Article Per Year (5 Year)
p-Index From 2021 - 2026
11.6
P-Index
This Author published in this journals
All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI SAINSMAT Chemica: Jurnal Ilmiah Kimia dan Pendidikan Kimia LaGeografiA Journal of Marine Research Media Komunikasi Geografi CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Environmental Science Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Inferensi PENGABDI: Jurnal Hasil Pengabdian Masyarakat Jurnal Dedikasi ARRUS Journal of Mathematics and Applied Science Journal of Multidisciplinary Applied Natural Science Journal of Mathematics: Theory and Applications Pedagogy : Jurnal Pendidikan Matematika Chemistry Education Review Seminar Nasional Pengabdian Kepada Masyarakat INOVASI: Jurnal Hasil Pengabdian Masyarakat Indonesian Journal of Fundamental Sciences Venn: Journal of Sustainable Innovation on Education, Mathematics and Natural Sciences Seminar Nasional Hasil Penelitian LP2M UNM Ininnawa: Jurnal Pengabdian Masyarakat Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) SMART: Jurnal Pengabdian Kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) Journal of Community Services and Development SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam
Wahidah Sanusi
Jurusan Matematika FMIPA Universitas Negeri Makassar, 90224
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

Published : 106 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 106 Documents
Search

 7   8   9   10   11 
PKM Pemberantasan Buta Aksara Bagi Kelompok Ibu Rumah Tangga Berbasis Literasi di Paladang Desa Mallongi-Longi. Side, Syafruddin; Sidjara, Sahlan; Pratama, Muh. Isbar; sanusi, wahidah; Yani, Ahmad
SMART: Jurnal Pengabdian Kepada Masyarakat Vol 3, No 2 (2023): Oktober
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/smart.v3i2.53937

Abstract

Berdasarkan data PKM tahun 2022s/d 2022 dan hasil observasi pada mitra yaitu kelompok IRT di dusun paladang, diketahuo bahwa tingkat pendidikan IRT di dusun paladang sebesar 80%  hanya tamat sekolah dasar saja, bahkan ada beberapa diantaranya yang tidak tamat SD. Hal ini berdampak pada anak-anak mereka yang beberapa diantaranya tidak melanjutkan sekolah ke jenjang lebih tinggi dan malas ke sekolah walaupun masih di tingkat Sekolah Dasar. Ketika melakukan wawancara terhadap beberapa orang IRT, mereka mengeluhkan sulitnya mendapatkan informasi melalui media sosial karena tidak bisa atau belum lancar membaca. Solusi yang dilakukan oleh tim PKM antara lain: (1) Mengajarkan baca tulis berbasis literasi dengan home scholling bagi IRT di dusun Paladang yang masih belum lancar dan belum mengetahui baca tulis. (2). Memberikan penyuluhan mengenai pentingnya pendidikan. (3). Mengadakan pembelajaran tambahan dalam rangka meningkatan kualitas pembelajaran di SD. Hasil pelaksanaan kegiatan menunjukkan bahwa 90% atau 9 dari 10 orang IRT di dusun Paladang Desa Mallongi-Longi, Kabupaten  Pinrang yang mengikuti kegiatan ini sudah dapat membaca, kemudian 100% atau 10 orang anak-anak di dusun Paladang Desa Mallongi-Longi, Kabupaten  Pinrang yang mengikuti kegiatan ini sudah dapat membaca.
APPLICATION OF GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY (GARCH) MODEL IN FORECASTING THE MARKET PRICE OF NICKEL IN INDONESIA Sidjara, Sahlan; Sanusi, Wahidah; Nyulle, Rusdianto
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9798

Abstract

Indonesia is one of the largest nickel exporting countries in the world, with the increasing demand for electric vehicles making nickel a target for producers. The increase in nickel demand makes it necessary to increase the observation of nickel prices to maintain the sustainability of the mining industry and economic growth. The purpose of this study is to forecast the price of Indonesia's nickel market using the GARCH method. The GARCH method is one of the methods used in time series data modeling that identifies heteroscedatic effects. The steps taken are to analyze the training data, check the stationery, estimate the parameters, and test the diagnostic model, then the best ARIMA model is selected based on the smallest AIC value, namely ARIMA (0,1,1). The residual values of the best ARIMA models are then used to determine the GARCH model. The best GARCH model obtained is GARCH (0.1) with an AIC value of 19.04061. Furthermore, forecasting was carried out using the GARCH model (0.1) and comparing the forecast results with the testing data to obtain MAPE values. The MAPE value obtained is 17.67014 % which shows that the GARCH model (0.1) has good forecasting accuracy, so this model is quite feasible to be used in forecasting the price of Indonesia's nickel market.
Evaluasi Performa Model Regresi Poisson Tweedie dan Conway Maxwell Poisson dalam Menangani Masalah Dispersi: Studi Angka Kematian Ibu di Provinsi Sulawesi Selatan Aswi, Aswi; Sanusi, Wahidah; Tiro, Muhammad Arif; Sukarna, Sukarna; Haekal, Muh. Fahri; Palarungi, Andi Gagah; Putri, Siti Choirotun Aisyah; Oktaviana, Oktaviana
Indonesian Journal of Fundamental Sciences Vol 11, No 2 (2025)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ijfs.v11i2.77506

Abstract

Model regresi Poisson digunakan untuk menganalisis hubungan antara satu atau lebih variabel independen dengan variabel dependen berupa data cacahan. Salah satu asumsi utamanya adalah kesamaan antara nilai mean dan variansi (equidispersi). Namun, dalam praktiknya, asumsi tersebut sering tidak terpenuhi. Kondisi ini menyebabkan model regresi Poisson kurang sesuai digunakan, karena dapat menghasilkan estimasi standar error yang terlalu kecil (underestimate). Model alternatif yang dapat digunakan untuk mengatasi masalah overdispersi adalah Regresi Poisson Tweedie dan Conway Maxwell Poisson (CMP). Penelitian ini bertujuan untuk mengevaluasi kinerja model regresi Poisson Tweedie dan regresi CMP dalam menangani masalah dispersi pada data Angka Kematian Ibu (AKI) di Provinsi Sulawesi Selatan, Indonesia. Estimasi parameter dilakukan dengan metode Estimasi Kemungkinan Maksimum (MLE), sedangkan kinerja model dinilai berdasarkan Akaike Information Criterion (AIC), Mean Square Error (MSE), dan signifikansi parameter. Hasil penelitian menunjukkan bahwa model regresi Poisson standar kurang sesuai karena adanya pelanggaran asumsi ekuidispersi. Sebaliknya, model CMP dan Poisson Tweedie memberikan alternatif yang lebih tepat, dimana Model CMP menunjukkan akurasi prediktif yang lebih tinggi dengan nilai MSE terendah. Faktor perdarahan, hipertensi, gangguan kardiovaskular, dan komplikasi pasca-aborsi ditemukan memiliki pengaruh yang signifikan terhadap kematian ibu, sementara infeksi tidak signifikan secara statistik. 
Probabilistic Modeling of Annual Maximum Rainfall for Intensity-Duration-Frequency Curve Construction in the Mamminasata Region, South Sulawesi Province, Indonesia Sanusi, Wahidah; Patahuddin, Sudarmin; Sidjara, Sahlan
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.373

Abstract

The evaluation of extreme rainfall events is crucial for the management and planning of water resources, particularly in the design of drainage systems and water storage reservoirs. Such evaluation can be carried out through the estimation of design rainfall, which is commonly represented as rainfall intensity–duration–frequency (IDF) data. The purpose of this study is not only to apply probabilistic models to annual maximum daily rainfall data but also to construct the IDF curves of rainfall in the Mamminasata region of South Sulawesi Province. This study utilizes annual maximum daily rainfall data obtained from the Water Resources, Human Settlements, Spatial Planning, and Development Office of South Sulawesi Province, as well as the Meteorology, Climatology, and Geophysics Agency (BMKG) of Indonesia. The dataset consists of observations from 8 rainfall stations in the Mamminasata region spanning 36 years, from 1989 to 2024. The methodology involves first determining the appropriate probability distribution for each rainfall station, followed by estimating rainfall intensity using the Mononobe method, and finally constructing the IDF curves based on the estimated design rainfall and rainfall intensities for different return periods. This study found that each regency or city within the Mamminasata region generally exhibits distinct rainfall probability distributions. This highlights the importance of evaluating multiple probabilistic models to appropriately characterize the variability and extremes rainfall pattern across different locations. Based on the IDF curve, the results indicate that the longer the rainfall duration, the lower the intensity. Likewise, the shorter the return period, the lower the corresponding intensity.
Mathematical Modeling of Typhoid Fever Control Through Non-Pharmaceutical Interventions in South Sulawesi Fausiatul Iffa; Wahidah Sanusi; Alimuddin Alimuddin
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/74nj6t57

Abstract

Typhoid fever remains one of the major public health problems in Indonesia, particularly in South Sulawesi. This article discusses mathematical modeling of the impact of non-pharmaceutical interventions on typhoid fever control. This study aims to develop a mathematical model that represents the dynamics of typhoid fever transmission and to solve the model numerically using the Variational Iteration Method (VIM). The model applied is the SICRB compartment model, which divides the population into five groups: susceptible (S), infected (I), chronic carrier (C), recovered (R), and bacterial concentration (B). The analysis results indicate that the basic reproduction number R₀ > 1, suggesting that typhoid fever has the potential to persist in the population. Numerical simulations are carried out using Maple for analytical derivation and R Studio for visualization of the dynamics. The implementation of non-pharmaceutical interventions, including health education, environmental sanitation, and herbal treatment, demonstrates a significant reduction in infection cases, an increase in recovery, and a decrease in bacterial concentration. The model shows stability toward the endemic equilibrium and consistency between mathematical analysis and numerical simulations.
Rumah Belajar Ceria: Tutoring in Mathematics and English for Elementary School Students in Tenrigangkae Village Lhenny Ardillah Latif; Muhammad Ammar Naufal; Hamzah Upu; Wahidah Sanusi; Zaid Zainal
Journal of Community Services and Development Vol. 1 No. 2 (2025): November 2025
Publisher : LPP Chani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64619/v1i1.9

Abstract

The Rumah Belajar Ceria program was implemented as part of the community service component of the KKN-PPL program of Universitas Negeri Makassar in Tenrigangkae Village, aiming to enhance elementary school students’ motivation and understanding of Mathematics and English. This initiative was driven by limited learning facilities and a lack of academic support outside school hours, causing children to spend more time playing without academic guidance. The program was conducted informally in three phases: planning, implementation, and evaluation. The learning strategy emphasized interactive, contextual, and game-based approaches. The results showed increased motivation, participation, and confidence among students, along with significant improvement in understanding basic concepts. In addition, the program received positive support from parents and the community, strengthening social bonds between students, parents, and university students. These findings highlight that informal game-based learning models can serve as an alternative solution to improve both educational quality and community empowerment in rural areas.
Analisis Keakuratan Pendekatan Hybrid ARIMAX dan Radial Basis Function Neural Network pada Pemodelan Data Curah Hujan di Kota Makassar Wahidah Sanusi; Alimuddin Alimuddin; Muhammad Farhan; Nurlaila Kaito; Nurkhalifah Anwar
Indonesian Journal of Fundamental Sciences Vol 12, No 1 (2026)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ijfs.v12i1.85986

Abstract

Abstrak. Penelitian ini bertujuan untuk mengatasi keterbatasan tersebut dengan mengembangkan sebuah model peramalan hybrid, serta menganalisis tingkat akurasinya. Menggabungkan keunggulan pemodelan linier dan non-linier, penelitian ini menerapkan arsitektur hybrid SARIMAX-Radial Basis Function Neural Network (RBFNN). Model ini dibangun melalui pendekatan dua tahap: pertama, model SARIMAX dengan parameter (0,1,1)(0,1,1)₁₂ digunakan untuk memodelkan pola linear-musiman. Kedua, RBFNN dilatih secara spesifik untuk memetakan pola non-linear yang terkandung dalam residual (kesalahan) dari model SARIMAX. Kinerja model hybrid terhadap data pengujian menunjukkan hasil yang sangat positif, terbukti secara signifikan lebih akurat dibandingkan model SARIMAX tunggal. Model hybrid menunjukkan kemampuan superior dalam mengikuti fluktuasi data aktual, yang pada akhirnya menghasilkan prediksi dengan galat yang jauh lebih rendah. Akurasi yang lebih tinggi ini dikonfirmasi melalui nilai Mean Absolute Percentage Error (MAPE) yang lebih kecil, yang mengindikasikan potensi besar dari pendekatan hybrid ini untuk menyediakan peramalan meteorologi yang lebih efektif dan dapat diandalkan untuk Kota Makassar
Penerapan Model Regresi Logistik Biner dalam Mengetahui Faktor-Faktor yang Berpengaruh terhadap Status Menganggur Lulusan SMK di Kota Makassar Maya Sari Wahyuni; Wahidah Sanusi; Fitriadita; Muh. Isbar Pratama
Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Vol. 9 No. 2 (2026): Exploring Mathematics through Education, Modeling, Finance, and Cultural Perspe
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/proximal.v9i2.8527

Abstract

Pengangguran masih menjadi masalah serius di Indonesia, khususnya pada lulusan Sekolah Menengah Kejuruan (SMK) yang justru dirancang untuk siap bekerja, namun menjadi kontributor terbesar Tingkat Pengangguran Terbuka (TPT) di Indonesia setiap tahunnya, mencapai 9,01% pada Agustus 2024 dibandingkan dengan jenjang lainnya. Isu ini diperparah di tingkat lokal, di mana Kota Makassar tercatat sebagai daerah dengan TPT tertinggi di Sulawesi Selatan yaitu 9,71% pada tahun 2024 dengan lulusan SMK menempati urutan pertama tingkat pengangguran tertinggi berdasarkan jenjang pendidikan. Penelitian ini merupakan penelitian terapan dengan pendekatan kuantitatif, menggunakan data sekunder hasil Survei Angkatan Kerja Nasional periode Agustus 2022, 2023, dan 2024 yang diperoleh dari BPS Provinsi Sulawesi Selatan. Tujuan penelitian ini adalah untuk menerapkan model regresi logistik biner dalam mengetahui faktor-faktor yang berpengaruh terhadap status menganggur lulusan SMK di Kota Makassar, dengan menguji variabel jenis kelamin, bidang keahlian, tahun kelulusan, dan kualifikasi keikutsertaan pelatihan. Estimasi parameter regresi logistik dilakukan dengan menggunakan metode Maximum Likelihood Estimation. Hasil dari penelitian ini menunjukkan bahwa faktor yang berpengaruh secara signifikan terhadap status menganggur lulusan SMK di Kota Makassar adalah periode kelulusan, dengan tiga kategori, yaitu lulusan baru, lulusan pandemi, dan lulusan lama, di mana lulusan baru dijadikan sebagai kategori referensi. Interpretasi odds ratio menunjukkan bahwa lulusan pandemi memiliki peluang menganggur sebesar 4,355 kali lebih tinggi dibandingkan lulusan baru dan lulusan lama memiliki peluang menganggur sebesar 6,369 kali lebih tinggi dibandingkan lulusan baru.
Forecasting Acute Respiratory Infection Incidence in South Sulawesi Province Through a Hybrid ARIMA–RBFNN Model Muthia Ramadhani Rafli; Muhammad Abdy; Wahidah Sanusi
Journal of Mathematics, Computations and Statistics Vol. 9 No. 2 (2026): Volume 09 Issue 02 (June 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/11958

Abstract

Abstract. Among all notifiable diseases in Indonesia, Acute Respiratory Infection (ARI) consistently registers the highest national burden of illness. Within South Sulawesi Province alone, the eight-month tally from January through August 2023 surpassed 320,942 confirmed cases, underscoring the critical need for reliable case-number projections to guide evidence-based health-service planning. The present work constructs a time series forecasting framework that integrates ARIMA (Autoregressive Integrated Moving Average) with a Radial Basis Function Neural Network (RBFNN) under the hybrid paradigm proposed by Zhang (2003). Monthly ARI incidence data spanning January 2014 to December 2024 provided 132 observations in total. Following a chronological split, the first 96 data points (January 2014–December 2021) served as the training set and the remaining 36 (January 2022–December 2024) as the hold-out evaluation set. ARIMA captured the linear dynamics of the series, whereas RBFNN was subsequently applied to the ARIMA residuals to account for any nonlinear structure that remained unexplained. Minimum-AIC model selection identified ARIMA(2,1,2) as the most suitable linear specification. For the RBFNN stage, a four-lag input vector—derived from the partial autocorrelation function—combined with four hidden units and a multiquadratic basis function delivered the best generalisation performance. Assessed against MAPE, RMSE, and R², the standalone ARIMA(2,1,2) attained 14.19%, 5038.37, and 0.6275, respectively; RBFNN alone produced 15.47%, 4714.93, and 0.5479; and the Hybrid ARIMA–RBFNN yielded 16.11%, 5014.99, and 0.6309. The superior R² of the combined model demonstrates its enhanced capacity to account for data variability. Because all three models returned MAPE values below the 20% threshold, they qualify as good predictors under the Lewis (1982) classification scheme. On this basis, the hybrid approach is put forward as the preferred tool for ARI early-warning and surveillance operations in South Sulawesi.
Comparison of Support Vector Regression and Random Forest Methods for Rainfall Prediction in Makassar City Ilmadinah Kadir; Wahidah Sanusi; Ja'faruddin Ja'faruddin
Journal of Mathematics, Computations and Statistics Vol. 9 No. 2 (2026): Volume 09 Issue 02 (June 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/Jmathcos12183

Abstract

This study aims to compare the performance of Support Vector Regression (SVR) and Random Forest (RF) methods in predicting daily rainfall in Makassar City and to identify the most influential meteorological factors. The dataset consists of daily climate data from 2019 to 2024, including rainfall as the response variable and temperature, humidity, wind speed, and sunshine duration as predictor variables. Data preprocessing was conducted through missing value imputation, time-series structuring, and normalization using the Z-score method for the SVR model. The SVR model was developed using several kernel functions, including linear, polynomial, radial basis function (RBF), and sigmoid, with hyperparameter tuning performed using grid search and k-fold cross-validation. Meanwhile, the Random Forest model was constructed using bootstrap aggregation and random feature selection, with optimal parameters determined based on the minimum out-of-bag (OOB) error. The results show that the SVR model with the RBF kernel achieved the best performance, with RMSE of 16.52 mm and MAE of 9.01 mm, outperforming the Random Forest model, which produced RMSE of 18.15 mm and MAE of 10.93 mm. Furthermore, feature importance analysis indicates that humidity and temperature are the most dominant variables influencing rainfall. Therefore, the SVR method is more accurate and reliable for rainfall prediction in Makassar City.
Co-Authors A. Armansyah AHMAD FAUZAN RIDHA SUJIONO ahmad yani Ahmad Zaki AHMAD ZAKI Ahmad Zaky Alimuddin Tampa Aliyah Arianti Halim Amal Amal Amal Amal Amal Arfan, Amal Amni Rasyidah Andi Abidah Andi Diki Nurbaldatun Islam Andi Muhammad Ridho Yusuf Sainon Andi Pandjajangi Andini, Reski Anggi Ananda Putri Annas, Suwardi Arkas, Amaliah Nurul Asdar Asdar Asdar Asmi, Nurul Asni, Asriani Arsita Asriani Arsita Asni Aswi, Aswi Aulia, Hikma Awi Dassa, Awi Beby Fitriani Besse Nur Afni Besse Nur Afni Bohari, Nurul Aulia Bohari, Nurul Aulia Diki Nurbaldatun Islam Elma Selviana Darwis Fausiatul Iffa Febriyanto Saman Fitriadita Fitriyani Fitriyani Fitriyani Folorunso, Serifat Adedamola G. Gunawan H. Hasriani Haekal, Muh. Fahri Hafilah Hardiono Hafilah. H Hamzah Upu Harisahani, Nur Hasan Basri Hasanah, Afifatun Hasnawiyah, Hasnawiyah Hasriani Hikma Aulia Hisyam Ihsan Ihsan U, Wa Irma Al Ika Pratiwi Ilham Minggi Ilmadinah Kadir Imam Muhajir Utama Irham Aryandi Basir Irham Aryandi Basir Irma Aswani Ahmad, Irma Aswani Irwan Irwan Irwan Irwan Irwan Irwan Irwan Irwan Thaha Ja'faruddin Ja'faruddin Janide, Anugrah Kahvi Nurani Kaito, Nurlaila Katrina Pareallo Lhenny Ardillah Latif Lisca Palerina Mudinillah, Adam Muh. Idris Muh. Ishaq Firdaus Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Ammar Naufal Muhammad Arib Musba Amalul Muhammad Arif Tiro, Muhammad Arif Muhammad Danial Muhammad Danial Muhammad Danial Muhammad Faisal Juanda Muhammad Farhan Muhammad Farhan Muhammad Isbar Pratama Muhammad Rakib Muhammad Rakib Muhammad Rakib Muhammad Syahrir Muhjria, Muhjria Mukarram, Trys Musliati Musliati Mustati'atul Waidah Maksum Muthia Ramadhani Rafli N Nurfadillah N Nurwakia Nasrullah Nasrullah Nirwana, St. Risma Ayu Nur Anny S. Taufieq Nur Anny S. Taufieq Nur Anny S. Taufieq Nur Anny Suryaningsih Taufieq Nur Fajri Setiawan Nur Hikmayanti Syam Nur Khaerati Rustan Nur Ridiawati Nur Ridiawati Nurani, Kahvi Nurazizah Nurdin, Nur Izzah Nurfadillah Nurhilaliyah, Nurhilaliyah Nurkhalifah Anwar Nurlaila Kaito Nurul Aulia Bohari Nurul Fadilah Syahrul Nyulle, Rusdianto Oktaviana Oktaviana Padjalangi, Andi Muhammad Ridho Yusuf Sainon Andi Palarungi, Andi Gagah Patahuddin, Sudarmin Patasik, Ghadytha Marie Lucia Pertiwi, Ika Pince Salempa Putri, Siti Choirotun Aisyah R. Rusli Rabiatul Adawiyah Rabiatul Adawiyah Rahman, Muhammad Fatur Rahmat Setiawan Rahmat Syam Rahmawati, Rahmawati Reski Andini Rhida Anggita Dasri Risna Ulfadwiyanti Rosidah Rosidah Ruliana Rustan, Nur Khaerati S Sukmawati Sahlan Sidjara Saiful Bahri Saman, Febriyanto Sari, Yulfiana Serly Diliyanti Restu Ningsih Serly Diliyanti Restu Ningsih Setiawan, Nur Fajri Sidjara, Sahlan Siti Helmyati Sudarmin Sudarmin Sukarna Sukarna Sukarna Sukarna Sukarna Sulaiman Sulaiman Suwardi Annas Syafruddin Side SYahnur, Andi Aulia Syuhri, Ajrian Takdir, Nurfajri Hamdani Talib, Dr. Ahmad Tampa, Alimuddin Taty Sulastri Taty Sulastri Taty Sulastri Trys Mukarram Ulfadwiyanti, Risna Usman Mulbar Utami Priono Wahyuliani, Dwi Wahyuni, Maya Sari Wulandari, Natalia Puspita Yusuf S.A.P., Andi Muh. Ridho Zainal, Zaid