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All Journal Indonesian Journal of Electronics and Instrumentation Systems Jurnal Sains dan Seni ITS IPTEK The Journal of Engineering JURNAL PENDIDIKAN TAMBUSAI Share : Journal of Service Learning PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Leverage, Engagement, Empowerment of Community (LeECOM) Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Kiprah Pendidikan Nautical: Jurnal Ilmiah Multidisiplin Indonesia Jurnal Ekonomi, Bisnis dan Manajemen Prosiding Seminar Nasional Official Statistics Al-DYAS : Jurnal Inovasi dan Pengabdian kepada Masyarakat Sewagati Indonesian Journal of Interdisciplinary Research in Science and Technology (MARCOPOLO) Scientica: Jurnal Ilmiah Sains dan Teknologi Triwikrama: Jurnal Ilmu Sosial Kohesi: Jurnal Sains dan Teknologi Cendikia: Jurnal Pendidikan dan Pengajaran Socius: Social Sciences Research Journal Jurnal Inovasi Global Journal Governance Society Jurnal kiprah pendidikan Jurnal Cakrawala Akademika
Sri Pingit Wulandari
Jurusan Statistika Institut Teknologi Sepuluh Nopember (ITS) Surabaya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT 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 Mathematics Mechanical Engineering Public Health Social Sciences Other

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Evaluasi Faktor Sosial dan Kemiskinan di Provinsi Papua: Pendekatan Analisis Komponen Utama Adinata, Aditya; Siahaan, Timotius Edward; Wulandari, Sri Pingit
Socius: Jurnal Penelitian Ilmu-Ilmu Sosial Vol 2, No 4 (2024): November
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14195875

Abstract

This study analyzes the poverty rate in Papua Province through a multivariate statistical approach using Principal Component Analysis (PCA). Papua faces complex challenges in the form of high poverty, social inequality, and low Human Development Index (HDI), exacerbated by difficult-to-access geography and limited infrastructure. Using secondary data from the Papua Province Central Statistics Agency, this study identified six main variables: the number of health workers, the number of poor people, the labor force participation rate, the percentage of households without sanitation facilities, the implicit price index of GRDP, and HDI. The results of the analysis show that these variables form two main factors: Demographic Social and Human Resources, which collectively explain 75.44% of the data variability. The Demographic Social factor covers access to facilities and social conditions of the community, while the Human Resources factor focuses on the quality of human resources in the region. However, although these two factors are significant, the model is considered less than optimal in summarizing all related variables. This study suggests the use of a lower significance level to strengthen the model and the development of more targeted government programs to overcome poverty in Papua. The PCA method used provides a focused picture to support more effective data-based policy making. Thus, this study contributes to mapping crucial factors to support sustainable development in Papua.
PENGELOMPOKAN INDIKATOR KEPENDUDUKAN PROVINSI JAWA TIMUR TAHUN 2021 MENGGUNAKAN ANALISIS CLUSTER Aliabit, Mukhammad; Habibie, Muhammad R Faathir; Wulandari, Sri Pingit
Triwikrama: Jurnal Ilmu Sosial Vol. 6 No. 2 (2024): Triwikrama: Jurnal Ilmu Sosial
Publisher : Cahaya Ilmu Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.6578/triwikrama.v6i2.8409

Abstract

Provinsi Jawa Timur memiliki dinamika kependudukan yang kompleks, tercermin dari indikator seperti jumlah penduduk, laju pertumbuhan, persentase, dan kepadatan penduduk. Penelitian ini menggunakan analisis klaster baik hierarki maupun non-hierarki, untuk mengelompokkan wilayah berdasarkan karakteristik demografi yang serupa. Hasil klasterisasi ini diharapkan membantu pemerintah dalam menetapkan kebijakan pembangunan yang lebih tepat sasaran, seperti alokasi infrastruktur di wilayah padat penduduk atau peningkatan kesejahteraan di wilayah dengan pertumbuhan rendah. Selain itu, penelitian ini juga memberikan manfaat bagi akademisi sebagai contoh penerapan analisis klaster dalam studi demografi. Namun, penelitian ini terbatas pada data kuantitatif kependudukan tahun 2021 dan belum mempertimbangkan faktor kualitatif yang relevan. Dengan pendekatan ini, diharapkan ketimpangan demografi antar wilayah dapat diminimalkan melalui kebijakan yang lebih efektif. East Java Province exhibits complex population dynamics reflected in indicators such as population size, growth rate, percentage, and density. This study employs cluster analysis, using both hierarchical and non-hierarchical approaches, to group regions based on similar demographic characteristics. The results aim to support the East Java Provincial government in formulating more targeted and effective development policies. For instance, regions with high population density can be prioritized for infrastructure and public service investments, while those with low growth rates can focus on welfare improvements. This study also serves as a reference for academics and researchers on the application of cluster analysis in population studies. However, it is limited to 2021 data and quantitative indicators, without considering qualitative factors that might be relevant. Through this approach, the study seeks to address demographic disparities and enhance resource allocation across regions in East Java.
ANALISIS PENGARUH JENIS CUACA TERHADAP TEMPERATUR DAN KECEPATAN ANGIN MENGGUNAKAN METODE MANOVA Abiba, Nisa; Firmansyah, Rico Dwi; Wulandari, Sri Pingit
Kohesi: Jurnal Sains dan Teknologi Vol. 4 No. 11 (2024): Kohesi: Jurnal Sains dan Teknologi
Publisher : CV SWA Anugerah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.3785/kohesi.v4i11.6623

Abstract

Weather plays an essential role in various human activities, especially in sectors such as agriculture, plantations, and aviation. Changes in weather conditions impact atmospheric variables like temperature and wind speed. Therefore, this study investigates the influence of weather types on temperature and wind speed using the MANOVA method. MANOVA, or Multivariate Analysis of Variance, is an extension of ANOVA, used to determine whether there are significant differences between the mean vectors of various treatments. The data used is secondary data obtained from the Kaggle website, which includes weather types (rainy, cloudy, sunny, and snowy). The data was analyzed for its characteristics using box plots and pie charts, and MANOVA assumptions were tested, including multivariate normal distribution using Q-Q plots, Bartlett's test, and variance homogeneity using Box’s M test. After the assumptions were met, MANOVA testing and LSD multiple comparisons were conducted, followed by interpretation and conclusion. The results of this study indicate that the highest average temperature occurs during sunny, while the highest average wind speed occurs during rainy weather. Only the multivariate normality distribution assumption was met in this study. The MANOVA test results reveal that at least one type of weather has a significant effect on temperature and wind speed. Multiple comparison tests based on temperature show that there are differences in the influence between each category of weather types, except for cloudy weather and rainy weather. Multiple comparison tests based on wind speed show that there are differences in the influence between each category of weather types, except for cloudy weather and snowy weather. Cuaca memiliki peran penting dalam berbagai aktivitas manusia, terutama pada sektor-sektor seperti pertanian, perkebunan, dan penerbangan. Perubahan kondisi cuaca memengaruhi variabel atmosfer seperti temperatur dan kecepatan angin. Maka dari itu, pada penelitian kali ini dilakukan penelitian terkait pengaruh jenis cuaca terhadap temperatur dan kecepatan angin menggunakan metode MANOVA. MANOVA atau analisis variansi multivariat adalah perluasan dari ANOVA, yang dilakukan untuk melihat apakah terdapat perbedaan yang signifikan antara vektor rata-rata dari berbagai perlakuan. Data yang digunakan adalah data sekunder yang diperoleh dari website Kaggle, yaitu data jenis cuaca (hujan, berawan, cerah, dan salju). Data tersebut kemudian dicari karakteristiknya menggunakan boxplot dan pie chart, serta diuji asumsi MANOVA yang terdiri dari uji asumsi berdistribusi normal multivariat menggunakan Q-Q plot, uji Bartlett, dan uji homogenitas varians menggunakan uji Box’s M. Kemudian setelah asumsi terpenuhi, dilakukan pengujian MANOVA dan uji perbandingan berganda LSD untuk selanjutnya diinterpretasi dan ditarik kesimpulannya. Hasil dari penelitian ini yaitu rata-rata temperatur tertinggi terjadi pada cuaca cerah, sedangkan rata-rata kecepatan angin tertinggi terjadi pada cuaca hujan. Hanya asumsi normalitas multivariat saja yang terpenuhi dalam praktikum ini. Hasil pengujian MANOVA mengungkapkan bahwa setidaknya ada satu jenis cuaca yang berpengaruh signifikan terhadap temperatur dan kecepatan angin. Uji perbandingan berganda berdasarkan temperatur menunjukkan bahwa terdapat perbedaan pengaruh antara masing-masing kategori jenis cuaca, kecuali pada cuaca berawan dengan cuaca hujan. Uji perbandingan berganda berdasarkan kecepatan angin menunjukkan bahwa terdapat perbedaan pengaruh antara masing-masing kategori jenis cuaca, kecuali pada cuaca berawan dengan cuaca salju.
Analisis Klaster pada Faktor-Faktor yang Mempengaruhi Indikator Kesejahteraan Sosial dan Ekonomi di Provinsi Jawa Timur Tahun 2023 Rohmatulillah, Oktaviana Nur; Nirmala, Karisma Bunga; Wulandari, Sri Pingit
Jurnal Ekonomi, Bisnis dan Manajemen Vol. 3 No. 4 (2024): Desember : Jurnal Ekonomi, Bisnis dan Manajemen (EBISMEN)
Publisher : FEB Universitas Maritim Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/ebismen.v3i4.2784

Abstract

Social and economic welfare reflects the quality of life in a region and is influenced by local social, economic, and environmental factors. East Java, as the second most populous province in Indonesia, faces challenges in improving the welfare of its residents, particularly due to varying regional characteristics such as employment, education, and population demographics. To understand the patterns of interrelationships among factors affecting welfare, this study conducted a klaster analysis to group regions based on similar characteristics. The klaster analysis employed both hierarchical (complete linkage) and non-hierarchical (K-means) approaches to determine the optimal number of klasters. The results revealed that the level of diversity across regions in East Java tends to be homogeneous in social and economic aspects, with average values exceeding standard deviations. Assumption tests for the klaster analysis confirmed that the data met the assumptions of multivariate normal distribution and dependency.Through hierarchical (complete linkage) and non-hierarchical (K-means) klaster analysis, two main klasters were formed, dividing districts/cities in East Java based on welfare characteristics. Using the complete linkage method, 27 regions were grouped into klaster 1, and 11 regions into klaster 2, while K-means grouped 26 regions into klaster 1 and 12 regions into klaster 2. Out of the six variables used, one variable was found to be insignificant in influencing the klastering results. Based on the mapping results, the grouping aligns with similar criteria, where urban areas predominantly fall into one klaster, and the other klaster is dominated by rural areas.
Distribusi Listrik Menurut Provinsi di Pulau Jawa Tahun 2022 Menggunakan Analisis Korespondensi Haque, Amara Luzumi Sabila; Wulandari, Sri Pingit
Al-DYAS Vol 4 No 1 (2025): FEBRUARI
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/aldyas.v4i1.4394

Abstract

Electricity distribution in Indonesia is uneven, influenced by economic activity and population density in different regions. This inequality impacts on the quality of life of people in underdeveloped areas and hinders local economic development and the provision of public services. This study aims to analyze the relationship between provinces in Java Island and electricity distribution customer groups using correspondence analysis method. This method explores categorical data without prior assumptions, using contingency tables and biplot visualization to identify relative relationships between groups of variables. The data used includes electricity distribution by province in Java Island in 2022 with customer groups such as commercial, street lighting, government buildings, and industry.The results show the dominance of the customer sector by region, DKI Jakarta is dominant in the commercial group, West Java in street lighting, Central Java in government buildings, DI Yogyakarta and East Java in social, and Banten in industry. In addition, there is a significant relationship between provinces and electricity customer groups that fulfill the dependent assumptions. This study provides an overview of the characteristics of electricity distribution in Java and is expected to help relevant agencies in optimizing resource allocation and planning for more efficient and effective energy infrastructure in the future.
Analisis Faktor Kondisi dan Kesehatan Lingkungan di Indonesia Tahun 2022 Abror, Ahmad; Rizki, Muhammad; Wulandari, Sri Pingit
Nautical : Jurnal Ilmiah Multidisiplin Indonesia Vol. 3 No. 4 (2025): Nautical: Jurnal Ilmiah Multidisiplin Indonesia
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/nautical.v3i4.1391

Abstract

Perubahan iklim di Indonesia, yang meliputi perubahan suhu, curah hujan, penyinaran matahari, kelembaban udara, dan kecepatan angin, menimbulkan dampak seperti cuaca ekstrem, gangguan pertanian, ketersediaan air bersih, peningkatan hama tanaman, dan masalah kesehatan akibat polusi udara, yang mengancam keberlangsungan ekosistem. Penelitian ini bertujuan untuk menyusun strategi dalam menghadapi tantangan kondisi lingkungan di Indonesia melalui analisis faktor. Analisis faktor digunakan untuk mereduksi data menjadi variabel yang lebih sedikit tanpa mengurangi informasi penting. Setelah menguji asumsi-asumsi analisis faktor, langkah selanjutnya adalah analisis faktor dengan Principal Component Analysis (PCA). Berdasarkan hasil penelitian, karakteristik data yang memiliki keragaman paling tinggi adalah variabel rata-rata kecepatan angin. Maka, variabel yang digunakan dalam penelitian ini memenuhi semua asumsi analisis faktor. Hasil analisis menunjukkan terbentuknya dua faktor yang diberi nama 'Kelembapan dan Curah Hujan' serta 'Radiasi dan Sirkulasi' dari faktor tersebut terbukti dapat meringkas variabel asli dengan varians terbesar yang dapat dijelaskan oleh faktor yang terbentuk adalah variabel suhu rata-rata, sedangkan varians terkecil yang dapat dijelaskan oleh faktor yang terbentuk adalah variabel jumlah curah hujan.
Pengelompokan Kabupaten/Kota Berdasarkan Indeks Pembangunan Manusia Provinsi Jawa Timur Tahun 2023 Muhammad Akmal Hafiz Abidin; Satria Raditya Nugroho; Sri Pingit Wulandari
Jurnal Cakrawala Akademika Vol. 1 No. 4 (2024): Edisi November - Desember
Publisher : PT. Pustaka Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70182/JCA.v1i4.10

Abstract

Quality human resources are the key to success in achieving goals, both individual and regional. One of the main indicators of the quality of human resources is the Human Development Index (HDI), which includes poverty, life expectancy, unemployment, education, and labor participation. East Java Province, with its diversity and large population, faces great challenges in improving the quality of human resources. One method of measuring whether these factors affect HDI is by dividing clusters based on the region, then analyzed using cluster analysis. Cluster analysis, both hierarchical and non-hierarchical methods, can be used to group cities/districts in East Java based on HDI indicators. This grouping is expected to assist the government in designing more targeted policies. In this practicum, a cluster analysis of HDI in 2023 was conducted using these methods. Data on factors affecting the Human Development Index (HDI) showed high variability, especially in the labor force participation rate, by fulfilling the assumptions of multivariate normal distribution and independence. Hierarchical cluster analysis showed two optimal clusters with the K-Means method: the first cluster included 13 districts/cities, while the second cluster contained 25 districts/cities. In the non-hierarchical cluster analysis, three clusters were formed with each member: 16 districts/cities in cluster 1, 10 in cluster 2, and 12 in cluster 3, and there were significant differences between clusters in the grouping of certain variables.
SWOT Analysis of Indonesian Public Health Policy Using PCA Method Imani, Revina Aprili Ghina; Sari, Nadifa Permata; Wulandari, Sri Pingit
Journal Governance Society Vol. 1 No. 2 (2024): November, 2024
Publisher : CV. Austronesia Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69812/jgs.v1i2.72

Abstract

This study aims to analyze the strengths, weaknesses, opportunities, and threats (SWOT) of Indonesian public health policies using the Principal Component Analysis (PCA). Public health in Indonesia has faced numerous challenges, including inadequate infrastructure, uneven access to health services, and emerging infectious diseases. Effective policy formulation is crucial to address these issues, but there is a need for a more structured approach to assess the dynamic factors influencing public health in the country. The purpose of this research is to employ SWOT analysis combined with PCA to provide a more comprehensive and data-driven evaluation of Indonesia public health policies. The research utilizes secondary data obtained from government reports, health surveys, and international health indexes. The data were processed through PCA to reduce dimensionality and identify the key components that most significantly affect the country health system. This statistical approach allows for a more objective identification of critical variables, which are then categorized into the four SWOT. A qualitative assessment is also used to interpret the results and suggest strategic recommendations for policy improvements. The results of the PCA revealed several key factors impacting Indonesian public health, including healthcare accessibility, funding, and the effectiveness of disease prevention programs. The analysis showed that while there are significant strengths in terms of government commitment and international partnerships, there are also notable weaknesses in infrastructure and healthcare distribution. Opportunities for improvement lie in the potential for digital health integration and public-private partnerships, while threats include the increasing burden of non-communicable diseases and natural disasters.
MODELLING MODELLING OF READING INTEREST ELEMANTARY SCHOOL STUDENT AS AN EFFORT FOR IMPROVING THE LITERACY RATES haryanto, Albertus Eka Putra; Hibatullah, Fausania; Fannani, Nina; Rositawati, Ayu Febriana Dwi; Nazhifah, Naurah; Wulandari, Sri Pingit
Jurnal Kiprah Pendidikan Vol. 1 No. 3 (2022): Jurnal Kiprah Pendidikan | Juli 2022
Publisher : Program Studi Pendididikan Guru Sekolah Dasar Fakultas Keguruan dan Ilmu Pendidikan Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33578/kpd.v1i3.44

Abstract

Salah satu target pembangunan berkelanjutan (Sustainable Development Goals/SDGs) adalah meningkatkan kualitas pendidikan. Kualitas pendidikan dapat dilihat dari tingkat Indeks Pembangunan Manusia (IPM). Salah satu unsur yang digunakan untuk menghitung IPM, yaitu angka melek huruf, di mana hal tersebut dapat ditingkatkan melalui minat baca. Kota Surabaya merupakan kota besar di Indonesia, di mana minat baca di Kota Surabaya sudah tergolong tinggi. Tingginya minat baca tersebut, diduga terdapat faktor memengaruhi, seperti faktor teknologi, peran sekolah, peran orang tua dan metode bercerita. Untuk mengetahui faktor mana yang sebenarnya berpengaruh secara signifikan maka dianalisis dengan menggunakan metode Structural Equation Modelling (SEM). Hasil analisis menyimpulkan bahwa peran orang tua dan peran sekolah merupakan faktor yang berpengaruh signifikan terhadap minat baca siswa SD/sederajat di Kota Surabaya. Sedangkan teknologi dan metode bercerita tidak berpengaruh signifikan terhadap minat baca siswa SD/sederajat di Kota Surabaya.
Evaluasi Keterkaitan Faktor Kesehatan Ibu di Bangladesh Menggunakan Analisis Komponen Utama dan Analisis Faktor Putranto, Alesandro Yoel Deca; Ihzza, Juwita Nur; Wulandari, Sri Pingit
Jurnal Inovasi Global Vol. 2 No. 11 (2024): Jurnal Inovasi Global
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jig.v2i11.214

Abstract

Kesehatan ibu merupakan salah satu indikator utama dalam menentukan kesejahteraan kesehatan suatu negara, terutama di negara berkembang seperti Bangladesh yang masih menghadapi angka komplikasi kehamilan dan persalinan yang tinggi. Faktor-faktor kesehatan seperti usia, tekanan darah sistolik dan diastolik, kadar glukosa darah, suhu tubuh, dan detak jantung memiliki keterkaitan kuat terhadap risiko komplikasi kesehatan ibu. Namun, kompleksitas hubungan antar variabel ini membuat analisis sederhana sulit untuk memberikan wawasan mendalam mengenai pengaruh masing-masing faktor. Oleh karena itu, penelitian ini dilakukan untuk menganalisis keterkaitan antar faktor kesehatan ibu di Bangladesh melalui metode Analisis Komponen Utama (PCA) dan analisis faktor, yang mampu mengidentifikasi variabel-variabel kunci serta mengelompokkan faktor-faktor terkait dalam dimensi yang lebih sederhana. Hasil penelitian menunjukkan bahwa karakteristik data menunjukkan bahwa data kurang bervariasi. Data memenuhi pemeriksaan dan pengujian asumsi pada analisis faktor dan variabel dengan varians terbesar yang dapat dijelaskan oleh faktor terbentuk adalah variabel age sedangkan variabel dengan varians terkecil yang dapat dijelaskan oleh faktor terbentuk adalah variabel body temperature terbentuk dua faktor baru yang diberi nama “Kesehatan Kardiovaskular” dan “faktor Kardiovital” yang tepat dalam merangkum variabel Age, Systollic Blood Pressure, Diastolic Blood Pressure, Blood Glucose, Body Temperature, dan Heart Rate.  
Co-Authors Abiba, Nisa Adinata, Aditya Aditya Pradana, Aditya Ahmad Abror Albertus Eka Putra haryanto Aliabit, Mukhammad Aloysius Audy Wijaya Amara Deviana Chaniago Andramiko, I Kadek Veari Aprilia Alifta Salsabyla Aulia Rahma Safitri Ayu Febriana Dwi Rositawati Berliana, Rizka Widya Dinanti, Lucia Ari Dwi Atmono Agus Widodo Eka Dian Savitri Eko Wahyu Wibowo El Haqq, Byrlianty Tsabita Endang Susilowati Eva Sundari Eva Sundari Fannani, Nina Fathony, Nyimas Syifa Dzulia Putri Fatkhiyatur Rizki Fausania Hibatullah Firmansyah, Rico Dwi Habibie, Muhammad R Faathir Haque, Amara Luzumi Sabila Haryanto, Albertus Eka Putra Hibatullah, Fausania Ida Ayu Sevita Intansari Ihzza, Juwita Nur Iis Dewi Ratih Ilmansyah, Muhammad Noorridho Imani, Revina Aprili Ghina Indria Wahyuni Indriyana, Maharani Ita Noviana Kornelia Zenitha Vyamili Kuntjoro Kuntjoro Kurniasari, Septiana Vera Kustantin, Sukriyah Lucia Ari Dinanti Lucia Ari Dinanti Lucia Ari Dinanti Lucia Ari Dinanti Lucia Aridinanti Mike Prastuti Muhammad Akmal Hafiz Abidin Muhammad Rizki Muinah Kusnul Kotimah Mutiah Salamah Chamid Naurah Nazhifah Nazhifah, Naurah Nazirotul Dwi Afrida Ni Gusti Made Rai Nina Fannani Nirmala, Karisma Bunga Noviana Maulidia Noviyanti Santoso Nugrahasyach, Muhammad Rafli Prastuti, Mike Puji Hidayatus Sholikhah Purhadi Purhadi Putranto, Alesandro Yoel Deca Putri, Eka Deviana Putri, Novira Rahmatanisa Putri, Nur Sinta Dewi Qolbi, Nur Latifatul Ratih, Iis Dewi Ratna Nurul Hidayah Rif’atila, Talitha Fitri Rizqi, Farhan Muhammad Rochman, Ehda Ayati Azkamila Rohmatulillah, Oktaviana Nur Rositawati, Ayu Febriana Dwi Sahira, Naswa Santi Wulan Purnami Sari, Dewi Putri Sekar Sari, Nadifa Permata Satria Raditya Nugroho Sawerigading, Muhammad Irvan Athillah Septiadi, Faniya Mahesty Setyo Pramono Siahaan, Timotius Edward Siska Puji Lestari Sri Mumpuni Retnaningsih Sukriyah Kustanti Moerad Syabrina, Devynta Ulvi Alin Mujahidah Wahendra Pratama Wahyu Wibowo Wahyu Wibowo Wahyu Wibowo Wahyu Wibowo Wahyu Wibowo Wildani, Zakiatul Wulandari, Ratna Maulidah Yasmin, Nadia Salsabila Zullah, Vies Sata