Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

31.727

P-Index

This Author published in this journals

Ema Utami

Universitas Amikom Yogyakarta

Author-ID : 259410

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy 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 : 434 Documents Claim Missing Document

Claim Missing Document

Articles

40 41 42 43 44

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,

Optimizing Sentiment Classification Models for TikTok Comments using Emotion-Based Preprocessing and Grid Search Ermawan, Bagas Restya; Prayoga, Mahendra Bayu; Fadhillah, Akmal Rafi; Utami, Ema
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11742

TikTok has become one of the social media platforms with a significant influence on public opinion formation in Indonesia. However, the linguistic characteristics of user comments which are expressive, concise, and feature emotional forms like emojis, emoticons, and excessive capitalization pose challenges for sentiment analysis. This research aims to optimize a sentiment classification model for TikTok comments using emotion-based preprocessing and hyperparameter optimization via Grid Search. The dataset comprises 4,500 comments from three different time periods discussing the Minister of Finance, Purbaya Yudhi Sadewa. Three testing scenarios were conducted: common preprocessing, emotion-based preprocessing, and a combination of emotion-based preprocessing with Grid Search. The results indicate that emotion-based preprocessing improved model accuracy by 4–5%, while Grid Search optimization provided an additional increase of up to 3%, achieving a peak F1-score of 0.92 with the LightGBM model. Analysis based on sentiment time-periods reveals that across the three different periods, sentiments remained predominantly positive. The integration of emotion-based processing and parameter tuning proved effective in enhancing the model's ability to understand emotional variations in text and to map periodic changes in public sentiment on Indonesian-language social media.

Analisis Eksperimental Penggantian Backbone YOLOv5 dengan EfficientNet-B4 pada Sistem Deteksi Nilai Mata Uang Sabar, Alfrida; Utami, Ema; Wibowo, Ferry Wahyu
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.

Comparative Analysis of Machine Learning-Based Software Defect Prediction in Object-Oriented and Structured Paradigms Using Apache Camel and Redis Datasets Nasiri, Asro; Setyanto, Arief; Utami, Ema; Kusrini, Kusrini
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.5315

Software Defect Prediction (SDP) is a crucial component of software engineering aimed at improving quality and testing efficiency. However, the majority of SDP research often overlooks the fundamental influence of the programming paradigm on the nature and causes of defects. This study presents a comparative analysis to identify the most influential software metrics for predicting defects across two distinct paradigms: Object-Oriented (OOP) and Structured. To ensure modern relevance and reproducibility, we constructed two new datasets from large-scale, open-source projects: Apache Camel (Java) for OOP and Redis (C) for Structured which exhibited realistic defect rates of 14.4% and 21.8%, respectively. The dataset creation process involved mining Git repositories for defect labeling and automated metric extraction using the CK and Lizard tools. Correlation analysis and baseline modeling using Random Forest revealed significant differences between the paradigms. In the OOP system, dominant defect predictors were related to the complexity of the class interface and features (e.g., uniqueWordsQty, totalMethodsQty, WMC, CBO). Conversely, defects in the structured system were strongly correlated with size and algorithmic complexity (e.g., file_tokens, file_loc, file_ccn_sum). Although the baseline models performed well (ROC–AUC = 0.82–0.87), the significant class imbalance resulted in low recall (44–50%). This motivates the need for more context aware approaches. These findings underscore that effective SDP strategies must be tailored to the underlying programming paradigm.

Benchmarking Relational and Array-Based Models for Genealogical Data Storage in PostgreSQL Raharjo, Suwanto; Utami, Ema
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.5629

Genealogical information systems manage inherently hierarchical data structures that represent family relationships across multiple generations. Traditional implementations predominantly rely on normalized relational database designs using junction tables to model parent–child relationships. While this approach ensures strong referential integrity, it often incurs substantial performance overhead due to complex join operations during deep hierarchical traversal. Recent versions of PostgreSQL provide native support for array data types This study compares two genealogical database models implemented in PostgreSQL: a normalized relational model using a junction table and a denormalized model that stores child identifiers directly as UUID arrays. To evaluate their performance, we conducted controlled benchmarking experiments using synthetically generated genealogical datasets with varying generational depth and branching patterns. The comparison focuses on storage efficiency, recursive traversal performance, and write operation costs under realistic hierarchical workloads. Results obtained from a large-scale dataset containing more than 7 million individual records show that the UUID array–based model reduces disk space usage by 31%. During deep recursive traversal involving over 12 million nodes at the tenth generation, the array-based model demonstrates improved data locality, leading to a 5.2% reduction in execution latency and 7% fewer shared buffer accesses compared to the relational model. Interestingly, contrary to common expectations in normalized database design, the array-based model achieves 22% faster single-insert performance because it avoids foreign key validation and multiple index updates. This improvement comes with slightly higher write amplification, reflected in a 6.6% increase in buffer usage due to PostgreSQL’s multi-version concurrency control mechanism. These findings contribute to the field of Informatics by providing empirical evidence on how database internal mechanisms influence performance trade-offs in hierarchical data management, offering guidance for designing scalable and read-efficient information systems beyond genealogical applications.

Analisis Performa WireGuard dan OpenVPN pada VPN Perbankan Berbasis MikroTik menggunakan ICMP, iPerf3, dan Mann–Whitney Muhajir, Fadhil; Ema Utami
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9438

The banking industry necessitates secure and reliable site-to-site connectivity between data centres and branch offices to support transactions, data replication, and monitoring that is sensitive to latency, jitter, and packet loss. In practice, VPN gateways often operate concurrently with routing and security functions, leading to specific issues characterised by a trade-off between network service quality and processing overhead on gateway devices. Given that OpenVPN remains widely used while WireGuard is increasingly adopted as a more streamlined protocol, there is a need for measurable evidence to determine the most suitable protocol in a banking environment based on MikroTik routers. This study aims to compare the performance of WireGuard and OpenVPN across three dimensions: connection quality via ICMP Ping (minimum/average/maximum round-trip time, jitter, packet loss), transfer capacity using iPerf3 in TCP/UDP scenarios (download and upload), and processing efficiency through monitoring of CPU and memory usage. Data will be summarised using descriptive statistics and tested with the Mann–Whitney U test under equivalent test conditions. The results indicate that WireGuard provides better delay stability (lower average/maximum round-trip time and jitter) and more efficient CPU utilisation compared to OpenVPN, whereas throughput is context-dependent, with WireGuard generally excelling in UDP scenarios and OpenVPN performing better in certain TCP situations. The contribution of this research lies in the replicable testing methodology and quantitative evidence that serves as a foundation for recommending VPN protocol selection for banking based on network performance, resource efficiency, and service continuity.

OPTIMIZING SENTIMENT ANALYSIS OF PRODUCT REVIEWS ON MARKETPLACE USING A COMBINATION OF PREPROCESSING TECHNIQUES, WORD2VEC, AND CONVOLUTIONAL NEURAL NETWORK Fahry, Fahry; Utami, Ema; Sudarmawan, Sudarmawan
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 1 (2023): JUTIF Volume 4, Number 1, February 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.1.815

This research attempts to identify the most accurate and effective model in performing sentiment analysis on product reviews in marketplaces using preprocessing techniques, word2vec, and CNN. We collected 20,986 reviews from 720 products in a marketplace using scrap method, then cleaned and labeled the data to include 515 positive reviews, 490 negative reviews. We then performed preprocessing on the data using four different scenarios and identified word vector representation using word2vec. Subsequently, we applied the results of word2vec to the CNN architecture to classify sentiment in product reviews. After trying various variations of each technique, we found that a combination of the third preprocessing technique (case folding, punctuation removal, word normalization, and stemming), the second word2vec parameter combination (size 50, window 2, hs 0, and negative 10), and the fourth CNN parameter combination (kernel size 2, dropout 0.2, and learning rate 0.01) had the best accuracy of 99.00%, precision of 98.96%, and recall of 98.96%. We also found that the word normalization technique greatly helped to increase model accuracy by correcting improperly written or incorrect words in the reviews. Based on the evaluation of word2vec, the hs 0 method produced a higher average accuracy compared to the hs 1 method because the hs 0 method used negative sampling which helped the model understand the context of the trained words. In the CNN parameter, higher learning rates can cause the model to learn faster, but can also cause the model to be unstable, while lower learning rates can make the model more stable but can also cause the model's learning process to be slower.

PENINGKATAN SKALABILITAS SISTEM REKOMENDASI WEBSITE BERITA MENGGUNAKAN CONTENT-BASED FILTERING DAN K-MEANS Muhamad Arldi Megantara; Ema Utami
STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Vol. 5 No. 1 (2026): Februari
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/storage.v5i1.7651

Perkembangan internet menghasilkan volume data yang besar termasuk website berita yang memunculkan tantangan pada model rekomendasi Content-based filtering (CBF) dengan kompleksitas komputasi linier O(N). Penelitian ini mengusulkan optimalisasi CBF dengan integrasi dengan algoritma K-Means yang akan menghasilkan partisi data dengan tujuan reduksi biaya komputasi. Digunakan 22.250 artikel berita dari antara news. Penentuan nilai cluster (K) optimal menggunakan elbow method dengan K terbaik K = 6 dan divalidasi dengan Silhouette Score dengan nilai 0,5201, yang mengindikasikan sebaran data baik. Hasil dari pengintegrasian CBF dan K-means menunjukan adanya efisiensi pada response time dan penggunaan memori hingga 6 kali lipat. Namun, ditemukan pula trade-off berupa penurunan Mean Average Precision (MAP) dari 0,89 (konvensional) menjadi 0,77 (K=6), yang masih baik pada kualitas rekomendasi. Selain itu, digunakan threshold dengan nilai 0,30 yang terbukti optimal dalam filter konten yang relevan. Kesimpulan yang dapat diambil dari penelitian adalah penggunaan partisi data mampu memberikan kualitas rekomendasi yang tetap andal namun pada beban komputasi yang ditekan.

Performance Improvement of CNN Algorithm with Data Augmentation for Tobacco Leaf Disease Classification Agung Nurhidayatullah, Rizqy; Ema Utami; Dhani Ariatmanto
Jurnal Teknika Vol 18 No 1 (2026): MARET
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30736/jt.v18i1.1639

Pengolahan citra digital daun tembakau merupakan pendekatan penting dalam deteksi dini dan akurat penyakit tanaman, khususnya untuk komoditas pertanian bernilai ekonomi tinggi. Penelitian ini mengusulkan pendekatan augmentasi data multi-strategi untuk meningkatkan akurasi klasifikasi penyakit daun tembakau menggunakan Convolutional Neural Networks (CNN). Tiga teknik augmentasi diterapkan: augmentasi tradisional, augmentasi sampel campuran, dan augmentasi berbasis model pada tiga arsitektur CNN (MobileNetV2, EfficientNetB0, dan VGG16). Dataset terdiri dari 400 citra daun tembakau dengan lima kelas penyakit yang dikumpulkan dari Kabupaten Wonosobo. Eksperimen dilakukan dengan dua skenario pembagian data: 70:30 dan 80:20. Hasil menunjukkan bahwa penerapan augmentasi multi-strategi berhasil meningkatkan akurasi klasifikasi hingga 81,25% pada MobileNetV2 dengan rasio 80:20, yang mewakili peningkatan 20% dibandingkan dengan model tanpa augmentasi. Selain itu, teknik augmentasi secara efektif mengurangi overfitting dengan menurunkan selisih antara akurasi pelatihan dan validasi dari 0,5-0,7 menjadi 0,1-0,2.

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 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

Title

Found 434 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 434 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 434 Documents
Search