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Ema Utami

Universitas Amikom Yogyakarta

Author-ID : 259410

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

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

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

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

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

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

VARFIS: A Hybrid Neuro-Fuzzy Model for Intelligent Microclimate Control in Black Soldier Fly Farming Systems Yunita Sartika Sari; Kusrini; Ema Utami; Ferry Wahyu Wibowo
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i2.46610

Maintaining optimal microclimate conditions is essential for Black Soldier Fly (BSF) cultivation, yet traditional systems often struggle with dynamic environmental changes. This study proposes the Vector Autoregressive-Fuzzy Inference System (VARFIS), a hybrid model combining Vector Autoregression (VAR) and Adaptive Neuro-Fuzzy Inference System (ANFIS), to enhance temperature and humidity control in BSF insectariums. VARFIS adapts to uncertainty using probabilistic learning, achieving a 48% reduction in prediction error (MAPE = 1.36%) and high accuracy (R² = 0.9695), outperforming standalone VAR and ANFIS models. The model effectively captures daily climate fluctuations, improving larval growth efficiency and waste conversion. However, it remains limited in handling extreme events such as sudden heatwaves or humidity spikes, indicating the need for enhancements like adaptive fuzzy rule tuning and integration of physical constraints. VARFIS presents a scalable solution for intelligent microclimate management, supporting sustainable insect farming and circular economy goals. This work contributes to precision agriculture by offering data-driven tools for resilient environmental control.

Inception-ResNet-V2 The U-Net Encoder for Road Segmentation using Sentinel 2A Yanuargi, Bayu; utami, ema
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 2 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i2.12089

Updating road network maps is essential for transportation services, as incomplete or inaccurate maps can lead to inefficiencies and diminish service quality. The online transportation industry generates vast amounts of GPS data as drivers navigate, which is valuable for mapping road networks and improving traffic management. However, since drivers do not cover all roads, satellite imagery plays a crucial role in identifying areas that are not mapped. By combining GPS data as labels with satellite imagery, the extraction of new road networks becomes more accurate. This research employs a deep learning Convolutional Neural Network (CNN) with the U-Net architecture for road segmentation, allowing for the identification of new paths. Two different encoders are tested in this research: Inception-ResNet-V2 and a pure U-Net encoder. The Inception-ResNet-V2 encoder achieves an accuracy of 91.3%, while the pure U-Net encoder achieves 90.7%. In terms of Dice Loss, the models record values of 0.051 and 0.08, respectively. The research highlights the effectiveness of different U-Net encoders in road network segmentation. With high accuracy and low Dice Loss, this approach provides a reliable method for automatically updating road maps. It has potential applications in navigation systems, urban planning, and AI-driven intelligent transportation systems.

Praktik Murabahah Emas Pada Bank Syariah di Indonesia Berdasarkan Tinjauan Hukum Fiqih Muamalah Juni Marianti, Dina; Rasyida, Zulfa; Utami, Ema
At-Tahdzib: Jurnal Studi Islam dan Muamalah Vol 10 No 2 (2022): At-Tahdzib
Publisher : Sekolah Tinggi Agama Islam At-Tahdzib, Ngoro, Jombang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61181/at-tahdzib.v10i2.275

Background. This study exists to examine the concept of investing or saving gold in Islamic banks which is carried out with the murabahah (buying and selling) financing model. Researchers found a problem, namely in the murabahah contract, and the gold payment mechanism which was carried out by means of fixed monthly installments.Aim. This paper aims to present the practice of gold murabahah at Bank Mandiri Syariah as an evaluation of the practice of saving gold with gold murabahah contracts in Islamic banksMethods. This study uses a comparative approach analysis method by analyzing the comparative law used by Islamic banks, namely the DSN MUI fatwa with a review of Fiqh muamalah according to the number of scholars. To explain this, the researcher uses a qualitative descriptive method with a muamalah fiqh approach, through this approach the researcher suggests how to practice according to the Shari'a.Results. The researcher found that there were differences of opinion among scholars regarding the concept of murabahah, and gold installments which the majority of scholars forbade it. Therefore, this study contributes to the analysis of the practice of saving gold in Islamic banks based on the fiqh muamalah review.

Graduation Prediction for Prospective University Students using Stacking Ensemble Learning Swastikawati, Claudia; Utami, Ema
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i6.5535

Student graduation is an important indicator in accreditation and serves as part of quality management strategies in higher education. Therefore, early prediction of student graduation is necessary to improve the effectiveness of data-driven admission decision-making. Differences in student graduation rates are influenced by a combination of academic, demographic, economic, and family factors. This study applies the Stacking Ensemble Learning method by combining Random Forest, K-Nearest Neighbors, and Support Vector Machine, with XGBoost serving as the meta-learner. The dataset used integrates student admission records and graduation status reports from the NeoFeeder PDDikti system, covering 16 academic and non-academic feature variables. The model was evaluated using accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). The results show that the stacking ensemble model outperformed single models, achieving 82% accuracy, a weighted F1-score of 80%, and an AUC of 87.15% on the test data. These findings contribute both the selected feature set and the implementation of an ensemble model for building a machine learning–based prediction system, particularly in addressing data imbalance and improving classification accuracy.

Reading Comprehension Strategies in EFL Classrooms: A Cognitive and Sociolinguistic Approach in Indonesian Schools Utami, Ema; Rahmat, Rahmat
Jurnal Tahuri Vol 20 No 1 (2023): February 2023
Publisher : Jurusan Pendidikan Bahasa dan Seni FKIP Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tahurivol20issue1page40-58

This study analyzes students’ reading comprehension strategies in the context of English as a Foreign Language (EFL) instruction in Indonesian schools through a cognitive and sociolinguistic approach. It focuses on how Indonesian learners interpret English texts when their linguistic proficiency is limited and when the sociocultural context of the text differs from their local experiences. Employing a qualitative multiple-case study design, the research was conducted in three secondary schools in Bandung Regency. Data were collected through classroom observations, teacher and student interviews, and analysis of students’ reading exercises and written reflections. The analysis integrated the framework of cognitive reading strategies, metacognition, inference, prediction, and self-monitoring, with the sociolinguistic perspective of literacy events to explore the relationship between individual cognitive processes and the social context of learning. The findings reveal that students who actively employ predicting, questioning, and summarizing strategies demonstrate deeper textual understanding. Linking reading materials to local sociocultural contexts, such as environmental issues or community traditions, significantly enhances motivation and engagement. However, a gap remains between teacher-centered instruction and students’ social experiences of meaning-making. The study introduces the Cognitive-Sociolinguistic Reading Framework, which integrates cognitive and sociolinguistic theories to reconceptualize reading comprehension as both a mental and sociocultural practice, contributing theoretical and pedagogical insights for EFL education in Southeast Asia.

Meningkatkan Dataset CodeXGLUE dengan Representasi Abstract Syntax Tree (AST) Ter Seragam untuk Analisis Kode Lintas Bahasa Siswo Utomo, Mardi; Utami, Ema; Kusrini, Kusrini; Setyanto, Arief
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 5: Oktober 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025125

Dataset kode sumber populer seperti CodeXGLUE belum menyediakan representasi sintaksis yang diseragamkan untuk penelitian lintas bahasa pemrograman. Hal ini akan menyulitkan saat dilakukan penelitian yang berkaitan dengan analisis syntax-aware. Penelitian ini menyediakan representasi sintaksis yang diseragamkan untuk memperkaya dataset CodeXGLUE. Kami menghadirkan dataset CodeXGLUE-AST (Abstract Syntax Tree) seragam untuk enam bahasa pemrograman: Go, Java, JavaScript, Python, Ruby, dan PHP. AST diekstraksi menggunakan Tree-sitter dan disimpan dalam format JSON terstruktur. Untuk menjaga konsistensi antar bahasa, kemudian dilakukan klasifikasi dan pemetaan tipe node guna menyatukan representasi struktur AST. Evaluasi dataset menggunakan analisis kelengkapan struktur AST, pengukuran akurasi rekonstruksi kode menggunakan skor BLEU, serta pengujian ekstraksi Data Flow Graph (DFG) untuk menjaga ketergantungan antar variabel. Selain itu juga dilakukan pengujian pada tugas peringkasan kode menggunakan model CodeT5 yang menunjukkan peningkatan nilai BLEU, METEOR, ROUGE dan ROUGE-L hampir disemua percobaan saat menggunakan AST yang diseragamkan. Dengan representasi AST yang telah diseragamkan, diharapkan pengembangan model ML multi bahasa yang lebih andal dan sadar sintaksis untuk tugas-tugas seperti klasifikasi kode, pembuatan ringkasan kode, dan rekonstruksi program akan menjadi lebih berkembang. Abstract Popular source code datasets like CodeXGLUE have not yet provided a standardized syntactic representation for cross-programming language research. This data gap will complicate research related to syntax-aware analysis. This research provides a standardized syntactic representation to enrich the CodeXGLUE dataset. We present a uniform CodeXGLUE-AST (Abstract Syntax Tree) dataset for six programming languages: Go, Java, JavaScript, Python, Ruby, and PHP. The AST is extracted using Tree-sitter and stored in a structured JSON format. To maintain consistency across languages, classification and mapping of node types were then performed to unify the AST structure representation. The dataset evaluation used AST structure completeness analysis, code reconstruction accuracy measurement using BLEU scores, and Data Flow Graph (DFG) extraction testing to maintain variable dependencies. Additionally, testing was conducted on the code summarization task using the CodeT5 model, which showed an increase in BLEU, METEOR, ROUGE, and ROUGE-L scores in almost all experiments when using the standardized AST. With the standardized AST representation, it is hoped that the development of more reliable and syntax-aware multilingual ML models for tasks such as code classification, code summarization, and program reconstruction will become more advanced.

Pengembangan dan Validasi Instrumen Kuesioner pada Model Evaluasi Game Digital Meega+ dengan Exploratory Factor Analysis (EFA) dan Cronbach’s Alpha Kurniawan, Mei; M. Suyanto; Utami, Ema; Kusrini
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 5: Oktober 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025125

Kemajuan pesat teknologi Game Edukasi Digital (DEG) berimbas pada meningkatnya kebutuhan evaluasi terhadap game edukasi yang lebih reliabel (dapat diandalkan). Model evaluasi MEEGA+ saat ini masih memiliki keterbatasan dalam hal aspek control dan feedback yang memiliki dampak pada nilai hasil evaluasi. Penelitian ini bertujuan untuk mengembangkan dan memvalidasi instrumen kuesioner MEEGA+ yang berbasis pada pendekatan statistik, termasuk Exploratory Factor Analysis (EFA) dan Cronbach’s Alpha, untuk meningkatkan keandalan dan validitas evaluasi DEG. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan desain survei eksplanatori. Instrumen dikembangkan berdasarkan model MEEGA+ yang dimodifikasi, kemudian diuji melalui penyebaran kuesioner daring kepada responden. Studi kasus dilakukan pada game edukasi Minecraft dan Duolingo melalui survei secara daring dengan melibatkan 1.200 siswa SMA yang tersebar di seluruh wilayah Indonesia. Data yang terkumpul dianalisis menggunakan teknik Exploratory Factor Analysis (EFA) untuk mengidentifikasi struktur faktor, dan dilanjutkan dengan pengujian reliabilitas menggunakan nilai Cronbach’s Alpha pada berbagai variasi jumlah butir pertanyaan. Analisis dilakukan melalui variasi kombinasi pertanyaan (sebanyak 1, 2, dan 3 butir). Hasil penelitian kemudian menunjukkan bahwa kuesioner dengan hanya 2 butir pertanyaan (a dan b) ternyata menghasilkan reliabilitas tertinggi dengan nilai Cronbach’s Alpha sebesar 0,903 untuk game edukasi Minecraft dan 0,913 untuk game edukasi bahasa Duolingo. Hasil ini tentu saja melampaui nilai Cronbach’s Alpha model MEEGA+ saat ini yaitu hanya sebesar 0,866. Temuan ini memberikan kontribusi dalam pengembangan instrument alat evaluasi MEEGA+, sekaligus juga mencerminkan kebaruan dalam pendekatan yang digunakan. Instrumen temuan ini diharapkan mampu menjadi alat evaluasi yang lebih relevan dan signifikan untuk mendukung peningkatan kualitas DEG dalam pendidikan modern saat ini dan kedepannya nanti. Abstract The rapid advancement of Digital Educational Game (DEG) technology has resulted in the increasing need for more reliable evaluation of educational games. The current MEEGA+ evaluation model still has limitations regarding control and feedback aspects that impact the evaluation result value. This study aims to develop and validate the MEEGA+ questionnaire instrument based on a statistical approach, including Exploratory Factor Analysis (EFA) and Cronbach's Alpha, to improve the reliability and validity of the DEG evaluation. The research method used is a quantitative approach with an explanatory survey design. The instrument was developed based on the modified MEEGA+ model, then tested through the distribution of online questionnaires to respondents. The case study was conducted on Minecraft and Duolingo educational games through an online survey involving 1,200 high school students spread throughout Indonesia. The collected data was analyzed using the Exploratory Factor Analysis (EFA) technique to identify the factor structure and continued with reliability testing using Cronbach's Alpha values on various variations in the number of questions. The analysis was done through various question combinations (as many as 1, 2, and 3 items). The study results then showed that the questionnaire with only two questions (a and b) produced the highest reliability with a Cronbach's Alpha value of 0.903 for the Minecraft educational game and 0.913 for the Duolingo language educational game. These results certainly exceed the Cronbach's Alpha value of the current MEEGA+ model, which is only 0.866. These findings contribute to developing the MEEGA+ evaluation tool instrument while also reflecting the novelty of the approach used. It is anticipated that the results of this instrument will be a more pertinent and important assessment tool to help raise the standard of DEG in contemporary education both now and in the future.

Analysis of the Similiarity Level of Source Code in the Kotlin Programming Language using Winnowing Algorithm Astica, Yustikamasy; Utami, Ema; Hartanto, Anggit Dwi
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.902

Plagiarism is an act of imitating the work of others directly or indirectly. In an academic environment, plagiarism applies not only to textual documents but also to source code documents. Source code plagiarism in academia usually occurs when students copy another student's code and submit it as if it were the student's work. So that an automatic plagiarism check is needed, the winnowing algorithm will be used to help detect similarities in source code as a way to detect an act of plagiarism. The Winnowing algorithm, which is usually used to detect document plagiarism, this research detects the source code. The results produced in this study are that the degree of similarity in the two source codes will produce different similarity values if the dataset used has gone through the text preprocessing stage or without preprocessing. If the dataset has gone through the text preprocessing stage, the similarity value will be pretty low because the number of characters used is significantly reduced. The Winnowing and Jaccard Similarity algorithms quickly detect plagiarism in source code and can be used to minimize plagiarism.

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

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