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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
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

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GEOMETRIC BROWNIAN MOTION WITH JUMP DIFFUSION AND VALUE AT RISK ANALYSIS OF PT BANK NEGARA INDONESIA STOCKS Zakiah, Ainun; Sulistianingsih, Evy; Satyahadewi, Neva
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp617-628

Abstract

Investments in stocks are made to make a profit, where the higher the expected profit, the greater the risk undertaken. The return on investing in stocks can be influenced by changes in the price of stocks that are difficult to predict, which can lead to uncertainty in the value of the return and the risk of the stock. The application of the Geometric Brownian Motion (GBM) model with Jump Diffusion is crucial for enhancing the accuracy of stock price forecasting and risk analysis by incorporating price jumps resulting from external events within complex market dynamics. The data used in this study are the closing price data of the daily stock of PT Bank Negara Indonesia for the period 1 December 2022 to 31 January 2024, where the stock return data has a kurtosis value greater than 3 (leptokurtic) so that the data indicates a jump. The GBM with Jump Diffusion model was implemented to predict the stock price with a simulation repetition of 1000 times. The analysis shows that the GBM model with Jump Diffusion has an excellent accuracy rate with the smallest MAPE value of 0.86%. The average value of the VaR with Monte Carlo simulation obtained at the reliability levels of 80%, 90%, 95%, and 99% in a row is 0.96%, 1.53, 1.97%, and 2.64%. This result shows that the higher the confidence level used, the greater the risk.
COMPARISON ANALYSIS OF CLAYTON, GUMBEL, AND FRANK COPULA FOR MODELING THE DEPENDENCE BETWEEN BBCA CLOSING PRICE AND INDONESIA MACROECONOMIC FACTORS Hanin, Noerul; Satyahadewi, Neva; Sulistianingsih, Evy
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2405-2418

Abstract

PT. Bank Central Asia Tbk is a company in Indonesia with the biggest market capitalization. These advantages attract investors to buy PT. Bank Central Asia Tbk (BBCA) shares. However, fluctuating share prices can lead to both gains and losses, where these are not entirely caused by the company’s finances, but also by the country’s macroeconomic conditions. Therefore, this study aims to examine the dependency between BBCA closing price and macroeconomic indicators, which are limited on only three macroeconomic variables, consists of inflation, interest, and USD-IDR exchange rate. This study compares the Clayton, Gumbel, and Frank copula to analyze the dependence characteristics between two non-normally distributed variables based on the highest log-likelihood value. The data used are monthly data from 2021 to 2023, consists of inflation and interest rate from Bank Indonesia website, USD-IDR exchange rate from Satu Data Kementerian Perdagangan website, alongside BBCA closing price from yahoo finance website. Based on the analysis, the best copula models to describe the relationship between each macroeconomic factor (inflation, interest, exchange rate) and BBCA closing price respectively is Clayton copula with parameter 2.042, Frank copula with parameter 10.3, and Frank copula with parameter 5.891. These findings indicate that inflation shows a strong dependence with BBCA closing price when both variables are low, while exchange rate and interest rate exhibit strong dependence with BBCA closing price when these variables are high. It provides valuable insights into the asymmetric relationships between macroeconomic conditions and stock prices, offering practical relevance for investors and policymakers.
INTEGRATION OF DAVIES-BOULDIN INDEX VALIDATION AND MEAN-VARIANCE EFFICIENT PORTFOLIO IN K-MEANS++ CLUSTERING FOR OPTIMIZATION OF THE LQ45 STOCK PORTFOLIO Dhandio, David Jordy; Sulistianingsih, Evy; Satyahadewi, Neva
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2609-2620

Abstract

Stock investment involves allocating funds to get returns based on the associated risks. In stock investments, returns and risks exhibit a linear correlation, meaning higher expected returns come with higher risks. Risk in stock investments can be minimized by forming portfolios using a cluster analysis approach, where the groups of stocks generated from the analysis represent the resulting portfolios. This research aims to form an optimal stock portfolio using K-Means++ Clustering, validated by the Davies Bouldin Index (DBI), the weighting of stocks in a portfolio using the Mean-Variance Efficient Portfolio (MVEP), and evaluated based on the Sharpe Index. The data used include stocks indexed in LQ45 from February 2020 to August 2024, stock closing prices from August 1, 2023, to August 1, 2024, company financial ratios as of June 2024, and the average Bank Indonesia interest rate from August 2023 to August 2024. Based on the financial ratios, K-Means++ Clustering and DBI validation identified three optimal clusters. Clusters 1 and 2, consisting of single stocks, cannot be directly utilized as portfolios due to the requirement for diversification. Each cluster’s stocks with the highest expected return were selected to form a new portfolio. According to the MVEP analysis, the investment proportion f each stock in portfolio 1 is 44.10% (BBCA.JK), 15.40% (BBNI.JK), 2.89% (BMRI.JK), 15.02% (CPIN.JK), and 22.60% (PGAS.JK). In portfolio 2, the weights are 27.68% (BBTN.JK), 36.00% (ADRO.JK), and 36.33% (BMRI.JK). Based on the Sharpe Index, portfolio 2 achieved the highest value (0.048404) compared to portfolio 1 (0.034465), indicating that portfolio 2 shows a better risk-adjusted return than portfolio 1.
Analysis of Multi-Input ARIMA Interventions with Additive Outlier for Forecasting Price of Crude Oil West Texas Intermediate Nabil, Ilhan Nail; Satyahadewi, Neva; Huda, Nur'ainul Miftahul
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 3 (2024): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i3.22147

Abstract

Crude oil is a liquid characterized by a thick texture and blackish color. It is composed of complex hydrocarbon compounds with various benefits that are spread around the world. Crude oil derived from fossil fuels can be used as primary fuels, such as gasoline, and is the most important of the energy resources. Based on that, crude oil play a crucial role in the global economy movement because can be used as the main sources of energy all over the world. However, one of the benchmarks for crude oil from the USA is West Texas Intermediate (WTI). Known to produce high-quality oil, the price of crude oil of WTI fluctuates. In addition, fluctuations occur because of several factors, such as the availability of oil supplies, the embargo on oil imports, and the COVID-19 pandemic. The research aims to analyze price forecasting that occurs over the next five months and the accuracy level of the method used. The data that exists outliers is usually removed from forecasting that contains outliers, but that can affect the estimation result in the model. So, in this research intervention and outlier factors are added to the research to overcome the constraints In this study, the Multi-Input ARIMA Intervention and Additive Outlier (AO) method are used by modelling ARIMA pre-intervention and then. After that, the procedure is adding intervention factorsand additive outlier with iterative procedures. Multi-Input ARIMA Intervention and Additive Outlier (AO) are used to determine the magnitude of fluctuations that occur. Data shocks causing outlier data can be used by adding AO factors. WTI oil price data was retrieved from investing.com with monthly data from January 2011 to June 2023. Based on the results of Mmulti-Iinput ARIMA intervention with Additive Outlier method, it has been determined that the movement of WTI oil prices in the next five months will increase compared to the last five periods of actual data. Because of incrased price of crude oil, it will impact of the economic growth all over the world. So, the government better controlled the price of crude oil at lower price. . withMulti-Input ARIMA interventions resulting in AIC, MAPE, and RMSE model each 941.490, 6.979%, and 5.913 . So, Multi-Input and AO proven can be used to forecast data with fluctuate that data occur. 
Pengelompokan Provinsi di Indonesia Menggunakan Time Series Clustering pada Sektor Ekspor Nonmigas Putri, Aulia Nabila; Satyahadewi, Neva; Aprizkiyandari, Siti
Jambura Journal of Mathematics Vol 6, No 1: February 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v6i1.21921

Abstract

Indonesia's export activities are dominated by non-oil and gas exports consisting of four sectors, namely the processing industry, agriculture, mining, and others. The government must pay attention to non-oil and gas exports for each province because exports can play an essential role in a country's economic growth. This study was conducted to cluster provinces in Indonesia using time series clustering in the non-oil and gas export sector based on data patterns concerning Dynamic Time Warping (DTW) distance. The sectors used in this study are the manufacturing industry sector and the agricultural sector in 34 Indonesian provinces in the period 2017 - 2021. Time series clustering analysis uses the average linkage method with DTW distance and the selection of the optimum number of clusters using the silhouette coefficient method. The results of the analysis in the processing industry sector resulted in 3 optimum clusters, namely cluster 1 consisting of 1 province that has high processing industry exports, cluster 2 consisting of 8 provinces that have medium processing industry exports, and cluster 3 consisting of 25 provinces that have low processing industry exports. As for the agricultural sector, it produces 2 optimum clusters, namely cluster 1 consisting of 5 provinces that have high agricultural industry exports, and cluster 2 consisting of 29 provinces that have low agricultural industry exports. The clustering results in the processing industry sector and the agricultural sectors have a silhouette coefficient value of 0.778 and 0.798, so it is said to have a strong cluster structure.
IMPLEMENTASI WEB SCRAPING UNTUK ULASAN PADA TWITTER MENGGUNAKAN ASOSIASI TEKS (STUDI KASUS: FILM KKN DI DESA PENARI) Antoni, Frans Xavier Natalius; Satyahadewi, Neva; Perdana, Hendra
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 1 (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/variancevol6iss1page21-28

Abstract

Pengguna twitter biasanya memberikan komentar yang berisi mengenai ulasan suatu film yang sedang tayang. Teknik yang dapat digunakan untuk mengambil komentar pada twitter yaitu Web Scraping. Penelitian ini bertujuan untuk mengimplementasikan Web Scraping dalam mengumpulkan data pada twitter dan mengimplementasikan Asosiasi Teks untuk mendapatkan informasi antar kata yang terbentuk. Penelitian ini menggunakan komentar yang berisi mengenai ulasan Film KKN di Desa Penari pada tanggal 30 April 2022. Komentar yang diperoleh tidak semua berisi ulasan, sehingga perlu dilakukan seleksi terhadap komentar tersebut. Hasil seleksi dari 866 komentar diperoleh sebanyak 116 ulasan positif dan 83 ulasan negatif. Data yang diperoleh dari komentar tidak bisa langsung dianalisis, sehingga perlu melalui tahap text preprocessing. Adapun tahap text preprocessing yaitu cleansing data, case folding, spelling normalization, filtering, dan tokenizing. Setelah melalui tahap text preprocessing, ulasan tersebut kemudian dianalisis untuk mendapatkan informasi yang penting dengan menggunakan Asosiasi Teks. Hasil Asosiasi Teks untuk ulasan positif diperoleh informasi bahwa penonton memberikan penilaian terhadap tokoh, akting dan sinematografi yang bagus, kemudian film yang ditayangkan juga sesuai dengan cerita thread pada twitter, dan sinematografi juga keren. Sedangkan untuk ulasan negatif penonton memberikan penilaian bahwa Film KKN di Desa Penari, film yang biasa dan hantu yang ditayangkan juga kurang seram.
Penerapan Model Harga Opsi Black Scholes dalam Penentuan Premi Asuransi Jiwa Dwiguna Unit Link Seftiani, Seftiani; Satyahadewi, Neva; Huda, Nur'ainul Miftahul
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 11 Issue 2 December 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v11i2.23049

Abstract

Unit-linked life insurance is one of the most popular insurance products. This product connects the element of protection with investment assets in a product. Regarding option pricing, the Black Scholes model is one method that can be used. The advantage of this model is that it is a call option valuation model and is in great demand among financial associations because the option rate obtained from the calculation of this model is an accurate value. This research aims to determine the premium value of unit-linked endowment life insurance by applying the Black Scholes option pricing model. This research begins by selecting the stocks used and completing the information needed, including the insured's age, gender, insurance period, and life expectancy based on TMI in 2011. The return value and stock volatility can be calculated based on the stock data used. Furthermore, applying the Black Scholes option pricing model on customer data with male gender, age 25 years, a selected interest rate of 5.75%, and an insurance period of 5 years obtained a unit link insurance premium value of Rp123,058,412. The results showed that the Black Scholes option price model is determined by stock prices, interest rates, insurance periods, and volatility. When the longer period of insurance taken causes the premium value to be higher, and for different ages, with increasing age, the value of premiums paid will also increase.
Determining the Optimum Number of Clusters in Hierarchical Clustering Using Pseudo-F Sinaga, Steven Jansen; Satyahadewi, Neva; Perdana, Hendra
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EULER: Volume 11 Issue 2 December 2023
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v11i2.23113

Abstract

Poverty refers to the condition where a person cannot meet the basic necessities based on the minimum living standards. Statistics Indonesia proxied an increase in the poverty rate in North Sumatra Province in 2021 from 8.75% to 9.01%. However, this increase is exclusive to North Sumatra Province, which has Indonesia's 3rd largest number of districts/cities. This study discussed mapping the North Sumatra Province region based on 10 poverty factor variables. The 10 variables are life expectancy, health complaints, poverty line, Gross Regional Domestic Product (GRDP), population growth rate, Expected Years of Schooling (EYS), Human Development Index (HDI), labor force participation rate, open unemployment rate, and district/city minimum wage. The Hierarchical Clustering analysis was employed to compare single, complete, and average linkage methods. The best method was determined based on the pseudo-F statistic value. 4 clusters had complete linkage methods, each of which possessed varied characteristics. Cluster 1 contains cities with the lowest poverty rate, including Medan City and  Pematang Siantar City. Cluster 2 consists of cities with low poverty rates, while Cluster 3 consists of cities with high poverty rates. Cities that are included in Cluster 4 have very high poverty rates, including South Nias District and Pakpak Bharat District. The clusters present significant poverty rate gaps among North Sumatra Province regions.
PEMODELAN SEKTOR UNGGULAN PROVINSI KALIMANTAN BARAT DENGAN MENGGUNAKAN PRINCIPAL COMPONENT ANALYSIS Satyahadewi, Neva; Aprizkiyandari, Siti; Radinasari, Nur Ismi
TRANSFORMASI Vol 7 No 2 (2023): TRANSFORMASI: Jurnal Pendidikan Matematika dan Matematika
Publisher : Pendidikan Matematika FMIPA Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/tr.v7i2.2760

Abstract

West Kalimantan is the province with the fourth largest area in Indonesia, namely 147,307 square km. West Kalimantan has 12 districts and 2 cities, one of which is Ketapang Regency which covers an area of ​​31,240.74 km2. The research is limited to three leading sectors which have the largest average contribution to GRDP in West Kalimantan Province, namely the agriculture, forestry and fisheries sectors; industrial processing; as well as wholesale and retail trade, and car and motorcycle repair. The focus of this research is aimed at modeling the leading sector for the West Kalimantan economy. The results of the modeling showed multicollinearity so it was continued with the Principal Component Analysis. The results of the analysis with the model show that there is no element of multicollinearity between the dependent variables.
IMPLEMENTASI BICLUSTERING MENGGUNAKAN ALGORITMA BCBIMAX DALAM PEMETAAN POTENSI EKONOMI PERIKANAN INDONESIA Cornellia, Amanda; Satyahadewi, Neva; Martha, Shantika
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 14, No 4 (2025): 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.v14i4.96035

Abstract

Pemanfaatan ekonomi perikanan Indonesia belum optimal dalam meningkatkan pembangunan ekonomi nasional karena potensi setiap provinsi yang berbeda-beda. Pemetaan potensi ekonomi perikanan Indonesia perlu dilakukan untuk menghasilkan perencanaan kebijakan dalam meningkatkan ekonomi perikanan. Penelitian ini menggunakan biclustering yang dapat mengelompokkan objek dan variabel dengan perilaku serupa. Tujuan penelitian ini adalah untuk mengelompokkan provinsi berdasarkan kemiripan potensi ekonomi perikanan secara simultan menggunakan biclustering dengan algoritma BCBimax. Data yang digunakan dalam penelitian ini adalah data sekunder tahun 2022 yang diperoleh dari Kementerian Kelautan dan Perikanan terkait ekonomi perikanan yaitu 9 variabel dari 34 provinsi di Indonesia. Proses analisis diawali dengan pembentukan matriks dari data, melakukan binerisasi, pembentukan bicluster dengan tahapan berupa pembagian matriks menjadi set kolom, pembagian matriks menjadi set baris, pembentukan dua submatriks, menyimpan bicluster, dan mengulangi pembentukan bicluster lainnya, diikuti pemetaan. Berdasarkan hasil penelitian, diperoleh sembilan bicluster dimana masing-masing bicluster bersifat tidak tumpang tindih karena terdiri dari provinsi yang berbeda-beda. Bicluster yang dihasilkan memiliki karakteristik yang berbeda-beda sehingga dapat dijadikan pertimbangan dalam perencanaan kebijakan. Dari 34 provinsi yang dianalisis menggunakan algoritma BCBimax, sebanyak 22 provinsi terpetakan dalam bicluster yang dihasilkan. Namun, terdapat 12 provinsi yang tidak masuk dalam bicluster, yaitu Provinsi Riau, Jambi, Bengkulu, DKI Jakarta, DI Yogyakarta, Banten, Bali, Nusa Tenggara Timur, Kalimantan Barat, Gorontalo, Sulawesi Barat, dan Papua Barat karena tidak memiliki kemiripan potensi ekonomi perikanan secara simultan.
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