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All Journal Journal of Marine Research 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 Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jurnal Edukasi (Ekonomi, Pendidikan dan Akuntansi) JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Biogenerasi 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 EBONI Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) Makara Journal of Technology 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 Nuansa Informatika AMMA : Jurnal Pengabdian Masyarakat 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 Informasi interaktif : jurnal informatika dan teknologi informasi Jurnal Riset Multidisiplin Edukasi J-CEKI PESHUM Jurnal Geosaintek Sirajuddin: Jurnal Penelitian dan Kajian Pendidikan Islam
Ahmad Faqih
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IMPLEMENTASI DATA MINING PADA KETEPATAN PENGIRIMAN BARANG DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS Dikananda, Arif Rinaldi; Wijaya, Nurjana Adi; Mulyawan, Mulyawan; Faqih, Ahmad
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.472

Abstract

Abstract The development of digital technology E-commers is increasing, online shop goods delivery services are needed to support daily needs. The delivery man is in charge of sending goods to customers, with the delivery of goods applications can monitor delays in delivery of goods to customers so as to obtain data on delays in delivery of goods or called Over SLA. However, in processing the data, they still use manuals with Microsoft Excel so that they are lacking in providing more accurate information such as the accuracy of the accuracy of the delivery of goods, grouping of data on delays in the delivery of goods. The method used in this study by utilizing data mining using the K-Nearest Neighbors or KNN algorithm to classify or group data on delays in shipping goods. This method is used in data mining using Rapidminer machine learning applications. This study aims to classify data on delivery of goods and grouping data on timeliness of delivery so that data can be processed properly so as to produce information about the accuracy of delivery of goods by delivery man, to be more effective and faster in presenting data and classifying data. Keywords: Data mining, Classification, K-Nearest Neighbor (KNN).
Implications of Planting a Living Pharmacy on the Economy of Sumberagung Weleri District Kendal Regency Laili Hidayatun Nikmah; Wahyu Ningrum Sulistyowati; Tissa Aunilla; Adellia Putriani; Selly Novita Sari; Nida Naswa; Ahmad Faqih
Prosiding Seminar Nasional Manajemen dan Ekonomi Vol. 3 No. 1 (2024): : Prosiding Seminar Nasional Manajemen dan Ekonomi
Publisher : Universitas Kristen Indonesia Toraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/semnas.v3i1.416

Abstract

Indonesia is one of the countries that cultivate various plants. Plants are not only used for food or decoration, plants are also very useful as medicines and healers. Plants that can be used to treat and cure diseases are commonly called live pharmacies. live pharmacy plants are quite useful to be used as a source of business because they can be sold and certainly improve the village economy.This research method uses a practical approach directly by going to the community to conduct counseling and planting practices. The results of this study are that the community is still unfamiliar with the concept of live pharmacy, with the practice of planting and counseling about live pharmacy making the Sumber Agung Village Community who are present there become more aware of the use of vacant land to plant useful plants.
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.
USING K-MEANS FOR DISTRICT-CITY POVERTY CLUSTERING IN INDONESIA Mukhyidin, Abdul; Faqih, Ahmad; Rinald, Ade Rizki
NUANSA INFORMATIKA Vol. 19 No. 1 (2025): Nuansa Informatika 19.1 Januari 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i1.300

Abstract

Poverty is one of the main challenges faced by the government in its efforts to improve people's welfare. Identifying regions based on the poverty line level is an important step to ensure well-targeted interventions. This study aims to categorize districts/cities based on poverty levels using the K-Means Algorithm, so that it can be a guide in data-based policy making. The research method starts with data collection, data selection process to handle missing values using the replacement method. Determination of the optimal number of clusters was done using Within Sum of Squares (WSS) to ensure that each region was grouped into clusters based on their level of similarity, which showed that three clusters were the ideal number. An evaluation of the clustering results was conducted to ensure the stability and accuracy of the clustering. The results show that the districts/municipalities are divided into three clusters based on the poverty line level, namely cluster 0 with a high poverty line level (241 regions), cluster 1 with a medium poverty line level (247 regions), and cluster 2 with a low poverty line level (90 regions). This study concludes that the K-Means Algorithm is effective in clustering regions based on poverty levels, providing a strong basis for data-driven decision-making. Future research is recommended to use more diverse data and cover more indicators, such as education level, access to health services, or infrastructure quality.
Mengoptimalkan Kinerja Naïve Bayes Pada Ancaman Modern Dengan Menggunakan PCA Pada Data Intrusion Detection System (IDS) Arlandy, Kevin Salsabil; Faqih, Ahmad; Rinaldi, Ade Rizki
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 8, No 1 (2025): Januari
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v8i1.303

Abstract

Abstrak: Intrusion Detection System (IDS) digunakan untuk mendeteksi serangan atau aktivitas mencurigakan dalam jaringan. Dengan meningkatnya ancaman siber modern, penelitian ini mengusulkan kombinasi metode Naïve Bayes dan Principal Component Analysis (PCA) untuk meningkatkan akurasi dan efisiensi deteksi. Metode tambahan PCA dapet mereduksi dimensi dataset menjadi 30 komponen utama tanpa kehilangan informasi penting, menggunakan dataset UNSW-NB15. Proses melibatkan standarisasi data dengan StandardScaler, reduksi dimensi menggunakan PCA, serta evaluasi model Naïve Bayes pada dataset dengan dan tanpa PCA. Analisis ini menggunakan program Python yang di eksekusi dengan Google Collab, dengan hasil menunjukkan bahwa model dengan PCA mencapai akurasi sebesar 96.65% dengan recall 1.00 untuk kelas ancaman, meskipun presisi masih rendah (0.49). Sebaliknya, tanpa PCA, akurasi hanya mencapai 92.72% dengan presisi 0.31 untuk kelas yang sama. Selain itu, penggunaan PCA berhasil mengurangi waktu komputasi dari 1 menit menjadi 30 detik. Kombinasi dengan teknik reduksi dimensi Principal Component Analysis (PCA) menunjukkan kinerja yang lebih baik dalam mengklasifikasikan data pada sistem Intrusion Detection System (IDS). PCA dan Naïve Bayes terbukti menjanjikan dalam mendeteksi ancaman modern, meskipun masih diperlukan perbaikan untuk mencapai kinerja yang lebih optimal.Kata kunci: Intrusion Detection System, Naïve Bayes, PCA, Keamanan JaringanAbstract:An Intrusion Detection System (IDS) is used to detect attacks or suspicious activities in the network. With the increase of modern cyber threats, this research proposes a combination of Naïve Bayes and Principal Component Analysis (PCA) methods to improve detection accuracy and efficiency. The additional PCA method can reduce the dataset dimension to 30 principal components without losing important information, using the UNSW-NB15 dataset. The process involves data standardization with Standard-Scaler, dimensionality reduction using PCA, and Naïve Bayes model evaluation on the dataset with and without PCA. This analysis used a Python program executed with Google Collab, with the results showing that the model with PCA achieved an accuracy of 96.65% with a recall of 1.00 for the threat class. However, the precision was still low (0.49). In contrast, without PCA, the accuracy only reached 92.72% with a precision of 0.31 for the same class. In addition, the use of PCA successfully reduced the computation time from 1 minute to 30 seconds combination with the Principal Component Analysis (PCA) dimension reduction technique shows better performance in classifying data in the Intrusion Detection System (IDS). PCA and Naïve Bayes proved promising in detecting modern threats, although improvements are still needed to achieve more optimal performance.Keywords: Intrusion Detection System, Naïve Bayes, PCA, Network Security
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.
Co-Authors -, Kaslani Abdullah Baharun Abi Fajar Ahmad Fauzi Achmad Supandi Ade Rizki Rinaldi Ade Rizki Rinaldy Adellia Putriani Adjie Setyadj, Mochammad Adnan Adnan Agung Triyono agus bahtiar Agus Riyadi Ahlam Musaydah Ahmad Jihadi Ahmad Rifai Akhmad Abu Khasan Muzakki Akhmad Subhan Al Ghozali, Muhammad Iqbal Ali, Ashehad Aswen Alma’as, Azis Amelia, Mita Andi Setiawan Andriawan, Dimas Annisa Rahmi Anshari, Rahman Ardiyanto Saleh Modjo Arif Rinaldi Dikananda Arlandy, Kevin Salsabil Arnas Arnas, Arnas Arum Sari Arya Wijaya, Arya Athhar Hafizha Luthfi ayu hardani, anita Aziz Ramadhani Badruddin Bafadal, Mentarry Bambang Siswoyo Basysyar, Fadhil Muhammad Chatarina Umbul Wahyuni Chulyatunni’mah Dadang Sudrajat 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 Dwi Kusuma, Lukman Edi Tohidi Eka Permana, Sandy Enjelita, Ratu Erieska Aprilyanti Esa Putra, Arga Ezra Pratama, Daffa Fadhil Muhammad Basysyar Fadilah, Euis Fajri, Ibnu Fajria, Azzahra Moudy Fathurrohman, Fathurrohman Febiyanto, Anggi Fidya Arie Pratama Fuad Pontoiyo Gagarin, Muhamad Yuri Giannetti, Niccolo Gifthera Dwilestari Gilang Ramadhan 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 Iffah Adelia, Luthfiyyah Ikraeni Safitri Ilah Holilah Ilma’nun, M. Lulu Iqbal Syaidin, Fadli Jamiatur Rasyidah Jannah, Afni Nur Juliandro, Daniel Juramang, Risnayanti R K. Toiyo, Frandika Kadir, Rian Kaslani Khaerul Anam Khairul Akmal, Khairul Khairussalam Khoirul Huda, Muhammad Knohl, Alexander Komalasari, Cahyaningrum Kurniasih, Desta Dwi La Alio La Alio Laili Hidayatun Nikmah Laksono, Agung Lestari, Anjar Ayuning Lestari, Wien Lila Zulfa Kamila M. Basysyar, Fadhil Ma'rufah, Ummu Madyant Mahludin H. Baruwadi Maman Abdurrahman Manarul Hidayat Maulana Sidiq, Cecep Maulana, Haris Mey Yulan Moko Mia Nurmala Mifta Almaripat Miftahul Huda Mohamad Riad Solihin Mohammad Sholehuddin Mohammad Syaefudulloh Mubarok, Fatkhan Muh. Arfah Syam Muhammad Daffa Ayyasy Muhammad Fajid, Marfelio Muharram Muharram Muhfidz Hidayat, Aziz Muhibuddin Mukdin, Novita B Mukhyidin, Abdul Mulyana, Dani Mulyawan Mulyawan Mulyawan, Mulyawan Nalahuddin Saleh Narasati, Riri Narasati Nasruddin Nasruddin Nida Naswa Ningrum, Cistia Ningsih, Indah Ratna Nisa Sari, Ainun Norma Feti Farida Novi Mardiana Nur Atika Astriani Nur Farida, Farah Nur Halimah Nur Rochmah, Aulia Nuraini, Asyifa Nurhadiansyah, Nurhadiansyah 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 R. Juramang, Risnayanti Rahayu, Helda Kusuma Rahma, Aliya Anisa Ramiro Firjatullah, Federicko Ramli Utina Raudya, Talitha Rifa'i, Ahmad Rifa’I, Ahmad Rinald, Ade Rizki Rinaldi Dikananda, Arif Riri Narasati Ristika Handarini Riyanto Adji Rizqy, Muhammad Enricco Rohmat, Cep Lukman Rosmeri Manurung, Agnes Rusmayana, Sigit Saeful Anwar, Saeful Saepu Qirom, Dani Saepudin, Asep Safitri, Ikraeni Sagita, Ayu Sandy Eka Permana Sandy Eka Permana, Faqih Selly Novita Sari Septianto, Muhamad Arif Sigit Rusmayana 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