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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 Jurnal Pengabdian pada Masyarakat
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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IMPLEMENTATION OF RESPONSE-BASED UNIT SEGMENTATION IN PARTIAL LEAST SQUARE (REBUS-PLS) FOR ANALYSIS AND REGIONAL GROUPING Al-Ham, Hairil; Satyahadewi, Neva; Preatin, Preatin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0197-0210

Abstract

Housing environmental health is a key indicator of community quality of life. In West Kalimantan Province, variations in geographical and socioeconomic conditions contribute to disparities in housing conditions. This study analyzes and classifies regions based on factors influencing housing environmental health using the Response-Based Unit Segmentation in Partial Least Squares (REBUS-PLS) method. REBUS-PLS helps detect unobserved heterogeneity by identifying subgroups with different structural relationships. The exogenous latent variables include household economics, education, and housing facilities, while the endogenous variable is housing environmental health, measured through 15 indicators. The results of the SEM-PLS analysis obtained 3 paths that had a significant effect: household economics on housing facilities, household economics on education, and housing facilities on the health of the Housing environment. SEM-PLS assumes homogeneity across data, meaning all observations follow the same structural pattern. However, this assumption may not hold, especially with data representing diverse regions. To address potential heterogeneity, REBUS-PLS was applied. The analysis revealed two distinct segments, each with stronger explanatory power than the global model, as indicated by higher R² values (Segment 1 = 95.6%, Segment 2 = 91.4%, compared to 87.7% in the global model). Segment 1 consists of Landak, Sanggau, Sekadau, Kayong Utara, and Singkawang City. Segment 2 includes Bengkayang, Melawi, Ketapang, Kapuas Hulu, Sanggau, Sekadau, Sintang, and Pontianak City. These findings confirm the presence of structural heterogeneity and demonstrate that REBUS-PLS provides a more accurate understanding of the factors affecting housing environmental health across regions.
IDENTIFIKASI FAKTOR DAN PERAMALAN INFLASI INDONESIA MENGGUNAKAN REGRESI LINEAR BERGANDA- BACKPROPAGATION NEURAL NETWORK Febrianti, Eka; Yundari, Yundari; Satyahadewi, Neva
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 14, No 5 (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.v14i5.102167

Abstract

Inflasi atau laju kenaikan harga barang dan jasa yang naik turun secara ekstrem, dan tidak terkendali di Indonesia berdampak terhadap perekonomian dan menurunkan daya beli masyarakat, hingga diperlukan pengendalian. Bermacam upaya yaitu dengan identifikasi faktor yang mempengaruhi dan peramalan. Data inflasi yaitu data deret waktu berpola non-linear dan dipengaruhi oleh lebih dari satu faktor. Regresi Linear Berganda dipakai untuk melihat pengaruh bermacam variabel bebas (X) terhadap variabel terikat (Y). Backpropagation Neural Network yaitu metode peramalan yang memodelkan hubungan diantara input dan output dengan memperbarui bobot secara berulang berdasarkan nilai error atau epoch. Penelitian ini bertujuan untuk identifikasi faktor yang berpengaruh secara signifikan pada Inflasi serta meramalkan tingkat inflasi di Indonesia menggunakan metode Backpropagation Neural Network (BPNN). Proses penelitian dilakukan dengan pengumpulan data inflasi, nilai tukar, impor, harga minyak dunia, jumlah uang beredar, serta suku bunga periode Januari 2015-Desember 2024. Lalu data diolah hingga diperoleh model regresi linear berganda selanjutnya dilakukan pengujian terhadap model yang yaitu uji F, uji t, menghitung koefisien determinasi, dan uji asumsi klasik. Sesudah didapat faktor yang berpengaruh signifikan, dilakukan normalisasi, membagikan data latih-uji, pelatihan dengan algoritma Backpropagation, pengujian data target, dan peramalan dengan BPNN. Hasilnya, harga minyak dunia dan jumlah uang beredar berpengaruh signifikan pada inflasi. Arsitektur BPNN terbaik yaitu 3-6-1, dengan data 80% latih dan 20% uji, learning rate 0,7, fungsi aktivasi sigmoid, dan 1000 epoch dengan MSE 0,149030 dan MAPE 11,07%. Sesudah dilakukan peramalan pada 2025, diperoleh nilai inflasi tertinggi 2,05% pada Agustus-Desember dan inflasi terendah 1,81% pada Januari.
SEGMENTING MATERNAL AND CHILD HEALTH DEGREE IN INDONESIA USING SEM-PLS POS Nurhanifa, Nurhanifa; Perdana, Hendra; Satyahadewi, Neva
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp0897-0912

Abstract

Maternal and child health represents a critical aspect of national development, reflecting both the well-being of the population and the success of regional health equity programs. In Indonesia, disparities in maternal and child health outcomes remain evident across provinces due to socio-economic inequalities and unequal access to health services. This study aims to model the causal relationships between key health determinants and classify provinces based on maternal and child health degree using Structural Equation Modeling with Partial Least Squares (SEM-PLS) combined with Prediction-Oriented Segmentation (POS). The study uses secondary data from 2023 sourced from the Central Statistics Agency (BPS) and the Ministry of Health, covering 34 provinces at the provincial level. Nineteen indicators are grouped into four latent variables: Health Services, Clean and Healthy Living Behavior (PHBS), Environment, and Health Degree. SEM-PLS was applied to identify direct and indirect relationships among these variables, while POS was used to identify homogeneous segments of provinces. The results show that PHBS positively affects Environment (path coefficient = 0.896; p < 0.001), while Health Services negatively affect Health Degree (path coefficient = –0.668; p < 0.01), indicating the presence of indirect pathways influencing health outcomes. The segmentation analysis identified three segments: Segment 1 includes provinces with moderate outcomes but weak child health services; Segment 2 includes provinces with relatively better maternal outcomes but sanitation gaps; Segment 3 consists of provinces with the most critical health conditions, including high stunting and malnutrition rates. These findings demonstrate that PHBS is a dominant influencing factor, while improved service access alone does not always translate to better outcomes. The SEM-POS approach effectively identifies segment-specific health disparities, supporting more targeted policy interventions to improve maternal and child health in Indonesia.
COMPARISON OF FIRST-TO-DIE AND LAST-SURVIVOR JOINT LIFE INSURANCE UNDER COMMON SHOCK Satyahadewi, Neva; Jaya, Louis Putra; Kurniawan, Hendri; Pratiwi, Yuyun Eka
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp0913-0926

Abstract

Joint life insurance is a type of life insurance policy that covers two individuals, typically a married couple, under a single contract. The benefit is paid either upon the first death (First-to-Die) or after both individuals have passed away (Last-Survivor), depending on the policy type. This study explores the comparative analysis of First-to-Die and Last-Survivor joint life insurance policies under the impact of Common Shock. Common Shock refers to external catastrophic events, such as accidents or natural disasters, that simultaneously increase the mortality risk of both insured individuals. In this study, the Common Shock effect is parameterized by assigning additional joint mortality probabilities ranging from 2.5% to 10%, with increments of 2.5%. A total of 8 scenarios were tested. The first four scenarios vary the Common Shock probabilities at 2.5%, 5.0%, 7.5%, and 10.0%, while keeping the Interest Rate constant at 6.25%. The remaining four scenarios vary the Interest Rates at 5.50%, 5.75%, 6.00%, and 6.25%, with the Common Shock probability fixed at 10.0%. The analysis is conducted through actuarial modeling using present value formulas to assess total insurance premiums under these varying conditions. Using a benefit value of IDR 500,000,000.00 and a premium payment period of 10 years, this study demonstrates how these factors influence premium amounts. The incorporation of Common Shock into premium calculations offers a more realistic perspective in assessing insurance risk and cost. Mortality assumptions are based on the 2023 Indonesian Mortality Table published by BPJS Kesehatan, and the present value of future benefits is calculated using the specified interest rates. The findings reveal that the First-to-Die policy consistently results in significantly higher total premiums compared to the Last-Survivor policy under the same assumptions. On average across all scenarios, the total premium for First-to-Die is 5.67 times greater, primarily due to the higher probability of earlier benefit claims and shorter investment durations from the insurer’s perspective. The First-to-Die policy is more suitable for those with chronic illnesses or financial dependents, while the Last-Survivor policy is preferable for individuals focused on legacy planning.
Optimalisasi Portofolio Saham Jakarta Islamic Index (JII) Sektor Energi dengan Metode Median Variance Savitri, Dini Dwi; Satyahadewi, Neva; Sulistianingsih, Evy
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 14, No 6 (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.v14i6.103635

Abstract

Investasi adalah aktivitas pengelolaan dana pada aset tertentu dengan tujuan memperoleh keuntungan melalui pendapatan atau peningkatan nilai aset. Saham menjadi salah satu instrumen investasi yang menarik, terutama saham yang terdaftar dalam Jakarta Islamic Index (JII), sebuah indeks yang berisi 30 saham perusahaan yang memenuhi prinsip syariah di Indonesia. Penelitian ini bertujuan mengoptimalkan saham pada sektor energi dalam JII menggunakan metode Median Variance, yang tidak memerlukan asumsi distribusi normal dan tidak rentan terhadap outlier, serta mengukur risiko menggunakan Value at Risk (VaR) dengan pendekatan simulasi historis. Data yang digunakan merupakan data saham harian dari JII sektor energi periode 31 Mei 2023 hingga 31 Mei 2024. Optimalisasi portofolio Median Variance dimulai dengan melakukan perhitungan nilai return saham, menentukan hubungan antar saham menggunakan korelasi Kendall-Tau, perhitungan nilai median return dan kovarian antar saham sebagai dasar dalam menentukan bobot optimal portofolio dengan metode Median Variance. Terakhir, risiko portofolio diukur menggunakan VaR dengan metode simulasi historis. Berdasarkan hasil analisis, bobot optimal untuk saham ITMG, PGAS, PTBA, ADRO, dan AKRA masing-masing adalah 25,48%, 33,01%, 4,29%, 7,12%, dan 30,09% memiliki nilai harapan keuntungan sebesar 0,025% atau Rp25.000,00 dan dengan tingkat risiko sebesar 0,014% atau Rp14.410,00 per periode. Pada tingkat kepercayaan 95%, dengan dana awal sebesar Rp100.000.000,00 estimasi VaR menunjukkan potensi kerugian maksimum harian sebesar -1,73% atau Rp1.730.391,98. Hasil ini dapat menjadi acuan bagi investor yang ingin berinvestasi sesuai dengan prinsip syariah, sekaligus tetap mempertimbangkan aspek return dan risiko sebagaimana dalam investasi konvensional.
Cayenne Pepper Price Forecast in Singkawang City Based on Rainfall using Transfer Function Model Maharani, Citra Cipta; Yundari, Yundari; Satyahadewi, Neva
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp53-62

Abstract

Fluctuations in the price of cayenne pepper are a significant problem in Indonesia’s agricultural sector, especially in Singkawang City. Weather conditions, including rainfall are often the main factor affecting the production and distribution of cayenne pepper, causing price instability. This study aims to analyze the relationship between rainfall and the price of cayenne pepper, and build a forecasting model using a transfer function approach. In this study, the input series used is rainfall, while the output series is the price of cayenne pepper. The data used is secondary data obtained from the Central Statistics Agency in Singkawang City from January 2016 to December 2023. The data is analyzed through the stationarity stage, then the identification of the ARIMA model for the input series. After that, prewhitening and cross-correlation analysis were carried out to identify the parameter values and determine the noise series ARMA model. The results show that the transfer function model with parameters with ARMA noise series is the best model for forecasting the price of cayenne pepper. The results of forecasting the price of cayenne pepper in Singkawang City have a MAPE value of , so it can be concluded that the transfer function model is quite good at forecasting the price of cayenne pepper in Singkawang City with the highest forecasting result of IDR 61,899 in May 2024 and the lowest is IDR 32,206 in April 2024. This study focuses solely on the transfer function model because it is specifically designed to analyze the dynamic relationship between an input variable (rainfall) and an output variable (price). Other forecasting methods such as ARIMA or exponential smoothing only capture internal patterns within a single series and cannot represent the influence of external factors. Therefore, the transfer function approach is considered more appropriate for the purpose of this study.
Forecasting the Stock Price of PT. Dayamitra Telekomunikasi with Single Input Transfer Function Model Arsanti, Resti; Satyahadewi, Neva; Martha, Shantika
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp87-96

Abstract

The unpredictable movement of stock prices is often a challenge for investors, so it requires a deeper understanding and consideration of various factors before making investment decisions. One of the factors that affect stock price movements is trading volume. Therefore, this study uses a single input transfer function model to forecast the daily closing stock price of PT. Dayamitra Telekomunikasi, with the closing stock price as the output variable and the stock trading volume as the input variable. The transfer function is a forecasting model that integrates ARIMA with multiple regression analysis, allowing modeling not only based on the values of the output variables, but also considering the influence of the input variables. ARIMA model estimation is performed on the input series for the prewhitening process, then the order of the transfer function is determined using cross-correlation plots, as well as model diagnostic tests to ensure its feasibility. Model accuracy is calculated to evaluate its performance in forecasting. The data used in this study are daily data from the period July 5, 2022 to October 9, 2024. The transfer function model obtained has an order of (2,0,0), with a MAPE value of 1.09%, which indicates that the model has good accuracy. Based on the forecasting results, it is estimated that there will be a decrease in the share price of PT. Dayamitra Telekomunikasi Tbk for the next five periods
Comparison of Single Net Premium of Unit Linked Endowment Life Insurance using Annual Ratchet Method and Black Scholes Model Idilla, Leona; Satyahadewi, Neva; Martha, Shantika
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp73-86

Abstract

Annual Ratchet is an indexing method. Black Scholes is a model used to determine option. The purpose of this study is to compare the results of single net premium of unit-linked endowment life insurance using the Annual Ratchet method and the Black Scholes Model. The data used in this study are data on the daily closing share price of PT Telkom Indonesia (Persero) Tbk for the period December 20, 2021 to December 20, 2022, Bank Indonesia interest rates and the 2019 Mortality Table. In this study, a comparison is made between the Annual Ratchet method and the Black-Scholes model to calculate the net single premium of unit-linked endowment life insurance for a 30-year-old male insured. The results show that the premium calculated using the Annual Ratchet method is greater than the premium from the Black-Scholes model, which is Rp 8,725,000. This is due to the additional protection feature in the Annual Ratchet method, which provides a minimum guaranteed investment value, thus increasing the premium value to be paid.
Estimation of Inpatient Health Insurance Premiums using the RP-2000 Table with Medical Cost Projection Scenario Satyahadewi, Neva; Perdana, Hendra; Tamtama, Ray
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 2 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss2pp97-104

Abstract

Inpatient health insurance serves as an essential form of financial protection to mitigate the risk of loss arising from hospitalization costs. This study aims to estimate inpatient health insurance premiums by combining the Indonesian Mortality Table IV and the RP-2000 Combined Healthy Table to determine age-specific hospitalization probabilities. Methodologically, this research employs a quantitative actuarial modeling approach based on life table techniques and expected present value calculations, using secondary data from the Indonesian Mortality Table IV, the RP-2000 Combined Healthy Table, and published information on medical inflation in Indonesia. The numerical illustrations are obtained through spreadsheet-based actuarial calculations. In addition to age, the premium calculation incorporates the interest rate, the insured’s gender, and cost components such as inpatient care, surgery, and intensive care unit (ICU) treatment so that the premium structure aligns with the coverage provided. A scenario of rising hospital costs due to medical inflation, assumed at 13% per year, is also included to obtain more realistic and economically relevant premium estimates. A case study is conducted for a 30-year-old participant with a two-year coverage period, offering benefits of an inpatient daily allowance of IDR 300,000 (maximum 40 days), surgical expenses up to IDR 3,000,000, miscellaneous hospital care up to IDR 7,000,000, and an ICU allowance of IDR 600,000 per day (maximum 15 days). The analysis results show monthly premiums of IDR 113,341 for male participants and IDR 121,904 for female participants, where the difference is attributed to higher hospitalization risks among females. Age variation analysis indicates that premiums increase with age, while interest rate variation analysis shows that higher interest rates result in lower premiums due to the discounting effect. These findings support the need for a dynamic actuarial approach to setting more accurate and sustainable health insurance premiums
PENGELOMPOKAN KEJADIAN BENCANA ALAM DI INDONESIA MENGGUNAKAN ALGORITMA K-MEANS++ DENGAN EVALUASI CALINSKI HARABASZ INDEX Regita, Luna Amara; Martha, Shantika; Satyahadewi, Neva
BIMASTER : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 15, No 1 (2026): 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.v15i1.105966

Abstract

Indonesia merupakan wilayah yang rawan terhadap berbagai jenis bencana alam, sehingga diperlukan analisis untuk memahami pola kerawanan antar wilayah. Penelitian ini bertujuan untuk mengelompokkan provinsi di Indonesia berdasarkan jumlah kejadian bencana alam menggunakan algoritma K-Means++ serta menentukan jumlah klaster yang optimal menggunakan evaluasi Calinski Harabasz Index (CHI). Data yang digunakan berasal dari PODES (Potensi Desa) 2023-2024 yang semula mencakup 11 jenis bencana alam seperti banjir, gempa bumi, dan variabel lainnya dan 1 kategori wilayah tanpa bencana. Setelah uji multikolinearitas, dua variabel dieliminasi sehingga analisis akhir menggunakan 9 jenis bencana dan 1 variabel “tidak ada bencana alam”. Sebelum proses klasterisasi, data distandardisasi untuk memastikan perbandingan antar variabel sama tanpa dipengaruhi perbedaan skala, kemudian melakukan pengecekan multikolinearitas dan menghitung jarak menggunakan metode Euclidean Distance. Berdasarkan nilai CHI, jumlah klaster optimal adalah dua klaster. Klaster pertama berisi provinsi dengan tingkat kerawanan tinggi, sehingga dikategorikan sebagai klaster multihazard (rawan bencana). Klaster kedua mencakup provinsi dengan tingkat kerawanan lebih rendah, sehingga dikategorikan sebagai hidrometeorologis (minim bencana). Hasil penelitian ini dapat digunakan sebagai dasar pendukung kebijakan mitigasi, prioritas penanganan, serta pemetaan risiko bencana di tingkat nasional maupun daerah.
Co-Authors . Apriansyah Afghani Jayuska Afghany Jayuska Al-Ham, Hairil Alfariz, Febrant Amriani Amir Amriani Amir Amriani Amir Andani, Wirda Annisa Auliarahmi Antoni, Frans Xavier Natalius Apriliyanti, Rita Aprizkiyandari, Siti Ardhitha, Tiffany Ari Hepi Yanti Arsanti, Resti 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 Hendri Kurniawan, Hendri Hendrianto, El Herina Marlisa Huda, Nur'ainul Miftahul Huriyah, Syifa Khansa Ibnur Rusi Idilla, Leona Ikha Safitri Imro'ah, Nurfitri IMRO’AH, NURFITRI Imtiyaz, Widad Isra’ Sagita Jawani Jawani Jaya, Louis Putra Jessica Audrey Valeria Karlina, Sela Kusnandar, Dadan Tonny Louis Putra Jaya Lucky Hartanti Lucky Hartanti Lucky Hartanti M. Deny Hafizzul Muttaqin Maga, Fahmi Giovani Maharani, Citra Cipta 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 Fikri Muhammad Radhi Muhammad Rizki Muliadi Muliadi Muslimah (F54210032) Nabil, Ilhan Nail Nanda Shalsadilla Naomi Nessyana Debataraja Naomi Nessyana Debataraja Nazwa Nursyifa Noerul Hanin Nona Lusia Novi Novi Nugrahaeni, Indah Nur Asih Kurniawati Nur Asiska Nurfadilah, Kori’ah Nurfitri Imro'ah Nurfitri Imro’ah Nurhalita Nurhalita Nurhanifa, Nurhanifa Nurmaulia Ningsih Oktaviani, Indah Ovi Indah Afriani Paisal Paisal Pertiwi, Retno Pitriani Pratama, Aditya Nugraha Pratiwi, Yuyun Eka 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 Regita, Luna Amara 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 Savitri, Dini Dwi 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 Yohanna Gabriel Richsita Yopi Saputra Yudhi Yuliono, Agus Yumna Siska Fitriyani Yundari, Yundari Yuveinsiana Crismayella Yuyun Eka Pratiwi Zakiah, Ainun