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Muhammad Zulfadhilah
Teknologi Informasi, Universitas Sari Mulia
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Evaluasi Maturity Level Tata Kelola Teknologi Informasi di Perpustakaan Perguruan Tinggi Menggunakan Cobit 5 Mambang Mambang; Finki Dona Marleny; Septyan Eka Prastya; Muhammad Zulfadhilah; Subhan Panji Cipta; Jaya Hari Santoso; Miranda Miranda; M Samsul Hasmi; M Samsul Hasbi
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 5, No 4 (2022): Agustus 2022
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v5i4.4546

Abstract

Abstrak- Solusi teknologi informasi harus diidentifikasi atau layanan yang diimplementasikan dan diamanatkan termasuk penyediaan layanan, manajemen keamanan dan kontinuitas, layanan dukungan  pengguna, manajemen data, dan fasilitas operasi. Untuk mengukur tingkat kematangan perpustakaan di lakukan audit tata kelola teknologi informasi untuk mengevaluasi, menganalisis, mengawasi, kepatuhan regulasi teknologi informasi apakah dalam manajemen risiko dalam perpustakaan layak digunakan atau tidak layak digunakan di perpustakaan. Metode dalam mendapatkan data dan informasi dari proses tata kelola TI pada Perpustakaan XYZ dengan kuesioner dan wawancara langsung. Berdasarkan rata - rata nilai maturity level di semua domain proses yang dilakukan audit dengan kerangka kerja COBIT 5 berada pada nilai 3,3 atau pada level 3 (Established). Pada level ini secara keseluruhan proses standar didefinisikan dan digunakan di seluruh organisasi. Rata-rata gap analisis berada pada nilai 1,63 yang menunjukan proses Tata Kelola IT di Perpustakaan XYZ sudah berjalan dengan baik. Semakin kecil nilai rata-rata gap analisis dengan nilai ekspektasi maka semakin bagus bagi pengeloaan TI pada sebuah Instansi, perusahaan dan bidang industry lainnya yang menggunakan infrastuktur IT baik pada pengelolaan perangkat keras, perangkat lunak dan pengelolaan sumber daya manusia. Untuk penelitian selanjutnya, bisa menambahkan lebih banyak lagi domain proses baik pada area Tata Kelola (Governance) dan area Manajemen (Management), sehingga proses audit dengan kerangka kerja COBIT 5 dapat dilakukan dengan komprehensif.Kata kunci: Maturity Level, Tata Kelola Teknologi Informasi, Perpustakaan, COBIT 5 Abstract- Information technology solutions should be identified or services implemented and mandated, including service provision, security and continuity management, user support services, data management, and operations facilities. Methods of obtaining data and information from the IT governance process at the XYZ Library with questionnaires and direct interviews. To measure the library's maturity level, an information technology governance audit is carried out to evaluate, analyze, supervise, and comply with information technology regulations whether in risk management in the library is feasible to use or unfit for use in the library. The average maturity level value in all process domains audited with the COBIT 5 framework is 3.3 or at level 3 (Established). The overall standard process is defined and used throughout the organization at this level. The average analysis gap is at a value of 1.63, which shows that the IT Governance process in the XYZ Library is already running well. The smaller the average value of the analysis gap with the expectation value, the better it is for IT management in an agency, company and other industrial fields that use IT infrastructure in hardware management, software and human resource management. For further research, we can add more process domains both in the Governance and Management areas so that the audit process with the COBIT 5 framework can be carried out comprehensively.Keywords: Maturity Level, Information Technology Governance, Library, COBIT 5
Rancang Bangun Alat Musik Tradisional Berbasis Android Mambang Mambang; Subhan Panji Cipta; Septian Eka Prastya; Muhammad Zulfadhilah; Finki Dona Marleny; Ropikah Ropikah; Muhammad Riduan Syafi’i; Nur Meilianti Maulida; Sandro Nesta Pembriano; Risma Risma; Muhammad Zaini Bakri; Kartika Kartika; Putri Putri
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 5, No 2 (2022): April 2022
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v5i2.4036

Abstract

Peradaban yang semakin maju dengan adanya teknologi digital telah membawa kita semua pada era baru, dimana perubahan terjadi dimana dan terasa sangat cepat. Perkembangan dan kemajuan teknologi digital sangat mempengaruhi perkembangan ilmu pengetahuan dari berbagai aspek. Teknologi telah mempengaruhi kehidupan ini dan tidak bisa dihindari, karena IPTEK memberikan banyak manfaat dan memudahkan pekerjaan. Rancang bangun alat musik daerah berbasis android yang dilakukan dalam penelitian ini adalah mengembangkan salah satu lat musik tradisional dari kalimantan selatan yaitu panting yang penggunaannya secara digital atau berbasis android. Pada penelitian ini motede yang kami gunakan adalah metode waterfall. Metode waterfall merupakan model pengembangan sistem informasi yang sistematik dan sekuensial. Pada penelitian ini menghasilkan sebuah aplikasi berbasis android yang berfungsi untuk memberikan kemudahan kepada masyarakat agar dapat mengetahui informasi mengenai alat musik panting, sehingga dengan adanya aplikasi berbasis android ini, dapat meningkatkan minat masyarakat khususnya generasi muda dalam melestarikan budaya lokal atau budaya daerah.
Perbedaan Efektifitas Kompres Air Hangat dan Daun Kembang Sepatu Dalam Menurunkan Suhu Tubuh Balita Saat Demam Sari, Rahmadah; Salmarini, Desilestia Dwi; Zulfadhilah , Muhammad
Jurnal Rumpun Ilmu Kesehatan Vol. 4 No. 1 (2024): Maret: Jurnal Rumpun Ilmu Kesehatan
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jrik.v4i1.2871

Abstract

The impact of LBW poses many risks regarding problems in the body's system due to unstable body condition which can cause death. The causes of LBW are due to fetal factors, placental factors and maternal factors. Preeclampsia is a problem of serious maternal factors and has a high level of complexity. The results of the preliminary study in 2021 totaled 34 people with preeclampsia and 60 cases of low birth weight babies. Research objective is to determine the effectiveness of compresses of warm water and hibiscus leaves in lowering the body temperature of toddlers in the Banua Lawas Health Center area. The research methods is Quasi-experimental research with a pre-test-post-test research design without a control group. A sample of 30 people were divided into warm water compress groups and hibiscus leaf compress groups. Collecting data by observing according to SOP (Standard Operating Procedure). Data analysis using wilxocon. Resulted that the mean temperature in the warm water compress group before being given was 36.9°C and after being given was 36.3°C (the difference was 0.58°C). The average temperature in the hibiscus leaf compress group before being given was 36.8 °C and after being given 36.1 °C (the difference was 0,33 °C). There is a difference between warm water compresses and hibiscus leaves in reducing temperature in toddlers with fever in the Banua Lawas Health Center area (p-value ˂ 0.000). Concluded that both types of compresses are effective in reducing body temperature in children with fever but warm water compresses are more effective than hibiscus leaf compresses.
Health monitoring before and after independent learning during the pandemic Handayani, Lisda; Suhartati, Susanti; Irawan, Angga; Zulfadhilah, Muhammad
Health Sciences International Journal Vol. 2 No. 2: August 2024
Publisher : Ananda - Health & Education Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71357/hsij.v2i2.40

Abstract

Background: The COVID-19 pandemic significantly impacted educational practices globally, including Indonesia's Merdeka Belajar-Kampus Merdeka (MBKM) program, which emphasizes real-world learning experiences. Health monitoring became a crucial aspect of student safety during MBKM activities, particularly in community settings. This report examines the health protocols implemented by Universitas Sari Mulia during a humanitarian mission in response to the South Kalimantan floods amidst the pandemic. Case presentation: Sari Mulia University deployed 327 students to assist in four sub-districts affected by floods. To prevent the spread of COVID-19, pre-deployment health protocols included rapid antigen testing, which identified five asymptomatic positive cases requiring isolation. After completing the two-month MBKM program, students were tested again, revealing seven additional cases, including one with moderate symptoms, while others were either mild or asymptomatic. Discussion: The university's health monitoring protocols, including pre- and post-deployment testing, isolation, and symptom-based treatments, significantly minimized virus transmission. The importance of early detection and close monitoring of asymptomatic individuals  is emphasized, as undetected cases could contribute to community transmission. Additionally, the program highlights the necessity of integrating health education into MBKM activities to ensure students understand preventive health measures. Conclusion: Universitas Sari Mulia successfully implemented comprehensive health monitoring during its MBKM program, protecting both students and the communities they served. This case underscores the need for ongoing health vigilance, education, and institutional collaboration to safely conduct off-campus learning during the pandemic. These practices serve as a model for future MBKM programs across Indonesia.
Prediction of linear model on stunting prevalence with machine learning approach Mambang, Mambang; Marleny, Finki Dona; Zulfadhilah, Muhammad
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4028

Abstract

An increase in the number of residents should be anticipated including in the health sector, especially the problem of stunting. Stunting in children disrupts height and lack of absorption of nutrients. Information and data drive change in many areas such as health, entertainment, economics, business, and other strategic areas. The stages carried out in this study are initiating, developing linear models, and making prediction results on linear machine learning models. The results of testing with the scikit-learn linear model with a minimum variable of 19 get the best test results, namely the polynomial regression with pipeline model with mean absolute percentage error (MAPE) 0.02, root mean square error (RMSE) 3.32, and coefficient of determination (R2) 1,00. Testing with the scikit-learn linear model with a maximum variable of 48 gets the best test results, namely the polynomial regression with pipeline model with MAPE 0.00, RMSE 3.79 and R2 1.00. Testing with the scikit-learn linear model with an average variable of 32 gets the best test results, namely the polynomial regression model with MAPE 0.01, RMSE 3.32, and R2 1.00. The results of testing with the scikit-learn linear model with the minimum, maximum, and average variables get the best test results, namely the polynomial regression with pipeline model.
Implementasi Algoritma Decision Tree dan Random Forest dalam Prediksi Perdarahan Pascasalin Sinambela, Dewi Pusparani; Naparin, Husni; Zulfadhilah, Muhammad; Hidayah, Nurul
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.393

Abstract

Perdarahan Postpartum (PPP) merupakan salah satu kegawatdaruatan pada persalinan yang dapat menyebabkan kematian di negara maju dan negara berkembang. Salah satu pencegahan terjadiya PPP dengan melakukan prediksi pada ibu bersalin dengan mempertimbangkan faktor faktor risiko menggunakan pendekatan model Machine Learning (ML). Algoritma Random Forest (RF) dan Decision Tree (DT) merupakan algoritma yang digunakan dalam prediksi kejadian PPP. Tujuan dari penelitian ini adalah mengembangkan kinerja dari Algoritma RF dan Algoritma RF untuk mengklasifikasi kejadian PPP. Hasil analisis Berdasarkan hasil analisis univariat yang ditunjukkan pada tabel 1 didapatkan ibu yang memiliki paritas > 4 sebanyak 102 orang (20,4%), jarak kehamilan ibu yang ≤ 2 tahun sebanyak 310 orang (62%), ibu pasca bersalin yang mengalami anemia sebanyak 124 orang (24,8%), ibu yang melahirkan bayi makrosomia sebanyak 60 orang (12 %), ibu yang mengalami komplikasi persalinan sebanyak 229 orang (45,8 %),ibu yang mengalami kehamilan ganda sebanyak 16 orang (3,2%), umur ibu yang berisiko sebanyak 132 orang (26,4%). Perbandingan tingkat akurasi algoritma RF mencapai 0,830 dibandingkan dengan algoritma DT sebesar 0.820, AUC RF 0.74. Hal ini menunjukan bahwa Algoritma RF mempunya perfomance metric lebih naik dibandingkan dengan algoritma DT. Algoritma Random Forest dapat dianggap sebagai salah satu algoritma representatif ML, yang dikenal karena kemudahannya dan efektivitasnya
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN CALON KETUA HIMA DENGAN MENGGUNAKAN METODE TOPSIS Hadi, Nofie; Nugraha, Bayu; Zulfadhilah, Muhammad
INTEKNA Jurnal Informasi Teknik dan Niaga Vol 23 No 2 (2023): Jurnal INTEKNA, Volume 23, No. 2, Nov 2023
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

HIMA (Himpunan Mahasiswa) adalah merupakan organisasi mahasiswa di jurusan dalam satu fakultas yang merupakan kegiatan bidang kemahasiswaan di jurusan. Dalam proses pemilihan ketua HIMA dimulai dari adanya penyeleksian berdasarkan pada beberapa kriteria tertentu yaitu, prestasi 40, sertifikat seminar 30, visi misi 10 dan mahasiswa aktif 20 yang memiliki bobot penilaian yang berbeda. Untuk menentukan pengambilan keputusan tersebut menggunakan sistem pendukung keputusan (SPK) dan menggunakan metode TOPSIS merupakan salah satu alat bantu dalam pemecahan masalah ini. Metode yang digunakan pada penelitian ini adalah TOPSIS (Technique for Order Preference by Similarity to Ideal Solution).Berdasarkan hasil penelitian ini yaitu, perangkingan yang no 1 adalah rusidah dengan nilai preferensi 0.012287951798694. Berdasarkan hasil penelitian yang sudah dilakukan kesimpulan penelitian ini diharapkan dapat dikembangkan lagi contohnya dengan memperbandingkan metode topsis dengan metode sistem pendukung keputusan yang lainnya.
Artificial Intelligence and Digital Economy: Comparative Adoption of Regions and Populations in ASEAN Countries Using EDA Samita, Mambang; Mambang; Muhammad Zulfadhilah; Septyan Eka Prastya; Finki Dona Marleny
Adpebi Science Series 2022: 1st AICMEST 2022
Publisher : ADPEBI

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this paper is to make a comparative analysis of artificial intelligence adoption and the potential of the digital economy in ASEAN countries. The regions of countries and populations of the ASEAN Region correlate with the adoption of artificial intelligence and the potential of the digital economy. This paper uses qualitative methods and experiments with secondary data sources from online websites. The data used has been validated with other online sources that are credible and follow global information provisions. This proposed paper has four variables used as indicators in data visualization related to AI Adoption, Area, Population, and the digital economy. The four countries analyzed are members of ASEAN. The results of exploratory data analysis using the Seaborn library using the Python programming language obtained correlation results consisting of the variables Adoption of AI, Area, Population, and Digital Economy. The correlation of the Adoption of AI variables with the Digital Economy correlates 0.94. Adoption of AI with Population correlates 0.93. Adoption of AI with an Area of 0.86. Furthermore, the Area or region variable has a correlation value of 0.97 with the digital economy. Areas with a population have a correlation value of 0.98. The Population variable has a very strong correlation with the digital economy of 1. Further research can add several variables such as the potential for future jobs and the number of countries so that it is not limited to ASEAN countries alone.
Analisis Sentimen Terhadap Aplikasi Parak Acil Online Berdasarkan Ulasan Masyarakat Menggunakan Metode Support Vector Machine (SVM) Mutmainah, Mutmainah; Cipta, Subhan Panji; Mambang, Mambang; Zulfadhilah, Muhammad; Naparin, Husni; Syapotro, Usman
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 5 (2024): Oktober 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i5.7962

Abstract

Abstrak - Perkembangan teknologi informasi mempermudah akses layanan publik, termasuk aplikasi Parak Acil Online yang dikembangkan oleh Pemerintah Kota Banjarmasin untuk pengurusan dokumen administrasi. Sejak diluncurkan, aplikasi ini telah digunakan oleh puluhan ribu warga. Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap aplikasi dan mengevaluasi performa Support Vector Machine dalam klasifikasi ulasan. Metode penelitian yang digunakan adalah Support Vector Machine untuk mengklasifikasikan ulasan pengguna. Hasil analisis menunjukkan bahwa algoritma Support Vector Machine (SVM) dalam mengklasifikasikan data ulasan mendapatkan akurasi tertinggi pada pembagian data latih dan data uji 70:30 sebesar 85,1%, presisi 78,2%, dan recall 97,2%. Dari klasifikasi dan visualisasi, didapatkan kata-kata yang sering muncul pada sentimen positif yaitu “good”, “easy”,  dan “helpful” serta kata-kata yang sering muncul pada sentimen negatif yaitu “difficult”, “take” dan “feature”. Sentimen masyarakat terhadap aplikasi Parak Acil Online menunjukkan bahwa mayoritas ulasan masyarakat terhadap aplikasi ini bersifat positif, dan performa analisis sentimen menggunakan metode Support Vector Machine yang digunakan dalam penelitian ini terbukti efektif dalam mengklasifikasikan sentimen dari ulasan pengguna. Diharapkan penelitian ini dapat membantu pengembang dan pemangku kebijakan dalam meningkatkan kualitas aplikasi Parak Acil Online serta memahami kebutuhan masyarakat.Kata kunci: Analisis Sentimen, Aplikasi Parak Acil Online, Support Vector Machine, Textblob. Abstract - The advancement of information technology has facilitated access to public services, including the Parak Acil Online application developed by the Banjarmasin City Government for managing administrative documents. Since its launch, this application has been used by tens of thousands of residents. This study aims to analyze user sentiment towards the application and evaluate the performance of Support Vector Machine (SVM) in classifying reviews. The research method used is Support Vector Machine (SVM) to classify user reviews. The analysis results show that the Support Vector Machine (SVM) algorithm achieves the highest accuracy in classifying review data with a 70:30 train-test split, reaching 85.1% accuracy, 78.2% precision, and 97.2% recall. Classification and visualization reveal that frequently occurring words in positive sentiment include "good," "easy," "helpful," and "fast," while frequently occurring words in negative sentiment include "difficult," "document," "take," and "feature." The sentiment of the public towards the Parak Acil Online application indicates that the majority of reviews are positive. The performance of sentiment analysis using the Support Vector Machine method employed in this study has proven effective in classifying sentiment from user reviews. It is hoped that this research can assist developers and policymakers in improving the quality of the Parak Acil Online application and understanding community needs.Keywords: parak acil online application, sentiment analysis, support vector machine, textblob.
Analisis Sentimen Pengaruh Digitalisasi Terhadap Penjualan UMKM di Kota Banjarmasin Menggunakan Metode SVM Kartika, Kartika; Cipta, Subhan Panji; Zulfadhilah, Muhammad; Prastya, Septyan Eka
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 5 (2024): Oktober 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i5.8006

Abstract

Abstrak – Digitalisasi telah menjadi faktor penting dalam meningkatkan efisiensi dan jangkauan pasar UMKM. Di Kota Banjarmasin, adopsi digitalisasi berpotensi mempengaruhi sentimen masyarakat terhadap produk-produk UMKM. Penelitian ini menganalisis sentimen untuk memahami dampak digitalisasi terhadap penjualan UMKM di kota ini. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang mempengaruhi sentimen terhadap produk UMKM setelah adopsi digitalisasi di Kota Banjarmasin. Selain itu, penelitian ini juga mengevaluasi efektivitas metode Support Vector Machine (SVM) dalam menganalisis sentimen tersebut. Data dikumpulkan melalui Lembar observasi Google Form yang disebarkan kepada 211 responden, dengan 205 data yang valid digunakan dalam analisis. Data dilakukan proses preprocessing dan pelabelan dengan kamus Lexicon . Metode SVM dengan kernel linear digunakan untuk mengklasifikasikan sentimen, dan model dievaluasi berdasarkan metrik akurasi, precision, recall, dan f1-score. Penelitian menunjukkan bahwa metode SVM dengan kernel linear mencapai akurasi sebesar 85,7% dalam mengklasifikasikan sentimen. Model menunjukkan kinerja yang baik dalam mengenali sentimen positif dengan precision 75% dan recall 86%. Namun, kinerja untuk kelas negatif masih rendah dengan recall 43% dan f1-score 0.55, mengindikasikan tantangan dalam mengidentifikasi sentimen negatif secara akurat.Digitalisasi memiliki pengaruh signifikan terhadap sentimen positif UMKM di Kota Banjarmasin. SVM menunjukkan kinerja yang baik untuk sentimen positif, terdapat tantangan dalam mengenali sentimen negatif yang perlu diatasi. Hasil penelitian ini memberikan wawasan penting untuk strategi digitalisasi yang lebih efektif bagi UMKM di masa mendatang.Kata kunci: Analisis Sentimen, Usaha Mikro Kecil dan Menengah (UMKM), Support Vector Machine (SVM)  Abstract – Digitalization has become an important factor in increasing the efficiency and reach of the MSME market. In Banjarmasin City, the adoption of digitalization has the potential to affect public sentiment towards MSME products. This study analyzes sentiment to understand the impact of digitalization on MSME sales in this city. This study aims to identify factors that influence sentiment towards MSME products after the adoption of digitalization in Banjarmasin City. In addition, this study also evaluates the effectiveness of the Support Vector Machine (SVM) method in analyzing these sentiments. Data were collected through Google Form observation sheets distributed to 211 respondents, with 205 valid data used in the analysis. The data were preprocessed and labeled with the Lexicon dictionary. The SVM method with a linear kernel was used to classify sentiment, and the model was evaluated based on accuracy, precision, recall, and f1-score metrics. The study shows that the SVM method with a linear kernel achieves an accuracy of 85.7% in classifying sentiment. The model performs well in recognizing positive sentiment with a precision of 75% and a recall of 86%. However, the performance for the negative class is still low with a recall of 43% and an f1-score of 0.55, indicating challenges in accurately identifying negative sentiment.Digitalization has a significant influence on positive sentiment of MSMEs in Banjarmasin City. SVM shows good performance for positive sentiment, there are challenges in recognizing negative sentiment that need to be addressed. The results of this study provide important insights for a more effective digitalization strategy for MSMEs in the future.Keywords: Sentiment Analysis, Micro, Small and Medium Enterprises (MSMEs), Support Vector Machine (SVM)
Co-Authors ., Mambang Abdul Kadir Abdul Kadir Abdul latif Abdul Latif Abdul Latif Adryan Ramadhan Ahmad Busairi Ahmad Faisal Ahmad Ghazali Madhony Ahmad Riki Renaldi Ahmad Riki Renaldy Angga Irawan Anggraini Susfarwanti Annisa Annisa Anshori Prasetya, Muhammad Riko Antonia Yenitia Asyiah Asyiah Aulia Rahma Aulia, Hudatul Aurelia Monica Sari Bayu Nugraha Bayu Nugraha Bima Wicaksono Cipta, Subhan Panji Darini Kurniawati Desilestia Dwi Salmarini Dewi Pusparani Sinambela, Dewi Pusparani Dwi Salmarini, Desilestia Eka Prastya, Septyan Ermadiningtyas, Retno Evi Lestari Pratiwi - Politeknik Hasnur Kalimantan Selatan, Evi Lestari Pratiwi Finki Dona Marleny Finki Dona Marleny Fitra Erlina Fitriani Fitriani Gusti Zahratunnisa Hadi, Nofie Haldi Budiman Haniffah Sri Rinjani Heni Pujiastuti Hudatul Aulia Husna Karima Husna Karima Ika Friscilla Imam Riadi Indah Wulandari Irawan, Angga Iwan Yuwindry Jaya Hari Santoso Junius Akbar Karlina Karlina Kartika Kartika Kartika Kartika Kelana, Enisda Libra Lisda Handayani, Lisda Lisyanti, Fatthiya Lufila Fila M Samsul Hasbi M Samsul Hasmi Mambang Maria Ulfah Maulana, Maghfur Maulana, Rahmat Melda Melda Miranda Miranda Misnawati Muhammad Alkaff Muhammad Khairul Akbar Muhammad Nursandi Muhammad Riduan Syafi’i Muhammad Riduansyah Muhammad Satrio Ayuba Muhammad Zaini Bakri Muhammad Ziki Elfirman Munsyi Muthia Elma Mutmainah Mutmainah Nadia Azaria Naparin, Husni Nastiti, Kunti Nita Hestiyana, Nita Noor Pratama, Ramadhani Nopie Hadi Nor Azizah Novalia Widiya Ningrum Novalia Widiya Ningrum Novita Dewi Iswandari Nur Hidayah Nur Lathifah Nur Meilianti Maulida Nur Syifa Nurhaeni Nurhaeni Nurhaeni Nurhaeni NURUL HIDAYAH Pebriadi, Muhammad Syahid Prastya, Septyan Eka Putri Putri Putri Yuliantie Rahmadaniati Hikmah Rahmini Rahmini Ratna Lindawati Rhafiq Abdul Ghani Ricardus Anggi Pramunendar Rifani, Muhammad Rifani Risma Maulida Risma Risma Rismawati Rismawati Rizka Aulia Rizkian Muhammad Fikri Ropikah Ropikah Rudy Ansari Rudy Anshari Sabrila, Trifebi Shina Samita, Mambang Sandro Nesta Pembriano Sari, Rahmadah Septian Eka Prastya Septyan Eka Prasetya Septyan Eka Prastya Septyan Eka Prastya Septyan Eka Prastya Septyan Eka Prastya Setia Budi Shopa Handayani Siti Gadis Hardianti Subhan Panji Cipta Subhan Panji Cipta Subhan Panji Cipta Subhan Panji Cipta Subhan Panji Cipta Sultan Arrasyid Sunardi, Ph.D., Sunardi Susanti Suhartati, Susanti Syapotro, Usman Tasya Salsabila Theresia Kurniati Seran Umi Hanik Fetriyah Usman Syapotro Viviana Viviana Wijaya, Eka Setya Winda Maolinda Wulandari Febriani Wusko, Ikna Urwatul Yudi prayudi Yunandar Yunandar Yuslena Sari, Yuslena Yusri Yusri Zaini Lambri Assyaifi