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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Jurnal Sistem Komputer JSI: Jurnal Sistem Informasi (E-Journal) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Desimal: Jurnal Matematika INOVTEK Polbeng - Seri Informatika BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal on Emerging Mathematics Education Jurnal ULTIMA InfoSys MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Sistem Informasi dan Aplikasi Journal of Information Technology and Computer Engineering J-SAKTI (Jurnal Sains Komputer dan Informatika) Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUKATIF : JURNAL ILMU PENDIDIKAN Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Journal of Information Systems and Informatics KAIBON ABHINAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) ICIT (Innovative Creative and Information Technology) Journal Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) IAIC Transactions on Sustainable Digital Innovation (ITSDI) JOINTER : Journal of Informatics Engineering International Journal of Engineering, Science and Information Technology Advance Sustainable Science, Engineering and Technology (ASSET) Journal of Information Technology (JIfoTech) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat JEECS (Journal of Electrical Engineering and Computer Sciences) Metris: Jurnal Sains dan Teknologi Scientific Journal of Informatics International Journal of Information Technology and Business INOVTEK Polbeng - Seri Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK
Hindriyanto Dwi Purnomo
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Analisa Segmentasi Customer Pada Perusahaan Bisnis Properties Menggunakan Model RFM (Kasus PT. Pollux Aditama Kencana) Arseta, Gama; Purnomo, Hindriyanto Dwi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.673

Abstract

The current business development in the property industry is promising, leading to a highly competitive market. As a result, PT. Pollux Aditama Kencana, which operates in the property business, must have strategies in every market competition, especially in gaining customer loyalty. This study uses the Recency, Frequency, and Monetary (RFM) model combined with K-Means. The RFM model is used for customer data clustering based on the number of transaction activities, transaction amount, and transaction time. Meanwhile, K-Means can describe the level of customer loyalty. The data used in this study were taken from sales reports from November 28, 2014 to September 19, 2022, involving 1966 customers in property purchases. The results show that the proposed use of the RFM and K-Means models is superior compared to using only the RFM model. Cluster 1 has 936 customers, indicating customers with high loyalty to the company, while Cluster 2 has 250 customers, indicating customers with low loyalty, and Cluster 3 has 780 customers, indicating customers with medium loyalty. The RFM and K-Means models used successfully produced several loyalty attributes that affect customer evaluations, with 4% in the top customer category, 12% in the high-value customer category, 34% in the medium-value customer category, 31% in the low-value customer category, and 19% in the lost customer category.
INTEGRASI ALGORITMA APRIORI DAN K-MEANS DALAM ANALISIS POLA PEMBELIAN UNTUK MENINGKATKAN STRATEGI PEMASARAN Putri, Violita Eka; Purnomo, Hindriyanto Dwi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5768

Abstract

UMKM pada bidang usaha kuliner sedang mengalami peningkatan yang signifikan sehingga muncul persaingan dalam dunia bisnis yang semakin tidak terelakkan. Selain itu, kebiasaan pelanggan dalam melakukan pembelian yang membutuhkan waktu lama menjadi perhatian khusus bagi pemilik bisnis Premium Salad.co untuk dapat membuat penawaran produk yang lebih sesuai dengan keinginan pelanggann. Oleh karena itu, penelitian ini bertujuan untuk membentuk sebuah strategi pemasaran dalam bentuk rekomendasi paket menu atau dapat juga digunakan sebagai paket bundling produk dengan memperhatikkan produk apa saja yang memiliki frekuensi penjualan yang sering dibeli secara bersamaan oleh pelanggan, hal ini bertujuan untuk meningkatkan daya tarik pelanggan. pada saat memilih dan membeli produk, meningkatkan keuntungan penjualan, pemerataan penjualan produk, sekaligus inovasi baru untuk mengimbangi adanya persaingan bisnis kuliner. Data transaksi yang sebelumnya tidak dimanfaatkan secara optimal oleh Premium Salad.co kini dapat dimanfaatkan untuk mencari pengetahuan lebih dalam mengenai gambaran penjualan produk yang terjadi secara keseluruhan dengan bantuan data mining. Pada penelitian ini metode data mining yang digunakan yaitu clustering dan aturan asosiasi. Algoritma k-means berperan untuk mengelompokkan data dalam 4 cluster dengan nilai uji validitas Davies Bouldin Index (DBI) sebesar 0,465. Algoritma apriori berpartisipasi dalam pencarian aturan asosiasi pada cluster. Tujuan dari penggabungan dua metode ini agar menghasilkan aturan asosiasi yang lebih variatif dan lebih sesuai dengan penyelesaian masalah yang dibutuhkan. Dengan menetapkan dukungan minimum sebesar 0,01 dan kepercayaan minimum sebesar 0,5. Pada cluster 0 dengan dataset 321 transaksi menghasilkan 1 aturan dengan tingkat kepercayaan tertinggi sebesar 75%. Cluster 3 dengan dataset paling kecil yaitu 127 transaksi mampu menghasilkan sejumlah 16 aturan dengan tingkat kepercayaan tertinggi mencapai 100%.
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.
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.
PERFORMANCE ANALYSIS OF GRADIENT BOOSTING MODELS VARIANTS IN PREDICTING THE DIRECTION OF STOCK CLOSING PRICES ON THE INDONESIA STOCK EXCHANGE Kho, Delvian Christoper; Purnomo, Hindriyanto Dwi; Hendry, Hendry
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1393-1408

Abstract

Accurately predicting stock market trends remains a significant challenge for investors due to its dynamic nature. This study explores the performance of Gradient Boosting models, including XGBoost, XGBoost Random Forest, CatBoost, and Gradient Boosting Scikit-Learn, in predicting stock market trends such as sideways movement, uptrends, downtrends, and volatility. Using four datasets from the Indonesia Stock Exchange, the research integrates technical, fundamental, and sentiment data, encompassing 37 features. Modeling and testing are conducted using Orange tools and Python, with performance evaluated through metrics such as Mean Absolute Percentage Error (MAPE), R-squared (R²), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). Results indicate that XGBoost and XGBoost Random Forest consistently outperform other models in predicting stock price movements. These findings highlight the potential of Gradient Boosting models in providing accurate and reliable predictions, offering valuable insights for investors, financial analysts, and researchers to enhance investment strategies and adapt to market fluctuations effectively.
Aplikasi Android untuk Monitoring Lahan Pertanian secara Realtime Berbasis Internet of Things Jihot Lumban Gaol; Hindriyanto Purnomo; Budhi Kristianto; Radius Tanone; Yos Richard Beeh; Nina Setiyawati; Markus Permadi; Raynaldo Raynaldo; Riko Yudistira
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 3 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i3.3039

Abstract

The development of technology is very helpful in agriculture by using the internet to get the information we need. The problem that farmers think of is that they cannot easily and quickly get information in the form of light intensity, precipitation, soil pH, soil moisture, soil temperature, humidity and air temperature. When farmers get the information they need from agricultural land, they usually get information through the internet so they are considered less efficient as it is quite time consuming. To solve this problem, a system is designed using the research and development method (RnD). A new Android-based application that can display data in text and graphics that are more easily accessible to farmers. This study creates an Android-based mobile application based on tests using the Android interface to display information about agricultural land conditions and display graphical data that is updated every 5 minutes. Keywords— Land monitoring, Agriculture, IoT, Android Mobile Application
Pendampingan Remaja dalam Alpha Camp Persekutuan Gereja-Gereja di Indonesia (PGI) Maslebu, Giner; Walangara Nau, Novriest Umbu; Sampoerno; Hermanto Abraham, Rendy; Wisnu Wibisono, Indra; Wahyono, Teguh; Dwi Purnomo, Hindriyanto; Kristianto, Budhi; Karema Sarajar, Dewita; Yuli Agung Suprabowo, Gunawan; C. Leuwol, Sylvie; Nahusona, Ferry; Picauly, Irma Amy
Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2024)
Publisher : Universitas Kristen Satya Wacana Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/jms.v5i22024p119-129

Abstract

Remaja merupakan suatu pelayanan kategorial yang menyasar kelompok usia antara anak-anak (sekolah minggu) dan pemuda. Tekanan stereotip, ekspektasi tinggi tanpa dukungan memadai, dibarengi dengan perubahan masif akibat kemajuan teknologi dan informasi dapat memicu permasalahan kesehatan mental generasi muda jika tidak dikelola dengan bijak. Tantangan lain yang dihadapi adalah mengenai spiritualitas remaja. Persekutuan Gereja-gereja di Indonesia (PGI) melihat perlunya mengadakan kegiatan bagi remaja dan pendamping/pembina remaja sebagai platform untuk memperlengkapi para remaja dan pembina dengan berbagai pengetahuan dan kapasitas yang diharapkan mampu membekali remaja dan pembina dalam pelayanan dan kehidupan berbangsa sehari-hari. Pendampingan yang dilakukan oleh para ahli di UKSW meliputi isu-isu seputar perkembangan psikologis, pengembangan bakat-minat, kecerdasan buatan dan implementasi dalam pelayanan serta gerakan cinta lingkungan lewat aksi tanam pohon di desa. Hasilnya, para peserta mendapatkan pengalaman berharga yang tampak dalam hasil survey kepuasan dimana mayoritas responden puas terhadap pendampingan dan 100 % responden memperoleh tambahan pengetahuan.
The Use of Naive Bayes for Broiler Digestive Tract Disease Detection Cahyaningtyas, Christyan; Purnomo, Hindriyanto Dwi; Kristianto, Budi
JITCE (Journal of Information Technology and Computer Engineering) Vol. 3 No. 01 (2019)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.3.01.1-7.2019

Abstract

Broiler chicken is a species of chicken that have high productivity. In order to get a good quality of chicken, good treatments of the breeding factors is needed, so the chicken will not easily infected by diseases. Gastrointestinal diseases are common disease that infects chickens. The mortality level caused by gastrointestinal diseases is considered high. This study is designed to address the problem by developing a system using the Naive Bayes algorithm. 60 chicken data samples were used, and the result shows that Naive Bayes might be used to detect gastrointestinal diseases among chickens with accuracy level of 93.3%. The number was confirmed by using confusion matrix evaluation method, and gave same level of accuracy compared to the expert judgments.
Digital Image Object Detection with GLCM Multi-Degrees and Ensemble Learning Kurniati, Florentina Tatrin; Purnomo, Hindriyanto Dwi; Sembiring, Irwan; Iriani, Ade
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.5597

Abstract

Object detection in digital images has been implemented in various fields. Object detection faces challenges, one of which is rotation problems, causing objects to become unknown. We need a method that can extract features that do not affect rotation and reliable ensemble-based classification. The proposal uses the GLCM-MD (Gray-Level Co-occurrence Matrix Multi-Degrees) extraction method with classification using K-Nearest Neighbours (K-NN) and Random Forest (RF) learning as well as Voting Ensemble (VE) from two single classifications. The main goal is to overcome the difficulty of detecting objects when the object experiences rotation which results in significant visualization variations. In this research, the GLCM method is used to produce features that are stable against rotation. Furthermore, classification methods such as K-Nearest Neighbours (KNN), Random Forest (RF), and KNN-RF fusion using the Voting ensemble method are evaluated to improve detection accuracy. The experimental results show that the use of multi-degrees and the use of ensemble voting at all degrees can increase the accuracy value, and the highest accuracy for extraction using multi-degrees is 95.95%. Based on test results which show that the use of features of various degrees and the ensemble voting method can increase accuracy for detecting objects experiencing rotation
Metaheuristics Approach for Hyperparameter Tuning of Convolutional Neural Network Purnomo, Hindriyanto; Tad Gonsalves; Evangs Mailoa; Santoso, Fian Julio; Pribadi, Muhammad Rizky
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 3 (2024): June 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i3.5730

Abstract

Deep learning is an artificial intelligence technique that has been used for various tasks. Deep learning performance is determined by its hyperparameter, architecture, and training (connection weight and bias). Finding the right combination of these aspects is very challenging. Convolution neural networks (CNN) is a deep learning method that is commonly used for image classification. It has many hyperparameters; therefore, tuning its hyperparameter is difficult. In this research, a metaheuristic approach is proposed to optimize the hyperparameter of convolution neural networks. Three metaheuristic methods are used in this research: ant colony optimization (ACO), genetic algorithm (GA), and Harmony Search (HS). The metaheuristics methods are used to find the best combination of 8 hyperparameters with 8 options each which creates 1.6. 107 of solution space. The solution space is too large to explore using manual tuning. The Metaheuristics method will bring benefits in terms of finding solutions in the search space more effectively and efficiently. The performance of the metaheuristic methods is evaluated using MNIST datasets. The experiment results show that the accuracy of ACO, GA and HS are 99,7%, 97.7% and 89,9% respectively. The computational times for the ACO, GA and HS algorithms are 27.9 s, 22.3 s, and 56.4 s, respectively. It shows that ACO performs the best among the three algorithms in terms of accuracy, however, its computational time is slightly longer than GA. The results of the experiment reveal that the metaheuristic approach is promising for the hyperparameter tuning of CNN. Future research can be directed toward solving larger problems or improving the metaheuristics operator to improve its performance.
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Ade Iriani Adimas Tristan Nagara Hartono Adriyanto Juliastomo Gundo Agung Wibowo Agus Priyadi Ahmad Bayu Yadila Andre Kurniawan Andrew Aquila Chrisanto Pabendon Andry Ananda Putra Tanggu Mara Andry Tanggu Mara Angela Atik Setiyanti Ani, Nyree Anton Hermawan Anwar, Muchamad Taufiq April Firman Daru April Lia Hananto Aris Puji Widodo Arseta, Gama Astawa, I Wayan Aswin Dew Atik Setyanti, Angela Aziz Jihadian Barid Azzahra Nurwanda Bandung Pernama Baun, Sindy Cristine Budhi Kristianto Budi Kristianto Budi Kristianto, Budi C. Leuwol, Sylvie Cahyaningtyas, Christyan Cahyo Dimas K Cesna, Galih Putra Chakim, Heru Riza Chandra Halim Charitas Fibriani Christyan Cahyaningtyas Daniel Kurniawan Daniel Kurniawan Danny Manongga Danu Satria Wiratama Deden Rustiana Dedy Prasetya Kristiadi Didit Budi Nugroho Dody Agung Saputro Dwi Hosanna Bangkalang Edwin Zusrony Eko Sediyono Eliansion Ivan eremia Silvester Sutoyo Erwien Christianto Evang Mailoa Evangs Mailoa Fajar Rahmat Faudisyah, Alfendio Alif Fauzi Ahmad Muda Feibe Lawalata Florentina Tatrin Kurniati Giner Maslebu Gladis Tri Enggiel Griya Jitri Pabutungan Gudiato, Candra Hanita Yulia Hanna Arini Parhusip Hari Purwanto Hendra Kusumah Hendra Waskita Hendradito Dwi Aprillian Hendro Steven Tampake Hendry Heni Pujiastuti Hermanto Abraham, Rendy Hery Santono HR. Wibi Bagas N Hsin Rau Huda, Baenil Hui-Ming Wee Irdha Yunianto Irwan Sembiring Istiarsi Saptuti Sri Kawuryan Istiarsih Saputri Sri Kawuryan Iwan Setiawan Iwan Setyawan Janinda Puspita Anidya Jihot Lumban Gaol Joanito Agili Lopo Jonas, Dendy Kainama, Marchel Devid Karema Sarajar, Dewita Kho, Delvian Christoper Krismiyati Kristoko Dwi Hartomo Lea Klarisa Lumban Gaol, Jihot Markus Permadi Mau, Stevanus Dwi Istiavan Maya Sari Mellyuga Errol Wicaksono Merryana Lestari Mira Mira Mira Muhammad Aufal Muhammad Rizky Pribadi Nadya Octavianna Lompoliuw Nahak, Yosef Jeffri Silvanus Nahusona, Ferry Nanle, Zeze Nina Rahayu Nina Setiyawati Ninda Lutfiani Nurrokhman, Nurrokhman Nurtino, Tio Permadi, Markus Picauly, Irma Amy Pratyaksa Ocsa Nugraha Saian Priatna , Wowon Purnama Harahap, Eka Purwanto - Purwanto Putri, Violita Eka Radius Tanone Ramos Somya Raynaldo Raynaldo Raynaldo Raynaldo, Raynaldo Richard William Kho Riko Yudistira Robert William Ruhulessin Rufina Rahma Ajeng Setyaningsih Safitri, Adila Sakalessy, Afelia Jozalin Elisa Sampoerno Santoso, Fian Julio Santoso, Fian Yulio Santoso, Joseph Teguh Sauntos, Oliver Setiyaji, Akhfan Sri Kawuryan, Istiarsi Saptuti Sri Sri Yulianto Joko Prasetyo Sugiman, Marcelino Maxwell Sutarto Wijono Syamsul Arifin Tad Gonsalves Tad Gonsalves Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tirsa Ninia Lina Tri Wahyuningsih Trivena Andriani Tukino, Tukino Tumbade, Marcho Oknivan Tungady, Cornelius Arvel Pratama Untung Rahardja Utama, Deffa Ferdian Alif Valentino Kevin Sitanayah Que Wahid, Syahrul Mu’Arif Walangara Nau, Novriest Umbu Wibowo, Mars Caroline Widyarini, Liza Wilujeng Ayu Nawang Sari Winny purbaratri Wisnu Wibisono, Indra Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yos Richard Beeh Yos Richard Beeh Yos Richard Beeh Yudistira, Riko Yuli Agung Suprabowo, Gunawan Yusuf, Natasya Aprila Zakaria, Noor Azura