Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

34.49

P-Index

This Author published in this journals

Ema Utami

Universitas Amikom Yogyakarta

Author-ID : 259410

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering 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 Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 448 Documents Claim Missing Document

Claim Missing Document

Articles

40 41 42 43 44

Komparasi Model Transformer dan LSTM dalam Prediksi Harga Saham Blue Chip di BEI Ricky Ferdiansyah; Ema Utami
JNANALOKA Vol 7 No 01 (2026): Vol. 07 No. 01 Maret Tahun 2026
Publisher : Lentera Dua Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36802/jnanaloka.2026.v7-no01-%p

Kompleksitas prediksi harga saham berakar dari sifat data runtun waktu keuangan yang fluktuatif dan non-linear. Studi ini menyelidiki bagaimana Long Short-Term Memory (LSTM) dan Transformer merespons variasi panjang sekuens historis dalam meramalkan harga penutupan saham PT Bank Central Asia Tbk (BBCA), saham blue-chip dengan kapitalisasi pasar terbesar di Bursa Efek Indonesia. Data historis OHLCV dikumpulkan dari Yahoo Finance mencakup periode Januari 2018 hingga Desember 2024. Panjang sekuens divariasikan pada 3, 5, 7, 10, dan 14 hari. Evaluasi menggunakan MAE, RMSE, MAPE, serta Uji Diebold-Mariano untuk mengonfirmasi signifikansi statistik perbedaan kinerja. Hasil eksperimen menunjukkan LSTM mencapai kinerja terbaik pada panjang sekuens 14 hari dengan MAPE 1,23%, sementara Transformer mencapai titik optimal pada panjang sekuens 3 hari dengan MAPE 1,40%. Transformer mengalami penurunan performa yang tajam seiring bertambahnya panjang sekuens, mencapai MAPE 5,26% pada 14 hari. Sebaliknya, LSTM menunjukkan performa yang stabil di seluruh variasi panjang sekuens. Perbedaan ini berkaitan dengan cara kerja masing-masing model dalam mengolah data historis. LSTM yang membaca data secara bertahap cenderung dapat mengumpulkan informasi dari sekuens panjang, sedangkan Transformer yang membandingkan semua data sekaligus justru tidak menunjukkan hal yang sama saat jumlah data bertambah. Temuan ini menegaskan bahwa pada dataset finansial dengan ukuran terbatas, pemilihan model dan panjang data historis harus disesuaikan secara hati-hati karena tidak semua arsitektur diuntungkan oleh penambahan data.

Analisis Eksperimental Penggantian Backbone YOLOv5 dengan EfficientNet-B4 pada Sistem Deteksi Nilai Mata Uang Alfrida Sabar; Ema Utami
SENTRI: Jurnal Riset Ilmiah Vol. 5 No. 1 (2026): SENTRI : Jurnal Riset Ilmiah, Januari 2026
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v5i1.5611

YOLOv5 is a variant of the You Only Look Once (YOLO) algorithm, which is widely recognized for its ability to perform fast and efficient object detection in a single-stage processing framework. The performance of YOLOv5 is strongly influenced by its backbone architecture, which is responsible for extracting visual features from input images. Consequently, backbone replacement is commonly employed as an experimental approach to analyze the impact of feature extraction variations on object detection performance. This study aims to conduct an experimental evaluation of replacing the YOLOv5 backbone with the EfficientNet architecture, specifically EfficientNet-B4, for a rupiah currency value detection system. The experiment was carried out by comparing the baseline YOLOv5 model with a modified YOLOv5 model incorporating the EfficientNet-B4 backbone, using a rupiah banknote dataset consisting of seven nominal classes. Model performance was evaluated using precision, recall, mAP@0.5, mAP@0.5:0.95, and inference time as evaluation metrics. The experimental results indicate that the use of EfficientNet-B4 leads to a decrease of 1.075% in mAP@0.5, while simultaneously increasing mAP@0.5:0.95 by 2.247%. This improvement suggests enhanced bounding box localization accuracy under more stringent Intersection over Union (IoU) evaluation criteria. However, the inference time increased significantly, from approximately 7 ms to 37.8 ms per image. Overall, these findings indicate that backbone replacement provides different performance characteristics and needs to be tailored to the specific requirements of the target application.

Optimasi Strategi Digital Website Menggunakan WebQual 4.0, IPA dan Model SVM Felisberto Pereira; Ema Utami
Journal Automation Computer Information System Vol. 6 No. 2 (2026): November (In Progress Issue)
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jacis.v6i2.194

Website memiliki peran penting dalam manajemen akademik dan meningkatkan reputasi suatu institusi pendidikan. Kualitas layanan website merupakan faktor krusial yang memengaruhi kepuasan pengguna platform digital. Universitas Dili (UNDIL) merupakan salah satu perguruan tinggi yang memanfaatkan website resmi sebagai sarana utama penyedia informasi akademik bagi mahasiswanya. Penelitian ini bertujuan untuk mengevaluasi kualitas layanan website UNDIL melalui pendekatan hibrida (hybrid approach) dengan mengintegrasikan metode kuantitatif Importance-Performance Analysis (IPA) dan pendekatan Text Mining berbasis Support Vector Machine (SVM). Data kuantitatif diperoleh dari 400 responden mahasiswa melalui kuesioner berbasis dimensi WebQual 4.0. Melalui uji validitas dan reliabilitas instrumen yang ketat, diperoleh 11 indikator valid yang siap diujikan. Hasil pemetaan Diagram Kartesius IPA menunjukkan bahwa Atribut Q23 (Tampilan website tetap rapi saat diakses melalui smartphone) menjadi satu-satunya parameter yang terisolasi di Kuadran I (Prioritas Utama). Untuk memvalidasi temuan spasial tersebut secara tekstual dan kontekstual, algoritma SVM dilatih menggunakan korpus data berupa 174 ulasan terbuka dari mahasiswa. Hasil pengujian komputasi pada lingkungan Google Colab menunjukkan bahwa model SVM berbasis pembobotan TF-IDF mampu mengklasifikasikan sentimen opini pengguna dengan tingkat performa yang optimal, mencapai akurasi sebesar 96,30%. Integrasi kedua metode ini membuktikan secara ilmiah bahwa kendala utama platform terletak pada aspek mobile-responsiveness, sehingga memberikan landasan objektif bagi manajemen IT UNDIL untuk memprioritaskan rekayasa ulang antarmuka (UI/UX design) yang ramah seluler demi mengoptimalkan kualitas layanan digital

EMOGRAM-CNN: A Gram-Correlation Enhanced Multi-Kernel Convolutional Network for Text Emotion Recognition Marselina Endah Hiswati; Ema Utami; Kusrini Kusrini; Arief Setyanto
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3043

Deep neural architectures have demonstrated substantial capability for handling temporal and sequential data; however, most recurrent-based models, such as LSTM, BiLSTM, GRU, and BiGRU, remain computationally expensive and prone to overfitting. This study proposes and evaluates the EMOGRAM-CNN model, a convolutional neural architecture enhanced with Gram-matrix feature correlation, to improve feature representation in temporal classification tasks. Model performance was compared with conventional CNNs and recurrent architectures on a balanced six-class dataset comprising 17,967 samples. Experimental results show that EMOGRAM-CNN achieved the highest classification accuracy of 94.48%, outperforming CNN (94.00%), GRU (92.00%), BiGRU (91.00%), BiLSTM (91.00%), and LSTM (90.00%). The model converged faster, with smoother loss behavior and lower validation error, indicating superior stability and generalization. The Gram-based correlation layer effectively preserved second-order dependencies across feature maps, enabling the network to capture both local and global temporal relationships without recurrent connections. These findings confirm that EMOGRAM-CNN offers a robust, computationally efficient alternative to recurrent deep networks for sequence classification.

Evaluating Cross-Language Structural Generalization of the Unified Abstract Syntax Tree Mardi Utomo; Ema Utami; Kusrini; Arief Setyanto
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3191

Cross-language code analysis requires syntax-aware representations that can reduce language-specific syntactic variation while preserving comparable program structure. Although unified Abstract Syntax Tree (AST) representations have been proposed, empirical evidence on their representation-level structural behavior across datasets and programming languages remains limited. This paper evaluates the structural generalization of a Unified AST representation as a schema-level abstraction, not as a parser-free or full semantic equivalence mechanism. The Unified AST schema is constructed from the CodeXGLUE code-to-text dataset covering Python, PHP, Ruby, Java, JavaScript, and Go. Its generalization is then examined on function-level aligned benchmarks from CodeXGLUE code-to-code translation (Java-C#) and multilingual HumanEval (Java, JavaScript, Go, Python, C++, and Rust). Tree Edit Distance (TED) similarity is used as the primary structural metric, while cosine similarity, BLEU, compression ratio, and identifier precision-recall are treated as auxiliary indicators of lexical similarity, reconstruction fidelity, compactness, and identifier retention. The results show an average TED similarity of 0.77 on CodeXGLUE code-to-code translation and 0.60 on HumanEval. These findings indicate that the Unified AST can preserve cross-language structural patterns under aligned benchmark assumptions, although it does not prove behavioral equivalence and remains dependent on language-specific parsing during AST extraction

Improving Database Quality by Applying Consistency Aspects to Naming Fields and Tables Raissa Maringka; Aulia Khoirunnita; Rodney Maringka; Ema Utami; Kusnawi
TEPIAN Vol. 2 No. 1 (2021): March 2021
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v2i1.304

The database is one of the benchmarks that affect the quality of information systems. An effective information system certainly has a quality database. Aspects that can be measured to determine the quality of the database are aspects of truth, consistency, range, level of detail, completeness, minimalism, ability to integrate and readability. One of the mistakes that are often encountered in databases is related to the consistency aspect. Consistency aspects that are not paid much attention to its application can lead to data conflicts due to ambiguity and data duplication. This study aims to improve the quality of the database by applying consistency to the naming of fields and tables. A naming method to produce consistency in standardization was applied in this study.

Multi-Scenario Preprocessing Analysis for Indonesian Spice Image Classification: A Comparative Study Using VGG16, MobileNetV3, and YOLOv11 Eric Ariyanto; Ema Utami
G-Tech: Jurnal Teknologi Terapan Vol 10 No 3 (2026): G-Tech, Vol. 10 No. 3 July 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i3.9849

Indonesian spice identification is challenging due to high inter-class visual similarity among rhizome species, yet the systematic impact of image preprocessing on classification performance remains underexplored. This study evaluates three preprocessing techniques (CLAHE, Background Removal, and Data Augmentation) arranged in eight factorial schemes across three architectures (VGG16, MobileNetV3-Large, and YOLOv11-cls), comprising 72 training runs on an 856-image four-class dataset, with Macro-F1 on stratified 80/10/10 splits as the primary metric. Data Augmentation alone (scheme S4) produced the most consistent gain, with VGG16 reaching 93.80% Macro-F1. The full pipeline degraded performance across all architectures because CLAHE and Background Removal interact antagonistically, refuting the assumption that preprocessing effects are additive. Externally defined augmentation was also found to be silently bypassed by the Ultralytics framework. All five primary findings replicated on an independent seven-class dataset using 5-fold cross-validation, and Background Removal proved beneficial only for large, high-contrast objects. The study establishes an empirical preprocessing benchmark and practical deployment guidance for spice recognition.

Sentiment Analysis and Topic Modelling of The COVID-19 Vaccine in Indonesia on Twitter Social Media Using Word Embedding Kartikasari Kusuma Agustiningsih; Ema Utami; Omar Muhamammad Altoumi Alsyaibani
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 8 No. 1 (2022): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v8i1.23009

This study aims to analyze the sentiments of the Indonesian people towards the COVID-19 vaccine on Twitter. Data collection was carried out from September 2020 to June 2021 with the keyword "covid vaccine," which resulted in 262306 tweets. After filtering and cleaning, there are 83384 tweets left. The labeling process was done manually by an expert. The label composition in the data is 35209 tweets of positive sentiment, 41596 tweets of neutral sentiment, and 6579 tweets of negative sentiment. The remaining data is preprocessed using case folding, removing punctuation, stopword removal, stemming, and the application of slang words. The highest number of tweets appeared in January 2021, after Joko Widodo became the first person in Indonesia to receive a vaccine injection. The number of tweets reached 23492 tweets. At the topic modeling stage, measurements were conducted using the Coherence Score. The distribution of the optimal number of topics is 3 topics. The first topic, with a token percentage value of 51.8%, leads to positive sentiment, while the second and third topics, with token percentage values of 24.5% and 23.7%, lead to neutral sentiment. Bidirectional LSTM architecture was implemented to perform sentiment classification. Fasttext and GloVe word embedding was tested to vectorize tweet data. The test accuracy generated by Fasttext word embedding reached 75,7690%, while the test accuracy produced with GloVe word embedding reached 74.7017%. The usage of slang words could not increase the test accuracy in this study. The use of the Modelcheckpoint to monitor model performance during training could produce a model with a slightly higher test accuracy, about 1.07% (in scenario 1 and scenario 6), compared to a model whose performance was monitored using Early Stopping. In future research, it can be tried to apply a lower learning rate to produce better accuracy in a large number of epochs, or it could be by changing the dropout parameter.

Analisa Perbandingan Algorithma K-Nearest Neighbors dan Random Forest untuk Klasifikasi Tindakan Medis Persalinan pada Data Kehamilan Multi-Variabel Alfin Mahadi; Ema Utami
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.556

Maternal mortality rate is still high in the most critical aspect affecting the quality of life of mothers and newborns. Very significant urgency considering the importance of proper medical in childbirth procedures. Kendal Islamic Hospital provides more complex data on maternal medical records of childbirth. Many optimization algorithms in classification have been proposed. Many swarm optimizations have been developed, particle swarm optimization is a superior optimization method. Comparison of K-Nearst Neighbors and Random Forest methods is often applied without optimization. This study compares the performance of the K-Nearest Neighbors (KNN) and Random Forest (RF) algorithms in classifying medical procedures for childbirth using medical records of maternity patients at RSI Kendal. The multivariable dataset includes age, weight, height, and more complete childbirth conditions. The preprocessing method involves imputation of empty values ??with KNN imputer, data normalization, and class oversampling using Synthetic Minority Over-sampling Technique (SMOTE). KNN and RF are optimized using Particle Swarm Optimization (PSO) to improve model accuracy. The results show that RF with an accuracy of 99.72% outperforms KNN with an accuracy of 97.03%. In the minority class, RF shows superiority with precision, recall, and F1-score reaching 100%, while KNN is more prone to errors in the minority class. This study confirms RF in handling complex multivariate data and highlights the importance of model optimization to improve accuracy in the classification of medical labor actions. These findings are expected to contribute to the development of machine learning-based decision support systems in the health sector.

Guava Disease Detection and Classification: A Systematic Literature Review Muhammad Bayu Kurniawan; Ema Utami
Telematika Vol 18, No 1: February (2025)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v18i1.2901

Guavas (Psidium guajava) are nutrient-rich fruits that provide significant health benefits. However, guava cultivation faces persistent threats from various diseases affecting both leaves and fruits, leading to substantial yield and quality losses. The early and accurate detection of these diseases is crucial but remains challenging due to economic constraints and limited infrastructure. While plant pathologists employ various diagnostic methods, these approaches are often time-consuming, costly, and sometimes inconsistent. Recent advancements in deep learning (DL) and machine learning (ML) have introduced innovative techniques for guava disease identification. This study conducts a Systematic Literature Review (SLR) to evaluate the existing research on guava leaf and fruit disease detection, focusing on dataset sources, identified disease categories, preprocessing and augmentation techniques, applied algorithms, and reported evaluation metrics. A comprehensive search was conducted across multiple databases, covering publications from 2017 to 2023, leading to the identification of 47 relevant studies. After applying exclusion criteria, 16 studies were selected for in-depth analysis. The findings highlight the most commonly used datasets, the predominant classification techniques, and the effectiveness of various deep learning models based on multiple performance metrics, providing insights into current research trends, existing limitations, and potential directions for future studies. This review serves as a valuable reference for researchers aiming to enhance the accuracy and efficiency of guava leaf and fruit disease diagnosis through data-driven approaches.

Co-Authors , Anggit Dwi Hartanto A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA Abdul Malik Zuhdi Abdullah Ardi Abdulrahmat E Ahmad Abyan Fauzi Widihasani Achmad Yusron Arif Ade Pujianto Adi Surya Adiatma, Biva Candra Lutfi 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 Ahmad Fauzi Ahmad Febri Diansyah Ahmad Fikri Iskandar Ahmad Fikri Iskandar Ahmad Fikri Iskandar Ahmad Hajar Ahsan, Muhammad Rafiqudin Ahsan, Muhammad Rafiqudin Ainul Yaqin Ainul Yaqin Ainul Yaqin Aji Said Wahyudi Hidayat Aji Triwerdaya Akbar Akbar Akhmad Arif Faisal Siregar Akhmad Dahlan Al Fathir As, Rahmat Saudi Aldy A Kulakat Alfansani, Abdul Rauf Alfin Mahadi Alfrida Sabar Alimuddin Yasin 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 Amali Amali 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 Anggi Muhammad Rifai 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 Hartanto, Anggit Dwi Anggit Hartanto Anggit Rianansyah 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 Arridho, Muhammad Noor 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 Baiq Sri Mardiani Bangun Watono Banu Dwi Putranto Basri, Nur Faizal Bayu Setiaji 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 Desy Bawan, Sarah Bunda Deta Oktariani 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 Septiyani Arwin Dwi Yuli Prasetyo Dzulhijjah, Dwi Ahmad Eddy Nurraharjo Eddy Nurraharjo 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 Taufik Lutfi Emha Taufiq Luthfi Emilya Ully Artha Emilya Ully Artha Enie Yuliani Enni Lindrawati Eric Ariyanto Ermawan, Bagas Restya 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 Felisberto Pereira 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 Gardyas Bidari Adninda Gusti F Rahman Gusti Fathur Rakhman Habib, Muhammad Hafidh Rezha Maulana Hafidz Sanjaya Hafidz Sanjaya, Hafidz Hafiz Ridha Pramudita Hafiz Ridha Pramudita, Hafiz Ridha Halim Bayuaji Sumarna Hamdani, Nahrowi Hamdikatama, Bimantyoso Hanafi Hanafi Hanafi Hanafi Hanafi Hani Setiani Hanif Al Fatta Hardita, Veny Cahya Hartanto, Anggit Dwi Hartatik Hary Susanto Hasna Nirfya Rahmandhani Hedy Leoni Henderi . HENDRA SETIAWAN Hendrawan, Ivan Rifky Hendrik Setiawan, Hendrik Herda Dicky Ramandita Herlandro Tribiakto Hidayat, Jati Arif Hikmianto, Riki Hirmayanti Hudha, Yans Safarid I Dewa Bagas Suryajaya, I Dewa Bagas I Made Adi Purwantara I Wayan Rangga Pinastawa Idris Idris Ikrahmi Ikrahmi Imam Ainuddin P Ina Sholihah Widiati, Ina Sholihah Indarto Indarto Indra Listiawan Irawan, Ridwan Dwi Irawan, Rio Irfan Kurniawan 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 Kumara Ari Yuana Kumara Ari Yuawan Kuncoro Hadi Kurniawan, Muhammad Bayu Kusnawi Kusnawi 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 Mardi Utomo Marianti, Dina Juni Maringka, Raissa Marselina Endah Hiswati Martina Endah Pratiwi Maulana Brama Shandy Megantara, Nugraha Asthra 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 Muhamad Arldi Megantara Muhamad Ekhsan Muhamad Fatahillah Z Muhamad Fatchan Muhamad Paliya Sadana Muhamad Ridwan Muhammad Agung Nugroho Muhammad Akbar Maulana Muhammad Altoumi Alsyaibani Muhammad Anwar Fauzi Muhammad Arfina Afwani Muhammad Bayu Kurniawan Muhammad Fajrian Noor Muhammad Firdaus Abdi Muhammad Ilyas Prakanada Muhammad Iqbal Muhammad Lathifuddin Arif Muhammad Paliya Sadana Muhammad Resa Arif Yudianto Muhammad Ricky Perdana Putra Muhammad Ricky Perdana Putra Muhammad Rizky Hajar Muhammad Rosikhu Muhammad Rusdi Rahman Muhammad Surahmanto Muhammad Suyanto 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 Nita Helmawati Nova Agustina Nova Noor Kamala Sari Nugroho Setio Wibowo Nugroho, Jangkung Tri 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 Muttaqien Nurul Pratiwi, Annisa Octhavia Alin 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 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 Purnawan Purwidiantoro, Moch. Hari Purwoko, Agus Putu Putrayasa Qolbun Salim As Shidiqi Qolbun Salim As Shidiqi Quratul Ain Raden Bagus Bambang Sumantri 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 Ricki Firmansyah Ricky Ferdiansyah Rifki Fahmi Rifqi Anugrah Rifqi Mizan Aulawi Riska K Abdullah Riska Kurniyanto Abdullah Risma, Vita Melati Rismayani Rismayani Riyanto Riyanto Rizki Firdaus Mulya Rizky Arya Kurniawan Rizky Handayani Rizky Handayani Rizqa Luviana Musyarofah Rodney Maringka Rodrigo Martínez Béjar Ronaldus Morgan James Roshandri, Wien Fitrian Roshandri, Wien Fitrian S, Muhammad Sabri Safor Madianto Saiful Bahri Salibana, Chlyfen Richard Samsul Bahri Samuel Adhi Bagaskoro Santi Santi Sapta Hary Surya Wibowo Saputra, Artha Gilang Saputra, Artha Gilang Sari, Rita Novita Sari, Yunita Sartika Sarkawi - Sartje Mala Rangkoly Satyo Widijanuarto 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 Siswo Utomo, Mardi Slameto, Andika Agus Sofyan Pariyasto Sofyawati, Siti Sri Hartati Sri Hartati 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 Suwondo, Adi 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 Tuhpatussania, Siti Tutut Maitanti Ulinuha, Hinova Rezha Utama, Hastari 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 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 Zitnaa Dhiaaul Kusnaa Washilatul Arba'ah Zitnaa Dhiaaul Kusnaa Washilatul Arba’ah Zitnaa Dhiaaul Kusnaa Washilatul Arba’ah Zulfa Rasyida Zulpan Hadi

Title

Found 448 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 448 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 448 Documents
Search