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All Journal Jurnal Teknologi Industri Pertanian Jurnal Masyarakat Informatika JUTI: Jurnal Ilmiah Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Jurnal Teknik Informatika STMIK Antar Bangsa JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Ekonomi, Manajemen Akuntansi dan Perpajakan (Jemap) J I M P - Jurnal Informatika Merdeka Pasuruan Applied Information System and Management Jurnal Teknoinfo JURNAL PENDIDIKAN TAMBUSAI Jurnal Nasional Komputasi dan Teknologi Informasi Energi & Kelistrikan Indonesian Journal of Applied Informatics Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Literasiologi CSRID (Computer Science Research and Its Development Journal) Antivirus : Jurnal Ilmiah Teknik Informatika Industri Inovatif : Jurnal Teknik Industri Jurnal Ilmu Komputer dan Bisnis Aisyah Journal of Informatics and Electrical Engineering Jurnal Sistem Informasi dan Informatika (SIMIKA) Journal of Innovation and Future Technology (IFTECH) TIN: TERAPAN INFORMATIKA NUSANTARA JURNAL AKTUAL AKUNTANSI KEUANGAN BISNIS TERAPAN (AKUNBISNIS) Journal of Intelligent Computing and Health Informatics (JICHI) Teknika Jurnal Sistem Informasi Journal of Industrial and Engineering System Jurnal Sains Indonesia Bulletin of Computer Science Research Journal of Students‘ Research in Computer Science (JSRCS) Journal Software, Hardware and Information Technology Jurnal Media Informatika JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) Jurnal Mandiri IT J-Intech (Journal of Information and Technology) Jurnal Pustaka Mitra : Pusat Akses Kajian Mengabdi Terhadap Masyarakat Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Sains dan Teknologi Jurnal Sains Informatika Terapan (JSIT) Paradigma Indonesian Journal Computer Science (ijcs) Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Jurnal Komputer dan Teknologi (JUKOMTEK) CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Information Technology, Software Engineering and Computer Science Jurnal Ilmiah Sistem Informasi Bulletin of Artificial Intelligence Riau Jurnal Teknik Informatika International Journal of Education, Vocational and Social Science Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Journal of Information Technology Jurnal Teknoinfo Komputasi : Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Jurnal Teknik Informatika dan Teknologi Informasi Journal of Decision Support Systems and Multi-Criteria Decision Making (JODESMA)
Sumanto Sumanto
Universitas Bina Sarana Informatika
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Combination of Response to Criteria Weighting Method and Multi-Attribute Utility Theory in the Decision Support System for the Best Supplier Selection Ulum, Faruk; Wang, Junhai; Megawaty, Dyah Ayu; Sulistiyawati, Ari; Aryanti, Riska; Sumanto, Sumanto; Setiawansyah, Setiawansyah
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1810

Abstract

Choosing the right supplier is a strategic factor in supporting operational efficiency and a company's competitive advantage. This process requires a decision support system that is able to assess various alternatives objectively and in a structured manner. This study aims to develop a decision support system in the selection of the best supplier by combining the Response to Criteria Weighting (RECA) and Multi-Attribute Utility Theory (MAUT) methods. The RECA method is used to objectively determine the weight of each criterion based on the variation of data between alternatives, so as to reduce subjectivity in the weighting process. Meanwhile, the MAUT method functions to calculate the total utility value of each supplier based on the normalization value and weight that has been obtained. The results of the RECA method show the objective weight of each criterion, which is then used in the MAUT calculation process. The results of the analysis, obtained in the best supplier selection based on the total score of each candidate, it can be seen that PT Global Niaga Mandiri ranks first with the highest score of 0.6512, this shows that this company is the best choice in the supplier selection process. In second place is UD Anugrah Bersama with a score of 0.399, followed by PT Indo Logistik Prima in third place with a score of 0.3451. The combination of the RECA and MAUT methods has been proven to be able to produce accurate, rational, and accountable decisions. This system provides a measurable approach in filtering supplier alternatives efficiently and is relevant to be applied to various other multi-criteria decision-making contexts.
Decision support for trucking vendor selection at PT. Ricakusuma Lestari Abadi Based on the SAW method Indriyanti, Zahra Kiky Dwi; Sumanto, Sumanto
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.420

Abstract

PT. Ricakusuma Lestari Abadi is a company engaged in freight forwarding services, distributing goods both domestically and internationally. In the shipping process, the company heavily relies on third-party trucking services. However, the selection process for trucking vendors has so far been conducted manually, without standardized evaluation criteria, which risks leading to subjective and inefficient decisions. Therefore, this study aims to develop a decision support system to select the best trucking vendor using the Simple Additive Weighting (SAW) method. The SAW method is used because it provides objective evaluation results based on the weighting of five main criteria: service quality (40%), cost (25%), vehicle condition (15%), vendor location (10%), and fleet availability (10%) (Alamsyah et al., 2021; Gunawan et al., 2023; Wibowo & Azizah, 2022). This research adopts a quantitative approach through observation, interviews, and literature study. The collected data were used to calculate the scores of seven trucking vendor alternatives. The results show that Johan Putra Perkasa scored the highest with a value of 0.80 and is recommended as the best vendor. Kumala ranked second with a score of 0.75, followed by Global Sukses Transportama with a score of 0.72. The developed system was implemented as a web-based application using PHP and MySQL to facilitate a more efficient, faster, and standardized vendor selection process (Lim & Silalahi, 2023).
Analisis Klaster Pasien Diabetes Menggunakan Algoritma K-Means Berdasarkan Usia, Kadar Glukosa, dan Tekanan Darah Rizqi Ramadhani, Muhammad; Naufal Hermawan, Rezan; Fajrian, Ihsan; Aulia Rachmat, Daffa; Sumanto; `Diah Kuswanto, Andi
Riau Jurnal Teknik Informatika Vol. 4 No. 2 (2025): Juli 2025
Publisher : Prodi Teknik Informatika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjti.v4i2.3435

Abstract

Diabetes melitus adalah penyakit kronis yang terjadi akibat gangguan produksi atau pemanfaatan insulin, menyebabkan kadar gula darah tinggi. Penyakit ini dapat memicu komplikasi serius seperti jantung, ginjal, dan kerusakan saraf. Jumlah penderita diabetes terus meningkat, termasuk di Indonesia, yang dipengaruhi oleh faktor seperti genetik, gaya hidup tidak sehat, dan pola makan buruk. Untuk mendeteksi risiko diabetes lebih dini, teknologi data mining dapat dimanfaatkan. Penelitian ini menggunakan algoritma K-Means Clustering untuk menganalisis data kesehatan seperti kadar glukosa darah, tekanan darah, dan usia. Algoritma ini mengelompokkan individu ke dalam beberapa klaster berdasarkan kesamaan karakteristik kesehatan, guna mengidentifikasi kelompok risiko diabetes. Hasil analisis ini diharapkan dapat membantu tenaga medis dalam merancang intervensi dan rekomendasi pencegahan yang lebih tepat sasaran. Pendekatan ini memberikan solusi efisien dalam pengelolaan data besar di bidang kesehatan dan mendukung upaya penanggulangan diabetes secara lebih sistematis di Indonesia
Reinforcement learning for bitcoin trading: A comparative study of PPO and DQN Prasetyo, Romadhan Edy; Sumanto, Sumanto; Chaidir, Indra; Supriyatna, Adi
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.455

Abstract

Bitcoin’s high volatility demands automated strategies that adapt to changing market regimes while managing risk. This study compares Proximal Policy Optimization (PPO) and Deep Q-Network (DQN) for Bitcoin trading using hourly BTC/USDT data from 2019 to early 2025. The models are trained to generate buy and sell signals from technical indicators including the Relative Strength Index (RSI), MA20, volatility, Moving Average Convergence Divergence (MACD), volume trend, SMA200, and a weekly trend filter. All features are computed on hourly bars. The evaluation shows that PPO tends to trade more aggressively and delivers higher performance during bullish phases, though with greater risk in unstable markets. By contrast, DQN trades more selectively and maintains better stability in sideways or choppy conditions. These findings support the effectiveness of reinforcement learning for adaptive cryptocurrency trading and highlight complementary strengths between PPO and DQN across market regimes.
Komparasi Naive Bayes dan SVM untuk Analisis Sentimen Pada E-Commerce Seller Center Yanuar Laik, Abraham Adrian; Nabilla, Adinda; Diah, Andi; Sumanto; Indra, Ahmad; Arya, Yudi
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3211

Abstract

The development of e-commerce drives the need to understand customer opinions through sentiment analysis to improveservice quality. Tokopedia and TikTok Shop as popular e-commerce platforms provide a review feature that can be asource of data to analyze consumer perceptions. This study aims to compare the performance of two text classificationalgorithms, namely Naive Bayes and Support Vector Machine (SVM), in analyzing the sentiment of customer reviews takenfrom the TikTok Tokopedia Seller Center dataset. The research method used is a computational experiment with aquantitative approach. The dataset used is sourced from the Kaggle site and is available in clean and labeled conditions(positive and negative). Model evaluation is done by measuring accuracy, precision, recall and F1-score. The results showthat Naive Bayes is superior with 97.50% accuracy and 84.00% F1-score, compared to SVM which obtained 94.90%accuracy and 76.80% F1-score. Thus, Naive Bayes is considered more effective for sentiment analysis of e-commercecustomer reviews
Optimizing printer usage through data analytics for enhanced institutional efficiency Kadir, Fauwas Abdul; Sumanto, Sumanto
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.453

Abstract

The advancement of information technology had simplified various workplace processes, including document processing and printing. In an institution, the use of printers played a crucial role in daily operations. However, without proper management, printer usage often became inefficient, leading to increased operational costs and unnecessary waste of resources. Therefore, an analytical system was needed to monitor and optimize printer usage. Such a system provided valuable insights by analyzing data generated from printing activities. This data analysis revealed patterns in work habits and allowed institutions to make informed decisions. As a result, institutions were able to improve operational efficiency, reduce costs, and minimize environmental impact. Paper and ink waste were significantly reduced by implementing data-driven policies. Overall, the integration of data analytics into printer management contributed to sustainable practices and better resource allocation in institutional environments.
Combination of Objective Weighting Method using MEREC and A New Additive Ratio Assessment in Coffee Barista Admissions Arshad, Muhammad Waqas; Suryono, Ryan Randy; Rahmanto, Yuri; Sumanto, Sumanto; Sintaro, Sanriomi; Setiawansyah, Setiawansyah
TIN: Terapan Informatika Nusantara Vol 5 No 3 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i3.5771

Abstract

A coffee barista is a professional who is skilled in the art of brewing and serving coffee in an attractive and high-quality way. The role of a barista is not only limited to operating an espresso machine and grinding coffee beans, but also includes in-depth knowledge of different types of coffee beans, manufacturing techniques, and the resulting flavors. The main problem in the acceptance of coffee baristas often has to do with the gap between industry expectations and the skills possessed by prospective workers. Many candidates may lack formal training or practical experience in brewing coffee, so they do not meet the standards expected by cafes or restaurants. The purpose of the research on the Combination of Objective Weighting Methods using MEREC and ARAS in Coffee Barista Admission is to develop and apply a more systematic and objective approach in the selection process of prospective baristas. The combination of objective weighting methods and the new additive ratio assessment (ARAS) approach offers a sophisticated framework for evaluating candidates in coffee barista admissions. The objective weighting method ensures that evaluation criteria are prioritized based on their intrinsic importance, thereby minimizing subjective preference. When combined with the ARAS method, which ranks alternatives based on their performance ratio to the ideal solution, this approach provides a balanced and comprehensive assessment for each candidate. Based on the results of the evaluation of the barista admission selection, Clara Dewi ranked first with the highest final score of 0.98553, followed by Hanafi Lestari with a score of 0.95921 and Erika Santosa with a score of 0.95726 who ranked second and third.
Texture Analysis of Citrus Leaf Images Using BEMD for Huanglongbing Disease Diagnosis Sumanto; Buono, Agus; Priandana, Karlisa; Paruhum Silalahi, Bib; Sri Hendrastuti, Elisabeth
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.1075

Abstract

Plant diseases significantly threaten agricultural productivity, necessitating accurate identification and classification of plant lesions for improved crop quality. Citrus plants, belonging to the Rutaceae family, are highly susceptible to diseases such as citrus canker, black spot, and the devastating Huanglongbing (HLB) disease. Traditional approaches for disease detection rely on expert knowledge and time-consuming laboratory tests, which hinder rapid and effective disease management. Therefore, this study explores an alternative method that combines the Bidimensional Empirical Mode Decomposition (BEMD) algorithm for texture feature extraction and Support Vector Machine (SVM) classification to improve HLB diagnosis. The BEMD algorithm decomposes citrus leaf images into Intrinsic Mode Functions (IMFs) and a residue component. Classification experiments were conducted using SVM on the IMFs and residue features. The results of the classification experiments demonstrate the effectiveness of the proposed method. The achieved classification accuracies, ranging from 61% to 77% for different numbers of classes, the results show that the residue component achieved the highest classification accuracy, outperforming the IMF features. The combination of the BEMD algorithm and SVM classification presents a promising approach for accurate HLB diagnosis, surpassing the performance of previous studies that utilized GLCM-SVM techniques. This research contributes to developing efficient and reliable methods for early detection and classification of HLB-infected plants, essential for effective disease management and maintaining agricultural productivity.
Prediksi Harga Emas di Indonesia menggunakan Metode Linear Regression Berbasis Data Historis Antam Cahya, Titus Dwi; Sumanto, Sumanto; Chaidir, Indra
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.21047

Abstract

This study uses a simple linear regression method to predict gold prices in Indonesia using historical Antam gold data. Linear regression is applied to model the linear relationship between the 2024 daily gold price (variable Y) and the date (variable X). Model performance is evaluated using Mean Squared Error (MSE) and R-squared (R²) to ensure more stable and accurate results. The evaluation results show that the linear regression model used has an MSE of 1403425123.8609 and an R² of 0.93, indicating good performance in predicting gold prices. This study concludes that the simple linear regression method can be used to predict gold prices throughout the year (long-term), but cannot accurately predict daily prices.
Pengembangan Sistem Deteksi Objek Botol Real-Time dengan YOLOv8 untuk Aplikasi Vision Triyanto, Dedi; Zidan, Muhammad; Wahyudi, Mochamad; Pujiastuti, Lise; Sumanto, Sumanto
Indonesian Journal Computer Science Vol. 3 No. 1 (2024): April 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijcs.v3i1.6070

Abstract

Plastik daur ulang berperan penting dalam menanggulangi masalah limbah lingkungan sekaligus mendukung praktik keberlanjutan. Penelitian ini bertujuan mengembangkan sistem deteksi botol plastik dan kaleng daur ulang secara real-time menggunakan algoritma YOLOv8 yang terkenal akan kecepatan dan akurasinya. Dengan memanfaatkan dataset yang terdiri dari 2.900 gambar dan melatih model melalui Google Colab selama 25 epoch, penelitian ini berhasil menunjukkan performa luar biasa dari YOLOv8, dengan hasil mAP sebesar 99,5%, precision 99,7%, dan recall 99,5%. Model ini terbukti sangat efektif dalam mendeteksi objek daur ulang, memberikan prediksi yang tepat tanpa kesalahan negatif pada confusion matrix. Untuk penelitian lanjutan, disarankan menambah variasi kelas objek seperti botol kaca dan karet serta memperluas dataset guna meningkatkan generalisasi model. Selain itu, pengujian dalam kondisi nyata sangat diperlukan untuk memastikan kinerja optimal dalam lingkungan yang lebih kompleks. Pendekatan serupa dalam penelitian sebelumnya juga telah membuktikan kinerja unggul dalam deteksi real-time, menjadikan metode ini salah satu yang terdepan dalam pengembangan teknologi berbasis YOLO.
Co-Authors Aberahamo Onoma Marundrury Achmad Rivai Syahputra Ade Budiman, Ade Ade Christian Ade Christian Ade Christian Ade Christian Adhiani, Budhi Adi Pangestu Adi Supriyatna Adinugroho, Wisnu Aditia Yudhistira Adryan Raihan Syakir Agung Wibowo Agus Buono Agus Santoso Ahmad Habibullah Ahmad Rais Ruli Ahmad Syukri Gozali Ahmad Yani ahmad yani Ahmad Yani Ahmad Yani , Ahmad Yani Alamsyah, Muhammad Arkan Alghifar Firgiawan Alghiffary, Muhammad Adya Ali Mahmudi Ali, Muhamad Hafis Ali, Satrio Nur Alwan Kapi Muntaha Alya Avisa Andi Diah Kuswanto Andi Setiawan Andika Amansyah Andri Amico Andriansyah Tri Laksono Anggreani, Namira Anita Adelia Syahfitri Apip Supiandi Ardiyansyah, Rizqi Ari Sulistiyawati Ariskawati, Mila Arnata Nur Rasyid Arshad, Muhammad Waqas Arya, Yudi Asmawati Asmawati Audy Aulia Azzahra Aulia Rachmat, Daffa Aziz Bayu Permata Azkia, Farah Diba Bib Paruhum Silalahi Bismo Raharjo, Yohanes Aryo Budhi Adhiani Budhi Adhiani Christina Budi Santoso Budiman, Ade Surya Cahya, Titus Dwi Cahyani Ayu Sulistyawati Damayanti Damayanti Darmawi . Dedi Darwis Dedi Triyanto Dedi Triyanto DENY KURNIAWAN Deny Kurniawan Desiana Nuranudin Putri Desyanti Desyanti Dewi, Revinta Arrova Diah, Andi Dinda Aprillia Dwiki Gilang Ramadhani Dyah Ayu Megawaty Dyani Kalyana Mitta Eka Dyah Setyaningsih Eka Putri Alvi Syahrina Elisabeth Sri Hendrastuti Erlangga Rizki Ekaptra Fadila Shely Amalia Fahrian Fahroni, Aldiwa Alfa Thira Nur Faiz Djarot, Raihan Jamal Faiz Najwan Zaky Fajar Akbar Fajar Yoga Adiansyah Fajrian, Ihsan Fardha Hasykir Farhan Fadhilah Faris Syahrendra Faruk Ulum Fathur Rismansyah Fauzan Nawwir Andriansyah Fauzan, Muhammad Indra Fransiscus Andre Suwarno Ganda Wijaya Ganda Wijaya, Ganda Ghofar Taufiq Gilang Virgiawan Ginting Wibi Prasetyo Hafis Nurdin Harianto Harianto Hariyanto Hariyanto HARIYANTO HARIYANTO Hartanti Hartanti Hartono Hartono Heni Nur Kusumawati Herdinan Tito Hetty Rohayani Hidayat, Manarul Hilmy Ibrahim, Farras Idha Rizqi Pratiwi Imam Budiawan Imam Budiawan Imam Budiawan Imam Budiawan Imam Budiawan Imam Wahyudi Iman Febriansya Putra Indah Oktavia Zalmi Indra Chaidir, Indra Indra, Ahmad Indriani , Karlena Indriyanti, Zahra Kiky Dwi Insani Abdi Bangsa Iqro Mukti Arto Jefina Tri Kumalasari Jefina Tri Kumalasari Jefina Tri Kumalasari Joko Tri Haryanto Joseph Melchior Nababan Juanny Cheristy Souisa Julkarnaen Karo-Karo Jumaryadi, Yuwan Junhai Wang Junhai Wang Junhai Wang Junhai Wang Junhai Wang Kadir, Fauwas Abdul Kaisar Ages Querio Karlena Indriani Karlisa Priandana Kevin Dwi Satria Kotjek, Rafie Kumalasari Kumalasari Kuswanto, Andi Diah Laura Gabriel da Silva Lia Mazia, Lia Lise Pujiastuti Lise Pujiastuti Lita Sari Marita Maharani Rona Makom Makom, Maharani Rona Mantriwira, Daniel Mardinawat Mardinawat Mardinawati Mardinawati Mardinawati, Mardinawati Megawaty, Dyah Ayu Meydina Aulia Savitri Micho Respati Putra Mochamad Fathur Milzam Mochamad Wahyudi Muhamad Fadli Fadhlullah Muhamad Rendi Gibran Muhammad Furqon Prasetyo Muhammad Haikal Abidin Muhammad Hendra Hernawan Muhammad Hussein Umar Muhammad Raviansyah Muhammad Rifqi Asy'ari Muksin Hi Abdullah Musfiroh Musfiroh, Musfiroh Nabilla, Adinda Naufal Hermawan, Rezan Nindya Dwi Lestari Ningtyas, Listina Ade Widya Nirwana Hendrastuty Noviyanto Noviyanto Nurfia Oktaviani Syamsiah Nurrahman, Alvin Paduloh Paduloh Pakpahan, Roida Pasaribu, A. Ferico Octaviansyah Paulus Paulus Permata, Permata Prasetyo Adi Suwignyo Prasetyo, Romadhan Edy Pribadi, Denny Pricillia Pujiastuti, Lise Purwandani, Indah Putra Satria Putra, Imam Hanif Qais Abdurrachman Rachmat Adi Purnama Raditya Rimbawan Oprasto Rafi Kurniawan Rafi Rasendriya Raihan Naufal Ramadhan Raihan Primadana Raihan Raihan Ramadani, Achmes Dade Ramadhan, Muhammad Gilang Ramadhani, Varla Octavia Rani, Maulidina Cahaya Rasya Abel Putra Gumulija Ratiyah* Ratiyah Ratnasari, Arum Retno Winarti Reynaldi , Reynaldi Rian Hidayat Riansyah Gustian Ridwan, Asrifia Rifda Ilahy Rosihan Rifki Nur Hidayat Putra Riska Aryanti Rivaldi, Muhammad Rizal Maulana Rizky Daud Antony Pangaribuan Rizqi Ramadhani, Muhammad Rofiqi, Ainur Roida Pakpahan Roida Pakpahan Roida Pakpahan Roida Pakpahan Roida Pakpahan Roni Saputra Pratama Ruhul Amin Rumidjan Rumidjan, Rumidjan Rusda Wajhillah Ryan Dwi Aprilyanto Ryan Randy Suryono Ryehan Alfiansyah Safinah Faatin Sanriomi Sintaro Santosa, Teguh Budi Saputra, Sabita Abigail Saputra, Yusup Saputri, Fifin Sefriani, Shintia Putriayu Sentanu, Quinn Abrar Athallah Sentot Achmadi Setiawan, Dandi Setiawansyah Setiawansyah Setiawansyah Siregar, Denny Solihin Solihin Sopyan Sri Hendrastuti, Elisabeth Sri Sugiharti Suci, Bintang Dyas SUKAMTI . Sulaiman Sulaiman Sulistyo Sulistyo Sumarna Sumarna Sumarna Sumarna Suparno Suparno Suwandi Suwandi Tabrani, Tabrani Tarmidzi Ibrahim Taufig, Ghofar Teguh Budhi Santosa Teguh Budi Santosa Temi Ardiansah Teuku Vaickal Rizki irdian Tri Widian Ratnasari Trisna Andhika Saputra Ulum, Faruk Umam, Hairul Ummu Radiyah, Ummu Vemi Januar Pratama Vera Agustina Yanti Wahyudi, Agung Deni Wang, Junhai Wardani, Maidy Tri Wattilah, Florentina Widya Viona Septi Tanjung Wijaya, Filzah Wina Ningsih Yakobus Linus Jumadi Yamani, Teuku Arrasy Yanuar Laik, Abraham Adrian Yunardus Yunardus Yundari, Yundari Yuri Rahmanto Zahwa Asfa Rabbani Zayyan Nauval Araf Zidan, Muhammad `Diah Kuswanto, Andi