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All Journal Jurnal Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Jurnal Informatika dan Teknik Elektro Terapan Jurnas Nasional Teknologi dan Sistem Informasi ANDHARUPA RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Informatika Jurnal Pilar Nusa Mandiri CogITo Smart Journal Indonesian Journal of Artificial Intelligence and Data Mining JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JMM (Jurnal Masyarakat Mandiri) JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah DoubleClick : Journal of Computer and Information Technology MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURTEKSI Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Building of Informatics, Technology and Science Infotekmesin Jurnal Teknologi Informasi dan Multimedia Journal of Information Systems and Informatics Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] Scientific Journal of Informatics JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) IJIIS: International Journal of Informatics and Information Systems Indonesian Journal of Data and Science JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Teknika Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Technology and Informatics (JoTI) TIERS Information Technology Journal Indonesian Journal of Innovation Studies Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Minfo Polgan (JMP) Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Pengabdian Mitra Masyarakat (JPMM) JOMPA ABDI: Jurnal Pengabdian Masyarakat Digital Transformation Technology (Digitech) Journal of Multimedia Trend and Technology Journal of Artificial Intelligence and Digital Business Jurnal Krisnadana Bulletin of Social Informatics Theory and Application Jurnal Pengabdian Kepada Masyarakat Ceria Jurnal Medika: Medika Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) TECHNOVATE Edu Komputika Journal Jurnal Informatika Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer ABDINE :Jurnal Pengabdian Masyarakat
Pungkas Subarkah
Universitas Amikom Purwokerto
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Classification of Rice Plant Disease Image Using Convolutional Neural Network (CNN) Algorithm based on Amazon Web Service (AWS) Anggraini, Nova; Kusuma, Bagus Adhi; Subarkah, Pungkas; Utomo, Fandy Setyo; Hermanto, Nandang
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5883

Abstract

− In agriculture, rice plays an important role in the Indonesian economy. Rice produces rice, one of the most widely consumed staple food sources in Indonesia. Many factors can cause rice production failure, one of which is leaf pests and diseases. Therefore, early identification and management of plant diseases is an important step in an effort to increase crop yields and ensure food safety. One way to detect rice leaf images early is to perform an image classification process and create a web-based application. The method that has the ability in image processing is deep learning technique with convolutional neural network (CNN) method. The Convolutional Neural Network (CNN) method works to perform and predict diseases in plants by using image categorization or object images. This research aims to apply the web application of image classification of rice plant diseases to the Amazon Web Service (AWS) by identifying and classifying various types of rice leaf diseases using the CNN algorithm, so that farmers can detect rice plant diseases quickly and accurately through image analysis. This application was created using Convolutional Neural Network (CNN) methodology and Software Development Life Cycle (SDLC). The result of this study is that researchers created a web application for the classification of rice plant diseases through leaf images which are divided into 4 categories, namely Healthy, Leaf Blight, Brown Leaf Blight and Hispa, which is made a classification model using CNN with an accuracy value of 0. 8608, then using the streamlit framework to build a website, and utilizing AWS services in the form of Amazon Elastic Compute Cloud (Amazon EC2) as a hosting service, Amazon Simple Storage Service (Amazon S3) as a service for storing rice plant disease classification models and for storing web files, and Amazon Identity and Access Management Role (Amazon IAM) as a service to create a role that gives permission to connect between AWS S3 and AWS EC2. Testing the disease classification model in rice plants implemented on the web in EC2 shows quite good results with an accuracy of 78.5%. This can affect the model's ability to recognize specific disease patterns
PELATIHAN APLIKASI SPEECHACE UNTUK MENINGKATKAN KEMAMPUAN BAHASA INGGRIS BAGI GURU Riandini, Dini; Marlita, Reva; Romadoni, Nova Salma; Subarkah, Pungkas
Jurnal Abdi Nusa Vol. 4 No. 3 (2024): October 2024
Publisher : LPPM Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/abdinusa.v4i3.289

Abstract

English language skills must be improved, especially for educators or teachers. This is especially problematic for madrasah teachers who are not English graduates. For this reason, speechace application training is needed to improve English language skills for teachers of MI Muhammadiyah, Kedungwuluh, Patikraja, Banyumas. The purpose of the course is to provide knowledge and skills for teachers in optimizing information technology, especially the speechace application to support the improvement of English language skills and abilities in the school environment. The implementation method used is the Community Language Learning (CLL) method which consists of the preparation stage, implementation stage and evaluation stage. The results of this service during the training were active participant participation and the results obtained with the pre-test and post-test pre-test and post-test, then out of 21 participants, 95% of the participants This activity is expected to contribute to efforts to improve English language skills among teachers.
PELATIHAN E-MODUL INTERAKTIF BERBASIS TEKNOLOGI INFORMASI UNTUK MENINGKATKAN LITERASI DIGITAL BAGI GURU Subarkah, Pungkas; Prasetyo Kartika, Nur Kholifah Dwi; Rofiqoh, Dayana; Arsi, Primandani; Marcos, Hendra
Jurnal Abdi Nusa Vol. 4 No. 3 (2024): October 2024
Publisher : LPPM Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/abdinusa.v4i3.311

Abstract

Mastering information technology, especially in the field of education for a teacher in the current era, is indeed a must that must be owned by each individual teacher. For this reason, professional flip pdf application training is needed to improve the ability to collaborate on more interactive learning media for students, for teachers of MI Muhammadiyah Wangon, Banyumas Regency. The purpose of this training is to provide knowledge and skills for teachers in optimizing information technology, especially the professional flip pdf application to support improving the ability to collaborate learning methods for students. The implementation method used is the Community Language Learning (CLL) method which consists of the preparation stage, implementation stage and evaluation stage. The results of this service during the training were active participant participation and the results obtained with the pre-test and post-test, then out of 15 participants, 97% of the trainees experienced an increase in their ability to use the professional flip pdf application. This activity is expected to contribute to efforts to improve information technology skills among teachers, especially in supporting teaching and learning activities for students to make them more interactive
Penerapan Algoritma Apriori untuk Rekomendasi Produk Spare Part Mobil Aditya Permana, Reza; Arsi, Primandani; Subarkah, Pungkas
Journal of Technology and Informatics (JoTI) Vol. 6 No. 1 (2024): Vol. 6 No.1 (2024)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v6i1.597

Abstract

Guna memberikan layanan optimal kepada pelanggan, bisnis spare part mobil perlu menerapkan strategi bisnis terbaik. Namun, terkadang beberapa faktor menghambat penentuan strategi tersebut. Salah satu penyebabnya adalah kesulitan dalam melakukan analisis terkait data penjualan pelanggan yang sudah ada. Berdasarkan data pelanggan yang disimpan dalam database, perusahaan mengidentifikasi bahwa sistem penjualan saat ini tidak efektif. Kemudian apabila produk banyak yang tidak terjual, maka keterlambatan dalam pengembalian modal bagi penjual juga akan menjadi masalah. Dalam mengatasi hambatan ini, perusahaan perlu mengadopsi strategi promosi penjualan dan menganalisis pola penjualan spare part untuk menentukan pola penjualan dan memberikan gambaran keterkaitan antar barang dengan menganalisis data transaksi penjualan. Metode yang akan digunakan dalam menganalisis pola penjualan pada penelitian ini adalah dengan menggunakan market basket analysis. Metode ini dihitung menggunakan Algoritma Apriori dengan menggunakan bantuan Google Collab dengan menentukan nilai minimum support sebesar 8 % dan minimum confidence sebesar 60 %. Perhitungan dalam Google Collab akan menghasilkan kumpulan item yang sering dibeli dengan kombinasi 1 itemset sampai dengan 5 itemset yang dibeli secara bersamaan. Hasil assosiation rule tersebut dapat dijadikan acuan kepada pengambil keputusan dalam upaya meningkatkan strategi pemasaran dan promosi produk suku cadang mobil bagi PT Milenia Mega Mandiri yang lebih baik.
Sentiment analysis of Indonesian government policy in the era of social commerce: public perception and reaction Sugiarti, Sugiarti; Arsi, Primandani; Subarkah, Pungkas; V, Jay
Bulletin of Social Informatics Theory and Application Vol. 8 No. 2 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i2.710

Abstract

This research explores public sentiment towards the Indonesian government’s policies in the era of social commerce, based on Minister of Trade Regulation No. 31 of 2023. Sentiment analysis was conducted on a dataset comprising 1013 tweets on Twitter, employing various machine learning algorithms, including Naïve Bayes, Logistic Regression, Random Forest, SVM, and KNN. The results reveal that the Support Vector Machine (SVM) algorithm achieved the highest accuracy rate of 87%, outperforming other algorithms. Analyzing public sentiment towards the mentioned government policies, positive sentiment accounted for 20.2%, while negative sentiment reached 79.8%. This suggests that the policies, as outlined in the regulation, did not elicit a positive response from the public. Recommendations for future research include expanding the dataset and incorporating diverse data sources beyond Twitter for enhanced accuracy. This study contributes valuable insights into public sentiment analysis, particularly in the context of social commerce policies, providing a foundation for further investigations and policy adjustments.
SENTIMEN ANALISIS EVALUASI PENGGUNA APLIKASI ORBIT TELKOMSEL PADA ULASAN PLAYSTORE MENGGUNAKAN ALGORITMA NAÏVE BAYES Lestari, Vika Febri; Arsi, Primandani; Subarkah, Pungkas
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.5538

Abstract

Dalam era digital, aplikasi mobile, khususnya aplikasi internet rumah, memainkan peran penting dalam mendukung aktivitas harian pengguna. Studi ini bertujuan untuk melakukan analisis sentimen terhadap aplikasi Telkomsel Orbit, layanan internet rumah serba digital yang menyediakan koneksi melalui modem WiFi dengan jaringan 4G LTE. Metodologi penelitian melibatkan proses scraping data, preprocessing teks, dan penerapan algoritma klasifikasi Naïve Bayes untuk menganalisis ulasan dan peringkat yang diberikan pengguna di Play Store. Telkomsel Orbit menawarkan fitur unggulan seperti pengaturan Wi-Fi melalui aplikasi MyOrbit, WiFi tamu, dan penyesuaian filter website. Hasil penelitian menunjukkan bahwa penerapan metode Naïve Bayes menghasilkan tingkat ketepatan mencapai 79%, dengan presisi sebesar 80% dan recall 79%.Temuan ini menunjukkan bahwa mayoritas ulasan yang diberikan oleh pengguna cenderung positif terhadap aplikasi Telkomsel Orbit. Hal ini mengindikasikan bahwa layanan tersebut dinilai secara positif oleh pengguna, dengan fitur-fiturnya yang dianggap bermanfaat dan kualitas layanannya yang memuaskan. Penelitian ini memberikan wawasan yang berharga bagi Telkomsel Orbit untuk memahami umpan balik pengguna dan terus meningkatkan pengalaman pengguna mereka. 
PELATIHAN MEDIA PEMBELAJARAN BERORIENTASI GAMIFIKASI UNTUK SISWA SEKOLAH DASAR Azzahra, Delia Oktaviana; Tarwoto, Tarwoto; Arsi, Primandani; Subarkah, Pungkas
Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif Vol. 2 No. 1 (2024): Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif
Publisher : PT. Gelora Cipta Nusantara

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

Abstract

Di SD Negeri 3 Sumpiuh terdapat masalah dalam proses pembelajaran dikelas, guru dalam mengajar siswa masih mengacu pada buku pelajaran, selain itu guru menyiapkan media seperti kartu, poster dan video yang diunduh pada internet.Namun beberapa siswa masih sering tidak memperhatikan dan terlihat bosan saat guru menerangkan, contohnya saat belajar berhitung siswa lebih cenderung ke rasa bosan dan tidak tertarik, oleh karna itu dikembangkan media pembelajaran berorientasi gamifikasi untuk kelas 3 SD untuk memfasilitasi proses belajar mengajar dan memotivasi siswa dalam suasana pembelajaran menjadi lebih menyenangkan. Dalam pengembangan media pembelajaran ini menggunakan platform yang terdapat didalam internet untuk belajar sambil bermain vidio game. Hasil penelitian ini berupa sebuah media pembelajaran yang baik yang dikemas dalam bentuk platform websaite edukasi game.
Peningkatan Kompetensi Pembuatan Website Menggunakan Framework Code Igniter Bagi Mahasiswa Purba, Mariana; Darmo, Cahyo Pambudi; Paisal, Paisal; Putra, Azhar Andika; Subarkah, Pungkas; Riyanto, Riyanto; Marcos, Hendra
Jurnal Pengabdian Kepada Masyarakat Ceria (JPKMC) Vol. 2 No. 1 (2024): Jurnal Pengabdian Kepada Masyarakat Ceria (JPKMC)
Publisher : PT. Gelora Cipta Nusantara

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

Abstract

Permasalahan utama pada mahasiswa ialah mengenai penguasaan teknologi informasi khususnya dalam penguasaan kompetensi dalam membuat website menggunakan framework code igniter. Metode pelaksanaan yang digunakan ialah persiapan, pelaksanaan dan evaluasi. Pelaksanaan kegiatan ini berjalan dengan lancar dimulai dari pembukaan sampai dengan penutupan. Materi yang disampaikan meliputi konsep dasar dari framework code igniter, konsep dasar framework code igniter, konsep MVC dan penerapannya pada website. Hasil yang didapatkan setelah pelatihan ini ialah para mahasiswa selaku peserta  menyampaikan bahwa adanya peningkatan kompetensi mengenai penggunaan Framework Code Igniter sebagai salah satu metode dalam pembuatan website yang dinamis.
Analisis Sentimen Media Sosial X Terhadap Kenaikkan PPN di Indonesia Menggunakan Algoritme Naïve Bayes dan Support Vector Machine (SVM) Ikhsan, Ali Nur; Pungkas Subarkah; Alifah Dafa Iftinani; Alif Nur Fadilah
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2518

Abstract

One of the ways to increase state revenue is by raising the Value-Added Tax (VAT). However, implementing a VAT hike policy often elicits both positive and negative responses from the public. With the presence of social media, people can voice their opinions about government policies, including through social media platform X. This study aims to analyze public sentiment on social media X using the Naïve Bayes and Support Vector Machine (SVM) algorithms. The research compares the highest accuracy results before and after the balancing process. The dataset comprises 2,852 rows in CSV format. The findings indicate that the SVM algorithm achieves an accuracy of 98% before balancing and 97% after balancing, while Naïve Bayes achieves an accuracy of 97% before balancing and 90% after balancing. Overall, both algorithms demonstrate good and balanced performance.
OPTIMIZATION OF CART ALGORITHM BASED ON ANT BE COLONY FEATURE SELECTION FOR STUNTING DIAGNOSIS Subarkah, Pungkas; Ikhsan, Ali Nur; Wahyudi, Rizki; Rofiqoh, Dayana
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 11, No 2 (2025): Maret 2025
Publisher : Universitas Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3579

Abstract

Abstract: One of the main health problems in children is stunting which is one of the concerns in the Sustainable Development Goals (SDGs). Specifically in Indonesia, the prevalence of stunting in 2024 is 21.6%. This figure is still relatively high, because the target prevalence of stunting is 14%. This study aims to implement machine learning knowledge through the Classification And Regression Trees (CART) algorithm based on Ant Be Colony (ABC) feature selection which aims to determine the increase in accuracy in analyzing stunting datasets. The data used comes from Kaggle which consists of 16500 datasets. The dataset consists of gender, age, birth length, birth weight, body length, body weight, breastfeeding and stunting status. The research methods used are data collection, data preprocessing, classification, and evaluation using K-fold cross validation. The results obtained in this research are the implementation of the CART algorithm obtained a value of 89.86% and the results of CART with Ant Be Colony (ABC) feature selection, which obtained an accuracy value of 93.65%. This shows that there is an increase in the accuracy value in the use of CART algorithm optimization and Ant Be Colony (ABC) feature selection by 3.76%. With the research results that have been obtained, it can be categorized as excellent accuracy value excellent. It is hoped that further research can be carried out by adding other classification algorithms or adding feature selection.            Keywords: classification; feature selection; optimazation; stunting Abstrak: Salah satu masalah kesehatan utama pada anak adalah stunting yang menjadi salah satu perhatian dalam Sustainable Development Goals (SDGs). Khusus di Indonesia angka Pravelensi stunting pada tahun 2024 di angka 21.6%. Angka ini masih tergolong tinggi, karena target angka pravelensi stunting ialah 14%. Penelitian ini bertujuan untuk mengimplementasikan pengetahuan machine learning melalui algoritma Classification And Regression Trees (CART) berbasis seleksi fitur Ant Be Colony (ABC) yang bertujuan untuk mengetahui peningkatan akurasi dalam menganalisis dataset stunting. Data yang digunakan bersumber dari Kaggle yang terdiri dari 16500 dataset. Dataset terdiri dari jenis kelamin, usia, panjang lahir, berat lahir, panjangg badan, berat badan, menyusui dan status stunting.  Metode penelitian yang digunakan adalah pengumpulan data, preprocessing data, klasifikasi, dan evaluasi menggunakan K-fold cross validation. Hasil yang diperoleh pada penelitian ini adalah Implementasi algoritma CART memperoleh nilai sebesar 89,86% dan hasil seleksi fitur CART dengan Ant Be Colony (ABC) memperoleh nilai akurasi sebesar 93,65%. Hal ini menunjukkan adanya peningkatan nilai akurasi pada penggunaan optimasi algoritma CART dan pemilihan fitur Ant Be Colony (ABC) sebesar 3,76%. Dengan hasil penelitian yang telah diperoleh dapat dikategorikan nilai akurasi yang diperoleh sangat baik. Diharapkan dapat dilakukan penelitian selanjutnya dengan menambahkan algoritma klasifikasi lain atau menambahkan seleksi fitur. Kata kunci: klasifikasi; optimalisasi; seleksi fitur; stunting
Co-Authors A. Kholil Hidayat Abdallah, Muhammad Marshal Abdul Azis Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adhimah, Laily Farkhah Aditya Permana, Reza Afifah, Erika Luthfi Agus Pramono Akhmad Mustolih Ali Nur Ikhsan Alif Nur Fadilah Alifah Dafa Iftinani Alifian , Raditya Sani Alya Khansa Dzakkiyah Amin, M. Syaiful Amira Aida Rashifa Anggi Tri Dewi Septiani Anggraeni, Eling Sekar Anggraini, Nova Anshari, Muhammad Rifqi Anunggilarso, Luky Rafi Arbangi Puput Sabaniyah Argiyan Dwi Pritama Arsi, Primandani Astrida, Deuis Nur Augst Nurandini Aulia Dian Agustina Aulia Shafira Tri Damayanti Aunillah, Puteri Johar Awal Rozaq, Hasri Akbar Awali, Uston Azhar Andika Putra Azhari Shouni Barkah Azizan Nurhakim Azmi, Mohd Sanusi Azzahra, Delia Oktaviana Baehaqi Wahyu Kurniawan Bagus Adhi Kusuma Bagus Adhi Kusuma Bagus Adi Kusuma Baihaqi, Wiga Maulana Banu Dwi Putranto Bibit Raikhan Azzaki Bryan Jerremia Katiandhago Budi Utami, Dias Ayu Busyro, Muhammad Chendri Irawan Satrio Nugroho Chyntia Raras Ajeng Widiawati Cindy Magnolia Damayanti, Wenti Risma Darmo, Cahyo Pambudi Dava Patria Utama Dermawan, Riky Dimas Desi Riyanti Dewi Fortuna Dhanar Intan Surya Saputra Dias Ayu Budi Utami Dias Ayu Budi Utami, Dias Ayu Budi Didit Suhartono Dinar Mustofa Dini Ambarwati Dini Riandini Dominic Dinand Dwi Krisbiantoro, Dwi Dwi Putra, Ruly Niko Eka Nada Rinjani Elistiana, Khoerotul Melina Enggar Pri Pambudi Epri Anggraeni Esti Widianti Fadilah, Alif Nur Fandy Setyo Utomo Faridatun Nida Farizi, Amar Al Febi Dwi Sasmita Fiby Nur Afiana Fiby Nur Afiana Firmanda, Reza Arief Fitriya Maharani, Lulu Amnah Gina Cahya Utami Harun Alrasyid Hellik Hermawan Hendra Marcos Hendra Marcos, Hendra Hidayah, Debby Ummul hidayatulloh, hanif Husna Maulida Ika Romadoni Yunita Ika Romadoni Yunita Ikhsan, Ali Nur Ilham, Fatah Iphang Prayoga Irfan Santiko Irma Darmayanti Isnaini, Khairunnisak Nur Isnaini, Khairunnisak Nur Jali Suhaman Katiandhago, Bryan Jerremia Khoerida, Nur Isnaeni Kholifah Dwi Prasetyo Kartika, Nur Kisma, Atmaja Jalu Narendra Kusuma, Bagus Adhi Kusuma, Velizha Sandy Latifah Adi Triana Lestari, Tri Endah Widi Lestari, Vika Febri Luki Rafi Anuggilarso Maharani Kusuma Dewi Maria Angelina Cahyani Candrakasih Marlita, Reva Ma’ruf, Muhammad Merliani, Nanda Nurisya Mohammad Imron Muflikhatun, Siti Muhammad Marshal Abdallah Muhammad Rifqi Anshari Mustolih, Akhmad Nanda Nurisya Merliani Nandang Hermanto Nandang Hermanto Nasar Ghanim, Nadif Neta Tri Widiawati Nida, Faridatun Nikmah Trinarsih Nur Hidayah, Septi Oktaviani Nur Isnaeni Khoerida Nuraini , Rema Sekar Nurul Hidayati Permana, Reza Aditya Pramudya, Reyvaldo Shiva Prasetya, Eko Budi Prasetyo Kartika, Nur Kholifah Dwi Prastyadi Wibawa Rahayu Prayoga, Iphang Primandani Arsi Primandani Arsi Purba, Mariana Purwadi Purwadi Ragil Wilujeng Ramadani, Nevita Cahaya Ranggi Praharaningtyas Aji Ratih Anggraeni Ratih Anggraeni Rayinda Maya Anjani Refida Septiana Putri Reykha Putri Randika Reza Aditya Permana Reza Arief Firmanda Riandini, Dini Riyanto Riyanto Riyanto Riyanto Riyanto Riyanto Riyanto Rizki Sadewo Rizki Wahyudi Rofiqoh, Dayana Rohman, M. Abdul Romadoni, Nova Salma Rosana Fadilla Sari Rujianto Eko Saputro Sabaniyah, Arbangi Puput Sadewo, Rizki Salma Ngarifatul Khofiyah Salsabiela, Ayuni Saputra, Dhanar Sari, Rida Purnama Sarmini Sarmini Satrio Nugroho, Chendri Irawan Sekhudin, Sekhudin Septi Nurhayati Septi Oktaviani Nur Hidayah Septi Oktaviani Nur Hidayah Sholikhatin, Siti Alvi SITI ALVI SHOLIKHATIN Siti Alvi Solikhatin Siti Alvi Solikhatin Siti Rahayu Selamat Sugiarti Sugiarti Suhaman, Jali Susanto, Wachyu Dwi Syabani, Amin Syamsiar, Syamsiar Tarwoto, Tarwoto Tri Astuti Trian Damai Triana, Latifah Adi Tripustikasari, Eka Tripustikasari Triyo Ginanjar Pamungkas Umma, Rofiqul Utami, Melida Ratna Utomo, Anwar Tri V, Jay Velizha Sandy Kusuma Wachyu Dwi Susanto Wahyu, Herta Tri Wanda Fitrianingsih Wenti Risma Damayanti Wenti Risma Damayanti Widiawati, Neta Tri Wiga Maulana Baihaqi Yanuar Wardanu Yofi Yulianto Yuli Purwati Yunita, Ika Romadhoni Zahra Revadinika Apriliani