to reveal how the subjective well-being of Tarim women is represented in contemporary literary works, as well as to analyze its relationship with asceticism values that are an integral part of Tarim people's lives. The research data was obtained through close reading of the novel, focusing on narratives and dialogues that describe the emotional experiences, life satisfaction, and religious practices of the female characters. The results show that the subjective well-being of Tarim women is formed through a complex interaction between life satisfaction based on spiritual values, positive affect derived from religious observance, and the practice of asceticism that is internalized in daily life. The findings provide a new perspective on how traditional values and modernity can coexist in shaping women's psychological well-being in the context of a traditional Muslim society.
Co-Authors A Meylin Abdul Aziz Abidin, Qumadha Zaenal Afriani Agus Satmoko Adi Aisharezka, Mutiara Akbar, Aditya Syarifudin Al Farizi, Muhammad Fikry Al Hasri, Ilham Maulana 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 Angga Kusuma Bayu Viargo Anies Yulinda W Anisa Laila Azhar Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ardiyanto, Figo Surya Aryati Aryati Auliyah, Nina 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 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 FIRMANSYAH, MOCHAMMAD Fitri Syaharani, Amadea Fitri, Marfa Audilla Fitri, Marfa Audilla Gaos Tipki Alpandi Halimatuzzahro, Fitria 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 Lilik Hidayati, Lilik Listyaningsih Listyaningsih M. Fariz Fadillah Mardianto Mahadesyawardani, Arinda Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Marisa Rifada Marthabakti, CitraWani Maula, Sugha Faiz Al Maulidya, Utsna Rosalin MAYA MUSTIKA KARTIKA SARI, MAYA Mediani, Andini Putri Mediani, Andini Putri Melati Tegarina Mohamad David Hermawan Muhammad Falah El Fahmi Mutiara Aisharezka 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 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 Siregar, Naufal Ramadhan Al Akhwal Siti Maizul Habibah Slamet Muchsin Soewignjo, Steven Subiyanto, Marcel Laverda Sufyan Ats Tsauri Suliyanto Sunariyanto, Sunariyanto Suryono, Alda Fuadiyah Suryono, Alda Fuadiyah Suwarno Suwarno 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 Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Nuryuliana Yolanda Swastika Yolanda Swastika Yonani Zahrotul Azizah Zidni Ilmatun Nurrohmah