Article Per Year (5 Year)
p-Index From 2021 - 2026
7.667
P-Index
This Author published in this journals
All Journal JURNAL SISTEM INFORMASI BISNIS Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal Sains dan Teknologi Prosiding SNATIF E-Dimas: Jurnal Pengabdian kepada Masyarakat Sistemasi: Jurnal Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL ILMIAH INFORMATIKA SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal DISPROTEK Jurnal Nasional Komputasi dan Teknologi Informasi EDUMATIC: Jurnal Pendidikan Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Jurnal Teknologi Informasi dan Pendidikan JATI (Jurnal Mahasiswa Teknik Informatika) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Information Technology Ampera Indonesian Journal of Technology, Informatics and Science (IJTIS) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Muria Jurnal Layanan Masyarakat Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Algoritma Jurnal Pengabdian Masyarakat Bhinneka Al-DYAS : Jurnal Inovasi dan Pengabdian kepada Masyarakat Jurnal Masyarakat Madani Indonesia Jurnal Pengabdian Teknik dan Sains (JPTS) semanTIK
Yudie Irawan
Universitas Muria Kudus
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Other

Published : 73 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 73 Documents
Search

 4   5   6   7   8 
Implementasi Sistem informasi monitoring pengiriman dan pick up paket berbasis dashboard (SIMPONI) pada PT Internusa Master Niaga Pati Ardiansyah Ardiansyah; Yudie Irawan
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 3 (2026): June
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i3.39629

Abstract

Abstrak Perkembangan teknologi informasi mendorong perusahaan untuk meningkatkan efisiensi dalam pengelolaan data dan penyajian informasi. PT Internusa Master Niaga masih menghadapi kendala dalam proses monitoring pengiriman dan pick up paket, seperti pencatatan data yang belum terintegrasi, penyajian informasi yang masih manual, serta keterbatasan dalam pemantauan secara real-time. Kegiatan pengabdian ini bertujuan untuk mengembangkan dan mengimplementasikan Sistem Informasi Monitoring Pengiriman dan Pick Up Paket berbasis dashboard (SIMPONI) guna meningkatkan efektivitas operasional perusahaan. Metode yang digunakan adalah Action Research dengan tahapan persiapan, perancangan, implementasi, pengujian, serta evaluasi dan pendampingan. Pengumpulan data dilakukan melalui observasi, wawancara, dan dokumentasi. Sistem yang dikembangkan mampu menyajikan data pengiriman dan pick up paket secara terintegrasi dalam bentuk dashboard interaktif. Hasil pengujian menggunakan metode Blackbox Testing menunjukkan bahwa seluruh fitur sistem berjalan sesuai dengan kebutuhan pengguna. Efektivitas sistem diukur secara kuantitatif melalui perbandingan proses monitoring sebelum dan sesudah implementasi sistem, yang menunjukkan peningkatan kecepatan akses informasi monitoring paket, kemudahan rekapitulasi data, serta penurunan kesalahan pencatatan data operasional. Implementasi sistem ini juga membantu proses monitoring menjadi lebih terpusat dan mendukung pengambilan keputusan yang lebih cepat dan akurat. Kata kunci: monitoring pengiriman; dashboard interaktif; pick up paket; data real-time; efisiensi operasional. Abstract The advancement of information technology encourages companies to improve efficiency in data management and information presentation. PT Internusa Master Niaga still faces challenges in monitoring shipment and package pick-up processes, such as non-integrated data recording, manual information presentation, and limitations in real-time monitoring. This community service activity aims to develop and implement a dashboard-based Shipment and Package Pick-Up Monitoring Information System (SIMPONI) to improve the company’s operational effectiveness. The method used in this study was Action Research, consisting of preparation, system design, implementation, testing, evaluation, and mentoring stages. Data collection techniques included observation, interviews, and documentation. The developed system is capable of presenting shipment and package pick-up data in an integrated manner through an interactive dashboard. System testing using the Blackbox Testing method showed that all features functioned according to user requirements. In addition, the effectiveness of the SIMPONI system was quantitatively measured through improvements in monitoring activities after implementation, including faster access to shipment data, easier report recap processes, and more effective real-time operational monitoring. The implementation results indicate that the system contributes positively to operational efficiency, simplifies monitoring activities, and supports faster and more accurate decision-making. Keywords: shipment monitoring; data visualization; package pick-up; real-time data; operational efficiency
Implementasi sistem informasi pengelolaan surat masuk dan surat keluar berbasis web di Satpol PP Kabupaten Kudus Syahrul Bagus Andreyan; Yudie Irawan
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 3 (2026): June
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i3.39453

Abstract

Abstrak Administrasi persuratan di instansi pemerintah merupakan aspek penting bagi efisiensi birokrasi, namun proses administrasi manual masih memerlukan waktu yang cukup lama dan sering menyebabkan keterlambatan layanan. Unit Polisi Pamong Praja (Satpol PP) Kabupaten Kudus sebagai mitra sasaran masih memiliki beberapa kendala operasional berupa risiko kerusakan dokumen fisik, pencarian arsip yang lambat, serta kesulitan dalam memantau disposisi surat. Melalui Pengabdian kepada Masyarakat ini, kami akan melaksanakan kegiatan pembuatan Sistem Informasi Manajemen Surat berbasis web untuk mendukung Penyelenggaraan Administrasi yang sudah terdigitalisasi. Proses pelatihan dan evaluasi sistem melibatkan 5 petugas dari Urusan Umum  dan Sekretariat Satpol PP Kabupaten Kudus yang terlibat langsung dalam pengelolaan surat masuk dan surat keluar . Tahap implementasi dengan menggunakan model waterfall dibagi menjadi 4 tahap: analisis kebutuhan, perancangan sistem dengan framework Laravel dan MySQL, implementasi, serta pelatihan juga bagi pihak-pihak yang terkait. Pelaksanaan kegiatan merupakan hasil yang membuat sistem informasi ini dapat mendigitalkan surat masuk dan surat keluar secara terpusat. Sistem ini secara kualitatif meningkatkan tingkat transparansi terkait alur disposisi, sedangkan secara kuantitatif, efisiensi waktu sebesar 85% diukur berdasarkan kecepatan pencarian arsip surat sebelum dan sesudah penggunaan sistem berbasis web.   Selain meningkatkan efisiensi, sistem berbasis web memberikan keamanan data yang lebih baik. Sistem juga mempermudah pengarsipan dokumen, mempercepat pembuatan laporan, serta meningkatkan transparansi pengelolaan surat dibandingkan metode manual sebelumnya.. Implementasi ini telah berhasil menghadirkan sistem administrasi yang jelas dan aman, serta merespons kebutuhan organisasi sehari-hari secara kolektif. Kata kunci:  sistem informasi; pengarsipan surat; web; satpol PP kudus; digitalisasi. Abstract      Correspondence administration in government institutions is an important aspect of bureaucratic efficiency; however, manual administrative processes still require considerable time and often cause delays in services. The Public Order Agency (Satpol PP) of Kudus Regency, as the target partner, still faces several operational problems, including the risk of physical document damage, slow archive retrieval, and difficulties in monitoring mail disposition. Through this community service activity, a web-based Mail Management Information System was developed to support digitalized administrative services. The system training and evaluation process involved 5 officer members from the General Affairs and Secretariat Division of Satpol PP Kudus Regency who were directly involved in managing incoming and outgoing mail. The implementation stage used the Waterfall model, which consisted of four stages: requirements analysis, system design using the Laravel framework and MySQL database, implementation, and user training. The implementation results showed that the system was able to digitalize the management of incoming and outgoing mail in a centralized manner. Qualitatively, the system improved transparency in the mail disposition process, while quantitatively, the 85% efficiency improvement was measured based on the speed of archive retrieval before and after the implementation of the web-based system. In addition to improving efficiency, the web-based system also provided better data security, simplified document archiving, accelerated report generation, and improved transparency compared to the previous manual system. This implementation successfully created a clearer and more secure administrative system that supports the organization’s daily operational needs. Keywords: information systems; letter archiving; web; kudus public order agency; digitalization
Imlementasi sistem informasi pengaduan masyarakat berbasis web pada satuan polisi pamong praja Kabupaten Kudus Khilal Arlisna Rahmadani; Yudie Irawan
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 3 (2026): June
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i3.39685

Abstract

Abstrak Satuan Polisi Pamong Praja (Satpol PP) Kabupaten Kudus masih mengelola pengaduan masyarakat secara konvensional melalui WhatsApp yang kemudian dicatat kembali ke dalam buku agenda dan Microsoft Excel. Kondisi tersebut menyebabkan proses pengelolaan pengaduan menjadi kurang efisien, berisiko kehilangan data, serta menyulitkan pemantauan status laporan secara real-time. Pelaksanaan program pengabdian tersebut difokuskan pada penerapan Sistem Informasi Pengaduan Masyarakat (SIPADU) berbasis web sebagai solusi digital dalam pengelolaan pengaduan masyarakat. Mitra sasaran kegiatan adalah Satpol PP Kabupaten Kudus, khususnya pada bagian pengelolaan dan penanganan pengaduan masyarakat, dengan melibatkan 2 peserta yang terdiri atas 1 penyelia dan 1 operator pengelola pengaduan. Metode kegiatan meliputi observasi, wawancara, pengembangan sistem menggunakan metode Waterfall, implementasi aplikasi, pendampingan penggunaan sistem, dan tahap pengujian menggunakan Black-Box Testing. SIPADU dirancang menggunakan framework Laravel serta database MySQL dengan fitur penyampaian pengaduan, pemantauan status laporan, tindak lanjut aduan, serta rekapitulasi data dalam format Excel. Hasil kegiatan menunjukkan bahwa SIPADU mampu mendukung pengelolaan aduan secara efektif, sistematis, serta transparan guna mengoptimalkan kualitas pelayanan publik di lingkungan Satpol PP Kabupaten Kudus. Kata kunci: sistem informasi; pengaduan masyarkat; website; waterfall; pelayanan publik. Abstract The Public Order Enforcement Agency (Satpol PP) of Kudus Regency still manages public complaints conventionally through WhatsApp, which are subsequently recorded in logbooks and Microsoft Excel. This condition results in inefficient complaint management processes, a higher risk of data loss, and difficulties in monitoring complaint statuses in real time. This community service program focused on implementing a web-based Public Complaint Information System (SIPADU) as a digital solution for managing public complaints. The target partner of this activity was the Public Order Enforcement Agency (Satpol PP) of Kudus Regency, particularly the unit responsible for complaint management and handling, involving two participants consisting of one supervisor and one complaint management operator. The methods employed included observation, interviews, system development using the Waterfall method, system implementation, user assistance, and testing through Black-Box Testing. SIPADU was developed using the Laravel framework and MySQL database, providing features for complaint submission, complaint status monitoring, complaint follow-up management, and report recapitulation in Excel format. The results indicate that SIPADU is capable of supporting complaint management in a more effective, systematic, and transparent manner, thereby enhancing the quality of public services within the Public Order Enforcement Agency of Kudus Regency. Keywords: information systems; public complaints; website; waterfall; public services.
ANALISIS PERBANDINGAN KINERJA ALGORITMA SVM, NAÏVE BAYES, DAN KNN DALAM KLASIFIKASI SENTIMEN ULASAN APLIKASI PINTEREST DENGAN SMOTE DAN PSO Muhamad Dimas Firmansyah; R. Rhoedy Setiawan; Yudie Irawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7095

Abstract

The rapid growth of social media usage has led to a continuous increase in the volume of user reviews, necessitating automated analysis based on machine learning techniques. This study focuses on the development of a sentiment classification model for Pinterest application reviews on the Google Play Store by evaluating three algorithms: Support Vector Machine (SVM), Naïve Bayes, and K-Nearest Neighbors (KNN), combined with Synthetic Minority Oversampling Technique (SMOTE) and Particle Swarm Optimization (PSO). A total of 10,000 reviews were collected through web scraping and processed through preprocessing stages, lexicon-based labeling using InSet, TF-IDF feature extraction, and an 80:20 data split. SMOTE was first applied to balance the class distribution, followed by PSO for parameter optimization of each classification algorithm. The experimental results indicate that SVM achieved the best performance, attaining 95% accuracy with a more balanced F1-score after the application of SMOTE and PSO, while Naïve Bayes and KNN remained sensitive to class imbalance. As the final output, this study developed a Streamlit-based prediction dashboard to display sentiment results in real time, thereby supporting practical and efficient analysis of user perceptions. These findings confirm the effectiveness of combining SVM, SMOTE, and PSO as an optimal approach for sentiment classification on imbalanced review data.  
EVALUASI PENGARUH FINE-TUNING DAN DATA AUGMENTATION TERHADAP KINERJA MOBILENETV2 DAN RESNET50 PADA KLASIFIKASI RAS KUCING MENGGUNAKAN TRANSFER LEARNING: EVALUATION OF THE EFFECTS OF FINE-TUNING AND DATA AUGMENTATION ON MOBILENETV2 AND RESNET50 PERFORMANCE IN CAT BREED CLASSIFICATION USING TRANSFER LEARNING Imam Munzagi; Yudie Irawan; Fajar Nugraha
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8004

Abstract

Manual identification of cat breeds often faces challenges due to the high similarity of visual features among breeds, potentially leading to errors in medical treatment and nutritional management. This study aims to compare the performance of the MobileNetV2 and ResNet50 architectures in classifying 13 cat breeds using a Transfer Learning approach. The CRISP-DM methodology was implemented through four experimental scenarios to evaluate the effects of Data Augmentation and Fine-Tuning, both individually and in combination. The results indicate that the combination of Data Augmentation and Fine-Tuning achieved the best performance. MobileNetV2 consistently outperformed ResNet50 across all scenarios, achieving the highest accuracy of 90,00% and an F1-Score of 90,02%, while ResNet50 achieved a maximum accuracy of only 39,69%. The 50,38% performance gap demonstrates that MobileNetV2 is more adaptive in extracting visual object features. The best-performing model was successfully implemented into an application prototype that is functional and user-friendly.
KOMPARASI KINERJA MACHINE LEARNING TEROPTIMASI SMOTE DAN PSO PADA KLASIFIKASI SENTIMEN ULASAN ROBLOX Amanda Diyas Setiyoadi; Yudie Irawan; Soni Adiyono
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8034

Abstract

The emergence of digital platforms like Roblox has led to an increase in the number of user reviews on the Google Play Store. These reviews contain important information regarding public perception, satisfaction levels, and user complaints about the app. However, the large volume of reviews and the unstructured nature of the text make manual analysis inefficient. Therefore, an automated solution in the form of machine learning-based sentiment classification is needed. This study was conducted to evaluate and compare the effectiveness of three machine learning algorithms, namely Logistic Regression, Support Vector Machine (SVM), and Random Forest, in classifying Roblox app review sentiment into three categories: positive, neutral, and negative. The research data consisted of 10,000 reviews collected through a crawling process from the Google Play Store. Synthetic Minority Oversampling Technique (SMOTE) was applied to address class imbalance, while Particle Swarm Optimization (PSO) was used to optimize model parameters. Experimental results show that Random Forest combined with SMOTE achieved the highest performance with an accuracy of 0.7219, a precision of 0.7241, a recall of 0.7219, an F1-score of 0.7228, and an AUC of 0.778. However, the accuracy of 72.19% is still a limitation for direct practical application, so further improvements are needed. This study also developed a Streamlit-based dashboard to monitor sentiment classification results in real-time. Based on these findings, the combination of Random Forest and SMOTE can be considered quite effective, although it still has limitations in the level of model accuracy.
ANALISIS SENTIMEN TERHADAP PROGRAM MAKAN BERGIZI GRATIS DI MEDIA SOSIAL X BERBASIS PEMBELAJARAN MESIN aufa hanif; Muhammad Arifin; Yudie Irawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8035

Abstract

Social media X provides many public responses to the Free Nutritious Meal Program (MBG), including support, questions, criticism, and neutral information. This study processes 6,000 tweets related to MBG to identify the direction of public opinion using a machine learning approach. The research flow consists of sentiment labeling, text cleaning, TF-IDF weighting, and model testing using Naive Bayes, Random Forest, and Support Vector Machine. The sentiment distribution shows 3,087 positive tweets, 2,213 neutral tweets, and 700 negative tweets. Model testing shows that Random Forest produced the strongest result with 94.75% accuracy, 95.66% precision, 94.75% recall, and 94.93% F1-score. These findings indicate that Random Forest is more suitable for recognizing sentiment patterns in the MBG tweet dataset than the other two models. The study also presents the analysis through a web-based system containing dashboard, dataset import, sentiment data, preprocessing, training, evaluation, and new opinion classification features.
Pemanfaatan Sistem Informasi Berbasis Web untuk Monitoring dan Pelaporan Data Pada Bidang Pemberdayaan Perempuan dan Perlindungan Anak (PPPA) Amelia Rahmawati; Yudie Irawan
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 2 (2026): Mei
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/tzs0h966

Abstract

Kegiatan pengabdian ini dilaksanakan pada Bidang Pemberdayaan Perempuan dan Perlindungan Anak di Dinas Sosial P3AP2KB Kabupaten Kudus yang mana pada bidang tersebut masih menghadapi kendala dalam pengelolaan data terkait program pemberdayaan, rumah aman, dan sekolah ramah anak, yang hingga saat ini belum terintegrasi secara sistematis. Kondisi tersebut menyebabkan proses monitoring dan pelaporan belum berjalan secara optimal. Oleh karena itu, kegiatan ini bertujuan untuk mengembangkan dan menerapkan sistem informasi berbasis web guna mendukung pengelolaan data yang lebih terstruktur dan terintegrasi. Kegiatan pengabdian ini menggunakan pendekatan Community Development Approach, dengan metode yang digunakan meliputi analisis kebutuhan, perancangan, pengembangan, pengujian, serta implementasi yang disertai pelatihan dan pendampingan kepada pengguna. Hasil kegiatan menunjukkan bahwa sistem yang dikembangkan mampu mengintegrasikan data dalam satu platform, mempermudah proses monitoring melalui dashboard visual, grafik serta mempercepat penyusunan laporan. Selain itu, terjadi peningkatan efisiensi dalam pengelolaan data dibandingkan dengan metode sebelumnya yang masih manual. Dengan demikian, sistem ini berpotensi mendukung peningkatan efektivitas pengelolaan program pemberdayaan perempuan dan perlindungan anak secara lebih optimal dan berbasis data.
An Integrated Safety Stock and Net Promoter Score System for Inventory and Customer Loyalty Arya Putra Badruzzaman; Yudie Irawan; Soni Adiyono
Jurnal Pendidikan Informatika (EDUMATIC) Vol 10 No 1 (2026): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v10i1.33557

Abstract

Manual and separate inventory management and customer loyalty monitoring often lead to information delays, record-keeping errors, low operational efficiency, and an unmonitored relationship between stock availability and customer perception. The aim of our research was to develop a web-based sales and loyalty information system that integrates Safety Stock and Net Promoter Score (NPS) methods into a single decision support framework. Our research is a study of system development using the Waterfall model, which includes the stages of requirements analysis, system design, implementation, testing, and maintenance, supported by use cases and activity diagrams. The findings of this study are an integrated system that is able to calculate minimum stock levels, safety stocks, risk of stock-outs, and display real-time NPS visualizations. The test results obtained through black box testing on system access, inventory processing, and NPS reporting show that all key functions are running well and to specification. The implications of this study suggest that the proposed system can improve inventory accuracy, reduce the risk of stock shortages, improve operational efficiency, and support objective, responsive, and sustainable managerial decision-making for small and medium-sized distributors through an integrated and reliable information system.
Mapping Digital Sentiment Landscapes of Hotel Reviews: A Machine Learning-Based Cross-Platform Analysis Muhammad Kholid Ridwan; Yudie Irawan; Raden Rhoedy Setiawan
Jurnal Pendidikan Informatika (EDUMATIC) Vol 10 No 1 (2026): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v10i1.33701

Abstract

The expansion of online travel agencies (OTAs) has produced large volumes of user-generated hotel reviews, offering important resources for sentiment analysis of consumer perceptions. However, prior studies largely rely on single-platform datasets and focus on classification performance, with limited attention to cross-platform sentiment consistency and the impact of data imbalance. This study aims to analyse and compare sentiment patterns across Traveloka, Tiket.com, and Accor, while evaluating a machine learning framework under imbalanced data conditions. This study adopts a quantitative experimental design using 3,000 Indonesian-language reviews collected via web scraping. The independent variable is reviewing text, and the dependent variable is sentiment classification (positive/negative). Data were preprocessed and transformed using TF-IDF, and classified using Multinomial Naïve Bayes, with performance evaluated by accuracy, precision, recall, and F1-score. The results show that positive sentiment consistently dominates across all platforms, with Accor achieving the highest performance, followed by Tiket.com and Traveloka. However, very high recall values for the positive class indicate substantial class imbalance, which biases predictions and reduces sensitivity to negative sentiment. This study provides empirical evidence of cross-platform sentiment consistency and highlights the importance of addressing data imbalance in sentiment modelling.
Co-Authors Aditya, Ahsanu 'Amala Adiyono, Soni Amanda Diyas Setiyoadi Amelia Rahmawati Andy Prasetyo Utomo Ardiansyah Ardiansyah Arif Setiawan Arifviando, Muhammad Villa Aris Sugiharto Arya Putra Badruzzaman aufa hanif Bagus Deva Pratama, Mohammad Chalim, Noor Diana Laily Fithri Dwi Puspitasari Dwi Puspitasari Eko Darmanto Elsa Violina Damayanti Endang Supriyati Endang Supriyati Endhito Hafiz Meifaza Fadila Ullul Azmie Fajar Nugraha Farhan, Faris Ahmad Fitri Budi Suryani, Fitri Budi Hakim, Adam Fathul Hikhmah, Fitria Nurul Ida Siti Marfuah Imam Munzagi Ina Kusumawardani Alina Fakhri Indana Fauzul Ula Indriyani, Sofiatul Janah, Susi Nor Jhany Feronica Ardina Kalya Agil Prasetya Khilal Arlisna Rahmadani Kurniawan, Aldhi Ari Kurniawan, Rizky Dwi Lukito, Aji Marchela Tri Amanda Mimbar Maulana, Bintang Sultan Mochammad Imron Awalludin Mohammad Rosul Mubarrizi, Nor Muhammad Muhamad Dimas Firmansyah Muhamad Sholikhudin Muhammad Arifin Muhammad Kholid Ridwan Muhammad Rizqi Pradana Mustafid Mustafid Nanik Susanti Nesicha, Yutia Nia Noor Latifah Noor Latifah Nurya Herlina Sari Pratomo Setiaji Pratomo Setiaji Priyambodo, Ragil Putri Kurnia Handayani Putri Kurnia Handayani R Rhoedy Setiawan R.Rhoedy Setiawan Raden Rhoedy Setiawan Rahmatika, Alifia Ayu Rahmawati, Yulinda Romadhon, Zainur Savitri Wanabuliandari Setiawan, Raden Rhoedy Silvia Himmatul Aliyyah Soni Adiyono Syafiul Muzid Syahrul Bagus Andreyan Taufiq, Muhammad Bagas Vika Aulia Munawaroh Widhiarta, Faris Widiyatmoko, Fahmi Agung Wiwit Agus Triyanto Zulfa Himmatul Ulya Zuyyina Syarifa Yahya