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Ema Utami

Universitas Amikom Yogyakarta

Author-ID : 259410

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A Conceptual Ontology Framework for Culturally-Adaptive Mobile Learning Interfaces: Integrating the Indonesian Wellbeing Scale Nugraha, Bhanu Sri; Suyanto, Muhammad; Kusrini; Utami, Ema
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 10 No. 1 (2025): May 2025
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v10i1.83437

This research addresses the lack of cultural sensitivity in existing Adaptive User Interface (AUI) frameworks, which predominantly rely on Western-centric paradigms and often overlook the collective and spiritual dimensions of student well-being. To bridge this gap, this study proposes a conceptual ontology framework that operationalizes the Indonesian Wellbeing Scale (IWS) into computational adaptation logic for mobile learning applications. Adopting a Design Science Research approach utilizing the NeOn methodology, we formally modeled multidimensional context factors—specifically spiritual observances, social relations, and self-acceptance—into a machine-readable semantic taxonomy. The proposed ontology was rigorously validated using a two-tiered verification strategy: logical consistency checking via the HermiT reasoner and functional validation through Competency Questions (CQs) mapped to SPARQL queries. The results demonstrate that the framework successfully infers complex user needs and triggers appropriate interface adaptations, such as prioritizing community interactions during social isolation or scheduling spiritual alerts, without logical conflicts. This study contributes a validated computational model for Culturally-Adaptive User Interfaces, providing a robust semantic foundation for future physical implementation and empirical user evaluation.

Credit Card Fraud Detection Using Ensemble Variation: Logistic Regression, Support Vector Classifier and Random Forest Salibana, Chlyfen Richard; Ema Utami
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 6 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i6.9343

Credit card fraud is a significant threat in the financial industry, causing significant financial losses annually, posing a challenge to both businesses and the financial sector. This requires research and development to identify fraud models that significantly improve over time. The purpose of this research is to develop a machine learning (ML)-based credit card fraud detection system with an ensemble approach to address the challenges of imbalanced data in digital financial transactions. The method used includes four main stages: data collection; SMOTE; Hyperparameter Tuning; and model evaluation. The dataset used is from Kaggle Credit Card Fraud Detection, which has a very low fraud proportion (0.17%). The increase in data volume was carried out using SMOTE on the training data. Three main models (Logistic Regression, Support Vector Classifier, Random Forest) and ensembles (hard and soft voting) were tested with hyperparameter tuning for optimal results. Random Forest performed best with an F1-Score of 0.8482 and an ROC-AUC of 0.9684. This model was able to detect 84% of fraudulent transactions with high precision, surpassing other models in handling imbalanced data. The combined advantages of RF and SMOTE are effective for fraud detection which is relevant for real-time systems in the financial sector.

Dilation Layer Menggunakan EfficientNetV2 untuk Mendeteksi Penyakit Retinopati Diabetik Mukhlishah, Aiman; Utami, Ema
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 6: Desember 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025126

Diabetic Retinopathy (DR) merupakan salah satu komplikasi serius akibat diabetes melitus yang dapat menyebabkan kebutaan jika tidak dideteksi dan ditangani secara dini. Deteksi otomatis berbasis citra fundus retina telah menjadi fokus utama dalam penelitian deep learning. Namun, fitur-fitur kecil seperti mikroaneurisma dan lesi halus seringkali sulit dikenali, terutama pada citra dengan kualitas rendah. Penelitian ini mengusulkan modifikasi arsitektur EfficientNetV2 dengan menambahkan dilation layer guna meningkatkan kemampuan model dalam menangkap fitur kontekstual dengan cakupan spasial yang lebih luas tanpa menambah kompleksitas secara signifikan. Dilated convolution memungkinkan perluasan receptive field tanpa mengurangi resolusi spasial, sehingga lebih efektif dalam mendeteksi fitur-fitur kritis pada DR. Pengujian dilakukan menggunakan dataset APTOS 2019 Blindness Detection yang menyediakan citra fundus retina beranotasi untuk lima tingkat keparahan DR. Model dilatih menggunakan optimizer Adam dengan learning rate sebesar 0,001 untuk mencapai konvergensi yang optimal. Evaluasi dilakukan terhadap beberapa varian EfficientNetV2, yaitu B0, B1, B2, B3, dan S. Hasil eksperimen menunjukkan bahwa model EfficientNetV2-B0 dan B1 memberikan akurasi terbaik, masing-masing sebesar 97,14%. Di antara keduanya, EfficientNetV2-B0 menghasilkan nilai presisi dan f1-score yang lebih tinggi. Temuan ini menunjukkan bahwa integrasi dilation layer pada arsitektur EfficientNetV2 berpotensi meningkatkan performa sistem klasifikasi DR otomatis secara signifikan dibandingkan model baseline tanpa modifikasi. Abstract Diabetic Retinopathy (DR) is a serious complication of diabetes mellitus that can lead to blindness if not detected and treated early. Automated detection based on retinal fundus images has become a primary focus in deep learning research. However, small features such as microaneurysms and subtle lesions are often difficult to identify, particularly in low-quality images. This study proposes a modification to the EfficientNetV2 architecture by incorporating dilation layers to enhance the model’s ability to capture contextual features over a broader spatial range without significantly increasing complexity. Dilated convolutions allow the expansion of the receptive field without reducing spatial resolution, making them more effective in detecting critical features associated with DR. The evaluation was conducted using the APTOS 2019 Blindness Detection dataset, which provides annotated retinal fundus images across five levels of DR severity. The model was trained using the Adam optimizer with a learning rate of 0.001 to achieve optimal convergence. The study assessed several variants of EfficientNetV2 - B0, B1, B2, B3, and S. Experimental results indicate that the EfficientNetV2-B0 and B1 models achieved the highest accuracy, each reaching 97.14%. Among these, EfficientNetV2-B0 yielded higher precision and F1-score values. These findings suggest that integrating dilation layers into the EfficientNetV2 architecture can significantly enhance the performance of automated DR classification systems compared to the unmodified baseline models.

A Systematic Literature Review of Retrieval-Augmented Generation: Methods, Applications, and Future Research Directions Hajar, Muhammad Rizky; Utami, Ema; Hendi Muhammad, Alva
Journal of Applied Computer Science and Technology Vol. 6 No. 2 (2025): Desember 2025
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v6i2.1170

Retrieval-Augmented Generation (RAG) represents a growing research direction in the advancement of large language models (LLMs) by incorporating external information sources into the response generation process. As LLM-based systems are increasingly deployed in information-sensitive domains such as healthcare, education, and law, the demand for responses that are not only fluent but also verifiable and context-aware has become more pronounced. This study conducts a systematic literature review (SLR) of 100 recent publications to examine methodological approaches, application domains, technical challenges, and research contributions related to RAG. The review draws on studies indexed in major academic databases, including IEEE, ACM, and Springer, and applies structured inclusion and exclusion criteria to ensure analytical rigor. The findings reveal a strong emphasis on architectural optimization, particularly in the interaction between retrieval and generation components, alongside widespread adoption in domain-specific contexts. Persistent challenges identified across the literature include limitations in retriever effectiveness, system integration complexity, and the absence of standardized evaluation benchmarks. Overall, this review provides a structured synthesis of current RAG research and highlights directions for future investigation and practical deployment..

Deep Learning-Enhanced Comparative Analysis of ARIMA, Seasonal ARIMA, and Gated Recurrent Unit Models for Forecasting Car Sales Zakaria, Fariz; Utami, Ema
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 7 No. 1 (2026): INJIISCOM: VOLUME 7, ISSUE 1, JUNE 2026 (ONLINE FIRST)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

This study aims to assess and compare the performance of three forecasting models—Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Gated Recurrent Unit (GRU)—in predicting car sales in Indonesia. The dataset presents intricate seasonal patterns and non-linear fluctuations, which pose challenges for conventional statistical models. The ARIMA model, suited for linear and stationary data, struggled to capture the complexities of the sales trends. While SARIMA, an enhanced version of ARIMA, aimed to handle seasonal components, it also failed to provide accurate predictions. In contrast, the GRU model, a deep learning-based technique, exhibited the best results in terms of predictive accuracy, with significantly lower values for Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The results highlight the superior performance of the Gated Recurrent Unit (GRU) model in forecasting car sales. This superiority is reflected in lower error values across all evaluation metrics compared to ARIMA and SARIMA. The GRU model provides accurate forecasts for complex business decision-making

Automating Performance-Based Budgeting Using a Knowledge-Based System Rantung, Tessa Vatma; Utami, Ema
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1286

This study investigates the implementation of a Knowledge-Based System (KBS) integrated with the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) to automate performance-based budgeting in a public university environment. The integration of Fuzzy AHP enhances the system’s ability to manage uncertainty and subjectivity in expert assessments, resulting in more consistent prioritization of performance indicators and improved decision accuracy. Data was obtained through interviews, questionnaires, and field observations, supported by institutional financial and performance reports. The developed system architecture—comprising a knowledge base, inference engine, and user interface—enables structured, transparent, and knowledge-driven budgeting analysis. The findings show that the system strengthens objectivity, coherence, and strategic alignment in the budgeting process while promoting accountability and efficiency in financial management. For university finance managers and administrators, this system provides a practical decision-support tool that facilitates data-based resource allocation and enhances institutional performance monitoring. The novelty of this research lies in the combination of Fuzzy AHP and KBS methodologies, offering an innovative model for intelligent, performance-oriented financial management in higher education institutions.

Systematic Review of the Use of the MIT-BIH Polysomnography Database for the Detection and Classification of Sleep Disorders Akbar, Akbar; Utami, Ema
SISTEMASI Vol 15, No 1 (2026): 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.v15i1.5819

The MIT-BIH Polysomnography Database (SLPDB) is a widely adopted benchmark for the development of automated methods for sleep disorder detection and sleep stage classification. This study presents a Systematic Literature Review of 35 articles that utilize the SLPDB, examining research focus areas, types of physiological signals employed, and the computational approaches applied. Five major methodological categories were identified: Sleep Apnea Detection, Sleep Staging, Signal Processing Enhancement, Multichannel Fusion Methods, and Interpretable Artificial Intelligence, with the first two categories being the most dominant. Four groups of physiological signals—EEG, ECG, respiratory signals, and multichannel data—form the basis for model development, where EEG is predominantly used for sleep staging and ECG for sleep apnea detection. Deep learning approaches, particularly CNNs, LSTMs, and hybrid models, are the most frequently employed techniques. Reported model accuracies range from 78% to over 99%, depending on the signal modality and modeling strategy. Future research should prioritize the development of more interpretable hybrid models and broader clinical validation to enhance reproducibility and implementation readiness.

Forecasting the Highest and Lowest Prices in Financial Markets Using a VMD-LSTM Hybrid Model Purwantara, I Made Adi; Kusrini, Kusrini; Setyanto, Arief; Utami, Ema
CogITo Smart Journal Vol. 11 No. 2 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i2.963.295-310

Accurate forecasting of the lowest and highest prices in financial markets poses a considerable challenge due to the inherent nonlinear behaviour, non-stationarity, and high noise levels of financial time series data. Most prior studies focus only on closing prices, with limited attention to the simultaneous prediction of high and low prices. Yet, predicting the lowest and highest prices is essential for investors to make informed trading decisions. To address this gap, this study proposes a hybrid DL framework that integrates VMD and LSTM networks for predicting daily high and low prices simultaneously. This study used 12 years of daily data from three diverse assets: AUD/USD, TLKM, and XAU/USD. The data underwent preprocessing, VMD-based decomposition, and were input into the LSTM. The dataset was split 80% for training and 20% for testing. Experiments varied the number of decomposition modes (K = 7, 10, 12) and sliding window sizes (5, 15, 30, 45, 60, 90). Results show that the VMD-LSTM model exhibits improved performance in most of the tested scenarios compared to traditional LSTM. These findings underscore that the use of VMD decomposition can help enhance the accuracy of forecasting the highest and lowest prices in the financial market.

Perbandingan Metode Random Forest dan KNN pada Analisis Sentimen Twitter Dzulhijjah, Dwi Ahmad; Sanjaya, Hafidz; Wahyudi Hidayat, Aji Said; Alwanda, Almi Yulistia; Utami, Ema
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 3 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i3.5106

Twitter menjadi salah satu platform media sosial yang sering digunakan untuk menyampaikan berbagai keresahan terhadap berbagai permasalahan yang ada termasuk dengan program-program yang dibuat oleh pemerintah. Tweets adalah salah satu layanan yang disediakan kepada penggunanya dimana tweets ini berisi ungkapan pendapat pengguna yang dapat juga dibaca oleh pengguna lain. Pada penelitian ini dilakukan perbandingan antara dua algoritma klasifikasi yaitu Support Vector Machine dan K-nearest Neighbor dari segi akurasi. Perbandingan ini tidak lain bertujuan untuk mengetahui algoritma klasifikasi mana yang dapat menghasilkan akurasi terbaik dalam mengklasifikasi analisis sentiment data twitter. Setelah dilakukan pengujian dan evaluasi didapatkan hasil akurasi dari algoritma SVM sebesar 83% dan KNN sebesar 49%.Â Kata Kunci: Analisis Sentimen; KNN; Support Vector Machine

Analisis Perbandingan Metode Tf-Idf dan Word2vec pada Klasifikasi Teks Sentimen Masyarakat Terhadap Produk Lokal di Indonesia Hendrawan, Ivan Rifky; Utami, Ema; Hartanto, Anggit Dwi
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 11, No 3 (2022): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v11i3.3902

Secara umum, proses menghasilkan setiap ulasan produk padaÂ dasarnya terkait dengan tingkat rating, yang membuat pengguna memberikan komentar yangÂ bias.Analisis sentimen dapat diterapkan pada ulasan produk Marketplace sehingga dapatÂ digunakan sebagai saran perbaikan produk untuk penjual dan pesaing sehingga dapat mengetahuiÂ produk apa yang disenangi dan dibutuhkan oleh masyarakat.Penelitian ini Â menggunakanÂ algoritma XGBoost dengan menggunakan dataset bahasa Indonesia yang dikombinasikan denganÂ TF-IDF dan Word2vec dan akan dievaluasi kombinasi mana yang lebih baik dalamÂ mengklasifikasikan data teks yang tidak seimbang.Berdasarkan penelitian yang telah dilakukan, dua vector space TF-IDF danÂ Word2vec menghasilkan nilai F1-Score yang berbeda pada algoritma klasifikasi XGBoost,Â kombinasi Word2vec+XGboost menghasilkan nilai F1-Score lebih tinggi 0.941% dibanding TF IDF+XGBoost 0.940%. Hal ini dikarenakan word2vec lebih baik karena memiliki keunggulanÂ dapat melihat hubungan semantik antar kata.Kata kunci: word2vec, tfidf, sentimen analisis, XGBoost,

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 Arwin, Dwi Septiyani 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 Dengen, Angel Fourtuna Deny Nugroho Triwibowo Dewa Saksana, Jidan 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 Kuncoro Hadi 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 Iqbal 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 Rantung, Tessa Vatma Rasyida, Zulfa Raynaldi Fatih Amanullah Resty Wulanningrum Reyhan Dwi Putra Reyhan Dwi Putra Rhomita Sari Ria Andriani Rianansyah, Anggit 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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