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Ema Utami

Universitas Amikom Yogyakarta

Author-ID : 259410

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Simple Selection Index (SSI) Method in Electric Vehicle Selection for Logistics Companies Bisono, Hadi Hikmadyo; Utami, Ema
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5434

The rapid development of electric vehicles (EVs) has encouraged various industrial sectors, including logistics, to transition from fossil fuel-based vehicles to more environmentally friendly solutions. While EVs offer advantages such as energy efficiency, reduced carbon emissions, and lower operating costs, selecting the right electric vehicle for a logistics company is not a straightforward task. The main challenge lies in the wide variety of available models, each with different technical and operational specifications. This complexity increases as companies must consider multiple criteria such as price, payload capacity, vehicle width, battery capacity, and cargo volume. Therefore, a systematic approach is needed to support decision-making. One commonly used approach is the Multi-Criteria Decision-Making (MCDM) method. This study introduces the Simple Selection Index (SSI) method, a newly developed MCDM approach designed as a simplified version of the Preference Selection Index (PSI) method. The novelty of SSI lies in its ability to eliminate complex steps such as the calculation of preference variation values and preference deviation scores, making the ranking process more concise and easier to apply—without compromising the accuracy of the results. The study aims to evaluate the performance of the SSI method in selecting the most suitable electric vehicle by directly comparing its results with those of the PSI method, using a dataset comprising four vehicle alternatives and five key criteria: price, payload, width, battery capacity, and cargo volume. The findings show that the SSI method produces an identical ranking to the PSI method, with EV-4 as the top recommendation and EV-1 as the second-best alternative. With its more efficient process, the SSI method holds strong potential for application in fast and straightforward multi-criteria decision-making scenarios.

DiG-MFV: Dual-integrated Graph for Multilingual Fact Verification Agustina, Nova; Kusrini; Utami, Ema; Hidayat, Tonny
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6695

The proliferation of misinformation in political domains, especially across multilingual platforms, presents a major challenge to maintaining public information integrity. Existing models often fail to effectively verify claims when the evidence spans multiple languages and lacks a structured format. To address this issue, this study proposes a novel architecture called Dual-integrated Graph for Multilingual Fact Verification (DiG-MFV), which combines semantic representations from multilingual language models (i.e., mBERT, XLM-R, and LaBSE) with two graph-based components: an evidence graph and a semantic fusion graph. These components are processed through a dual-path architecture that integrates the outputs from a text encoder and a graph encoder, enabling deeper semantic alignment and cross-evidence reasoning. The PolitiFact dataset was used as the source of claims and evidence. The model was evaluated by using a data split of 70% for training, 20% for validation, and 10% for testing. The training process employed the AdamW optimizer, cross-entropy loss, and regularization techniques, including dropout and early stopping based on the F1-score. The evaluation results show that DiG-MFV with LaBSE achieved an accuracy of 85.80% and an F1-score of 85.70%, outperforming the mBERT and XLM-R variants, and proved to be more effective than the DGMFP baseline model (76.1% accuracy). The model also demonstrated stable convergence during training, indicating its robustness in cross-lingual political fact verification tasks. These findings encourage further exploration in graph-based multilingual fact verification systems.

PENINGKATAN RESOLUSI VIDEO MUSIK LAWAS INDONESIA MENGGUNAKAN REAL ESRGAN X4PLUS Alfansani, Abdul Rauf; Utami, Ema; Ariatmanto, Dhani
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.6146

Video musik Indonesia lawas yang diproduksi pada era VCD umumnya memiliki kualitas visual rendah dan degradasi artefak yang signifikan. Penelitian ini mengevaluasi efektivitas model Real?ESRGAN?X4plus dalam meningkatkan resolusi video-video tersebut menggunakan pendekatan super?resolusi berbasis pembelajaran mendalam. Eksperimen dilakukan pada lima video dengan resolusi awal 480p yang ditingkatkan menjadi 1920p, dengan variasi parameter denoise_strength dari 0,0 hingga 1,0 dan tile_size dari 64 hingga 256. Model ini dibandingkan dengan metode interpolasi bicubic dan ESRGAN publik sebagai baseline. Evaluasi dilakukan menggunakan metrik PSNR dan SSIM, serta uji statistik paired t?test. Hasil menunjukkan bahwa konfigurasi optimal adalah denoise_strength = 0.0 dan tile_size = 256, menghasilkan PSNR tertinggi (35,10 dB) dan SSIM terbaik (0,956). Dibanding baseline, Real?ESRGAN memberikan peningkatan kualitas yang signifikan baik secara obyektif maupun visual. Model ini juga menunjukkan potensi dalam mempertahankan detail halus dan konsistensi temporal antar frame. Temuan ini mendukung pemanfaatan Real?ESRGAN sebagai solusi restorasi video budaya Indonesia, serta membuka peluang untuk pengembangan lanjut berbasis VSR temporal.

Evaluating YOLOv8-Based Distance Estimation: A Comparison of OpenCV and Coordinate Attention Weighting in Blind Navigation Systems Syahrudin, Erwin; Utami, Ema; Hartanto, Anggit Dwi; Raharjo, Suwanto
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 2 (2025): August 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i2.24395

Background: Recent developments in assistive technologies for the visually impaired have increasingly utilized computer vision techniques for real-time distance estimation. However, challenges remain in balancing accuracy, latency, and robustness under dynamic environmental conditions. Objective: This study aimed to evaluate and compare the performance of OpenCV and Coordinate Attention Weighting (CAW) models for distance estimation in blind navigation systems, particularly focusing on their effectiveness in real-time scenarios. Methods: A quantitative experimental study was conducted using an image dataset labeled with actual distances. The baseline performances of OpenCV and CAW were measured and compared. Subsequently, targeted optimizations were applied to the OpenCV model, including adaptive image filtering, hyperparameter tuning, and integration of a Kalman filter. Results: Initial evaluation showed that CAW achieved a higher baseline accuracy of 88% compared to OpenCV. However, after optimizations, OpenCV’s accuracy improved by 15%, reaching approximately 85%. Additionally, the optimized OpenCV model demonstrated reduced latency, outperforming CAW in real-time detection speed. Under varying lighting and motion conditions, OpenCV also exhibited superior robustness compared to CAW. Conclusion: The findings suggest that with proper optimization, OpenCV can match or exceed CAW in key performance aspects, making it a viable and efficient alternative for real-time distance estimation in blind navigation systems. Future research should explore further model integration and hardware acceleration for deployment in wearable devices.

Hybrid Fuzzy Logic, Genetic Algorithms, and Artificial Neural Networks for Cattle Body Weight Prediction Anjar Setiawan; Ema Utami; Dhani Ariatmanto
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2025): Juli : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v5i2.1319

Cattle serve as the primary means of meat and milk production in numerous regions across the globe. Enhancing efficiency and productivity in cow ranching can provide significant economic consequences. The cattle industry is significant as it enables the estimation of cow weight, directly influencing beef and milk quality. This study aims to enhance the accuracy of cattle weight estimation by minimizing the Mean Squared Error (MSE) values. The integration of artificial neural network (ANN), fuzzy logic (FL), and genetic algorithm (GA) techniques is a promising artificial intelligence tool for predicting and modeling cattle weight in livestock weight prediction systems. The cow weight forecast yielded a Mean Squared Error (MSE) value of 10.9 kg, which is the best result. The results demonstrate the progress made in agriculture using advanced technologies. They offer a detailed examination of how artificial intelligence, fuzzy logic, and evolutionary techniques can be combined to address the many difficulties associated with estimating cattle body weight.

Deep Learning Models For Youtube Sentiment Analysis: A Comparative Study Of Bert And Gru In Danantara Indonesia Rizy, M. Alfa; Utami, Ema
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 2 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i2.12064

This study aims to analyse public sentiment toward Danantara Indonesia through YouTube comments and compare the performance of two deep learning models, BERT and GRU, in sentiment classification. The dataset consists of 1,065 comments collected through scraping techniques, which were pre-processed and classified into three sentiment categories: positive, neutral, and negative. The results indicate that the IndoBERT model achieved 100% accuracy, with perfect precision, recall, and F1-score for all sentiment classes. In contrast, the GRU model only achieved 60% accuracy, showing a tendency to classify almost all comments as negative sentiment. Sentiment distribution analysis reveals that the majority of comments (60%) express negative sentiment, followed by positive sentiment (25%) and neutral sentiment (15%). The dominance of negative sentiment suggests public distrust and criticism regarding the policies and transparency of Danantara Indonesia. These findings demonstrate that BERT is a more accurate model for sentiment analysis of Indonesian-language texts. Furthermore, this study recommends further evaluation to address data imbalance and improve the model’s generalization across various social contexts in digital media.

Prediksi Harga Bitcoin Menggunakan Model Hibrida Transformer Dan Long Short Term Memory Irawan, Rio; Utami, Ema
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 9 (2025): JPTI - September 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1091

Peramalan harga Bitcoin merupakan tantangan signifikan akibat fluktuasi pasar yang tinggi, di mana model deret waktu konvensional seringkali gagal menangkap dependensi data jangka pendek dan panjang secara bersamaan. Untuk mengatasi masalah tersebut, penelitian ini bertujuan mengembangkan dan mengevaluasi model deep learning hibrida guna meningkatkan presisi peramalan harga Bitcoin. Model yang diusulkan mengintegrasikan arsitektur Long Short-Term Memory (LSTM), yang andal dalam memproses data sekuensial, dengan mekanisme atensi pada Transformer yang mampu mengidentifikasi hubungan data yang relevan. Metode penelitian mencakup penggunaan data harga historis Bitcoin yang telah melalui tahap pra-pemrosesan dan normalisasi. Arsitektur model terdiri dari dua lapisan LSTM (30 unit), diikuti oleh lapisan Transformer dengan Multi-Head Attention (satu head, dimensi kunci empat), dan diakhiri dengan lapisan Global Average Pooling. Pelatihan model dilakukan menggunakan konfigurasi optimal selama 10 epoch dengan ukuran batch 64. Hasil evaluasi menunjukkan kinerja prediksi yang sangat akurat, dibuktikan dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 0,000695 dan R-squared (R²) 0,99999. Temuan ini menegaskan bahwa pendekatan hibrida efektif dalam menangkap pola kompleks pada data harga Bitcoin, sehingga menawarkan alat yang lebih kuat untuk analisis keuangan di pasar cryptocurrency.

DEGREE: Development and Validation of a User Experience Model for Digital Educational Games Using Cronbach’s Alpha and Fuzzy Logic Kurniawan, Mei Parwanto; Suyanto, M.; Utami, Ema; Kusrini, Kusrini
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4942

The rapid growth of digital educational games demands an evaluation model that accurately captures user experience and adopts a human-centred approach. This study introduces DEGREE (Digital Educational Game Review and Evaluation Engine), an enhanced model extending MEEGA+ by incorporating two previously underrepresented dimensions: Control and Feedback. Using a quantitative approach, questionnaires were distributed to high school students who actively use Minecraft and Duolingo, yielding 4800 responses.Reliability analysis via Cronbach’s Alpha revealed that the Player Experience + Control combination achieved the highest score (α = 0.914), while the inclusion of Feedback reduced reliability (α = 0.864), leading to its exclusion in the final model. The DEGREE model consists of two core domains: Usability (Aesthetics, Learnability, Operability, Accessibility) and Player Experience (Focused Attention, Fun, Challenge, Social Interaction, Confidence, Relevance, Satisfaction, Perceived Learning, User Error Protection, Control). Evaluation scores were calculated using the Fuzzy Weighted Average (FWA) method and Mean of Maximum (MoM) defuzzification. The Control dimension emerged as the most influential (0.2735), followed by Fun (0.2664) and Satisfaction (0.2516), highlighting the significance of user agency in digital learning environments. The DEGREE model offers a statistically robust and user-oriented framework for evaluating educational games, delivering actionable insights for developers and educators to design more effective and engaging digital learning experiences. This study contributes a new validated and generalizable evaluation framework that strengthens the theoretical foundation of user experience assessment in educational game design.

DEVELOPMENT RICE PLANT DISEASE CLASSIFICATION USING CNN WITH TRANSFER LEARNING Fitrony, Fachri Ayudi; Utami, Ema
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 4 (2025): September 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i4.4159

Abstract: The rice plant, Oryza sativa, is a major food source in Indonesia. This plant is processed into rice, a staple food for the Indonesian people. Rice growth is crucial to ensure the rice produced is of good quality. One part of the rice plant that is susceptible to disease is the leaves, which can inhibit growth and reduce rice quality. Therefore, early detection and accurate classification of rice diseases are crucial to minimize these negative impacts. This has driven the development of a Deep Learning model capable of high-performance automatic classification. This study aims to create a rice leaf classification model using the CNN algorithm and several transfer learning architectures such as ResNet101, VGG16, and Xception. A dataset of 859 rice leaf images collected from the Kaggle website was then processed using augmentation techniques to a total of 2,439 images, plus 215 smartphone photos for external data validation. Thus, the total dataset increased to 2,656 images, covering four categories: leafblast, brownspot, healthy, and hispa. The model was processed in two stages: on the initial dataset (Non-Augmented Dataset) and the Augmented Dataset. The best experimental results were obtained using the ResNet architecture, with a training accuracy of 96.17% and a validation accuracy of 95.22%. Based on the research results, the rice plant disease classification model using deep learning demonstrated good performance. Keywords: convolutional neural network; deep learning; fine-tuning; image classification; resnet; rice plant

PERBANDINGAN ALGORITMA SVM DAN RANDOM FOREST PADA KLASIFIKASI KESEHATAH MENTAL BERDASARKAN SLEEP DISORDERS Pulungan, Linda Nurul Taqwa; Utami, Ema
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.7392

Kesehatan mental semakin menjadi isu global yang mendesak, dengan meningkatnya prevalensi gangguan mental yang mempengaruhi jutaan individu di seluruh dunia. Penelitian ini bertujuan untuk mengevaluasi kinerja dua algoritma pembelajaran mesin, yaitu Support Vector Machine (SVM) dan Random Forest, dalam mendeteksi gangguan kesehatan mental melalui analisis pola tidur. Data yang digunakan berasal dari dataset "Stress Level Detection" di Kaggle, yang telah mengalami augmentasi menjadi 1.375 sampel. Dataset dibagi menjadi 80% untuk pelatihan model dan 20% untuk pengujian. Hasil penelitian menunjukkan bahwa algoritma Random Forest memiliki kinerja yang lebih baik dibandingkan SVM, dengan akurasi mencapai 91% dan F1-score rata-rata 89%. Sementara itu, SVM memperoleh akurasi 83% dan F1-score rata-rata 81%. Secara spesifik, Random Forest lebih efektif dalam mendeteksi pola tidur normal serta gangguan seperti insomnia. Temuan ini menunjukkan potensi pembelajaran mesin, terutama Random Forest, sebagai alat yang efektif untuk deteksi dini gangguan kesehatan mental melalui analisis pola tidur, yang dapat digunakan untuk mendukung diagnosis lebih cepat dan akurat.

Co-Authors , Anggit Dwi Hartanto A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA Abdul Malik Zuhdi Abdullah Ardi Abdullah, Riska K Abdulrahmat E Ahmad Abyan Fauzi Widihasani Achmad Yusron Arif Ade Pujianto Adi Surya Adiatma, Biva Candra Lutfi Adipradana, Candra Afif, Muhammad Sholih Afifah Nur Aini Afis Julianto Aflahah Apriliyani Afu Ichsan Pradana Agun Nurul Widiyanto Agung Budi Prasetio Agung Budi Prasetio Agung Budi Prasetio Agung Budi Prasetyo Agung Dwi Cahyanto Agung Nurhidayatullah, Rizqy Agung Susanto Agus Fathurahman Agus Fatkhurohman AGUS PURWANTO Agustin, Tinuk Agustina Srirahayu Agustina, Nova Ahmad Fauzi Ahmad Febri Diansyah Ahmad Fikri Iskandar Ahmad Fikri Iskandar Ahmad Fikri Iskandar Ahmad Hajar Ahsan, Muhammad Rafiqudin Ahsan, Muhammad Rafiqudin Ain, Quratul Ainul Yaqin Ainul Yaqin Ainul Yaqin Aji Said Wahyudi Hidayat Akbar Akbar Akhmad Dahlan Al Fathir As, Rahmat Saudi Aldy A Kulakat Alfansani, Abdul Rauf Alfin Mahadi Alimuddin Yasin Alin, Octhavia Almi Yulistia Alwanda Alqowiy, Mohd Qorib Alsyaibani, Omar Muhammad Altoumi Alva Hendi Muhammad Alva Hendi Muhammad Alva Hendi Muhammad Alvhinia Meinda Amitaba Alvian Trias Kurniawan Alvian Trias Kurniawan Alvina Felicia Watratan Amir Fatah Sofyan Amir, Fail Amrullah, Ahmad Afief Amrullah, Ahmad Afief Amrullah, Yusuf Amri Andang Wijanarko Andhika Wisnu Widyatama Andhika Wisnu Widyatama Andi Sunyoto Andrie Prajanueri Kristianto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto, Anggit Dwi Anggit Hartanto Anggriandi, Dendi Anip Moniva Anisa Rahmanti Anisya Nursyah Gusman Anjar Setiawan Annisa Rahayu P Anwar Sadad Ardi, Abdullah Arfian Hendro Priyono Arham Rahim Ari Rudiyan Arief Setyanto Arief, M.Rudyanto Arif Nur Rohman Arif Rahman Arif Santoso Arif Sutikno Arif, Achmad Yusron Aris Setiyadi aristin chusnul khotimah Arli Aditya Parikesit Armadiyah Amborowaty Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Arvi Pramudyantoro Arya Luthfi Mahadika Asrawi, Hannan Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asrul Abdullah Astica, Yustikamasy Atin Hasanah Aziza Devita Indraswari Bambang Sumantri, R Bagus Bangun Watono Banu Dwi Putranto Basri, Nur Faizal Bayu Setiaji Béjar, Rodrigo Martínez Bety Wulan Sari BHANU SRI NUGRAHA Bima Widianto Bisono, Hadi Hikmadyo Biva Candra Lutfi Adiatma Bonifacius Vicky Indriyono Bonifacius Vicky Indriyono, Bonifacius Vicky Brahmantha, Gede Putra Aditya Budi, Agung Prasetio Buyut Khoirul Umri Cahya Pangestu, Galang Candra Adipradana Candra Aditya Pinuyut Carolina, Vinnesa Patricia Catur Iswahyudi Catur Iswahyudi Catur Riyono Heri Wibowo Cecep Yedi Permana Chan Uswatun Khasanah Chavid Syukri Fatoni Christina Andriyani Constantin Menteng D. Diffran Nur Cahyo Dalillah Razan S Danar Putra Pamungkas, Danar Putra Dandi Sunardi Dany Fajar Kristanto Saputro Wibowo David Agustriawan Dede Sandi Dedy Ikhsan Dedy Sugiarto Deny Nugroho Triwibowo Dewi Yustika Lakoro Dhana Aulia Ayu Kurniawan Dhanar Intan Surya Saputra Dhani Ariatmanto DHANI ARIATMANTO Dhani Ratna Sari Dhani Ratna Sari, Dhani Ratna Dibyo Sudarsono Dimaz Arno Prasetio Dina Juni Marianti Dloifur Rohman Al Ghifari Donni Prabowo Donny Yulianto Dwi Ahmad Dzulhijjah Dwi Hartanto, Anggit Dwi Hartono, Anggit Dwi Rahayu Dwi Yuli Prasetyo Dzulhijjah, Dwi Ahmad Edhy Sutanta (Jurusan Teknik Informatika IST AKPRIND Yogyakarta) Edi, Mohammad Eko Boedijanto, Eko Eko Darmanto Eko Pramono Eko Pramono Eko Pramono Eko Pramono Eko Purwanto Elim, Marthinus Ikun Elvis Pawan Elvis Pawan Emha T. Luthfi Emha T. Luthfi, Emha T. Emha Taufik Lutfi Emha Taufiq Lutfi Emha Taufiq Lutfi, Emha Taufiq Emha Taufiq Luthfi Emha Taufiq Luthfi Emha Taufiq Luthfi Emha Taufiq Luthfi Emha Taufiq Luthfi Emha Taufiq Luthfi Emilya Ully Artha Emilya Ully Artha Enie Yuliani Enni Lindrawati Ermawan, Bagas Restya Erwin Syahrudin Esha Alma'arif Fachruddin Edi Nugroho Saputro Fadhillah, Akmal Rafi Fahmi Ilmawan Fahry, Fahry Fail Amir Faisal Fadhila Fajar Ardanu Fajar Rohman Hariri Fajar Surya Putro Farid Fitriadi Fariz Zakaria Fathoni Dwiatmoko Fatoni, Chavid Syukri Fendi Sumanto Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Fersellia, Fersellia Fidya Farasalsabila Firdaus, M. Haikal Firdiyan Syah Firdiyan Syah Firstyani Imannisa Rahma Firstyani Imannisa Rahma Firza Septian Fitrah Eka Susilawati Fitriana, Frizka Fitriani Fitriani Fitrony, Fachri Ayudi Gabriel Bintang Timur Gardyas Bidari Adninda Ghifari, Dloifur Rohman Al Gusti F Rahman Gusti Fathur Rakhman Habib, Muhammad Hafidh Rezha Maulana Hafidz Sanjaya Hafidz Sanjaya, Hafidz Hafiz Ridha Pramudita Hafiz Ridha Pramudita, Hafiz Ridha Hajar, Muhammad Rizky Halim Bayuaji Sumarna Hamdani, Nahrowi Hamdikatama, Bimantyoso Hanafi Hanafi Hanafi Hanafi Hanafi Hani Setiani Hanif Al Fatta Hanif Al Fatta Hanif Al Fatta HANIF AL FATTA Hanif Al Fatta Hanif Al Fatta Hanif Al Fatta Hanif Al-Fatta Hardita, Veny Cahya Hartanto, Anggit Dwi Hartatik Hary Susanto Hasna Nirfya Rahmandhani Hastari Utama Hedy Leoni Helmawati, Nita Henderi . Hendi Muhammad, Alva HENDRA SETIAWAN Hendrawan, Ivan Rifky Hendrik Setiawan, Hendrik Herda Dicky Ramandita Herlandro Tribiakto Hidayat, Jati Arif Hikmianto, Riki Hirmayanti Hirmayanti, Hirmayanti Hudha, Yans Safarid I Dewa Bagas Suryajaya, I Dewa Bagas I Made Adi Purwantara I Wayan Rangga Pinastawa Idris Idris Idris Idris Ikrahmi Ikrahmi Imam Ainuddin P Ina Sholihah Widiati, Ina Sholihah Indarto Indarto Irawan, Ridwan Dwi Irawan, Rio Irma Yanti Irsyad Khalid Ilyas Irwan Siswanto Iskandar, Ahmad Fikri Isra Andika Bakhri Ivan Rifky Hendrawan Ivan Rifky Hendrawan Ivan Rifky Hendrawan Jangkung Tri Nugroho Januario Freitas Araujo Bernardo Jihadul Akbar Juni Marianti, Dina Kartikasari Kusuma Agustiningsih Kasim, Rafli Junaidi Khifni Beyk Ahmad Khoirunnita, Aulia Khusnawi Khusnawi Krisnawati Krisnawati Kriswantoro, Andi Kurniawan, Mei Kurniawan, Muhammad Bayu Kurniawan, Muhammad Bayu Kusnawi Kusnawi KUSRINI Kusrini Kusrini Kusrini Kusrini, Kusrini Kuswantoro, RB. Hendri Langgeng Hadi Prasetijo Lewu, Retzi Lindrawati, Enni Lisa Dinda Yunita M Imam Budi Laksamana M. Imam Budi Laksamana M. Imam Budi Laksamana M. Nuraminudin M. Rudyanto Arief M. Rudyanto Arief M. Rudyanto Arief M. Rudyanto Arief M. RUDYANTO ARIEF M. Suyanto M. Suyanto, M. M. Syafri Lamato M. Ulil Albab M. Zainal Arifin M. Ziaurrahman Ma'ruf Aziz Muzani Mahdi Ridho Mahmud Zunus Amirudin Marianti, Dina Juni Maringka, Raissa Martina Endah Pratiwi Maulana Brama Shandy Megantara, Nugraha Asthra Mei P Kurniawan Mei P Kurniawan Mei P.Kurniawan MEI PARWANTO KURNIAWAN Miftah Alfian Firdausy Mochammad Yusa Mochammad Yusa Mochammad Yusa Mochammad Yusa, Mochammad Moh Muhtarom Mohammad Edi Monalisa Fatmawati Sarifah Moniva, Anip Mudawil Qulub Muh Adha Muh Adha Muh Wal Ikram Muh Wal Ikram Muhajir, Fadhil Muhamad Arldi Megantara Muhamad Fatahillah Z Muhamad Paliya Sadana Muhamad Ridwan Muhammad Akbar Maulana Muhammad Altoumi Alsyaibani Muhammad Anwar Fauzi Muhammad Arfina Afwani Muhammad Fadli Muhammad Fadly Muhammad Fajrian Noor Muhammad Firdaus Abdi Muhammad Ilyas Prakanada Muhammad Lathifuddin Arif Muhammad Noor Arridho Muhammad Noor Arridho Muhammad Paliya Sadana Muhammad Resa Arif Yudianto Muhammad Ricky Perdana Putra Muhammad Rosikhu Muhammad Rusdi Rahman Muhammad Surahmanto Muhammad Suyanto, Muhammad Muhammad Syaiful Anam Muhammad Syukri Mustafa Muhammad Syukri Mustafa, Muhammad Syukri Mukhadimah Mukhlishah, Aiman Mursyid Ardiansyah Mutiara Dwi Anggraini NABILA OPER NAHROWI HAMDANI Nahrun Hartono Nahrun Hartono, Nahrun Nalda Kresimo Negoro Napianto, Riduwan Nasiri, Asro Ngaeni, Nurus Sarifatul Ngajiyanto, Ngajiyanto Ni Nyoman Utami Januhari, Ni Nyoman Nita Helmawati Nova Agustina Nova Noor Kamala Sari Nugroho Setio Wibowo Nugroho, Jangkung Tri Nugroho, Muhammad Agung Nuk Ghurroh Setyoningrum Nuk Ghurroh Setyoningrum Nur Hamid Sutanto Nur Hamid Sutanto Nur?aini, Nur?aini Nura Nugraha, Icha Nurcahyo, Azriel Christian Nurfaizah Nurfaizah Nurfajri Asfa Nurhasan Nugroho Nuri Cahyono Nurmasani, Atik Nurul Ilma Hasana Kunio Nurul Pratiwi, Annisa Okfan Rizal Ferdiansyah Oktariani, Deta Olivia Maria Inacio Tavares Omar Muhamammad Altoumi Alsyaibani Omar Muhammad Altoumi Alsyaibani Pangera, Abas Ali Patmawati Hasan Pebri Antara Prabowo Budi Utomo Pramudyantoro, Arvi Pranata, Caraka Aji Prasetio, Agung Budi Prasetyo, Ade Prasetyo, Yoga Adi Pratama, Rendy Bagus Pratama, Zudha Prayoga, Dimas Prayoga, Mahendra Bayu pujiharto, eka wahyu Pulungan, Linda Nurul Taqwa Purnawan Purnawan Purwidiantoro, Moch. Hari Purwoko, Agus Putra, Muhammad Ricky Perdana Putu Putrayasa Qolbun Salim As Shidiqi Qolbun Salim As Shidiqi Raditya Maulana Anuraga Rahardyan Bisma Setya Putra Rahmad Ardhani Rahmat Rahmat Rahmat Taufik R.L Bau Rahmatullah, Sidik Rakhma Shafrida Kurnia Ramadoni, Ramadoni Ramdhani, Arie Rahmat Rantung, Tessa Vatma Rasyida, Zulfa Raynaldi Fatih Amanullah Resty Wulanningrum Reyhan Dwi Putra Reyhan Dwi Putra Rhomita Sari Ria Andriani Ricki Firmansyah Rifki Fahmi Rifqi Anugrah Rifqi Mizan Aulawi Riska Kurniyanto Abdullah Risma, Vita Melati Rismayani Rismayani Riyanto Riyanto Rizki Firdaus Mulya Rizky Arya Kurniawan Rizky Handayani Rizky Handayani Rizqa Luviana Musyarofah Rizy, M. Alfa Rodney Maringka Ronaldus Morgan James Roshandri, Wien Fitrian Roshandri, Wien Fitrian S, Muhammad Sabri Sabar, Alfrida Safor Madianto Saiful Bahri Salibana, Chlyfen Richard Samsul Bahri Samuel Adhi Bagaskoro Sapta Hary Surya Wibowo Saputra, Artha Gilang Saputra, Artha Gilang Sarah Bunda Desi Bawan Sarah Bunda Desy Bawan Sari, Rita Novita Sari, Yunita Sartika Sarkawi - Sartje Mala Rangkoly Sasoko, Wasis Haryo Selamet Riadi Selvi Marcellia Selvy Megira Setiawan Budiman Setiawan, Bambang Abdi Setiawan, Hendi Setya Putra, Rahardyan Bisma Sidiq Wahyu Surya Wijaya Sigit Sugiyanto Sigit Suryono Siregar, Akhmad Arif Faisal Siswo Utomo, Mardi Slameto, Andika Agus Sodikin, Muh Ikbal Sofyan Pariyasto Sofyawati, Siti Sri Hartati Sri Hartati Sri Wahyuni Sri Yanto Qodarbaskoro Subastian Wibowo Sudarmawan Sudarmawan Sudarmawan, Sudarmawan Sudirman, San Sukoco Sukoco Sukoco Sukoco Sukrisno Amikom Suliswaningsih Suliswaningsih Suparyati Suparyati Supriadi, Oki Akbar Surya Ade Saputera Surya, Satria Dwi Suryono, Sigit Suryono, Wachid Daga Sutanto, Nur Hamid Sutrisno Sutrisno Suwanto Raharjo Suwanto Suwanto Suyadi - Suyatmi Suyatmi Swastikawati, Claudia Syah, Firdiyan Syah, Firdiyan Syahrudin, Erwin Syarham, Syarham Tamaulina Br Sembiring Tamrizal A. M. Tamsir, Kurniawati Tantoni, Ahmad Tantoni, Ahmad Teguh Ansyor Lorosae Tigus Juni Betri Tika Novita Sari Tikasni, Elisa Tinuk Agustin Tommy Dwi Putra TONNY HIDAYAT Toto Indriyatmoko Toto Rusianto Tri Amri Wijaya Tri Yusnanto Triana Triana Triwerdaya, Aji Tuhpatussania, Siti Tutut Maitanti Ulinuha, Hinova Rezha Veny Cahya Hardita Verra Budhi Lestari Vian Ardiyansyah Saputro Wahyu Ciptaningrum Wahyu Hidayat Wahyu Hidayat Wahyu Hidayat Wahyu Hidayat Wahyu Hidayat Wahyu Hidayat Wahyu Hidayat Wahyu Hidayat Wahyudi Hidayat, Aji Said wahyuni, wenti ayu Wicaksono, Sherif Aji Widijanuarto, Satyo Widjiyati, Nur Wijaksana, Candra Putra Wijaya, Tri Amri Yans Safarid Hudha Yanuargi, Bayu Yaqin, Aiinul Yefta Tolla Yetman Erwadi Yohanes Aryo Bismo Raharjo Yosef Murya Kusuma Ardhana Yulianto Mustaqim Yulita Fatma Andriani Yumarlin MZ Yusa, Mochammad Zakaria, Fariz Zitnaa Dhiaaul Kusnaa Washilatul Arba'ah Zitnaa Dhiaaul Kusnaa Washilatul Arba’ah Zitnaa Dhiaaul Kusnaa Washilatul Arba’ah Zulfa Rasyida Zulpan Hadi

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