p-Index From 2021 - 2026
11.389
P-Index
This Author published in this journals
All Journal Jurnal Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Jurnas Nasional Teknologi dan Sistem Informasi ANDHARUPA Jurnal Informatika Jurnal Pilar Nusa Mandiri CogITo Smart Journal Indonesian Journal of Artificial Intelligence and Data Mining JITK (Jurnal Ilmu Pengetahuan dan Komputer) 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 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 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 Decode: Jurnal Pendidikan Teknologi Informasi Indonesian Journal of Innovation Studies Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) Jurnal Pengabdian Mitra Masyarakat (JPMM) JOMPA ABDI: Jurnal Pengabdian Masyarakat Digital Transformation Technology (Digitech) ABDINE Jurnal Pengabdian Masyarakat 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
Claim Missing Document
Check
Articles

Perancangan Aplikasi Bimbingan Karir Berbasis Website Job Journey Untuk Membantu Peserta Didik Merencanakan Karir Awali, Uston; Subarkah, Pungkas; Riyanto, Riyanto
Digital Transformation Technology Vol. 4 No. 1 (2024): Periode Maret 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i1.3898

Abstract

Penelitian ini bertujuan untuk merancang fitur-fitur baru pada aplikasi bimbingan karir berbasis website, Job Journey, yang belum ada pada aplikasi bimbingan karir sebelumnya. Aplikasi ini diharapkan membantu siswa SMA dalam merencanakan karir mereka dengan lebih baik. Metode penelitian yang digunakan adalah model waterfall, yang meliputi tahapan analisis, desain, implementasi, pengujian, dan pemeliharaan. Fitur-fitur baru yang dikembangkan meliputi layanan konsultasi, mentoring, webinar, kelas online, informasi lowongan kerja, dan tes psikologi. Pengujian sistem dilakukan dengan metode Blackbox Testing untuk memastikan validitas dan kinerja sistem. Hasil pengujian menunjukkan bahwa fitur-fitur aplikasi berfungsi dengan baik sesuai dengan harapan. Aplikasi Job Journey berhasil memfasilitasi siswa dalam merencanakan karir mereka melalui interaksi langsung dengan profesional, memberikan wawasan dan nasihat dari para ahli, serta meningkatkan kesiapan mereka untuk memasuki dunia kerja. Selain itu, aplikasi ini memudahkan administrator dalam mengelola data pengguna, pembayaran, artikel, serta memantau perkembangan siswa dalam menggunakan layanan aplikasi. Kesimpulannya, Aplikasi Job Journey efektif dalam memenuhi kebutuhan perencanaan karir siswa dan memudahkan pengelolaan serta pemantauan layanan oleh administrator
Visual Rebranding Desain Kemasan Produk Olahan Gula Jahe Seduh UMKM Berkah di Kabupaten Banyumas Wahyu, Herta Tri; Sarmini, Sarmini; Subarkah, Pungkas
ANDHARUPA: Jurnal Desain Komunikasi Visual & Multimedia Vol. 9 No. 04 (2023): December 2023
Publisher : Dian Nuswantoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/andharupa.v9i4.8311

Abstract

Abstrak Produk gula jahe seduh menjadi salah satu produk olahan rempah di Kabupaten Banyumas tepatnya di Kota Purwokerto. UMKM “Berkah” mencoba memasuki terobosan baru dalam mengejar tren gaya hidup sehat yang kekinian. Untuk meningkatkan eksistensi di khalayak konsumen dari produk ini, maka dilakukan proses rebranding terkait desain kemasan. Mengingat pentingnya proses rebranding, hal ini dilakukan untuk menyampaikan nilai tambah dan citra brand UMKM “Berkah” kepada konsumen. Metode dalam penelitian kualitatif ini menggunakan pendekatan Analisis USP (Unique Selling Proposition), Analisis SWOT, dan Analisis STP (Segmenting, Targeting, dan Positioning). Proses pengambilan data dengan wawancara agar nantinya mendapat informasi yang tepat dan mendalam. Melalui serangkaian tahapan perancangan dan pengujian mendapatkan respon yang positif untuk mengembangkan produk UMKM lebih dikenal oleh konsumen. Hasil penelitian ini adanya keterbaharuan desain kemasan pada produk olahan gula jahe seduh “Berkah” yang digunakan untuk keberlangsungan proses penjualan. Ada harapan bahwa melalui penelitian ini, produk olahan gula jahe seduh “Berkah” akan dapat bersaing bersama kompetitor lainnya. Kata Kunci: desain kemasan, gula jahe, rebranding, UMKM AbstractGinger Sweetened Sugar Products became one of the spice-processed products in the Banyumas District precisely in Purwokerto City. UMKM “Berkah” is trying to enter a breakthrough in pursuing the trend of a healthy lifestyle. To increase the existence in the consumer audience of this product, then carried out a rebranding process related to packaging design. Given the importance of the rebranding process, it is done to convey added value and image of UMKM brand 'Berkah' to consumers. The methods in this qualitative research use the USP (Unique Selling Proposition) analysis, SWOT analysis, and STP analysis approaches. (Segmenting, Targeting, and Positioning). The process of data collection with interviews to obtain accurate and in-depth information. Through a series of design and testing stages get a positive response to develop UMKM products better known by consumers. The result of this research is a renewal of the packaging design on the processed products of ginger sugar "Berkah" used for the sustainability of the sales process. It is hope that through this research, the processed ginger sugar product "Berkah" will be able to compete with other competitors. Keywords: ginger sweetened sugar, MSME, packaging design, rebranding
Performance Comparison of CART And KNN Algorithms for Analyzing Early Predictions of Mental Health Anggraeni, Eling Sekar; Fitriya Maharani, Lulu Amnah; Desi Riyanti; Aji, Ranggi Praharaningtyas; Pungkas Subarkah
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4232

Abstract

Currently, mental health is an unresolved mental health problem both at the national and international levels. Mental health disorders are conditions where a person has difficulty in adjusting to the conditions around them. Mental Health is an important aspect of overall health. Efforts to maintain and improve it can help a person achieve better well-being in everyday life.  This research aims to conduct Early Prediction Analysis related to mental health problems experienced by students by measuring the accuracy level of the analysis. This research was conducted using the CART (Classification and Regression Trees) and KNN (K-Nearest Neighbor) algorithms with a set of Mental Health Datasets consisting of 11 attributes and 101 data.  The data is processed using the Weka Application and the accuracy results of each algorithm are obtained, amounting to 94.0594% for the CART Algorithm and 91.0891% for the KNN Algorithm. From this achievement, it can be concluded that the performance of the CART and KNN algorithms falls into the Excellent Classification category. Judging from the accuracy obtained, the CART algorithm has a higher accuracy value than the KNN algorithm, so the CART algorithm has a high performance for analyzing early prediction of mental health of students who do not take steps in seeking mental health support.
SENTIMENT ANALYSIS ON RENEWABLE ENERGY ELECTRIC USING SUPPORT VECTOR MACHINE (SVM) BASED OPTIMIZATION Pungkas Subarkah; Bagus Adhi Kusuma; Primandani Arsi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 2 (2024): JITK Issue November 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i2.5575

Abstract

Government policy regarding the discourse on the use of renewable energy in electricity, this discourse is widely discussed in the community, especially on social media twitter. The public's response to the implementation of the use of renewable energy varies, there are positive, negative and neutral responses to this government policy. Sentiment analysis is part of Machine Learning which aims to identify responses in the form of text. The data used in this study amounted to 1,367 tweets. The purpose of this study is to determine the sentiment analysis of government discourse related to the use of renewable energy using an optimisation-based Support Vector Machine (SVM) algorithm approach. This research involves several stages including data collection, data pre-processing, experiments and modelling and evaluation. The data is divided into 3 classes, 120 positive, 1221 neutral and 26 negative. In this research, there are five optimisation models used namely Forward Selection, Backward Elimination, Optimised Selection, Bagging and AdaBoost. The results obtained are the use of Optimised Selection (OS) optimisation with the Support Vector Machine (SVM) algorithm obtained an increase in accuracy from 93% to 96%. The increase in the use of SVM using selection optimization obtained the highest increase, because other optimization techniques only reached 1% and 2% of the original results using the SVM algorithm, namely the accuracy value of 93% to 96% (high accuracy). From the research that has been done, it is certainly important to understand public sentiment towards renewable energy policies, especially renewable energy electricity, the hope is that this research will become a reference for the government.
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.
Prediksi Vaksinasi Terhadap Penambahan Kasus Covid-19 Dengan Neural Network Damayanti, Irma; Hakim, Arief Rachman; Subarkah, Pungkas; Utami, Dias Ayu Budi; Rahayu, Prastyadi Wibawa
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 4 No. 1: MARET 2024
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v4i1.354

Abstract

Covid-19 menjadi masalah kritis yang harus segera diselesaikan. Karena telah menyebabkan peningkatan kasus dan kematian yang signifikan di seluruh dunia. Upaya pencegahan dan pengendalian yang dilakukan oleh berbagai negara meliputi penutupan, pembatasan sosial, dan termasuk vaksinasi tak terkecuali di Indonesia. Analisis dan pemahaman yang lebih mendalam tentang hubungan antara vaksinasi dan penambahan kasus Covid-19 diperlukan. Dengan perkembangan teknologi dan berdasarkan penelitian terdahu model kecerdasan buatan yang salah satunya berupa jaringan saraf tiruan (neural network) dapat membantu dalam memodelkan dan memprediksi dampak vaksinasi terhadap penambahan kasus Covid-19. Penelitian ini melakukan perhitungan prediksi vaksinasi terhadap laju kenaikan kasus di Indonesia dengan Neural Network menggunakan struktur backpropagation. Data yang digunakan dalam penelitian ini yaitu data Covid-19 dan data vaksinasi ditahun 2020 sampai 2021. Hasil yang didapa bahwa model Neural Network dapat melakukan prediksi vaksinasi. Dengan pola skenario batchSize = 32, hidden layer = 5, learningRate = 0.3, momentum = 0.2 , dan trainingTime = 100 menunjukan akurasi 60,73% dengan nilai RMSE 0.484, yang mana diketahui bahwa 99 data yang berhasil diprediksi dengan tepat.
Pendampingan Teknologi Informasi E- Smart Care sebagai Upaya Pencegahan Stunting secara Dini pada Remaja melalui Sekolah Siaga Kependukan (SSK) Subarkah, Pungkas; Hermanto, Nandang; Sari, Rida Purnama; Kholifah Dwi Prasetyo Kartika, Nur; Nasar Ghanim, Nadif; Arsi, Primandani
ABDINE: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024): ABDINE : Jurnal Pengabdian Masyarakat
Publisher : Sekolah Tinggi Teknologi Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/abdine.v4i2.984

Abstract

Sekolah Siaga Kependudukan (SSK) di SMA Negeri 1 Wangon, merupakan SSK rintisan sekolah yang mengintegrasikan pndidikan kependudukan dan keluarga berencana, ke dalam beberapa mata pelajaran sebagai pengayaan materi pembelajaran, dimana di dalamnya terdapat pojok kependudukan sebagai salah satu sumber belajar peserta didik. Permasalahan yang dihadapi oleh mitra yaitu belum adanya teknologi informasi yang menunjang untuk pencegahan stunting secara dini di SSK. Metode pelaksanaan pengabdian masyarakat ini dilakukan dengan tahapan pra-pelaksanaan, tahap pelaksanaan dan tahap evaluasi. Dari hasil pelaksanaan kegiatan yang sudah dilakukan maka didapatkan  para peserta kegiatan mengikuti pelatihan dengan baik,  dengan menguasai materi selama pelatihan berlanggsung dan peningkatan kemampuan peserta dalam menggunakan teknologi infomasi E-Smart Care berbasis android dan website. Dengan terlaksana program pendampingan ini dari Tim Program Kemitraan Masyarakat (PKM) 2024, bahwa mitra mendapatkan peningkatan pengetahuan yaitu penggunaan aplikasi E-smart Care berbasis android serta para peserta mendapatkan peningkatan keterampilan cara mengoperasikan aplikasi secara benar. Hasil respon terhadap pelatihan ini yaitu rata-rata memberikan predikat “Sangat Baik”.
Co-Authors A. Kholil Hidayat Abdallah, Muhammad Marshal Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adhimah, Laily Farkhah Aditya Permana, Reza Afifah, Erika Luthfi 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 Anggraeni, Epri Anggraini, Nova Anshari, Muhammad Rifqi Anunggilarso, Luky Rafi Arbangi Puput Sabaniyah Arief Rachman Hakim Arsi, Primandani Astrida, Deuis Nur Aunillah, Puteri Johar Awal Rozaq, Hasri Akbar Awali, Uston Azhar Andika Putra Azhari Shouni Barkah Azizan Nurhakim Azzahra, Delia Oktaviana Bagus Adhi Kusuma Bagus Adhi Kusuma Baihaqi, Wiga Maulana Bryan Jerremia Katiandhago Budi Utami, Dias Ayu Busyro, Muhammad Chendri Irawan Satrio Nugroho Chyntia Raras Ajeng Widiawati Cindy Magnolia Damayanti, Aulia Shafira Tri 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 Dwi Krisbiantoro, Dwi Dwi Putra, Ruly Niko Elistiana, Khoerotul Melina Enggar Pri Pambudi Fadilah, Alif Nur Fandy Setyo Utomo Faridatun Nida Farizi, Amar Al 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 Ikhsan, Ali Nur Ilham, Fatah Iphang Prayoga Irfan Santiko Irma Damayanti Irma Darmayanti Isnaini, Khairunnisak Nur Isnaini, Khairunnisak Nur Jali Suhaman Katiandhago, Bryan Jerremia Khoerida, Nur Isnaeni Khofiyah, Salma Ngarifatul 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 Marlita, Reva Merliani, Nanda Nurisya Mohammad Imron Mohd Sanusi Azmi Muflikhatun, Siti Muhammad Marshal Abdallah Muhammad Ma’ruf Muhammad Rifqi Anshari Mustolih, Akhmad Nanda Nurisya Merliani Nandang Hermanto Nandang Hermanto Nasar Ghanim, Nadif Neta Tri Widiawati Nikmah Trinarsih Nur Hidayah, Septi Oktaviani Nur Isnaeni Khoerida Nuraini , Rema Sekar Nurul Hidayati Pramudya, Reyvaldo Shiva Prasetya, Eko Budi Prasetyo Kartika, Nur Kholifah Dwi Prastyadi Wibawa Rahayu Prastyadi Wibawa Rahayu Prayoga, Iphang Primandani Arsi Primandani Arsi Pritama, Argiyan Dwi Purba, Mariana Purwadi Ragil Wilujeng Ramadani, Nevita Cahaya Ranggi Praharaningtyas Aji Ratih Anggraeni Rayinda Maya Anjani Reza Aditya Permana Reza Aditya Permana Reza Arief Firmanda Riandini, Dini 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 Sandy Kusuma, Velizha Saputra, Dhanar Sari, Rida Purnama Sarmini Sarmini Satrio Nugroho, Chendri Irawan Sekhudin Sekhudin Selamat, Siti Rahayu Septi Oktaviani Nur Hidayah Septi Oktaviani Nur Hidayah Septiana Putri, Refida Sholikhatin, Siti Alvi SITI ALVI SHOLIKHATIN Siti Alvi Solikhatin Siti Alvi Solikhatin Sugiarti Sugiarti Suhaman, Jali Susanto, Wachyu Dwi Syabani, Amin Syamsiar, Syamsiar Tarwoto, Tarwoto Tri Astuti Trian Damai Triana, Latifah Adi Tripustikasari, Eka Tripustikasari Umma, Rofiqul Utami, Melida Ratna Utomo, Anwar Tri V, Jay Wachyu Dwi Susanto Wahyu, Herta Tri Wanda Fitrianingsih Wenti Risma Damayanti Wenti Risma Damayanti Widiawati, Neta Tri Yuli Purwati Yunita, Ika Romadhoni Yunita, Ika Romadoni