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All Journal Jurnal Ilmu Komputer dan Informasi Prosiding SNATIKA Vol 01 (2011) SITEKIN: Jurnal Sains, Teknologi dan Industri SMATIKA Jurnal Ilmiah KOMPUTASI Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science (JOINTECS) JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknoinfo INTECOMS: Journal of Information Technology and Computer Science JURIKOM (Jurnal Riset Komputer) Jurnal Ilmu Kedokteran dan Kesehatan Minda Baharu STRING (Satuan Tulisan Riset dan Inovasi Teknologi) INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Pena Justisia: Media Komunikasi dan Kajian Hukum Jurnal Mantik Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Computer Networks, Architecture and High Performance Computing Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal PkM (Pengabdian kepada Masyarakat) JUSTIN (Jurnal Sistem dan Teknologi Informasi) International Journal Software Engineering and Computer Science (IJSECS) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Jurnal Sistem Informasi Bisnis (JUNSIBI) Green Intelligent Systems and Applications JUNIF: Jurnal Nasional Informatika Abdi Implementasi Pancasila: Jurnal Pengabdian kepada Masyarakat Innovative: Journal Of Social Science Research PANDITA: Interdisciplinary Journal of Public Affairs Antasena: Governance and Innovation Journal SWADIMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Masyarakat Mandiri: Jurnal Pengabdian Dan Pembangunan Lokal WINDRADI: Jurnal Pengabdian Masyarakat Smatika Jurnal : STIKI Informatika Jurnal
Sari Ningsih
Fakultas Teknologi Komunikasi Dan Informatika - Universitas Nasional
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Implementation Convolutional Neural Network for Visually Based Detection of Waste Types Wedha, Bayu Yasa; Sholihati, Ira Diana; Ningsih, Sari
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3427

Abstract

Waste detection plays an essential role in ensuring efficient waste management. Convolutional Neural Networks are used in visual waste detection to improve waste management. This study uses a data set that covers various categories of waste, such as plastic, paper, metal, glass, trash, and cardboard. Convolutional Neural Networks are created and trained with refined architecture to achieve precise classification results. During the model development stage, the focus is on utilizing transfer learning techniques to implement Convolutional Neural Networks. Utilizing pre-trained models will speed up and improve the learning process by enriching the representation of waste features. By using the information embedded in the trained model, the Convolutional Neural Network can differentiate the specific attributes of various waste categories more accurately. Utilizing transfer learning allows models to adapt to real-world scenarios, thereby improving their ability to generalize and accurately identify waste that may exhibit significant variation in appearance. Combining these methodologies enhances the ability to identify waste in diverse environmental conditions, facilitates efficient waste management, and can be adapted to contemporary needs in environmental remediation. The model evaluation shows satisfactory performance, with a recognition accuracy of about 73%. Additionally, experiments are conducted under authentic circumstances to assess the reliability of the system under realistic circumstances. This study provides a valuable contribution to the advancement of waste detection systems that can be integrated into waste management with optimal efficiency.
Online Tutoring's Technological Foundation and Future Prospects: Enterprise Architecture Development Ningsih, Sari; Wedha, Bayu Yasa; Sholihati, Ira Diana
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3433

Abstract

This study examines the advancement of enterprise architecture with the objective of enhancing the technological infrastructure and long-term strategies in the online student tutoring sector. Online tutoring has emerged as the primary option for supporting the learning process in the rapidly advancing digital age. Identify the essential elements involved in establishing robust groundwork for an online tutoring platform, with a focus on highlighting the strategic significance of enterprise architecture. Examining the technological infrastructure that is customized to fulfill the demands of the tutoring sector constitutes the research methodology utilized in this investigation. Enterprise architecture serves as the fundamental framework that enables smooth integration among different systems, applications, and services used in online tutoring. Creating an enterprise architecture will subsequently generate a well-defined technology roadmap, empowering tutoring companies to innovate with greater precision. This architecture enhances the role of online tutoring in providing a more adaptable and personalized learning experience for students by utilizing advanced technologies like artificial intelligence and data analytics. This study emphasizes the significance of enterprise architecture in facilitating educational transformation and establishing a robust framework for online tutoring companies to progress efficiently. To foster the growth and advancement of the online tutoring industry, it is crucial to strategically enhance the technological infrastructure and implement a well-designed enterprise architecture. This will enable the sector to play a substantial role in shaping a dynamic and forward-thinking educational landscape.
The Impact of Big Data on Enterprise Architectural Design: A Conceptual Review Sholihati , Ira Diana; Wedha, Bayu Yasa; Ningsih, Sari; Sari, Ratih Titi Komala
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3449

Abstract

A conceptual analysis of the impact of big data on enterprise architecture design is provided in this article. Within the framework of expanding digitalization, big data has emerged as a pivotal component in delineating the strategy and framework of organizations. The objective of this study is to investigate the ways in which big data can impact and facilitate the growth of efficient enterprise architecture. Qualitative analysis is the method utilized by researchers to comprehend the intricacies of the interaction between enterprise architecture and big data. This article examines several facets by conducting an extensive review of the literature, including the ways in which big data can facilitate the enhancement of analytical capabilities, innovation in business processes, and strategic decision-making. Emerging challenges, including data security, privacy, and the necessity for IT infrastructure adaptation, are also considered in this study. The outcomes of the review indicate that the implementation of big data in enterprise architecture may substantially alter business strategies and operations. These encompass enhanced system adaptability, customized service provision, and predictive functionalities. Nonetheless, these modifications necessitate modifications to privacy policies, risk management, and data governance. This study presents novel findings regarding the influence of big data on enterprise architecture and provides researchers and practitioners with recommendations for developing and executing successful big data strategies. This research thereby enhances the current body of literature and offers practical guidance in the field.
Twitter Sentiment Analysis of Mental Health Issues Post COVID-19 Pamungkasari, Panca Dewi; Ningsih, Sari; Rifai, Achmad Pratama; Nandila, Alisyafira Sayyidina; Nguyen, Huu Tho; Penchala, Sathish Kumar
Green Intelligent Systems and Applications Volume 5 - Issue 1 - 2025
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v5i1.588

Abstract

The Coronavirus Disease 2019 (COVID-19) impacted many aspects of daily life, including mental health, as some individuals struggled to adjust to the rapid changes brought on by the pandemic. This paper investigated sentiment analysis of Twitter data following the COVID-19 pandemic. Specifically, we analyzed a large corpus of tweets to understand public sentiment and its implications for mental health in the post-pandemic context. The Naïve Bayes and Support Vector Machine (SVM) classifiers were used to categorize tweets into positive, negative, and neutral sentiments. The collected tweet data samples showed that 38.35% were neutral, 32.56% were positive, and 29.09% were negative. Results using the SVM method showed an accuracy of 84%, while Naïve Bayes achieved 80% accuracy.
Land Subsidence Analysis Using Machine Learning Algorithm Random Forest Method in DKI Jakarta Nur Hidayah, Camelia; Pamungkasari, Panca Dewi; Ningsih, Sari; Azhiman, Muhammad Fauzan; Widodo, Joko; Widayaka, Elfady Satya
Green Intelligent Systems and Applications Volume 5 - Issue 1 - 2025
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v5i1.606

Abstract

Land subsidence is an environmental phenomenon that causes the earth's surface to decline gradually or suddenly. Land subsidence occurred in DKI Jakarta due to various factors such as excessive groundwater exploitation, infrastructure loads, and geological conditions. The purpose of this study was to analyze land subsidence in DKI Jakarta and the distribution of existing land subsidence. The results were compared with previous findings using PS-InSAR. Land subsidence was predicted using the Random Forest algorithm. Random Forest, as a type of machine learning, was able to reduce noise and minimize the impact of overfitting through ensemble techniques. Researchers used four metrics, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), R², and Kling-Gupta Efficiency (KGE), to assess the accuracy of the algorithm. The analysis results of land subsidence in DKI Jakarta using Random Forest aligned with the PS-InSAR method. It was observed that areas experiencing land subsidence were predominantly in North and West Jakarta compared to other regions. Furthermore, the prediction of land subsidence using the 2017–2021 dataset indicated a decrease of up to -60 mm/year.
PELATIHAN PENGEMBANGAN MATERI PEMBELAJARAN INTERAKTIF BERBASIS TEKNOLOGI Ningsih, Sari; Gunawan, Arie; Fauziah; Hindarto, Djarot; Yulianto, Lili Dwi; Desmana, Satriawan
Abdi Implementasi Pancasila:Jurnal Pengabdian kepada Masyarakat Vol 4 No 2 (2024): November
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/abdi.v4i2.7802

Abstract

Pelatihan pengembangan materi pembelajaran interaktif berbasis teknologi bertujuan untuk meningkatkan kompetensi guru MTS Asyafi’iyah 04 Jakarta dalam mengintegrasikan teknologi ke dalam proses pembelajaran. Kegiatan ini dilatarbelakangi oleh kebutuhan mendesak untuk mempersiapkan guru dalam menghadapi tantangan era digital dan memastikan pembelajaran yang relevan serta efektif bagi siswa. Metode yang digunakan dalam pelatihan ini meliputi workshop, simulasi, dan evaluasi. Workshop dirancang untuk memberikan pemahaman dasar mengenai teknologi pendidikan dan aplikasinya. Simulasi dilakukan untuk memberikan pengalaman langsung dalam mengembangkan dan menggunakan materi pembelajaran interaktif. Evaluasi dilakukan untuk menilai pemahaman dan kemampuan guru setelah mengikuti pelatihan. Hasil dari pelatihan ini menunjukkan peningkatan yang signifikan dalam kemampuan guru dalam menggunakan teknologi untuk membuat materi pembelajaran interaktif. Selain itu, terdapat peningkatan motivasi dan keterlibatan guru dalam proses pembelajaran. Pelatihan ini diharapkan dapat menjadi model bagi institusi pendidikan lainnya dalam upaya meningkatkan kualitas pembelajaran melalui integrasi teknologi.
Sosialisasi untuk Pengembangan Website Klasifikasi Sampah Dinas Lingkungan Hidup dan Kebersihan (DLHK) di Kota Depok Sari Ningsih; Panca Dewi Pamungkasari; Asrul Sani; Erina Rahmazani; Lili Dwi Yulianto; Ferdiansyah Ferdiansyah; Ghina Rahma; Muhammad Mustaqim; Muhammad Rangga
Masyarakat Mandiri : Jurnal Pengabdian dan Pembangunan Lokal Vol. 2 No. 3 (2025): Juli : Masyarakat Mandiri : Jurnal Pengabdian dan Pembangunan Lokal
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/masyarakatmandiri.v2i3.1998

Abstract

This Community Service Program (PKM) aims to enhance the understanding of the staff at the Environmental and Sanitation Agency (DLHK) of Depok City in utilizing information technology through socialization and training on the development of a waste classification website. The website is designed to assist the public in identifying types of waste and to encourage more responsible and integrated waste management practices. The implementation methods for this program include socialization sessions, technical training workshops, and system usage demonstrations. Participants were introduced to the functionalities of the website, including how to classify various waste types and its role in supporting environmental sustainability. The program also provided hands-on training to ensure the staff could effectively use the website and incorporate it into their daily tasks. As a result, the staff’s understanding of the concept of digital-based waste classification has significantly increased. Additionally, the potential benefits of using such technology to support sustainable environmental management programs were clearly recognized. The program not only enhanced the staff's technical skills but also contributed to a deeper understanding of the importance of waste classification in the broader context of environmental conservation. The outcomes of this initiative are expected to encourage the staff to actively promote the use of the website to the public, thus fostering a more responsible and efficient waste management system in Depok City. This program demonstrates the effectiveness of integrating technology in supporting local government initiatives aimed at improving environmental management and sustainability. Furthermore, it underscores the importance of digital tools in modernizing waste management systems and enhancing public awareness and engagement.
ALGORITMA K-MEANS UNTUK ANALISIS CLUSTER KINERJA DOSEN PADA BIDANG KEAHLIANNYA DI UNIT PENJAMINAN MUTU FTKI UNIVERSITAS NASIONAL: ALGORITMA K-MEANS UNTUK ANALISIS CLUSTER KINERJA DOSEN PADA BIDANG KEAHLIANNYA DI UNIT PENJAMINAN MUTU FTKI UNIVERSITAS NASIONAL Ningsih, Sari
Jurnal Nasional Informatika (JUNIF) Vol. 2 No. 1 (2021): Jurnal Nasional Informatika
Publisher : Program Studi Teknik Informatika, Institut Bisnis dan Informatika (IBI) Kosgoro 1957

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55122/junif.v2i1.517

Abstract

Penelitian ini berkaitan dengan analisis data dosen untuk mengevaluasi kinerja dosen pada sekelompok data di beberapa program studi di suatu unit kerja pada Fakultas berdasarkan bidang keahlian dosen. Seiring dengan berkembangnya teknologi dibutuhkan penelitian yang bertujuan untuk membantu seorang pimpinan dalam mengelompokkan data nilai hasil kemampuan dari tiap dosen yang memiliki kemampuan yang beragam berdasarkan beberapa kriteria antara lain bidang keahlian, tingkat pendidikan, lamanya bekerja sebagai dosen , jabatan fungsional, penelitian dan pengabdian pada masyarakat yang sudah menjadi kewajiban seorang dosen dalam kegiatan mengajar di suatu Perguruan Tinggi baik Negeri atau Swasta. Unit Penjaminan Mutu pada Fakultas mempunyai tugas dan wewenang untuk memonitoring dan Evaluasi (Monev) seluruh kegiatan di Fakultas agar tercapai hasil yang sesuai .Algoritma K-Means Clustering akan membuat pengelompokan dosen berdasarkan data nilai kinerja dosen melalui klusterisasi yang ada sehingga memudahkan pihak pimpinan untuk acuan pengambilan keputusan seperti kenaikan jabatan, reward atau punishment dari semua hasil kinerja dari dosen yang bersangkutan. Evaluasi kinerja dosen dapat diambil dari data hasil kuesioner mahasiswa yang menilai kinerja dosen untuk setiap mata kuliahnya berdasarkan bidang keahlian dosen yang bersangkutan. Hasil perhitungan analisis cluster didapat 3 cluster dosen, yaitu : C1 sebagai Cluster dosen tingkat Atas sebesar 16,67% , C2 sebagai cluster dosen tingkat Menengah sebesar 70 % dan C3 sebagai cluster dosen tingkat dasar / pemula sebesar 13,33%.
KLASTERISASI LAGU PADA PLATFORM SPOTIFY BERDASARKAN FITUR AUDIO MENGGUNAKAN ALGORITMA K-MEANS DAN K-MEANS++ Indah Safitri, Ramadanti; Ningsih, Sari
Jurnal Sistem Informasi Bisnis (JUNSIBI) Vol. 6 No. 2 (2025): Jurnal Sistem Informasi Bisnis (JUNSIBI)
Publisher : Program Studi Sistem Informasi Institut Bisnis dan Informatika (IBI) Kosgoro 1957

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55122/junsibi.v6i2.1684

Abstract

Perkembangan teknologi telah mengubah cara pengguna menikmati musik, dengan platform seperti Spotify menyediakan jutaan lagu dari berbagai genre. Namun, dengan jumlah lagu yang sangat besar, pengelompokan lagu berdasarkan karakteristik audio menjadi tantangan tersendiri. Penelitian ini bertujuan untuk mengelompokkan lagu-lagu di Spotify berdasarkan fitur audio menggunakan algoritma K-Means dan K-Means++. Dataset yang digunakan mencakup atribut seperti danceability, energy, valence, tempo, loudness, speechiness, instrumentalness, acousticness, dan liveness. Metode klasterisasi K-Means dan K-Means++ diterapkan untuk membagi lagu ke dalam tiga klaster utama, berdasarkan hasil Elbow Method. Lalu kluster dilabeli dengan Energik, Mellow, dan Ceria berdasarkan analisis hasil rata-rata pada tiap cluster. Evaluasi menggunakan Silhouette Score menunjukkan bahwa K-Means++ menghasilkan klasterisasi yang lebih optimal dibandingkan K-Means, dengan nilai 0.32246467825287023. Klaster Energik menjadi kelompok terbesar (56.5%), diikuti oleh Mellow (24.3%) dan Ceria (19.2%). Visualisasi menunjukkan pemisahan klaster yang cukup jelas, meskipun terdapat sedikit beririsan antara klaster Ceria dan Energik.
Capacity-Building Training on Website Development for SMA 58 Jakarta Students Using HTML and JavaScript Programming Languages Fauziah, Fauziah; Ningsih, Sari; Hayati, Nur; Andrianingsih, Andrianingsih; Shalihati, Ira Diana; Riyantoro Riyantoro; Indra Lukmana; Syaiful Syaiful; Muhammad Nurdin; Wijanarko, Sigit
Masyarakat Mandiri : Jurnal Pengabdian dan Pembangunan Lokal Vol. 2 No. 4 (2025): Oktober: Masyarakat Mandiri : Jurnal Pengabdian dan Pembangunan Lokal
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/masyarakatmandiri.v2i4.2140

Abstract

Hyper Text Markup Language (HTML) is a markup language used to structure and format text documents through the use of tags that control the appearance of content on web pages. HTML defines various document elements such as headings, paragraphs, images, and lists, which form the basic structure of a webpage. JavaScript, on the other hand, serves as a programming language that adds interactivity and dynamics to web pages. While HTML provides the basic framework for website layout, JavaScript enhances functionality with features that cannot be achieved through HTML alone, such as dynamically manipulating elements and responding to user interactions. Together, these two languages form the core foundation for web development. This program aims to equip students of SMAN 58 with the skills to practice using HTML tags, understand the basics of JavaScript programming, and develop interactive web pages through online simulations. The training will be conducted in stages, beginning with the submission of a proposal to the school and followed by the scheduled training in June 2024. Students will use the One Compiler platform for real-time practice, allowing them to write and execute HTML and JavaScript code directly in the browser. The training will be conducted interactively, introducing the fundamental concepts of HTML and JavaScript, along with demonstrations showing how to create dynamic websites. In the final phase, students will take a quiz designed to assess their understanding of the material and their ability to apply the knowledge gained. Through this program, it is expected that students will master the basic skills of website creation and have the ability to independently develop their own interactive web projects. Additionally, this program aims to enhance students' digital awareness and technical skills in the era of information technology.
Co-Authors Achmad Pratama Rifai Adinta, Brema Adisti Suryaningtyas Putri Wirawan Aditya Nur Rohman Aditya Nuryudha Iriandi Agam Beny Styawan Agung Triayudi Ahmad Deni Maulana Ahmad Muslih Mardia Ahmad Rafiansyah Fauzan Ahmad Rifqi Alfath Yauma Alfin Syaifudin Alfin Syaifudin Ali, Akbar Alica Dwi Fahira Amran Koto, Eryus Andrianingsih Anis Supriatin Anis Supriatin Ardhi, Agil Zaky Ardiyansah, Ardiyansah Ariana Azimah Arie Gunawan Arie Gunawan Aris Gunaryati Ariwirawan Djali Arman Mubarokh Asif Awaludin Asrul Sani Ayun Sriatmi Azhiman, Muhammad Fauzan Azis Hakim Babag Purbantoro Babag Purbantoro Bagas Dwi Ardianto Bayu Anggara Bayu Yasa Wedha Bayu Yasa Wedha Budi Supriyatno Budyarti, Sisca Chuy Mandala Putra Cintia Marito Sihombing Deni Yulian Deny Hidayatullah Deny Hidayatullah Deny Hidayatullah Deny Hidayatullah Desmana, Satriawan Dhema, Salestinus Petrus Dhieka Avrilia Lantana Dhieka Avrilia Lantana Dhieka Avrilia Lantana Dicke Rifki Fajrin Dinda Nurkhaliza Putri Djarot Hindarto Djoko Widodo Eky Pambudi Syiamtoni Endah Tri Esthi Handayani Endah Tri Esti Handayani Eri Mardiani Eri Mardiani Erina Rahmazani Erina Rahmazani Ermanto, Conrita Fachry, Fachry Fajrin, Dicke Rifki Fauziah Fauziah Fauziah Ferdiansyah Ferdiansyah Frenda Farahdinna Ghina Rahma Guon Fernando Tarimakase Guridno, Ciptoningaji Hakim, Aziz Hariyadi, Ade Reza Hasbulloh Hasbulloh Hasbulloh, Hasbulloh Hindarto, Djarot Humaira, Andini Putri Imelta Natalia Ginting Indah Safitri, Ramadanti Indra Lukmana Ira Diana Sholihati Ira Diana Sholihati Ira Diana Sholihati Iriandi, Aditya Nuryudha Irmawati Irmawati Iskandar Fitri Iskandar Fitri Iskandar Fitri Iskandar Fitri, Iskandar Junior, Reza Phahlevi Keysha Belynda Tyva Panggabean Laveda, Anggita Talita Lili Dwi Yulianto Lili Dwi Yulianto Lombu, Azzaleya Agashi Mandala Anugrah Putra Mandala, Zulhafis Maraghi Agil Prabowo Mardia, Ahmad Muslih Mardiani, Eri Moh. Iwan Wahyuddin Mohammad Iwan Wahyuddin Muhammad Mustaqim Muhammad Nurdin Muhammad Rangga Muhammad Zahran Alfarizi Muhammad Zahran Alfarizi Nandila, Alisyafira Sayyidina Nguyen, Huu Tho Novi Dian Nathasia Nur Hayati Nur Hidayah, Camelia Nur Rahmansyah Nur Rahmansyah Nurfaiz, Kelfin Nurhayati Nurhayati Pamungkasari, Panca Dewi Panca Dewi Pamungkasari Penchala, Sathish Kumar Perdana, Muhammad Rizky Pramitasari, Anisa Prasetyo, Yoga Dwi Putri, Ranti Dwi Putro, Prayogo Dwi Cahyo Rafie, Rakhmi Rahmansyah, Nur Ratih Titi Komala Sari, Ratih Titi Komala Ratih Titi Komalasari Ratih Tri Lestari Reynaldo, Yohanes Reza Phahlevi Junior Ridwan Baharudin Ripin, Muhamad Riyantoro Riyantoro Rozikin, Imam Satria Putra Putra Satriawan Desmana Septi Andryana Setyawati, Kiki Shalihati, Ira Diana Shinta Dwi Rahayu Sholihati , Ira Diana Sholihati, Ira Diana Sifonne Adi Wijaya Suhartono Suhartono Suhatmojo, Guing Tri Syaiful Syaiful Syiamtoni, Eky Pambudi Tegar Budiman Titih Aji Kurniawan Tri Waluyo Trie Widiarti Ningsih Tunggul Puliwarna Ucuk Darusalam Ulfiah, Ulfiah Wedha, bayu Yasa Widayaka, Elfady Satya WIJANARKO, SIGIT Willi Akbar Satria Winarsih Winarsih Winarsih Winarsih Wulandana, Nabila Puspita Wulandari, Yuke Yauma, Alfath Yohanes Reynaldo Yulianto, Lili Dwi Yunan Fauzi Wijaya Yuni Latifah Yusriana Chusna Fadilah