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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 Sisforma: Journal of Information Systems 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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Deep Learning Based LSTM Model for Predicting the Number of Passengers for Public Transport Bus Operators Siswanto, Joko; Manongga, Danny; Sembiring, Irwan; Wijono, Sutarto
JOIN (Jurnal Online Informatika) Vol 9 No 1 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i1.1245

Abstract

The bus public transportation system has low reliability and ability to predict the number of passengers. The accuracy of predicting the number of passengers by public transport bus operators is still weak, which results in failure to implement solutions by operators. A prediction model with LSTM based on deep learning is proposed to predict passengers for 4 bus public transportation operators (Go Bus, New Zealand Bus, Pavlovich, and Ritchies) which are evaluated by MSLE, MAPE, and SMAPE with variations in epoch, batch size, and neurons. The dataset is a CSV performance report on Auckland Transport (AT) New Zealand metro patronage buses (01/01/2019-07/31/2023). The best prediction model was obtained from the lowest evaluation value and relatively fast time at variations of epoch 60, batch size 16, and neurons 32. The prediction results on training and testing data improved with the suitability of the model tuning. The proposed prediction model performs predictions 12 months later for 4 predictions simultaneously with predicted fluctuations occurring simultaneously. Strong negative correlation on New Zealand Bus-Pavlovich, strong positive correlation on Go Bus with Ritchies and Pavlovich. Predictions that are less closely related and dependent are New Zealand Bus against Go Bus, Pavlovich, and Ritchies. The proposed prediction modeling can be used as a basis for creating operator policies and strategies to deal with passenger fluctuations and for the development of new prediction models.
Analisis Verifikasi Proof of Stake (POS) NFT dengan Teknologi Smart Contract Sumampouw, Eleazer Gottlieb Julio; Sembiring, Irwan
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 Pinontoan, Phillnov Yohanes; Sembiring, Irwan
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.
Analisis Perbandingan Sistem Pelaporan Kinerja Kementerian Dalam Negeri menggunakan Metode Usability Testing Ardaneswari, Awanda; Manongga, Daniel H.F; Sembiring, Irwan
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 1 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i1.29565

Abstract

Performance Evaluation System for Apparatus Positions (Sikerja) is a web-based application owned by the Ministry of Home Affairs (MoHA), used to assess and measure the performance of civil servants across all units within MoHA. Currently, MoHA uses two versions of the Sikerja application: the old Sikerja and the new Sikerja. The purpose of this study is to compare the usability levels between 2 systems using the usability testing method, focusing on the performance input menu. The study employs a quantitative descriptive approach using a survey method involving 100 respondents from the Directorate General of Regional Governance, with a questionnaire as the research instrument. The questionnaire items are derived from the five usability indicators based on Jacob Nielsen's framework. The results of the validity and reliability tests on the questionnaire confirmed that it is valid and reliable. Subsequently, a descriptive analysis was conducted for each usability indicator. The analysis results show that the learnability score of the old Sikerja system is 3.24 (high), efficiency is 2.18 (moderate), memorability is 2.98 (moderate), errors is 1.88 (low), and satisfaction is 3,17 (high). On the other hand, the new Sikerja system has a learnability score of 2,23 (moderate), efficiency of 2.07 (moderate), memorability of 1.02 (low), errors of 2.77 (moderate), and satisfaction of 2.54 (moderate). It can be concluded that the new Sikerja system requires workflow simplification, increased user training and socialization, and regular evaluation for employees. These recommendations are expected to improve the usability score of the new Sikerja system within the Ministry of Home Affairs.
Pelatihan Data Science Pada 2024 Guru dan Siswa SMA/SMK Provinsi Nusa Tenggara Timur Manongga, Danny; Iriani, Ade; Kristianto, Budhi; Sembiring, Irwan; Hendry, -; Mailoa, Evangs; Setiyawati, Nina; Bangkalang, Dwi Hosanna
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 6, No 2 (2023): Mei 2023
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/ja.v6i2.1290

Abstract

Data menjadi aset paling berharga untuk organisasi mana pun karena dapat memandu pengambilan keputusan. Oleh karena itu kemampuan data science merupakan salah satu skill penting. Data science tergambarkan sebagai proses yang dimulai dari pengumpulan dan pengolahan, kemudian disajikan sebagai informasi yang berguna untuk pengambilan keputusan atau bermanfaat bagi pihak yang berkepentingan dengan data. Data science memiliki banyak fungsi dan manfaat dimana beberapa diantaranya adalah membantu menciptakan budaya keputusan berbasis data, mengurangi ketidakpastian dan meningkatkan konsistensi dan keandalan data. Melihat pentingnya kemampuan data science, maka Fakultas Teknologi Informasi bekerja sama dengan ASEAN Foundation serta Dinas Pendidikan dan Kebudayaan Provinsi Nusa Tenggara Timur (NTT) melakukan Pengabdian kepada Masyarakat (PkM) dalam bentuk pelatihan kepada 2024 guru dan siswa SMA/SMK Provinsi NTT sebagai bagian untuk mencetak talenta digital Indonesia. Pelatihan didukung oleh SAP yang merupakan perusahaan software dan teknologi yang berbasis di Jerman melalui platform SAP Analytics Cloud (SAC). PkM dilaksanakan secara daring dan luring. Guru dan siswa antusias mengikuti pelatihan ini terlihat dari hasil evaluasi yang bisa dikerjakan dengan baik oleh para peserta.
A Prototype of Decentralized Applications (DApps) Population Management System Based on Blockchain and Smart Contract Saian, Septovan Dwi Suputra; Sembiring, Irwan; Manongga, Daniel H. F.
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.1861

Abstract

The Indonesian population reached 270,20 million in 2020. Each resident is equipped with various secret identities. The COVID-19 pandemic has made all activities use technology as a basis, causing residents' identities to be stored digitally. Some applications that keep these identities experience data leaks. However, with the advent of Web3 and its emphasis on decentralization through blockchain, a new era of secure data management is possible. Blockchain, with its inherent security features, ensures that data stored is secure, difficult to damage or lose due to mutual consensus. Every transaction is recorded, making it easy to carry out the audit process. Therefore, this research will design and implement prototype dApps for secure population management, leveraging the superior security of blockchain technology. The initial stage of research is to conduct a literature study. Furthermore, it is to create designs such as system, infrastructure, and activity diagrams. Then do the development of the dApps prototype. The last is testing using OWASP ZAP and cost analysis. A dApps prototype was implemented on a blockchain. Every transaction is recorded and publicly viewable through the Etherscan platform. Other data stored on a blockchain have gone through an AES-256 encryption process with the data owner's account key so that the owner can only see the data. The results of the tests performed show that there is no high-level warning. The cost analysis results show that the most used costs are when deploying smart contracts and making new data. For further development, it is implementing permissionless blockchain and multi-accounts.
The role of gamification implementation in improving quality and intention in software engineering learning Wahyuningsih, Tri; Sediyono, Eko; Hartomo, Kristoko Dwi; Sembiring, Irwan
Journal of Education and Learning (EduLearn) Vol 18, No 1: February 2024
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v18i1.20823

Abstract

Gamification can make learning more fun and engaging for students. Software engineering can utilize gamification to help students learn and improve their skills from the complexity of software engineering. This study used quantitative research to examines perceived ease of use, student satisfaction, and perceived usefulness to measure gamification quality, which can have an impact on software engineering intention, namely intention, loyalty, and participation in following and understanding software engineering materials. The data was collected based on an online questionnaire survey, 90 data were collected and then measured and analyzed using SmartPLS 3. The results showed that perceived ease of use, student satisfaction, and perceived usefulness have a significant influence on gamification quality, which also leads to a positive impact on software engineering intention. This research guides teachers and educational institutions that gamification is very successful as a learning medium to simplify complex information to be more interactive.
Analysis of Attack Detection on Log Access Servers Using Machine Learning Classification: Integrating Expert Labeling and Optimal Model Selection Ridwan, Mohammad; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49424

Abstract

Purpose: As the complexity and diversity of cyberattacks continue to grow, traditional security measures fall short in effectively countering these threats within web-based environments. Therefore, there is an urgent need to develop and implement innovative, advanced techniques tailored specifically to detect and address these evolving security risks within web applications.Methods: This research focuses on analyzing attack detection in log access servers using machine learning classification with two primary approaches: expert labeling integration and best model selection. Expert labeling determines whether log entries are safe or indicate an attack.Result: Validation in labeling was applied using different datasets to minimize errors and increase confidence in the resulting dataset. Experimental results show that the Decision Tree and Random Forest models have nearly identical accuracy rates, around 89.3%-89.4%, while the ANN model has an accuracy of 81%.Novelty: This study proposes a fusion of expert knowledge in labeling log entries with a rigorous process of selecting the best classification model. This integration has not been extensively explored in previous research, offering a novel approach to enhancing attack detection within web applications. The research contribution lies in the integration of expert security assessment and the selection of the best model for detecting attacks on server access logs, along with validating labels using various datasets from different log devices to enhance confidence in the analysis results.
Exploring Alternative Approaches for TwitterForensics: Utilizing Social Network Analysis to Identify Key Actors and Potential Suspects Sembiring, Irwan; Iriani, Ade; Suharyadi, Suharyadi
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 7 No 2 (2023): August 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v7i2.18894

Abstract

SNA (Social Network Analysis) is a modeling method for users which is symbolized by points (nodes) and interactions between users are represented by lines (edges). This method is needed to see patterns of social interaction in the network starting with finding out who the key actors are. The novelty of this study lies in the expansion of the analysis of other suspects, not only key actors identified during this time. This method performs a narrowed network mapping by examining only nodes connected to key actors. Secondary key actors no longer use centrality but use weight indicators at the edges. A case study using the hashtag "Manchester United" on the social media platform Twitter was conducted in the study. The results of the Social Network Analysis (SNA) revealed that @david_ornstein accounts are key actors with centrality of 2298 degrees. Another approach found @hadrien_grenier, @footballforall, @theutdjournal accounts had a particularly high intensity of interaction with key actors. The intensity of communication between secondary actors and key actors is close to or above the weighted value of 50. The results of this analysis can be used to suspect other potential suspects who have strong ties to key actors by looking.
Uji Perbandingan Akurasi Analisis Sentimen Pariwisata Menggunakan Algoritma Support Vector Machine dan Naive Bayes Susanti, Novita Dewi; Sediyono, Eko; Sembiring, Irwan
Nusantara of Engineering (NOE) Vol 3 No 2 (2016)
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/noe.v3i2.12338

Abstract

Analisis sentimen saat ini banyak digunakan sebagai bahan untuk mengetahui opini masyarakat tentang suatu hal. Dengan menggunakan analisis sentimen kita dapat mengklasifikasikan data apakah data tersebut termasuk opini positif atau opini negatif. Paper ini membahas analisis sentimen untuk mengukur tingakat akurasi dari opini masyarakat pada suatu tempat wisata di Jawa Tengah dengan metode Naive Bayes dan Support Vektor Machine yang berguna untuk mengetahui nilai akurasi yang manakah yang lebih bagus dari dua metode yang digunakan tersebut. Ada beberapa metode yang bisa digunakan untuk mengklasifikasikan opini tersebut, namun dalam paper ini dipilih metode Support Vektor Machine dan metode Naive Bayes dengan alasan metode tersebut adalah metode yang paling banyak digunakan saat ini karena dapat menghasilkan nilai akurasi yang tinggi dari penelitian sebelumnya. Hasil yang didapatkan dari penelitian ini adalah berupa data perbandingan Precision, Recall dan Akurasi. Hasil precision pada NB adalah 65,97%, pada SVM 87,25%. Nilai Recall pada NB adalah 96,39%, pada SVM 80,60%. Nilai akurasi yang didapatkan pada NB 65,78%, pada SVM 76,47% Kata Kunci : Analisis sentimen, opini, klasifikasi, metode, Suport Vektor Machine, Naive Bayes, akurasi
Co-Authors Abas Sunarya, Po Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agus Sugiarto Agustinus, Ari Aji, Bintang Kristianto April Lia Hananto Apriliasari, Dwi Ardaneswari, Awanda Arthur, Christian Astawa, I Wayan Aswin Dew Ayu Sanjaya, Yulia Putri Bayu Setyanto Pamungkas Budhi Kristianto Budi Santoso Budi, Reza Setya Cahyaningtyas, Christian Candra Supriadi 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 Ferry Alamsyah Fian Yulio Santoso Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gerry Santos Lasatira Girinzio, Iqbal Desam Gudiato, Candra Hamdan . Hasnudi . Henderi Henderi . Hendry Hendry, - Henuk, Yusuf Leonard Herdin Yohnes Madawara Hidriyanto Dwi Purnomo Hindriyanto Dwi Purnomo Huda, Baenil I Gusti Ngurah Suryantara Ignatius Agus Supriyono Ilham Hizbuloh Indrastanti Ratna Widiasari Iwan Setiawan Iwan Setiawan Iwan Setyawan Iwan Setyawan Joko Listiawan Sukowati Joko Siswanto Jonas, Dendy Joseph Teguh Santoso Julians, Adhe Ronny Juneth Manuputty Jusia Amanda Ginting Krismiyati Kristoko Dwi Hartomo Kusumajaya, Robby Andika Limbong, Josua Josen Alexander Marsyel Sampe Asang Marvelino, Matthew Mau, Stevanus Dwi Istiavan Maya Sari Merryana Lestari Migunani Migunani Mira Mira Mira Mohammad Ridwan Muhamad Yusup Myra Andriana 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 Putra, Yonathan Rahadi Qurotul Aini Qurotul Aini 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 Setiawan Hakim Sri Ngudi Wahyuni, Sri Ngudi Sri Yulianto Joko Prasetyo Suharyadi Sulistio Sulistio Sumampouw, Eleazer Gottlieb Julio Susanti, Novita Dewi Sutarto Wijono Suwijo Danu Prasetyo Teady Matius Surya Mulyana 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 Wiwin Sulistyo Yerik Afrianto Singgalen Yessica Nataliani Yohan Maurits Indey Yohnes Madawara, Herdin Yolan Dita Dewi Pramudita Yulian Hany Makaruku