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All Journal Jurnal Matematika BIMASTER Epsilon: Jurnal Matematika Murni dan Terapan CESS (Journal of Computer Engineering, System and Science) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) KABILAH : Journal of Social Community Jurnal Pendidikan Sejarah dan Riset Sosial Humaniora (KAGANGA) BULETIN AL-RIBAATH Jambura Journal of Mathematics GERVASI: Jurnal Pengabdian kepada Masyarakat Sarwahita : Jurnal Pengabdian Kepada Masyarakat M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Transformasi : Jurnal Pendidikan Matematika dan Matematika Variance : Journal of Statistics and Its Applications International Journal of Economics, Business and Accounting Research (IJEBAR) Insan Cita Jurnal Pengabdian Kepada Masyarakat Jurnal Pendidikan Dasar Perkhasa Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Mathematics Education and Science AR-RIAYAH : Jurnal Pendidikan Dasar Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi CENDEKIA : Jurnal Ilmu Pengetahuan Journal of Community Development Empiricism Journal Jurnal Eurekamatika Jurnal Forum Analisis Statistik Pattimura International Journal of Mathematics (PIJMath) STATISTIKA Bina Bahari : Jurnal Pengabdian Kepada Masyarakat Equiva
Neva Satyahadewi
Program Studi Statistika Fakultas MIPA Universitas Tanjungpura, Indonesia
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REGRESI LOGISTIK ORDINAL DENGAN PROPORTIONAL ODDS MODEL PADA KELENGKAPAN IMUNISASI DASAR BALITA KALIMANTAN BARAT Rahmawati, Fenti Nurdiana; Satyahadewi, Neva; Martha, Shantika; Kusnandar, Dadan
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 13, No 6 (2024): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v13i6.87661

Abstract

Kalimantan Barat menduduki posisi tujuh terendah pada persentase imunisasi dasar lengkap tahun 2022. Regresi logistik ordinal  dapat  digunakan untuk menentukan faktor yang memengaruhi kelengkapan imunisasi. Salah satu model yang umum digunakan dalam regresi logistik ordinal adalah proportional odds model. Data yang digunakan merupakan data sekunder yang  berasal  dari Badan Pusat Statistik (BPS) yakni  data Survei Sosial-Ekonomi Nasional (Susenas) 2022. Sampel  penelitian sebanyak 277  memiliki kriteria anak balita usia 12-59 bulan yang melakukan imunisasi dan tidak imunisasi di Provinsi Kalimantan Barat.  Variabel dependen yang digunakan yaitu kelengkapan imunisasi, sedangkan variabel independennya yaitu  daerah administratif (X1),  kepemilikan buku Kesehatan Ibu dan Anak (KIA)/Kartu Menuju Sehat (KMS) (X2),  dan klasifikasi wilayah (X3).  Tujuan penelitian ini adalah menganalisis hasil regresi logistik ordinal dengan proportional odds model dan menentukan variabel independen yang secara signifikan berpengaruh terhadap kelengkapan imunisasi dasar anak balita di Provinsi Kalimantan Barat. Proses analisis diawali dengan melakukan uji multikolinearitas dengan kriteria Variance Inflation Factor (VIF) ≤ 10. Setelah variabel independen terbebas dari multikolinearitas, dilakukan estimasi parameter, pembentukan model regresi, uji simultan dengan uji rasio likelihood, uji parsial dengan uji Wald, pengujian koefisien determinasi dengan pseudo R-square Nagelkerke, uji asumsi parallel lines, uji kecocokan model, perhitungan nilai odds ratio, diikuti interpretasi. Berdasarkan hasil analisis,  diperoleh kesimpulan bahwa pseudo R-square Nagelkerke menunjukkan kemampuan variabel independen menjelaskan variabel dependen sebesar 15,5%,  sedangkan  84,5% faktor lain di luar model.    Berdasarkan model  yang dihasilkan  diketahui bahwa variabel X2 dan X3 signifikan berpengaruh terhadap kelengkapan imunisasi, sedangkan  variabel  X1 tidak berpengaruh signifikan terhadap kelengkapan imunisasi.  Kata Kunci :  susenas, parallel lines, pseudo r-square nagelkerke.
ANALISIS STATISTIK DALAM PENGUKURAN PROBABILITAS DAN HUBUNGANNYA DENGAN PROFITABILITAS Sumiani, Sumiani; Yundari, Yundari; Satyahadewi, Neva
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 13, No 5 (2024): Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/bbimst.v13i5.85714

Abstract

Setiap perusahaan mempunyai laporan keuangan yang disusun untuk menganalisis ada atau tidaknya keuntungan perusahaan. Data laporan keuangan digunakan untuk menganalisis profitabilitas perusahaan, dengan mengukur seberapa besar laba yang diperoleh oleh perusahaan. Laporan keuangan juga dapat digunakan untuk menghitung probabilitas kebangkrutan, yaitu kemungkinan perusahaan mengalami kesulitan keuangan yang dapat menyebabkan kebangkrutan pada suatu perusahaan. Penelitian ini bertujuan untuk menganalisis pengaruh probabilitas kebangkrutan dan profitabilitas terhadap manajemen laba pada perusahaan perbankan yang terdaftar di Bursa Efek Indonesia (BEI) selama periode 2020-2022. Dalam penelitian ini, model Merton digunakan untuk menghitung probabilitas kebangkrutan, sementara manajemen laba diukur menggunakan Discretionary accrual. Populasi penelitian mencakup 57 perusahaan perbankan yang terdaftar di BEI, dengan sampel sebanyak 46 perusahaan atau 138 sampel penelitian yang dipilih melalui metode purposive sampling. Metode yang digunakan adalah analisis deskriptif dan regresi linear berganda untuk menilai pengaruh probabilitas kebangkrutan dan profitabilitas terhadap manajemen laba. Hasil penelitian menunjukkan bahwa probabilitas kebangkrutan yang diperoleh sangat kecil yaitu sebesar 0,0478 serta variabel probabilitas kebangkrutan dan profitabilitas tidak memiliki pengaruh signifikan terhadap manajemen laba pada perusahaan perbankan yang diteliti. Dengan demikian, dapat disimpulkan bahwa tingkat profitabilitas dan probabilitas kebangkrutan baik tinggi maupun rendah tidak mempengaruhi manajemen laba pada perusahaan perbankan tersebut.Kata Kunci:  Laporan Keuangan, Manajemen Laba, dan Model Merton.
A ORDINAL LOGISTIC REGRESSION BAGGING FOR MODELING AND CLASSIFICATION OF THE NUTRITIONAL STATUS OF TODDLERS IN SOUTHEAST PONTIANAK SUB-DISTRICT Sista, Sekar Aulia; Kusnandar, Dadan Tonny; Satyahadewi, Neva
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page195-204

Abstract

Although Pontianak's 2022 stunting rate of 19.7% is higher than the RPJMN's 2020–2024 target of 14%, this is still significant. The categories of stunts are very short (severely stunted), short (stunted), normal, and high, based on a high index of the body by age (TB/U). Ordinal Logistic Regression is one classification that can be used to group stunts based on the TB/U index. This approach makes the unstable parameter. Use the bagging to get stable parameters. The study aims to model and classify toddlers' nutritional status using the TB/U index. Utilizing secondary data for 150 toddlers from Pontianak Tenggara's UPT Puskesmas Parit Haji Husin II. This will monitor kids' growth from 24 to 59 months in 2022. Response factors include short, very short, normal, and high. The mother's job position, birth weight, length, and gender are the predictive variables. Due to imbalanced data utilized in the first analysis using Ordinal Logistics Regression, a decent model, and the final classification result, they used the Bagging OLR ensemble method. The study's findings are a very effective model using OLR Bagging, with an accuracy rate of 99.33%, a sensitivity value of 98.91%, and a specificity value of 98.52%. The results also revealed significant variables that influence the mother's employment status and the birth length variable.
IMPLEMENTATION GRID SEARCH OF RBF AND POLYNOMIAL ON SUPPORT VECTOR REGRESSON FOR CLOSING STOCK PRICES PREDICTION ON PT INDOFARMA (INAF) Salsabilla, Arla; Satyahadewi, Neva; Andani, Wirda
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page133-142

Abstract

Stocks represent evidence of ownership of an asset. The highly volatile nature of stock prices makes it difficult for investors to predict stock prices, necessitating the analysis of stock investments. This research aims to forecast for the next 30 days the closing price of PT Indofarma (INAF) stocks using the best model, and the accuracy level of the employed model was analyzed based on the data from the last seven years. The research used the Support Vector Regression (SVR) method, which is known for its capability to handle nonlinear data through kernel functions. The Radial Basis Function (RBF) and polynomial kernels are used in this case. The challenge with SVR lies in determining the optimal hyperparameter, which can be addressed through hyperparameter tuning using grid search. The research results show that the best model is the SVR kernel RBF model with optimal hyperparameter C=1,γ=0.01, and ε=0.01. Based on the performance evaluation results of the best model, the MAPE, MSE, and MAE values are equal to 1.537%,1483.936, and 23.409.
APPLICATION OF THE QUEST AND CHAID METHODS IN CLASSIFYING STUDENT GRADUATION Banu, Syarifah Syahr; Sulistianingsih, Evy; Debataraja, Naomi Nessyana; Satyahadewi, Neva
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page155-164

Abstract

Graduation is the final result of the learning process during the course. Student graduation time is affected by many factors. Whether or not the time of student graduation is appropriate is an important thing that must be considered. Graduating well and on time is one measure of success in the learning process. This research aims to build a student graduation classification model by applying the QUEST (Quick, Unbiased, and Efficient, Statistical Tree) and CHAID (Chi-squared Automatic Interaction Detection) methods, examining the factors that affect student graduation, and comparing the classification results of the two methods. Both methods produce output in the form of tree diagrams, making it easier to interpret. Based on the classification tree formed from the two methods, four final nodes of the classification tree were generated, and three categories were grouped. Factors that affect student graduation include age and IPK. The classification results show that the percentage of classification accuracy for student graduation with QUEST and CHAID methods is 76.1%.
Analisis Semiotika Ornamentasi pada Rumah Tradisional Melayu: Pengaruh Budaya Islam dan Adat Melayu Hamzah, Erwin Rizal; Ciptadi, Wahyudin; Harimurti, Puspito; Radhi, Muhammad; Satyahadewi, Neva
Empiricism Journal Vol. 5 No. 2: December 2024
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/ej.v5i2.1770

Abstract

Penelitian ini menganalisis makna simbolis ornamentasi pada rumah tradisional Melayu dengan menggunakan pendekatan semiotika triadik Peirce. Tujuannya adalah untuk mengeksplorasi bagaimana elemen dekoratif merepresentasikan identitas budaya Melayu dan pengaruh nilai-nilai Islam. Data dikumpulkan melalui observasi lapangan, dokumentasi visual, dan wawancara dengan pemilik rumah tradisional. Hasil penelitian mengidentifikasi lima kategori motif utama flora, fauna, alam, kaligrafi, dan geometris yang masing-masing mengandung nilai-nilai budaya dan religius. Temuan menunjukkan bahwa ornamentasi tidak hanya memperkaya estetika arsitektur, tetapi juga memainkan peran penting dalam melestarikan nilai sosial, spiritual, dan identitas komunitas Melayu. Penelitian ini menawarkan wawasan penting tentang bagaimana motif tradisional dapat diadaptasi dalam konteks modern untuk menjaga relevansi budaya di tengah arus globalisasi. Semiotic Analysis of Ornamentation in Traditional Malay Houses: The Influence of Islamic Culture and Malay CustomsAbstractThis study analyzes the symbolic meaning of ornamentation in traditional Malay houses using Peirce's triadic semiotic approach. The aim is to explore how decorative elements represent Malay cultural identity and Islamic values. Data were collected through field observation, visual documentation, and interviews with traditional house owners. The findings identify five main motif categories flora, fauna, nature, calligraphy, and geometric patterns each embodying cultural and religious values. Results show that ornamentation not only enriches architectural aesthetics but also plays a vital role in preserving social, spiritual, and communal identity within Malay communities. This research provides valuable insights into how traditional motifs can be adapted in modern contexts to maintain cultural relevance amid globalization.
Binary Logistics Regression To Predict The Opportunity Of SNMPTN Graduation In Statistics Study Program Of Tanjungpura University Satyahadewi, Neva; Tamtama, Ray; Perdana, Hendra; Huriyah, Syifa Khansa
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 8 No. 1 (2023): Mathline
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v8i1.269

Abstract

The National Selection of State University Entrance or Seleksi Nasional Masuk Perguruan Tinggi Negeri (SNMPTN) is one of the selections for high school students seeking higher education. The Statistics Study Program as one of the study programs at Tanjungpura University has a capacity of 20 seats in the SNMPTN. This limited capacity causes prospective students to prepare the right strategy in order to be accepted through the SNMPTN. In this study, logistics regression was used to predict the probability of graduation status on the SNMPTN path in the Statistics Study Program of Untan. Binary logistic regression is a statistical analysis technique for representing the relationship between a response variable with two (binary) categories and one or more predictor variables on a continuous or categorical scale. Data for this study were primary data from a questionnaire that received 93 samples. The response variable used is graduation status (Y) through the SNMPTN in Statistics Study Program, Tanjungpura University classified as 1 (passed) and 0 (not passed). Based on the results of the study, it is known that the variables that have a significant effect on graduation status are the status of choice in Statistics Study Program (X1), national level achievement ownership (X3), the average value of Mathematics (X4), the average value of Chemistry (X6), Biology average score (X7), Indonesian average score (X8), and English average score (X9). Meanwhile, provincial level achievement (X2) and Physics average (X5) did not have a significant effect on graduation status. The binary logistic regression model obtained has an accuracy error of 15,05% with an accuracy rate of 84,95%, meaning that this model has a good criteria.
ANALISIS CONDITIONAL VALUE AT RISK PORTOFOLIO SAHAM DENGAN COPULA CLAYTON Karlina, Sela; Sulistianingsih, Evy; Satyahadewi, Neva
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 2 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i2.13261

Abstract

Conditional Value at Risk (CVaR) is known as a risk measurement tool to estimate losses in investing. Financial data tends not to be normally distributed so that the flexible Copula method can be used to analyze financial data without requiring the assumption of normality. This study aims to analyze the CVaR of a stock portfolio with Clayton's Copula. The study began with collecting daily stock closing price data for the period October 3, 2022 to November 3, 2023. After the data was collected, the return value of the closing stock price was calculated. Furthermore, autocorrelation and heteroscedasticity tests were carried out on the closing stock price return data. Then, the Kendall's Tau correlation was calculated to obtain the Clayton Copula parameters. After that, the stock weights in the portfolio were calculated using the Mean Variance Efficient Portfolio (MVEP) method and new return data was generated using the Clayton Copula parameters. Furthermore, the portfolio return was calculated to obtain the VaR value of the formed portfolio. Then, it was repeated by generating data up to the VaR calculation 1000 times to obtain the average value of the portfolio VaR. Then, the same thing was done to CVaR. The results of the CVaR analysis of the stock portfolio with Copula Clayton on the two stocks, namely PT Aneka Tambang Tbk (ANTM) and PT Timah Tbk (TINS), obtained losses of 3.04%, 3.56%, and 4.57% with a confidence level of 90%, 95%, and 99%. This value indicates the percentage of investment risk that may be obtained in the next one-day period. This shows that the higher the level of confidence, the greater the CVaR value will be.
Analisis Portofolio Optimal dengan Metode Liquidity Adjusted Capital Asset Pricing Model Pada Indeks Saham LQ-45 Safira, Shafa Alya; Satyahadewi, Neva; Huda, Nur'ainul Miftahul
Journal of Mathematics Education and Science Vol. 7 No. 2 (2024): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/james.v7i2.2282

Abstract

Investor wajib mempunyai kemampuan analisis terhadap hubungan diantara return yang diharapkan dan risiko. Salah satu model yang dikembangkan dalam pembentukan portofolio optimal adalah Liquidity Adjusted Capital Asset Pricing Model (LCAPM). LCAPM adalah model CAPM yang dipengaruhi oleh risiko likuiditas. Dalam penelitian, dilakukan pembentukan bobot optimal menggunakan LCAPM untuk indeks saham LQ-45 periode Februari 2019-Januari 2022. Penelitian ini bertujuan membentuk portofolio optimal indeks saham LQ-45 dan menerapkan LCAPM pada pengambilan keputusan investasi saham. Teknik pengambilan sampel pada penelitian ini menggunakan purposive sampling. Langkah penelitian setelah data terkumpul yaitu menghitung return harga penutupan indeks saham LQ-45, return pasar (IHSG), uji signifikan parameter, menghitung likuiditas saham serta likuiditas pasar, return bebas risiko, nilai beta saham, serta expected return dan memilih saham yang memiliki expected return yang bernilai positif untuk dibentuk portofolio. Kemudian dilakukan penyusunan kombinasi, pembobotan serta pengukuran kinerja portofolio. Hasil penelitian menunjukkan dari ketiga portofolio yang terbentuk memiliki nilai indeks sharpe yang bernilai negatif.. Investor lebih baik berinvestasi di bank yang menghasilkan expected return lebih tinggi dibanding portofolio saham yang dibentuk.
PERAMALAN NILAI TUKAR RUPIAH TERHADAP DOLAR AS MENERAPKAN ARIMA, VAR DAN RANDOM FOREST ANDANI, WIRDA; SATYAHADEWI, NEVA
CENDEKIA: Jurnal Ilmu Pengetahuan Vol. 5 No. 1 (2025)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/cendekia.v5i1.4305

Abstract

The weakening of the rupiah affects imported goods, pushing up products that use imported raw materials so that production costs will increase and logistics costs soar. Consequently, UMKM players and t society are victimized. Another impact is that foreign debt becomes more expensive to pay. This certainly impacts the suppression of the State Budget (APBN). The assumption of the rupiah exchange rate against the United States dollar (US) plays a vital role in the structure of the APBN, so analysis is needed to determine the dynamics of changes in the rupiah exchange rate against the US dollar. Therefore, an accurate rupiah exchange rate forecasting model is required. Various methods can be used to produce accurate predictions. This research, will conduct forecasting of the Rupiah exchange rate against the US Dollar by comparing the ARIMA, VAR, and Random Forest methods. The best method will be selected based on the smallest MAPE. The data is secondary data from January 2021 to March 2024 obtained from the BI and BPS websites. Based on the MAPE, the best model was chosen in forecasting the rupiah exchange rate against the US dollar, namely ARIMA (0,2,1) with a MAPE of 1%. The output of forecasting the rupiah exchange rate against the US dollar for April - December 2024 using ARIMA (0,2,1) ranges from Rp. 15,841 - Rp. 16,202 with an average of Rp. 16,021. ABSTRAKMelemahnya rupiah berpengaruh terhadap barang impor yang mendorong kenaikan produk-produk yang menggunakan bahan baku tersebut. Akibatnya, biaya produksi akan meningkat dan ongkos logistik melonjak. Konsekuensinya, pelaku UMKM dan masyarakat menjadi korban. Dampak lainnya adalah meningkatnya biaya untuk melunasi utang luar negeri. Hal ini tentu berimbas pada penekanan Anggaran Pendapatan dan Belanja Negara (APBN). Asumsi nilai tukar rupiah terhadap dolar Amerika Serikat (AS) memainkan peran vital dalam struktur APBN, maka diperlukan analisis untuk mengetahui dinamika perubahan nilai tukar rupiah terhadap dolar AS. Oleh karena itu, diperlukan model peramlaan nilai tukar rupiah yang akurat. Terdapat berbagai metode yang dapat dioperasikan untuk menghasilkan prediksi yang akurat. Pada penelitian akan dilakukan peramalan nilai tukar Rupiah terhadap Dolar AS dengan membandingkan metode ARIMA, VAR dan Random Forest. Metode terbaik akan dipilih berdasarkan nilai MAPE terkecil. Data yang diaplikasikan merupakan data bulanan dari bulan Januari 2021 sampai dengan bulan Maret 2024 yang berasal dari website BI dan BPS. Berdasarkan nilai MAPE, terpilihlah model terbaik dalam meramalkan nilai tukar rupiah terhadap dolar AS yaitu ARIMA (0,2,1) dengan MAPE sebesar 1%. Output peramalan nilai tukar rupiah terhadap dolar AS untuk bulan April – Desember 2024 menggunakan ARIMA (0,2,1) berkisar antara Rp. 15.841 – Rp. 16.202 dengan rata-rata Rp. 16.021.
Co-Authors . Apriansyah Afghani Jayuska Afghany Jayuska Al-Ham, Hairil Amriani Amir Amriani Amir Amriani Amir Andani, Wirda Antoni, Frans Xavier Natalius Apriliyanti, Rita Aprizkiyandari, Siti Ardhitha, Tiffany Ari Hepi Yanti Arsyi, Fritzgerald Muhammad Arti, Reyana Hilda Ashari, Asri Mulya Asri Mulya Ashari Asty Fistia Ningrum Atikasari, Awang Aulia Puteri Amari Bambang Kurniadi Banu, Syarifah Syahr ciptadi, wahyudin Cornellia, Amanda Crismayella, Yuveinsiana Dadan Kusnandar Dadan Kusnandar Dadan Kusnandar David Jordy Dhandio Debataraja, Naomi Nessyana Della Zaria Desriani Lestari Desriani Lestari Desriani Lestari Dhandio, David Jordy Dinda Lestari Dwi Nining Indrasari Dwinanda, Maria Welita Eka Febrianti, Eka Esta Br Tarigan Evy Sulistianingsih Ewaldus Okta Ferdina Ferdina Feriliani Maria Nani Fitriawan, Della Fransisca Febrianti Sundari Fransiska Fransiska Grikus Romi Gusti Eva Tavita Gusti Eva Tavita Hairil Al-Ham Halim, Alvin Octavianus Hamzah, Erwin Rizal Handayani, Aditya Hanin, Noerul Harimurti, Puspito Harnanta, Nabila Izza Helena, Shifa Hendra Perdana Hendrianto, El Herina Marlisa Huda, Nur'ainul Miftahul Huriyah, Syifa Khansa Ibnur Rusi Ikha Safitri Imro'ah, Nurfitri IMRO’AH, NURFITRI Imtiyaz, Widad Isra’ Sagita Jawani Jawani Karlina, Sela Kusnandar, Dadan Tonny Lucky Hartanti Lucky Hartanti Lucky Hartanti M. Deny Hafizzul Muttaqin Maga, Fahmi Giovani Margareta, Tiara Margaretha, Ledy Claudia Marlisa, Herina Marola, Geby Martha, Shantika Mega Sari Juane Sofiana Mega Sari Juane Sofiana Mega Tri Junika Millennia Taraly Misrawi Misrawi Muhammad Ahyar Muhammad fauzan Muhammad Radhi Muhammad Rizki Muliadi Muliadi Muslimah (F54210032) Nabil, Ilhan Nail Nanda Shalsadilla Naomi Nessyana Debataraja Naomi Nessyana Debataraja Noerul Hanin Nona Lusia Nugrahaeni, Indah Nur Asih Kurniawati Nur Asiska Nurfadilah, Kori’ah Nurfitri Imro'ah Nurfitri Imro’ah Nurhalita Nurhalita Nurmaulia Ningsih Oktaviani, Indah Ovi Indah Afriani Paisal Paisal Pertiwi, Retno Pratama, Aditya Nugraha Preatin, Preatin Putri Putri Putri, Aulia Nabila Qalbi Aliklas R Puspito Harimurti Radhi, Muhammad Radinasari, Nur Ismi Rafdinal Rafdinal Rahadi Ramlan Rahmadanti, Putri Rahmanita Febrianti Rusmaningtyas Rahmawati, Fenti Nurdiana Ramadhan, Nanda Ramadhania, Wahida Reni Unaeni Retnani, Hani Dwi Ria Andini Ria Fuji Astuti Rina Rina Risky Oprasianti Rita Kurnia Apindiati Rivaldo, Rendi Riza Linda Rizki Nur Rahmalita Rizki, Setyo Wira Rosi Kismonika Roslina Rosi Tamara Rovi Christova Safira, Shafa Alya Salsabilla, Arla Santika Santika Sary, Rifkah Alfiyyah Seftiani, Seftiani Selvy Putri Agustianto Setyo Wir Rizki Setyo Wira Rizki Setyo Wira Rizki Setyo Wira Rizki Shantika Martha Shantika Martha Sinaga, Steven Jansen Sintia Margun Sista, Sekar Aulia Siti Aprizkiyandari Siti Aprizkiyandari, Nurul Qomariyah, Shantika Martha, Siti Hardianti Suci Angriani Sukal Minsas Sukal Minsas syuradi, Syuradi Tamtama, Ray Taraly, Inggriani Millennia Tiara, Dinda Trifaiza, Fadhela Wahyu Diyan Ramadana Wahyudin Ciptadi Warsidah Warsidah Warsidah, Warsidah Wilda Ariani Wirda Andani Yopi Saputra Yudhi Yuliono, Agus Yumna Siska Fitriyani Yundari, Yundari Yuveinsiana Crismayella Zakiah, Ainun