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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknik Elektro Jurnal Media Wahana Ekonomika PREDIKSI Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sistem dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL MANAJEMEN BISNIS Jurnal Literasiologi Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Tekno Kompak Jurnal Ilmiah Kebidanan Indonesia (Indonesian Midwifery Scientific Journal) Jurnal Teknologi Informasi dan Multimedia Jurnal Abdidas Jurnal SASAK : Desain Visual dan Komunikasi Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian UNDIKMA Journal of Electrical Engineering and Computer (JEECOM) Science in Information Technology Letters Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Silva Samalas: Journal of Forestry and Plant Science Jurnal Elkasista ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal PRIMED:Primary Education Journal atau Jurnal Ke-SD An Journal of Engineering, Technology and Computing (JETCom) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Journal of Management, Economic and Accounting (JMEA) Insand Comtech : Information Science and Computer Technology Journal International Journal of Engineering Continuity Valid Jurnal Pengabdian Journal of Economics and Management Scienties Jurnal Riset Rumpun Ilmu Pendidikan (JURRIPEN) Prosiding Seminar Nasional Unimus UPGRADE: Jurnal Pendidikan Teknologi Informasi ABDIMASTEK Prosiding Seminar Nasional CORISINDO Media Pendidikan Matematika
Hairani Hairani
Universitas Bumigora, Mataram, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Analisis Kinerja Model Random Forest dengan Teknik Manhattan-SMOTE pada Deteksi Fraud Transaksi Kartu Kredit Imbalance Nuzululnisa, Bq Nadila; Hairani, Hairani
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5257

Abstract

Ketidakseimbangan data merupakan salah satu tantangan utama dalam pengembangan sistem deteksi penipuan transaksi kartu kredit. Model pembelajaran mesin cenderung bias terhadap kelas mayoritas, sehingga sulit mendeteksi transaksi fraud yang tergolong sebagai kelas minoritas. Penelitian ini bertujuan untuk meningkatkan kinerja deteksi fraud dengan mengimplementasikan teknik oversampling Manhattan-SMOTE sebagai solusi penyeimbang data sebelum pelatihan model Random Forest. Manhattan-SMOTE merupakan pengembangan dari metode SMOTE konvensional yang menggunakan jarak Manhattan dalam proses interpolasi data sintetis, sehingga lebih stabil dan akurat untuk data berdimensi tinggi. Hasil evaluasi menunjukkan bahwa model Random Forest tanpa oversampling menghasilkan akurasi 81.18% dengan recall yang rendah, yaitu 36.26%. Setelah diterapkan Manhattan-SMOTE, nilai recall meningkat menjadi 67%, F1-score menjadi 0.50, dan ROC AUC melonjak dari 0.75 menjadi 0.96, meskipun akurasi menurun menjadi 70%. Hasil ini menunjukkan bahwa teknik Manhattan-SMOTE secara signifikan meningkatkan kemampuan model dalam mengenali transaksi penipuan tanpa mengorbankan performa klasifikasi secara keseluruhan. Kombinasi Random Forest dan Manhattan-SMOTE terbukti efektif dalam mengatasi ketidakseimbangan kelas dan layak diterapkan dalam sistem deteksi fraud berbasis kecerdasan buatan.
Penerapan SMOTE dan Random Forest dalam Klasifikasi Tren Harga Saham Harian: Studi Kasus Saham PT Telkom Indonesia Tbk (TLKM) Hadi, M Fawazi; Hairani, Hairani; Wijaya, Hartono; Vidiasari, Herlita
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5267

Abstract

Salah satu masalah utama dalam sistem klasifikasi tren harga saham adalah ketidakseimbangan kelas dalam data historis saham.  Studi ini melihat bagaimana menggunakan teknik over-sampling synthetic minority (SMOTE) dan algoritma Random Forest untuk mengklasifikasikan tren harga saham harian PT Telkom Indonesia Tbk (TLKM).  Data diukur dengan lima metrik utama: volume, open, high, low, dan close. Semua ini diperoleh dari Kaggle.  Hasil uji menunjukkan bahwa kombinasi SMOTE dan Random Forest mampu meningkatkan distribusi data dan memberikan kinerja klasifikasi yang cukup baik, dengan akurasi sebesar 51% dan skor macro F1-sebesar 0.51.  Temuan ini menunjukkan bahwa, meskipun data berubah, model mengenali kedua arah tren dengan cukup andal.  Penelitian ini membangun fondasi untuk sistem yang mendukung keputusan investasi berbasis data.
Perbandingan Kinerja Model ARIMA dan Jaringan Saraf Tiruan (ANN) dalam Memprediksi Jumlah Mahasiswa Baru Zuhri, Saifuddin; Hairani, Hairani
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5450

Abstract

Prediksi jumlah mahasiswa baru merupakan aspek krusial dalam perencanaan strategis perguruan tinggi, yang mempengaruhi alokasi sumber daya, perencanaan infrastruktur, dan pengembangan program akademik. Penelitian ini mengkaji penerapan dua metode prediksi time series yang berbeda: AutoRegressive Integrated Moving Average (ARIMA) dan Artificial Neural Network (ANN) untuk memprediksi jumlah mahasiswa baru. Menggunakan data historis penerimaan mahasiswa selama 6 tahun (2019-2024), penelitian ini membandingkan akurasi prediksi kedua metode dalam konteks perencanaan perguruan tinggi. Hasil penelitian menunjukkan bahwa metode ANN memberikan akurasi prediksi yang lebih tinggi dengan nilai MAPE 11.65% dibandingkan ARIMA dengan MAPE 17.9%. Evaluasi performa model dilakukan menggunakan metrik evaluasi MSE (Mean Absolute Error), RMSE (Root Mean Square Error), dan MAE (Mean Absolute Error). Model Artificial Neural Network menunjukkan performa yang lebih baik dalam memprediksi jumlah mahasiswa baru dengan tingkat akurasi yang dapat diterima untuk keperluan perencanaan institusi. Namun, ARIMA memberikan interpretabilitas yang lebih baik dalam memahami pola seasonality dan trend jangka panjang.
Analisis Kemampuan Pemecahan Masalah Matematika Pada Materi Pola Bilangan Ditinjau Dari Gaya Kognitif Konseptual Tempo Hairani, Hairani; Prayitno, Sudi; Turmuzi, Muhammad; Soepriyanto, Harry
Media Pendidikan Matematika Vol. 11 No. 2 (2023)
Publisher : Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/mpm.v11i2.9885

Abstract

The purpose of this study was to describe the ability of mathematical problem solving on number pattern subjects in terms of the conceptual tempo and cognitive style of class VIII students of SMP Negeri 11 Mataram. The type of research is descriptive-qualitative. The instruments used are the Matching Familiar Figure Test, the math problem-solving ability test, and interview guidelines. Data collection methods include cognitive style tests, math problem-solving ability tests, interviews, and documentation. Data analysis techniques used are data reduction, data presentation, and conclusion drawing. Indicators of Krulik and Rudnick problem-solving stages are reading and thinking, exploring and planning, selecting a strategy, finding answers, reflecting, and developing. The results showed that students with fast, accurate, and reflective cognitive styles were able to fulfill five indicators of the Krulik and Rudnick problem-solving stages. Reflective students allocate time appropriately and thoroughly in solving problems compared to fast-accurate students, so that the answers given by reflective students are more accurate than those given by fast-accurate students. Students with an impulsive cognitive style are able to run four indicators, while slow inaccurate students are able to run three indicators of Krulik and Rudnick. Slowly inaccurate students take a long time and are less thorough than impulsive students, so the answers given by slow inaccurate students are less accurate than those given by impulsive students.
MACHINE LEARNING OPTIMIZATION USING CORRELATION FEAUTER SELECTION AND SMOTE-ENN FOR EDUCATOR SENTIMENT: Indonesia Jupriadi, Jupriadi; Anggarawan, Anthony; Hairani, Hairani
Journal of Engineering, Technology and Computing (JETCom) Vol. 4 No. 3 (2025): Journal of Engineering, Technology and Computing (JETCom)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/jetcom.v4i3.314

Abstract

Abstrak : Tenaga pendidik memiliki peran strategis dalam kemajuan pendidikan nasional, sehingga pemahaman terhadap sentimen mereka penting dalam meningkatkan kesejahteraan dan kualitas layanan pendidikan. Dalam pengolahan data sentimen, seringkali ditemui tantangan seperti ketidakseimbangan data antara sentimen mayoritas dan minoritas, serta tingginya jumlah fitur yang menyebabkan dimensionalitas data menjadi besar.Tujuan penelitian ini adalah menganalisis sentimen attitude tenaga pendidik di Indonesia menggunakan metode klasifikasi Machine Learning, dengan pendekatan seleksi fitur berbasis korelasi dan penyeimbangan data melalui Synthetic Minority Over-sampling Technique–Edited Nearest Neighbours (SMOTE ENN). Model klasifikasi dibangun menggunakan algoritma Naïve Bayes dan Support Vector Machine (SVM).Hasil penelitian menunjukkan bahwa SVM memberikan akurasi lebih tinggi dibandingkan Naïve Bayes, baik pada data asli maupun setelah penerapan SMOTE ENN. Akurasi Naïve Bayes meningkat dari 61% menjadi 89% setelah seleksi fitur berbasis korelasi, sedangkan SVM meningkat dari 69% menjadi 97%. Penelitian ini membuktikan bahwa kombinasi SVM, SMOTE ENN, dan seleksi fitur berbasis korelasi mampu meningkatkan akurasi klasifikasi sentimen tenaga pendidik di Indonesia secara signifikan. Kata kunci : analisis sentimen, tenaga pendidik, SVM, SMOTE, seleksi fitur Abstract : Educators play a strategic role in the progress of national education, so understanding their sentiments is important for improving their well-being and the quality of educational services. In sentiment data processing, challenges are often encountered, such as data imbalance between majority and minority sentiments, and a high number of features leading to high data dimensionality. The purpose of this study is to analyze the sentiment of Indonesian educators' attitudes using Machine Learning classification methods, with a correlation-based feature selection approach and data balancing through Synthetic Minority Over-sampling Technique–Edited Nearest Neighbours (SMOTE ENN). Classification models were built using the Naïve Bayes and Support Vector Machine (SVM) algorithms. The research results show that SVM provides higher accuracy compared to Naïve Bayes, both on the original data and after applying SMOTE ENN. Naïve Bayes' accuracy increased from 61% to 89% after correlation-based feature selection, while SVM's increased from 69% to 97%. This study proves that the combination of SVM, SMOTE ENN, and correlation-based feature selection can significantly improve the accuracy of sentiment classification for Indonesian educators Keywords: Sentiment analysis, Educators, SMOTE, Feature selection
Strategi Pencegahan Stunting melalui Edukasi Gizi dan Suplementasi Tablet Tambah Darah pada Remaja Desa Mandala Haji Isviyanti, Isviyanti; Triandini, I Gusti Agung Ayu Hari; Gumangsari, Ni Made Gita; Hidayati, Diana; Gustiya, Sherly Dwi; Hairani, Hairani; Kandisa, Amelia; Mayasari, Astri
Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat Vol. 10 No. 4 (2025): December
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/0cy98828

Abstract

Stunting masih menjadi permasalahan kesehatan masyarakat di Indonesia yang berimplikasi pada kualitas generasi mendatang. Salah satu faktor penyebabnya adalah anemia pada remaja putri yang dapat berlanjut hingga masa kehamilan. Program pengabdian masyarakat ini bertujuan meningkatkan pengetahuan gizi remaja serta kepatuhan konsumsi tablet tambah darah (TTD) sebagai upaya pencegahan stunting. Kegiatan dilaksanakan di Desa Mandala Haji pada 162 remaja melalui diskusi interaktif, games, diskusi kelompok, pembagian leaflet, dan pendampingan konsumsi TTD. Hasil pengukuran keberhasilan kegiatan diukur dengan kuesioner pre test dan post test yang kemudian dianalisis dengan uji t yang menunjukkan peningkatan pengetahuan gizi sebesar 45% dan kepatuhan konsumsi TTD sebesar 75%. Program ini efektif meningkatkan kesadaran gizi remaja dan mendukung upaya pencegahan stunting berbasis teman sebaya. Upaya ini memberikan gambaran bahwa kader remaja efektif dalam promosi kesehatan pada remaja. Stunting Prevention Strategy through Nutrition Education and Iron Supplementation for Adolescents Mandala Haji Village Abstract Stunting remains a public health problem in Indonesia, impacting the quality of future generations. One contributing factor is anemia in adolescent girls, which can persist into pregnancy. This community service program aims to improve adolescent nutritional knowledge and adherence to iron supplementation (IBT) consumption as a stunting prevention measure. The program was conducted in Mandala Haji Village with 162 adolescents through interactive discussions, games, group discussions, leaflet distribution, and iron supplementation support. The success of the program was measured using pre- and post-test questionnaires, which were then analyzed using a t-test, showing a 45% increase in nutritional knowledge and a 75% increase in iron supplementation compliance. This program effectively increases adolescent nutritional awareness and supports peer-based stunting prevention efforts. These efforts demonstrate the effectiveness of youth cadres in promoting health among adolescents
Combination Forward Chaining and Certainty Factor Methods for Selecting the Best Herbs to Support Independent Health Muhamad Azwar; Sri Winarni Sofya; Riwayati Malika; Hairani Hairani; Juvinal Ximenes Guterres
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4485

Abstract

The use of herbal medicine as an alternative treatment is increasingly popular due to its natural benefits and cultural significance. However, a lack of public knowledge about the effectiveness, appropriate dosages, and processing methods of herbal remedies poses a significant barrier to their proper utilization. This knowledge gap often leads to suboptimal or even unsafe usage of herbal medicines. To address this issue, this study proposes an application-based system combining the Forward Chaining and Certainty Factor methods to provide personalized recommendations for the best herbal remedies supporting self-health management. The research aims to enhance accessibility to reliable information on herbal treatments while ensuring accurate and user-specific recommendations. By utilizing the ForwardChaining and Certainty Factor method, this system identifies suitable herbal plants based on the type of disease, processing techniques, recommended dosages, and duration of treatment. Meanwhile, the Certainty Factor method calculates the level of certainty for each recommendation provided. The study’s results showed a validation rate of 90%, indicating that the combination of these two methods effectively bridges the gap between traditional herbal knowledge and modern health needs. This study concludes that the system offers a practical tool for individuals to select and use herbal treatments safely and effectively, promoting better health outcomes.
Detection of Rice Diseases Using Leaf Images with Visual Geometric Group (VGG-19) Architecture and Different Optimizers Lalu Zazuli Azhar Mardedi; Fahry Fahry; Miftahul Madani; Hairani Hairani
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 25 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v25i1.5286

Abstract

Rice is a major food commodity in Indonesia that plays a vital role in maintaining national food security. However, rice productivity often declines due to pest and disease attacks, especially when the disease is not detected early. Currently, the process of identifying rice diseases is generally still carried out manually by farmers or experts through direct observation, which is subjective, time-consuming, and prone to identification errors. To overcome these limitations, a technology-based solution is needed that is able to detect rice diseases automatically, quickly, and accurately. This study aims to develop a rice disease detection system based on leaf images using a deep learning approach with the Visual Geometric Group (VGG-19) architecture. The research method used is experimental by comparing the performance of the VGG-19 architecture using three different types of optimizers, namely Adaptive Moment Estimation (ADAM), Root Mean Square Propagation (RMSProp), and Stochastic Gradient Descent (SGD), to obtain the best accuracy in rice disease classification. The findings show that the combination of VGG-19 with the ADAM optimizer produces the highest accuracy of 96.45%, followed by RMSProp at 95.96% and SGD at 87.08%. These findings indicate that the selection of optimizers plays an important role in improving the performance of deep learning models, especially in detecting rice diseases based on leaf images.
PERAN AKUNTANSI DALAM MENGELOLA RISIKO VALUTA ASING: TANTANGAN DAN SOLUSI DI PASAR GLOBAL Ihsan, Khairil; Andini, Nisha; Hairani, Hairani
Journal of Management, Economic and Accounting (JMEA) Vol. 4 No. 2 (2025): Volume 4 Issue 2 May 2025
Publisher : CV. Pusdikra Mitra Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51178/(jmea).v4i2.3109

Abstract

In an era of intensifying globalization, companies worldwide operate in an increasingly complex and dynamic business environment. Tighter global economic integration has encouraged companies to conduct cross-border transactions, thus involving various foreign currencies. This is inevitable considering the increasingly complex global supply chain, increasing business competition, and the need to expand markets. This type of research is a qualitative descriptive study that focuses on available sources of information about the power of data analysis. These sources come from various books and publications that discuss existing theories clearly and comprehensively to create text in the form of articles. Risk management is an essential strategic instrument in identifying, measuring, and mitigating uncertainty to achieve organizational goals and increase stakeholder trust. In a global market ecosystem influenced by the flow of globalization and regulatory complexity, understanding foreign exchange is very crucial because of its function as an international payment instrument and investment instrument that maintains economic stability. The low public compliance is triggered by various multidimensional factors, ranging from minimal awareness and knowledge of taxation, fluctuations in economic income, to the absence of strict legal sanctions for violators. As a solution, the village authorities are taking an approach through optimizing public services and persuasive outreach to provide education regarding the rights and obligations of citizens, which ultimately aims to restore the stability of regional tax revenues.
PEMIKIRAN EKONOMI ISLAM IBN TAIMIYAH Hairani, Hairani; Andini, Nisha
Journal of Management, Economic and Accounting (JMEA) Vol. 4 No. 3 (2025): Volume 4 Issue 3 August 2025
Publisher : CV. Pusdikra Mitra Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51178/(jmea).v4i3.3134

Abstract

Ibn Taimiyah provides an answer for the State in terms of the market mechanism, which is to become a post for deep quality improvement to make its people aware of the importance of moral standards and moral quality as a rule of progress and can make it happen in financial life. An Ibn Taymiyyah is of the view that looking at the market mechanism is actually not limited to monetary issues, more than that it includes several parts of state and religious life.
Co-Authors Abdillah, Mokhammad Nurkholis Abdul Hadi Abdurraghib Segaf Suweleh Abdurraghib Segaf Suweleh Abu Tholib Adam, M. Awaludin Adawiyah, Rabi'atul Adrianto, Muhammad Subhan Dwi Afrig Aminuddin Ahmad Ahmad Ahmad Fathoni Ahmad Zuli Amrullah Aleeka Jasmine Amelia, Bengi Amin, Farda Milanda Andani, Nazwa Putri Andi Sofyan Anas Andi, Moh syaiful Andini, Nisha Anggarawan, Anthony Anthony Anggrawan Arfa, Muhammad Arifah Ulayya Ashadi, Diki Astuti, Ni Luh Budi Ayu Dasriani, Ni Gusti Bukran Bukran Candra, M. Ade Christine Eirene Christopher Michael Lauw Christopher Michael Lauw Dadang Priyanto Dedi Aprianto Dedy Febry Rachman Dedy Febry Rahman Dekki Widiatmoko Deny Jollyta Diah Ekawati Dian Syafitri Didik Dwi Prasetya Diki Ashadi Dirgantara, Bhintang Djoko Rahardjo Donny Kurniawan Dyah Susilowati Dyah Susilowaty ED. Yunisa Mega Pasha ED. Yunisa Mega Pasha Efendi, Muhamad Masjun Eka Setiawan, Rian Putra Ezra Azzahra Fahry, Fahry Fathorazi Nur Fajri Fatimatuzzahra Fatimatuzzahra Febriana, Annisa Dwi Fikrulia, Hidayah Jihan Firdaus, Adhitya Fitra Rizki Ramdhani Galih Hendro Martono Gede Yogi Pratama Gibran Satya Nugraha Gibran Satya Nugraha Guntara, Muhammad Gusti Ayu Diah Gita Kartika Santi, I Gustiya, Sherly Dwi Guterres, Juvinal Ximenes Hadi, M Fawazi Hammad, Rifqi Hartono Wijaya Haryono Haryono Hasanah, Maulida Hasbullah Hasbullah Herawati, Baiq Candra Heru Kurnianto Tjahjono Hery Widijanto Hidayati, Diana Huda, Dias Nabila Husain Husain I Gusti Agung Ayu Hari Triandini I Nyoman Switrayana Ida Putu Andika Ifnaldi Ifnaldi Iis Sopiah Suryani Ilham Saifuddin Indah Puji Lestari Indradewa, Rhian Irawan, Dudi Isviyanti, Isviyanti Janhasmadja, Mengas Jauhari, M. Thonthowi Jupriadi, Jupriadi Juvinal Ximenes Guterres Juvinal Ximenes Guterres Juvinal Ximenes Guterres Juvinal Ximenes Guterres Kandisa, Amelia Kasiyanto Kasiyanto Kasiyanto Kasiyanto, Kasiyanto Khairan marzuki Khairil Ihsan Khasnur Hidjah Khurniawan Eko Saputro Kurniadin Abd Latif Kurniawan Kurniawan Lalu Ganda Rady Putra Lalu Zazuli Azhar Mardedi Lestari, Jumiati Indah Lilik Nurhayati lnnuddin, Muhammad M. Ade Candra M. Rasyid Ridho M. Rizki M. Thoriq Panca Mukti M.Khaerul Ihsan M.Khaerul Ihsan Maariful Huda, Muhammad Malika, Riwayati Mamay Maulana Mamay Maulana Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Mayadi Mayadi Mayadi Mayadi Mayadi, Mayadi Mayasari, Astri Melati Rosanensi Mia Nisrina Anbar Fatin Michael Lauw, Christopher Miftahul Madani Mubarak, Ahmad Nazhif Mudawil Qulub Muhamad Azwar Muhamad Azwar, Muhamad Muhamad Reza Pahlevi Muhamad Reza Pahlevi Muhamad Wisnu Alfiansyah Muhammad Arfa Muhammad Fahmi Muhammad Ghifari, Muhammad Muhammad Innuddin Muhammad Maariful Huda Muhammad Ridho Akbar Muhammad Ridho Hansyah muhammad Syahbudi, muhammad Muhammad Tahir Muhammad Turmuzi Muhammad Zulfikri Muhammad Zulfikri Muhammad Zulkarnaen Haris Mujahid Mujahid Neny Sulistianingsih Ni Made Gita Gumangsari Nindya Alifia Khumaira Nisa, Rahayu Noor Akhmad Setiawan Novitasari Tsamrotul Fuadah Nur Intan Hayati Nur Intan Hayati Nurhayati, Lilik Nurul Azmi Nurvianti, Nurvianti Nuzululnisa, Bq Nadila Pahrul Irfan Pratama, Gede Yogi Putu Tisna Putra Qososyi, Sayidina Ahmadal Rahayun Amrullah Husaini Rahman, Mochamad Farhan Caesar Rahmawati, Lela Ramadhanti Ramadhanti Ramadhanti, Ramadhanti Rangga Wijaya Regandara, Ellysia Putri Rhomdani, Rohmad Wahid Rian Putra Eka Setiawan Rifqi Hammad Rio Riswanto Simanjuntak Riosatria, Riosatria Riwayati Malika Rizki Wahyudi Robo, Salahudin rokhim utomo Rosyda, Miftahurrahma RR. Ella Evrita Hestiandari Saifuddin Zuhri Saifuddin, Ilham Saifudin, Ilham Samsul Hadi Santoso, Heroe Shudiq, Wali Ja'far Soepriyanto, Harry Sofiansyah Fadli Soni Muhsinin Sri Farida Utami Sri Winarni Sofya Sri Winarni Sofya Sudi Prayitno Sukron, Moh Sutarman Sutarman Syahrir, Moch. tadianta m., Winardi aries Teguh Bharata Adji Tri Nur Jayanti Tri Nur Jayanti Triwijoyo, Bambang Krismono Triyanna Widiyaningtyas Umi Hanifah Vidiasari, Herlita Vidiasari, Viviana Herlita Vina Vitniawati Wahyuningsih, Rr. Sri Handari Wangiyana, I Gde Adi Suryawan Wening Asih Sutrisno Wening Asih Sutrisno Widhya Aligita Widhya Aligita Widiatmoko, Dekki Wira Hendri Wiyanto, Suko Ximenes Guterres, Juvinal Yuri Ariyanto Yuri Ariyanto Zilullah Nazir Hadi