Article Per Year (5 Year)
p-Index From 2021 - 2026
14.744
P-Index
This Author published in this journals
All Journal ARABIYAT Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Studi Agama dan Masyarakat Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Madaniyah: Terciptanya Insan Akademis Berkualitas Dan Berakhlak Mulia JIKO (Jurnal Informatika dan Komputer) qolamuna : Jurnal studi islam Jurnal SOLMA BAREKENG: Jurnal Ilmu Matematika dan Terapan JURNAL ILMIAH INFORMATIKA Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT Jambura Journal of Food Technology Jurnal Tekno Kompak Jurnal Edukasi (Ekonomi, Pendidikan dan Akuntansi) JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Biogenerasi JISA (Jurnal Informatika dan Sains) BERNAS: Jurnal Pengabdian Kepada Masyarakat Al-Fusha : Arabic Language Education Journal Jurnal Pendidikan dan Teknologi Indonesia Mosharafa: Jurnal Pendidikan Matematika Tanwir Arabiyyah: Arabic as Foreign Language Journal Jurnal Dinamika Informatika (JDI) Jurnal EBONI Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) PENA ABDIMAS : Jurnal Pengabdian Masyarakat Makara Journal of Technology Jurnal Sistem Informasi dan Teknologi (SINTEK) Indonesian Journal of Fundamental Sciences Journal of Tourism Education Prosiding Seminar Nasional Manajemen dan Ekonomi JURSIMA Iqtida: Journal of Da'wah and Communication Huma: Jurnal Sosiologi Jurnal Biologi Babasal Al-Zayn: Jurnal Ilmu Sosial & Hukum Jurnal Sistem Informasi dan Manajemen Maddana: Jurnal Pengabdian Kepada Masyarakat Sirajuddin : Jurnal Penelitian dan Kajian Pendidikan Islam Prosiding Seminar Nasional Unimus Jurnal Kemitraan Masyarakat Informasi interaktif : jurnal informatika dan teknologi informasi Jurnal Riset Multidisiplin Edukasi Regulate: Jurnal Ilmu Pendidikan, Hukum dan Bisnis Jurnal Cendekia Ilmiah PESHUM Jurnal Geosaintek Sintek Kuwera Sirajuddin: Jurnal Penelitian dan Kajian Pendidikan Islam Bianglala Informatika
Ahmad Faqih
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture 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 Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 119 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 119 Documents
Search

 4   5   6   7   8 
Strategi Pemberdayaan UMKM Logam oleh Astra melalui Yayasan Dharma Bakti Astra Tarikolot Kabupaten Bogor Ilma’nun, M. Lulu; Faqih, Ahmad; Riyadi, Agus
Jurnal SOLMA Vol. 13 No. 3 (2024)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v13i3.16894

Abstract

Background: UMKM diIndonesia menyerap tenaga kerja sebesar 96,9% dari total tenaga kerja dan proporsi nasional 60,5% UMKM berkontribusi signifakan terhadap PDB. Maka, pemberdayaan UMKM logam Tarikolot adalah bentuk kontribusi Astra melalui Yayasan Dharma Bakti Astra terhadap pertumbuhan ekonomi di Indonesia. Tujuan dari kegiatan pemberdayaan UMKM yaitu untuk mendukung pengembangan UMKM melalui pengembangan kapasitas, akses pembiayaan, dan pemasaran. Selain itu, tujuan kegiatan ini untuk menjadikan UMKM mandiri dan naik kelas serta menciptakan lapangan pekerjaan bagi masyarakat sekitar UMKM. Metode: metode yang dilakukan Yayasan Dharma Bakti Astra dalam memberdayakan UMKM logam yaitu survei lapangan, memberikan pelatihan, pendampingan, fasilitasi pemasaran dan pembiayaan kepada UMKM logam agar pelaku UMKM diberikan teori yang bisa diimplementasikan kepada usahanya. Hasil: melalui kegiatan pelatihan, pendampingan, fasilitasi pemasaran dan pembiayaan, para pelaku UMKM mendapatkan pengembangan kapasitas, akses pembiayaan dan juga pemasaran yang dikenal di pasar lebih besar. Langkah tersebut strategis dijalankan karena pelaku UMKM dibekali ilmu teori dan praktik untuk meningkatkan produktivitas usahanya. Kemudian, strategi program tersebut mempunyai dampak berkembangnya UMKM logam menjadi mandiri dan naik kelas, menciptakan lapangan pekerjaan yang dapat menaikkan taraf hidup masyarakat terutama pelaku UMKM. Kesimpulan: Melalui program pemberdayaan UMKM yang dilakukan YDBA adalah upaya yang kompherensif untuk meningkatkan kesejahteraan pelaku UMKM dan masyarakat sekitar UMKM itu berada. Yang tentunya dilakukan dengan penedakatan yang holistik dan terintegrasi.
YOUTH AGAINST RELIGIOUS RADICALISM: AN INTRARELIGIOUS APPROACH IN KOMUNITAS SANTRI BATANG IN KABUPATEN BATANG, JAWA TENGAH Faqih, Ahmad; Umar, Achmad Jauhari
Jurnal Studi Agama dan Masyarakat Vol 18 No 2 (2022): JURNAL STUDI AGAMA DAN MASYARAKAT
Publisher : IAIN Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23971/jsam.v18i2.4031

Abstract

Youth is a part of the structure of society that is vulnerable to being exposed to radicalism. According to a report from the Setara Institute 2011-2012, cases of intolerance that occur in Indonesia are often committed by youth, especially high school age teenagers. In 2017, there has been a spread of religious radicalism doctrine in Batang carried out by several religious leaders towards high school youth age. In response to that, a group of youths in Batang formed a youth community aimed to counteract the spread of radicalism in Batang, Komunitas Santri Batang (KSB). This study wants to see the extent to which the role of youth represented by the KSB against religious radicalism by campaigning for the idea of 'religious moderation'. This study formulates two problems related to the role of youth in campaigning for religious moderation, (1) What is the strategy of the KSB in promoting religious moderation idea? (2) how effective are the programs organized by the KSB related to the prevention of radicalism among youth groups? To answer these questions, the researcher will interview several members of the KSB and participants of the KSB programs. The results of this study indicate that there is synergy between the KSB youth and several agencies in cultivating moderation and diversity dialogue among the community. This can be seen through the KSB community strategy in countering religious radicalism using an inclusive approach and social engagement dialogue. Also, KSB pays attention to strengthening intra-religious relations by involving various youths from different religious mass organization backgrounds in several activities. This strategy is considered effective to counter religious radicalism which often attacks young people.
Komparasi Metode Apriori Dan FP-Growth Untuk Meningkatkan Pola Penjualan ayu hardani, anita; Faqih, Ahmad; Permana , Sandy Eka
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 10 No 1 (2025): JII Volume 10, Number 1, Januari 2025
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

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

Abstract

Dalam era persaingan bisnis yang semakin ketat, strategi penjualan yang efektif menjadi sangat penting, terutama di sektor ritel. Data transaksi penjualan sering kali hanya disimpan sebagai arsip tanpa dimanfaatkan untuk mendukung keputusan strategis. Penelitian ini bertujuan membandingkan dua algoritma data mining populer, Apriori dan FP-Growth, dalam menganalisis pola penjualan sandal merek Peter. Data transaksi penjualan yang dikumpulkan selama lima bulan diproses menggunakan perangkat lunak RapidMiner untuk menemukan pola pembelian konsumen. Hasil analisis menunjukkan bahwa algoritma Apriori lebih sederhana dalam penerapannya namun membutuhkan waktu komputasi yang lebih lama. Di sisi lain, algoritma FP-Growth lebih cepat dan efisien, terutama untuk dataset besar, meskipun membutuhkan struktur data yang lebih kompleks. Studi ini memberikan panduan praktis bagi perusahaan untuk memilih algoritma yang sesuai dengan kebutuhan analisis data mereka, serta memberikan wawasan tentang pola pembelian konsumen yang dapat dimanfaatkan untuk meningkatkan penjualan.
Biaya Ujroh Atas Transaksi Jual Beli Saham Syariah Ahmad Faqih
Madaniyah Vol 14 No 2 (2024): Edisi Juli 2024
Publisher : Sekolah Tinggi Ilmu Tarbiyah (STIT) Pemalang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58410/madaniyah.v14i2.863

Abstract

Mekanisme perdagangan saham di pasar modal syariah saat ini sudah menggunakan sistem online yang mana dalam melakukan transaksi jual beli saham syariah tidak secara langsung saling bertemu. Para pihak yang melakukan transaksi hanya memutuskan apakah dia akan menjual atau membeli suatu saham. Melalui perantara perusahaan pedagang efek yang sudah menjadi anggota bursa. Transaksi tersebut terjadi dan dilakukan penyelesaian transaksinya. Atas jasa perusahaan pedagang efek sebagai pialang saham syariah, setiap transaksi yang terjadi dilantai bursa ada beberapa biaya yang harus dibayarkan oleh investor. Salah satunya adalah fee (ujrah) atas jasa keperantaraannya. Nominal fee dari masing-masing transaksi berbeda, yaitu 0,15% untuk setiap transaksi beli, dan 0,25% untuk setiap kali transaksi jual. Jenis penelitian yang digunakan pada penulisan ini adalah jenis penelitian kualitatif melalui studi kepustakaan (Library Research), data diperoleh dari berbagai sumber primer dan sekunder (artikel, buku, jurnal, sumber lainnya) dengan metode yang bersifat deskriptif. Berdasarkan hasil penelitian dapat disimpulkan bahwa transaksi jual beli saham secara online di bursa efek Indonesia tidak mempertemukan secara langsung antara investor beli dan investor jual. Masing-masing pihak memberikan kuasa (wakalah) kepada perusahaan pedagang efek untuk melakukan transaksi sahamnya dilantai bursa atas order (instruksi) investor yang menjadi nasabahnya yang disampaikan melalui aplikasi syariah online trading system. Kata kunci: ujrah, jual beli, saham syariah.
House Price Prediction Analysis Using a Comparison of Machine Learning Algorithms in the Jabodetabek Area Ningsih, Indah Ratna; Faqih, Ahmad; Rinaldi, Ade Rizki
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.733

Abstract

Jabodetabek, as the largest metropolitan area in Indonesia, has complex property price dynamics, making it difficult for developers and buyers to determine house prices. This study aims to analyze and compare the performance of the Multiple Linear Regression and Random Forest Regression algorithms in predicting house prices in the region. The data was obtained through scraping techniques from the rumah123.com website in October 2024, covering 999 data points with variables such as price, location, building area, land area, number of bedrooms, bathrooms, and garages. A comparative approach with cross-validation was applied to evaluate the performance of both algorithms using the metrics MAE, MSE, RMSE, MAPE, and R². The research results show that Random Forest Regression using GridsearchCV has better predictive performance, with an MAE value of Rp.645,764,815, MAPE of 28.12%, and R² of 0.864. The main factors influencing house prices in Jabodetabek include building size, land size, number of bedrooms, bathrooms, garages, and location. This finding emphasizes the superiority of Random Forest Regression in capturing complex data patterns and the significant role of these variables in determining house prices.
Accuracy in Sentiment Analysis of the by.U Application Using Naïve Bayes and SMOTE Techniques Athhar Hafizha Luthfi; Ahmad Faqih; Gifthera Dwilestari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.737

Abstract

Imbalanced data is a significant challenge in sentiment analysis, as it often impacts the performance of machine learning models. This study applies the Naïve Bayes algorithm, enhanced with the Synthetic Minority Oversampling Technique (SMOTE), to address class imbalance in user reviews of the by.U application. Using the Knowledge Discovery in Databases (KDD) framework, the research involves data selection, preprocessing (text cleaning, normalization, stemming), transformation using TF-IDF, and train-test data splitting. SMOTE is applied to the training data to improve minority class representation, while Naïve Bayes performs sentiment classification. Model evaluation using cross-validation demonstrates that SMOTE increases accuracy from 84.42% to 85.83%. These results underscore the effectiveness of integrating SMOTE with Naïve Bayes in addressing imbalanced data, offering meaningful insights into user sentiment and aiding the development of improved features for the by.U application.
Using the Apriori Algorithm to Identify Purchase Patterns for Enhancing Sales in Personal Shopper Services Fadilah, Euis; Ahmad Faqih; Sandy Eka Permana
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.741

Abstract

This research aims to explore the application of the Apriori algorithm in identifying purchasing patterns in the drop-off service industry in order to increase sales. Drop-off services often face challenges in designing effective marketing strategies due to limited understanding of customer purchasing behavior. In this study, the Apriori algorithm is applied to uncover recurring purchase patterns among customers, which are then used to develop more efficient marketing strategies. Customer transaction data is analyzed to find associations that reflect their purchasing preferences. The results show that the application of the Apriori algorithm successfully identifies patterns that can improve marketing strategies and, ultimately, increase sales. This research emphasizes the importance of applying data mining techniques to improve the performance of delivery services.
The Effect of SMOTE Application on Support Vector Machine Performance in Sentiment Classification on Imbalanced Datasets Andriyani, Dini; Ahmad Faqih; Sandy Eka Permana
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.742

Abstract

This research explores the effect of applying Synthetic Minority Oversampling Technique (SMOTE) on the performance of Support Vector Machine (SVM) algorithm in sentiment classification on imbalanced datasets. Public review data was collected from social media platform X (formerly Twitter) regarding the Free Lunch Program, with a total of 2,368 reviews automatically labeled using the BERT model into three categories: positive, negative, and neutral. Sentiment imbalance in the dataset was addressed by applying SMOTE to generate synthetic data on minority classes. The research method follows the stages of Knowledge Discovery in Databases (KDD), including data selection, preprocessing, labeling, transformation using TF-IDF, SVM model training, and performance evaluation. The experimental results show that the application of SMOTE successfully improves the accuracy of the SVM model by 12.48%, from 71.41% to 83.89%. Other evaluation metrics, such as precision, recall, and F1-score, also showed significant improvement from 0.69, 0.71, and 0.68 to 0.84, respectively. These findings confirm that SMOTE is effective in overcoming data imbalance, resulting in a more accurate and reliable sentiment classification model. This research contributes to the application of sentiment analysis in data-driven public policy evaluation.
Improving Sentiment Analysis Performance of Tokopedia Reviews Using Principal Component Analysis and Naïve Bayes Algorithm Lestari, Anjar Ayuning; Ahmad Faqih; Gifthera Dwilestari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.743

Abstract

Tokopedia one of Indonesia's largest e-commerce platforms, offers a wide range of products with diverse customer reviews. These reviews reflect consumer opinions and provide valuable insights for service improvement and marketing strategies. Sentiment analysis is crucial for understanding customer perceptions, but processing large-scale, high-dimensional text data remains a challenge, impacting model efficiency and accuracy. This research uses Principal Component Analysis (PCA) to reduce data dimensionality without losing important information for sentiment classification. The study begins by collecting Tokopedia product reviews and preprocessing the text, including data cleaning, tokenization, stopword removal, and stemming. The reviews are then converted into numerical vectors using the Term Frequency-Inverse Document Frequency (TF-IDF) method. A Gaussian Naïve Bayes model is employed to classify sentiment into three categories: positive, neutral, and negative. The results demonstrate that PCA significantly improves model accuracy from 63.13% to 70.47%, with gains in precision (71.85%), recall (70.47%), and F1-score (71.06%). This research contributes to enhancing sentiment analysis techniques using PCA for Tokopedia reviews and offers a valuable approach that can be applied to other e-commerce platforms.
The Impact of Principal Component Analysis Dimensionality Reduction on Sentiment Classification Performance Using Support Vector Machine Fajria, Azzahra Moudy; Faqih, Ahmad; Dwilestari, Gifthera
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.744

Abstract

This study investigates the application of Principal Component Analysis (PCA) to enhance sentiment classification performance using the Support Vector Machine (SVM) algorithm. User reviews of the ChatGPT application from the Play Store were collected, preprocessed, and analyzed to identify the sentiment within the text (positive, negative, or neutral). The research follows the Knowledge Discovery in Databases (KDD) framework, starting with data selection, preprocessing, transformation, and applying PCA for dimensionality reduction. PCA was used to reduce the complexity of the high-dimensional text data, improving SVM's efficiency in sentiment classification. Evaluation results show that applying PCA led to an improvement in model performance, with accuracy increasing from 72.65% to 73.20%, precision from 71.58% to 72.24%, recall from 71.77% to 72.66%, and F1-score from 71.56% to 72.32%. Although the improvements were modest, the findings demonstrate that PCA effectively simplifies complex datasets and enhances SVM performance in sentiment classification, offering benefits in processing high-dimensional text data.
Co-Authors -, Kaslani Abdullah Baharun abdur rohman Abi Fajar Ahmad Fauzi Achmad Supandi Ade Rizki Rinaldi Ade Rizki Rinaldy Adella, Luthfiyyah Iffah Adellia Putriani Adjie Setyadj, Mochammad Adnan Adnan Agung Triyono agus bahtiar Agus Riyadi Ahlam Musaydah Ahmad Jihadi Akhmad Abu Khasan Muzakki Akhmad Subhan Al Ghozali, Muhammad Iqbal Ali, Ashehad Aswen Amelia, Mita Andi Setiawan Andriawan, Dimas Annisa Rahmi Anshari, Rahman Ardiyanto Saleh Modjo Arif Rinaldi Dikananda Arnas Arnas, Arnas Arum Sari Arya Wijaya, Arya Athhar Hafizha Luthfi ayu hardani, anita Aziz Ramadhani Azzahra, Fitriyani Badruddin Bafadal, Mentarry Bambang Irawan Bambang Siswoyo Basysyar, Fadhil Muhammad Bisma Mahendra Chatarina Umbul Wahyuni Cika Cahya Kafita Purnama Dadang Sudrajat Denni Pratama Devika Rahayu Daud Dewi Wahyuni K. Baderan Diding Herudin Diding Herudin Diding Herudin, Diding Herudin Dienwati Nuris, Nisa Dikananda, Arif Rinaldi Dikananda, Fatihanursari Dini Andriyani Dita Rizki Amalia Dita, Mesya Sabhna Adma Djamadi, Dian Anggreini Edi Tohidi Eka Permana, Sandy Enjelita, Ratu Erieska Aprilyanti Ezra Pratama, Daffa Fadhil Muhammad Basysyar Fadilah, Euis Fajri, Ibnu Fajria, Azzahra Moudy Fathurrohman, Fathurrohman Febiyanto, Anggi Fidya Arie Pratama Fitria, Ananda Rizki Fuad Pontoiyo Gagarin, Muhamad Yuri Giannetti, Niccolo Gifthera Dwilestari Gilang Ramadhan Gita Antar Wulan Gumelar, Restu Habiballoh, Hafshoh Hafshoh Habiballoh Hamdan, Faiz Dzul Fahmi Hamzah, Hasyrul Haqiyah, Aridhotul Hasim Hasim Hasim Hasim Herdiyana, Ruli Hermawan, Bagus Hermawan, Muhammad Andi Hidayat, Manarul Hikmah Maulani Himawan, Toni Ilah Holilah Ilma’nun, M. Lulu Indra Wiguna Marthanu Irfan Ali, Irfan Jamiatur Rasyidah Jannah, Afni Nur Juliandro, Daniel K. Toiyo, Frandika Kadir, Rian Kaslani Khaerul Anam Khairul Akmal, Khairul Khairussalam Khoirul Huda, Muhammad Knohl, Alexander Komalasari, Cahyaningrum Kurnia, Dian Ade Kurniasih, Desta Dwi La Alio La Alio Laili Hidayatun Nikmah Laksono, Agung Lestari, Anjar Ayuning Lestari, Wien Lidina, Lidina Lila Zulfa Kamila M. Basysyar, Fadhil Ma'rufah, Ummu Mahendra, Yusril Muhamad Izha Mahludin H. Baruwadi Maman Abdurrahman Manarul Hidayat Martanto Maulana Sidiq, Cecep Maulana, Haris Mey Yulan Moko Mia Nurmala Mifta Almaripat Miftahul Huda Mohammad Sholehuddin Mohammad Syaefudulloh Muh. Arfah Syam Muharram Muharram Muhfidz Hidayat, Aziz Muhibuddin Mukdin, Novita B Mulyana, Dani Mulyawan Mulyawan Mulyawan, Mulyawan Nalahuddin Saleh Narasati, Riri Narasati Nasruddin Nasruddin Nida Naswa Ningsih, Indah Ratna Nor Faizatun Nikmah Norma Feti Farida Novi Mardiana Nur Atika Astriani Nur Farida, Farah Nur Halimah Nur Hikmatul Azizah Nuraini, Asyifa Nurhadiansyah Nurhakim, Bani Nurjana Adi Wijaya Nurul Aini, Yuli Odi Nurdiawan Oktavia, Riska Permadani Pertiwi, Pirda Parida Permana , Sandy Eka Permana, Sandy Eka Pratama, Denni Pratama, Fidya Arie Putra, Aris Pratama Rahayu, Helda Kusuma Rahma, Aliya Anisa Ramiro Firjatullah, Federicko Ramli Utina Raudya, Talitha Rayhan, Tubagus Muhammad Riri Narasati Risma Septiana Putri Risnayanti R Juramang Ristika Handarini Riyanto Adji Rizqy, Muhammad Enricco Rohmat, Cep Lukman Rosmeri Manurung, Agnes Rudi Kurniawan Rusmayana, Sigit Saeful Anwar, Saeful Saepu Qirom, Dani Saepudin, Asep Safitri, Ikraeni Sagita, Ayu Sandy Eka Permana Sandy Eka Permana, Faqih Satria Kamalil Hidayat Selly Novita Sari Septianto, Muhamad Arif Sigit Rusmayana Siti Ifroh Alwildah SM, Farid Solihudin, Dodi Subaegi, Angga Sugihartono, Tri Suharno, Achmad Sulaeman, Muhamad Supandi, Achmad Suryani Dewi, Ike Susana, Heliyanti Syaefudulloh, Mohammad Syam, Muh Arfah Syam, Muh. Arfah Syayid Al Manar Tania June Tati Suprapti Tengku Riza Zarzani N Tissa Aunilla Tomayahu, Tian Toriquddin Umar, Achmad Jauhari Wahyu Ningrum Sulistyowati Wanada, Gada Wanda, Aliffa Wijaya, Nurjana Adi Yonny Koesmaryono Yoshua, Deden Yudhistira Arie Wijaya Yuliantin, Yovi