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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Peternakan Integratif Elkom: Jurnal Elektronika dan Komputer Journal of Education and Learning (EduLearn) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika Scientific Journal of Informatics Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization AdBispreneur Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Informatika Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mnemonic Journal Sensi: Strategic of Education in Information System Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Infotech: Journal of Technology Information Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Applied Research (IJAR) Journal of Applied Data Sciences JOINTER : Journal of Informatics Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal of Information Technology (JIfoTech) Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Jurnal Algoritma Nusantara of Engineering (NOE) Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL SmartComp Jurnal Indonesia : Manajemen Informatika dan Komunikasi Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Irwan Sembiring
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Improving performance of air quality monitoring: a qualitative data analysis Manongga, Danny; Rahardja, Untung; Sembiring, Irwan; Aini, Qurotul; Abas Sunarya, Po
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i4.pp3793-3807

Abstract

This research aims to improve performance of air quality monitoring and understand the latest relevant technological developments. Employing the Kitchenham systematic literature review (SLR) method, the study examines 436 journal articles and conference proceedings published from 2019 to 2023, sourced from the Web of Science (WoS) and Scopus databases. The analysis was carried out using Leximancer 5.0 and identified research five themes; i) air quality, ii) artificial intelligence (AI), iii) pollution, iv) middleware, and v) smart environment. The results showed that only 48 journals had strict inclusion and exclusion criteria include relevance to the research theme, methodological quality, and contribution to the research field. In addition, this research integrates AI and middleware, which has significantly contributed to improving air quality. These findings can become the basis for the development of air quality monitoring technology that is more sophisticated and responsive to environmental needs. This research contributes to further understanding air quality monitoring technology trends and designing solutions to improve overall air quality.
Network Intrusion Detection Using Transformer Models and Natural Language Processing for Enhanced Web Application Attack Detection Priatna, Wowon; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.82462

Abstract

The increasing frequency and complexity of web application attacks necessitate more advanced detection methods. This research explores integrating Transformer models and Natural Language Processing (NLP) techniques to enhance network intrusion detection systems (NIDS). Traditional NIDS often rely on predefined signatures and rules, limiting their effectiveness against new attacks. By leveraging the Transformer's ability to capture long-term dependencies and the contextual richness of NLP, this study aims to develop a more adaptive and intelligent intrusion detection framework. Utilizing the CSIC 2010 dataset, comprehensive preprocessing steps such as tokenization, stemming, lemmatization, and normalization were applied. Techniques like Word2Vec, BERT, and TF-IDF were used for text representation, followed by the application of the Transformer architecture. Performance evaluation using accuracy, precision, recall, F1 score, and AUC demonstrated the superiority of the Transformer-NLP model over traditional machine learning methods. Statistical validation through Friedman and T-tests confirmed the model's robustness and practical significance. Despite promising results, limitations include the dataset's scope, computational complexity, and the need for further research to generalize the model to other types of network attacks. This study indicates significant improvements in detecting complex web application attacks, reducing false positives, and enhancing overall security, making it a viable solution for addressing increasingly sophisticated cybersecurity threats
WEBSITE VULNERABILITY TESTING USING THE PENETRATION TESTING METHOD REFERRING TO NIST SP 800 – 155 (CASE STUDY (Astonprinter.com Domain)) Agustinus, Ari; Sembiring, Irwan
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.3859

Abstract

Information security is a very important aspect in maintaining the confidentiality, integrity and availability of data on a system, especially on websites that are vulnerable to various cyber threats. This research aims to test website vulnerabilities using the penetration testing method by referring to the NIST SP 800-115 standard. The case study used in this research is the astonprinter.com website. The penetration testing method applied in this research follows the NIST SP 800-115 guidelines which include the Planning, Discovery, Attacking and Reporting stages. The results of the research show that the astonprinter.com website has 20 vulnerabilities that can be exploited, with details of 2 vulnerabilities which are in the high threat level, namely DNS Server Spoofed Request Amplification Ddos and Path Traversal, then it has 7 vulnerabilities which are in the medium threat level, including DNS Server Chace Snooping Remote Information Disclosure and Vulnerable Js Library and 11 vulnerabilities that are in the low threat level including ICMP Timestamp Request Remote Date Disclosure, SSH Server CBC Mode Ciphers Enabled, , Cookie No HttpOnly Flag and Cookie without SameSite Attribute. These findings can provide valuable insight for website managers in strengthening security systems and reducing the risk of cyber attacks in the future.
The object detection model uses combined extraction with KNN and RF classification Kurniati, Florentina Tatrin; Manongga, Daniel HF; Sembiring, Irwan; Wijono, Sutarto; Huizen, Roy Rudolf
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp436-445

Abstract

Object detection plays an important role in various fields. Developing detection models for 2D objects that experience rotation and texture variations is a challenge. In this research, the initial stage of the proposed model integrates the gray-level co-occurrence matrix (GLCM) and local binary patterns (LBP) texture feature extraction to obtain feature vectors. The next stage is classifying features using k-nearest neighbors (KNN) and random forest (RF), as well as voting ensemble (VE). System testing used a dataset of 4,437 2D images, the results for KNN accuracy were 92.7% and F1-score 92.5%, while RF performance was lower. Although GLCM features improve performance on both algorithms, KNN is more consistent. The VE approach provides the best performance with an accuracy of 93.9% and an F1-score of 93.8%, this shows the effectiveness of the ensemble technique in increasing object detection accuracy. This study contributes to the field of object detection with a new approach combining GLCM and LBP as feature vectors as well as VE for classification.
Exploring the Relationship between Artificial Intelligence and Business Performance Lutfiani, Ninda; Sembiring, Irwan; Setyawan, Iwan; Setiawan, Adi; Rahardja, Untung; Sulistio, Sulistio
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 1 (2025): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.86697

Abstract

The integration of Artificial Intelligence (AI) into business operations has garnered significant attention due to its potential impact on business performance. However, the relationship between AI adoption and business performance remains not fully understood. This article comprehensively analyzes this relationship through three key aspects: the acceptance and implementation of AI within organizations, the impact of AI on various dimensions of business performance, and the potential challenges associated with AI adoption. In this study, we employ SmartPLS as an analytical tool to evaluate the relationships between identified factors and the impact of AI adoption on business performance. Our findings reveal that several factors influence the adoption and implementation of AI, including data availability, organizational culture, leadership support, technical expertise, and ethical considerations. Moreover, AI adoption significantly influences business performance metrics such as productivity, efficiency, revenue, and customer satisfaction. Nonetheless, challenges arising from AI adoption, including shifts in job roles, data privacy, and security concerns, also require substantial attention. In conclusion, successful AI adoption and implementation necessitate careful consideration of organizational, technical, and ethical factors. This research provides valuable insights for business leaders and researchers seeking a deeper understanding of the relationship between Artificial Intelligence and business performance.
Aesthetic Photography Analysis on Instagram: A Visual Study of Social Media using ATLAS.ti Wibowo, Mars Caroline; Purnomo, Hindriyanto Dwi; Hartomo, Kristoko Dwi; Sembiring, Irwan
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.13985

Abstract

Purpose: This study aims to analyze the dominant trends in color and composition within aesthetic photography on Instagram and explore their influence on user interaction, specifically likes and comments. Given the growing role of visual aesthetics in digital marketing, understanding these elements is crucial for content creators, brands, and businesses aiming to maximize engagement. Unlike previous studies that focus on general social media engagement, this research integrates technology-driven qualitative analysis using ATLAS.ti, enabling structured coding and thematic identification of visual elements. Methods: A qualitative content analysis was conducted on 591 Instagram posts tagged with #AestheticPhotography and #VisualAesthetic. Data was collected using Instagram scraping (PhantomBuster), extracting both visual (color palettes, composition techniques) and textual (captions, metadata) elements. The ATLAS.ti software was used to analyze recurring visual patterns and color extraction was performed via Google Colab and Python for accuracy. Result: The results show that natural colors (48.18%) and pastel tones (30.90%) are dominant in aesthetic photography, contributing to higher engagement due to their harmonious and calming effect. Composition techniques such as center alignment (40.51%) and the Rule of Thirds (23.27%) significantly correlate with user interaction, as they align with cognitive load theory and visual perception principles. Additionally, short captions (≤10 words) were more effective in enhancing engagement, receiving 8,876 likes and 4,432 comments on average, compared to longer captions. Novelty: This study bridges the gap between visual aesthetics and computational analysis, using ATLAS.ti to systematically examine social media trends. Unlike previous studies that focus solely on quantitative metrics, this research provides qualitative insights into how color and composition influence engagement. The findings offer practical guidance for content creators, designers, and marketers, suggesting that strong visual composition and color harmony can enhance audience engagement.
Predicting Transjakarta Passengers with LSTM-BiLSTM Deep Learning Models for Smart Transportpreneurship Siswanto, Joko; Hendry, Hendry; Rahardja, Untung; Sembiring, Irwan; Lisangan, Erick Alfons
Aptisi Transactions On Technopreneurship (ATT) Vol 7 No 1 (2025): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v7i1.440

Abstract

Travel pattern variations pose challenges in building a prediction model that accurately captures seasonal patterns or precision of BRT passenger numbers. An approach that integrates sophisticated prediction algorithms with high accuracy is needed to address the Transjakarta BRT passenger number prediction model problem. The proposed prediction model with the best accuracy is sought using deep learning on 8 models. The prediction model is used for short-term and long-term predictions, as well as looking for correlations in the prediction results of 13 Transjakarta corridors. The Python programming language with the Deep Learning Tensor Flow framework is run by Google Colaboratory used in the prediction simulation environment. The combination of BiLSTM-CNN was found to have the best accuracy of the evaluation value (SMAPE = 15.9387, MAPE = 0.598, and MSLE = 0.0425), although it has the longest time (134 seconds). Fluctuations in short-term predictions of passenger numbers evenly occur simultaneously across all corridors. Fluctuations in long-term predictions evenly occur simultaneously across all corridors, except in February. There is no negative correlation in the 13 prediction results and there are 8 corridors that have a close positive correlation. The prediction results can be used by transportation operators and the government to optimize resource planning and transportation policies to support sustainable community and economic mobility.
IoT-Based Community Smart Health Service Model: Empowering Entrepreneurs in Health Innovation Jonas, Dendy; Purnomo, Hindriyanto Dwi; Iriani, Ade; Sembiring, Irwan; Kristiadi, Dedy Prasetya; Nanle, Zeze
Aptisi Transactions On Technopreneurship (ATT) Vol 7 No 1 (2025): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v7i1.461

Abstract

The Indonesian government aims to improve public health by integrating a unified health platform with regional systems for effective decision-making. However, the existing health information system is inadequate for broader decision-making needs, focusing primarily on individuals with existing health issues and not adequately addressing the needs of disaster victims, such as those affected by floods, accidents, and burns. Tangerang City, located in Banten Province, is a flood-prone area that faces annual disasters, highlighting this gap. To address this issue, this study proposes the development of a Health Internet of Things (HIoT) model designed to support rapid decision-making and enhance community health services. The proposed IoT-based network will be implemented in residential complexes, private clinics, schools, and places of worship, enabling real-time monitoring of health conditions and facilitating disaster or pandemic mitigation. Data collected from these communities will be transmitted to nearby hospitals for immediate medical assistance. Preliminary findings suggest that the IoT-based e-health system offers significant benefits, including faster patient care, improved data accuracy, and reduced operational costs. These results underscore the potential of HIoT to enhance community-based health services. The study provides a foundation for future research and practical applications. Further investigation will be conducted to evaluate the scalability of the system in diverse communities and its impact on long-term health outcomes.
Analisis Verifikasi Proof of Stake (POS) NFT dengan Teknologi Smart Contract Eleazer Gottlieb Julio Sumampouw; Irwan Sembiring
Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Vol. 4 No. 1 (2024): EduTIK : Februari 2024
Publisher : Jurusan PTIK Universitas Negeri Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/edutik.v4i1.9214

Abstract

ABSTRAK Penelitian mengenai Analisis Verifikasi Proof of Stake (PoS) NFT dengan Teknologi Smart Contract, yang dilakukan melalui metode eksperimental, menghasilkan pencapaian yang sesuai dengan tujuan penelitian. Peneliti berhasil mengembangkan dan menjalankan sistem sesuai dengan tujuan yang diinginkan. Beberapa pencapaian utama mencakup implementasi berhasil dari proses verifikasi PoS, serta proses Stake, Unstake, dan Claim yang menggunakan integrasi Web3 dan dompet Metamask. Rekam transaksi dengan akurat mencatat waktu pengirim dan penerima bersama dengan prosedur verifikasi pemilik. Lebih lanjut, penelitian ini menyajikan analisis perbandingan antara Proof of Work (PoW) dan Proof of Stake (PoS). Temuan penelitian menunjukkan keunggulan Proof of Stake (PoS) dalam efisiensi waktu transaksi, biaya transaksi yang lebih rendah, peningkatan keamanan melalui pemilihan validator yang cermat, dan ketahanan terhadap berbagai jenis serangan. Secara keseluruhan, penelitian ini mengukuhkan keefektifan dan keunggulan implementasi Proof of Stake (PoS) dalam konteks Non-Fungible Tokens (NFTs) menggunakan Smart Contract. ABSTRACT The research on the Analysis Verification of Proof of Stake (PoS) NFT Smart Contract Technology, conducted through experimental methods, has yielded successful outcomes aligning with the research objectives. The researcher has successfully developed and executed the system, achieving the intended goals. Key accomplishments include the successful implementation of the PoS verification process, as well as the Stake, Unstake, and Claim processes, utilizing Web3 and Metamask wallet integration. Transaction records accurately capture the timing of sender and receiver actions, alongside owner verification procedures. Furthermore, the research presents a comparative analysis between Proof of Work (PoW) and Proof of Stake (PoS). The findings underscore the superiority of Proof of Stake (PoS) in terms of transaction time efficiency, lower transaction costs, enhanced security through meticulous validator selection, and resilience against various types of attacks. Overall, the research substantiates the efficacy and advantages of implementing Proof of Stake (PoS) in the context of Non-Fungible Tokens (NFTs) using Smart Contracts.
Implementasi dan Analisis Deteksi Serangan Jaringan pada Web Server NFT Menggunakan Suricata Phillnov Yohanes Pinontoan; Irwan Sembiring
Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Vol. 4 No. 1 (2024): EduTIK : Februari 2024
Publisher : Jurusan PTIK Universitas Negeri Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/edutik.v4i1.9428

Abstract

ABSTRAK Penelitian ini berfokus pada masalah keamanan jaringan yang menjadi krusial bagi perusahaan teknologi blockchain dan Non-Fungible Token (NFT) yang rentan terhadap serangan siber seperti DDoS, injeksi SQL, dan malware. Serangan ini tidak hanya menyebabkan kerugian finansial tetapi juga merusak reputasi dan kepercayaan pengguna. Suricata, sebagai sistem deteksi dan pencegahan intrusi open-source, menawarkan berbagai fitur untuk memonitor dan menganalisis lalu lintas jaringan secara real-time. Penelitian ini mengevaluasi efektivitas Suricata dalam mendeteksi ancaman pada web server NFT melalui pendekatan eksperimental. Pengujian dilakukan dengan metode scanning port, web penetration testing, DDoS, dan identifikasi kerentanan sistem web server menggunakan alat seperti NMap, Hping3, Nikto, dan Metasploit. Hasil menunjukkan bahwa Suricata mampu mencatat aktivitas mencurigakan dan mencegah anomali dengan integrasi firewall PFsense. Implementasi Suricata memberikan informasi deteksi serangan web scanning, meskipun tidak memiliki aturan shared object seperti perangkat lunak intrusi lainnya. Penelitian ini memberikan rekomendasi bagi pengembang dan operator platform NFT untuk melindungi aset digital mereka dari serangan siber, serta berkontribusi pada peningkatan keamanan jaringan di sektor NFT. ABSTRACT This research focuses on the critical issue of network security for blockchain technology and Non-Fungible Token (NFT) companies, which are vulnerable to cyberattacks such as DDoS, SQL injection, and malware. These attacks not only cause financial losses but also damage reputation and user trust. Suricata, an open-source intrusion detection and prevention system, offers various features to monitor and analyze network traffic in real-time. This study evaluates the effectiveness of Suricata in detecting threats on NFT web servers through an experimental approach. Testing methods include port scanning, web penetration testing, DDoS, and identifying web server vulnerabilities using tools such as NMap, Hping3, Nikto, and Metasploit. The results show that Suricata can log suspicious activities and prevent anomalies when integrated with the PFsense firewall. While Suricata provides information on web scanning attacks, it lacks shared object rules found in other intrusion software. This research offers recommendations for NFT platform developers and operators to protect their digital assets from cyberattacks and contributes to improving network security in the NFT sector. Thus, this study is highly relevant in the digital era, where information and data security are top priorities for business continuity and user privacy protection.
Co-Authors Abas Sunarya, Po Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agus Sugiarto Agustinus, Ari Aji, Bintang Kristianto Andriana, Myra April Lia Hananto Apriliasari, Dwi Ardaneswari, Awanda Arthur, Christian Astawa, I Wayan Aswin Dew Ayu Sanjaya, Yulia Putri Bayu Setyanto Pamungkas Bayu, Teguh Indra Budhi Kristianto Budhi Kristianto Budi Santoso Budi, Reza Setya Cahyaningtyas, Christian Daniawan, Benny Danny Manongga Danny Sebastian Dedy Prasetya Kristiadi Dwi Hosanna Bangkalang Dwi Setiawan Edi Suharyadi Efendy, Rifan Eka Purnama Harahap Eko Sediono Eko Sediyono Eleazer Gottlieb Julio Sumampouw Elmanda, Vonda Erick Alfons Lisangan Esti Zakia Darojat Evangs Mailoa Evi Maria Faisal Hakim Amrullah Faturahman, Adam Fauzi Ahmad Muda Fian Yulio Santoso Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gerry Santos Lasatira Ginting, Jusia Amanda Girinzio, Iqbal Desam Gudiato, Candra Hamdan . Hasnudi . Henderi Henderi . Hendry Hendry, - Henuk, Yusuf Leonard Herdin Yohnes Madawara Hindriyanto Dwi Purnomo Huda, Baenil Ignatius Agus Supriyono Ilham Hizbuloh Indrastanti Ratna Widiasari Iwan Setiawan Iwan Setiawan Iwan Setyawan Joko Listiawan Sukowati Joko Siswanto Jonas, Dendy Julians, Adhe Ronny Juneth Manuputty Krismiyati Kristoko D Hartomo Kristoko Dwi Hartomo Kusumajaya, Robby Andika Limbong, Josua Josen Alexander Manongga, Daniel H.F Manongga, Daniel H.F. Manongga, Daniel HF Marsyel Sampe Asang Marvelino, Matthew Mau, Stevanus Dwi Istiavan Maya Sari Merryana Lestari Migunani Migunani Mira Mira Mira Mohammad Ridwan Muhamad Yusup Nanle, Zeze Nazmun Nahar Khanom Nina Setiyawati Ninda Lutfiani Nining Fitriani Nugroho, Samuel Danny Nuryadi, Didik Nurzainah Ginting Pamungkas, Bayu Setyanto Phillnov Yohanes Pinontoan Pinontoan, Phillnov Yohanes Priatna , Wowon Purbaratri, Winny Purnomo, Hidriyanto Dwi Putra, Yonathan Rahadi Qurotul Aini Qurotul Aini R. Suharyadi Rahardja.,M.T.I.,MM, Dr. Ir. Untung Raymond Elias Mauboy Rimes Jopmorestho Malioy Roy Rudolf Huizen Saian, Septovan Dwi Suputra Sandry Lanovela Pasaribu Santoso, Nuke Puji Lestari Sediyono, Eko - Setiawan Hakim Sri Ngudi Wahyuni Sri Ngudi Wahyuni, Sri Ngudi Sri Yulianto Joko Prasetyo Suharyadi Sulistio Sulistio Sumampouw, Eleazer Gottlieb Julio Supriadi, Candra Susanti, Novita Dewi Sutarto Wijono Suwijo Danu Prasetyo Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tintien Koerniawati Tio Nurtino Tirsa Ninia Lina Tomasoa, Lyonly Tri Wahyuningsih Tri Wahyuningsih Tukino, Tukino Untung Rahardja Untung Rahardja Wibowo, Mars Caroline Wijaya, Angga Zakharia Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yohan Maurits Indey Yohnes Madawara, Herdin Yulian Hany Makaruku