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All Journal International Journal of Electrical and Computer Engineering Tekno : Jurnal Teknologi Elektro dan Kejuruan Teknologi dan Kejuruan: Jurnal teknologi, Kejuruan dan Pengajarannya Jurnal Inovasi Teknologi Pendidikan International Journal of Advances in Intelligent Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Briliant: Jurnal Riset dan Konseptual JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Knowledge Engineering and Data Science Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JOURNAL OF APPLIED INFORMATICS AND COMPUTING Pendas : Jurnah Ilmiah Pendidikan Dasar Cetta: Jurnal Ilmu Pendidikan ILKOM Jurnal Ilmiah at-tamkin: Jurnal Pengabdian kepada Masyarakat SENTIA 2016 SENTIA 2015 MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Karinov TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Edunesia : jurnal Ilmiah Pendidikan Discovery : Jurnal Ilmu Pengetahuan Indonesian Journal of Data and Science Letters in Information Technology Education (LITE) Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Decode: Jurnal Pendidikan Teknologi Informasi Emerging Information Science and Technology Bulletin of Community Engagement Journal of Education Research Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Reflection Journal JUSIFOR : Jurnal Sistem Informasi dan Informatika Jurnal Ekonomi, Bisnis dan Pendidikan (JEBP) Advance Sustainable Science, Engineering and Technology (ASSET) Systematic Literature Review Journal
Didik Dwi Prasetya
Universitas Negeri Malang
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Detecting emotions using a combination of bidirectional encoder representations from transformers embedding and bidirectional long short-term memory Wibawa, Aji Prasetya; Cahyani, Denis Eka; Prasetya, Didik Dwi; Gumilar, Langlang; Nafalski, Andrew
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp7137-7146

Abstract

One of the most difficult topics in natural language understanding (NLU) is emotion detection in text because human emotions are difficult to understand without knowing facial expressions. Because the structure of Indonesian differs from other languages, this study focuses on emotion detection in Indonesian text. The nine experimental scenarios of this study incorporate word embedding (bidirectional encoder representations from transformers (BERT), Word2Vec, and GloVe) and emotion detection models (bidirectional long short-term memory (BiLSTM), LSTM, and convolutional neural network (CNN)). With values of 88.28%, 88.42%, and 89.20% for Commuter Line, Transjakarta, and Commuter Line+Transjakarta, respectively, BERT-BiLSTM generates the highest accuracy on the data. In general, BiLSTM produces the highest accuracy, followed by LSTM, and finally CNN. When it came to word embedding, BERT embedding outperformed Word2Vec and GloVe. In addition, the BERT-BiLSTM model generates the highest precision, recall, and F1-measure values in each data scenario when compared to other models. According to the results of this study, BERT-BiLSTM can enhance the performance of the classification model when compared to previous studies that only used BERT or BiLSTM for emotion detection in Indonesian texts.
Analisis Penggunaan Listrik PLN di Jawa Timur Menggunakan Algoritma K-Medoids Hafiizh, Muhammad; Prasetyo, Muchamad Wahyu; Prasetya, Didik Dwi
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol 5, No 02 (2024): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v5i2.10606

Abstract

Listrik merupakan kompoen penting dalam kehidupan sekarang dan masa yang akan datang, untuk meningkatkan efisien produksi listrik di masa mendatang, maka perlunya dilakukan pengolahan data dari tahun tahun sebelumnya. Dalam pengolahan data ini peneliti mempunyai tujuan untuk melakukan forecasting kebutuhan listrik dimasa mendatang di Provinsi Jawa Timur, selain kebutuhan listrik harapannya peneliti dalam melakukan forecasting pada listrik terjula, jumlah data terpasang dan pelanggan listrik. Dalam melakukan forecasting peneliti menggunakan metode K-Medoids dalam pengelompokan (Clustering) Produksi Listrik, Listrik Terjual, Data Terpasang, dan Jumlah Pelanggan di Provinsi Jawa Timur. Dari data pengelompokan tersebut diperoleh 3 cluster, yaitu cluster rendah terdiri dari 2 data dan kota, cluster sedang terdiri dari 23 data dan kota, cluster tinggi terdiri dari 25 data dan kota. Diharapkan dengan adanya forecasting dapat meningkatkan efisiensi dalam penggunaan dan produksi listrik dimasa mendatang sehingga listrik dapat terus tersedia dalam keberlangsungan hidup manusia.
LSTM-Based Machine Translation for Madurese-Indonesian Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almu'iini
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.113

Abstract

Madurese is one of the regional languages in Indonesia, which dominates East Java and Madura Island in particular. The use of Madurese as a daily language has declined significantly due to a language shift in children and adolescents, some of which are caused by a sense of prestige and difficulty in learning Madurese. The scarcity of research or scientific titles that raises the Madurese language also helps reduce literacy in the language. Our research focuses on creating a translation machine for Madurese to Indonesian to maintain and preserve the existence of the Madurese language so that learning can be done through digital media. This study use the latest dataset for the Madurese-Indonesian language by using a corpus of 30,000 Madura-Indonesian sentence pairs from the online Bible. This study scrapped online Bible pages to organize the corpus based on the Indonesian and Madurese bilingual Bible. Then This study manually process text to match the two languages' scrapping results, normalization, and tokenization to remove non-printable characters and punctuation from the corpus. To perform neural machine translation (NMT), This study connected the RNN encoder with the RNN decoder of the language model, while for training and testing, This study used a sequential model with LSTM, while the BLEU measure was used to assess the accuracy of the translation results. This study used the SoftMax optimization function with Adam Optimizer and added some settings, including using 128 layers in the training process and adding a Dropout layer so that This study got the average evaluation result for BLEU-1 is 0.798068, BLEU-2 is 0.680932, BLEU-3 is 0.623489, and for BLEU-4 is 0.523546 from five tests conducted. Given the language differences between Madurese and Indonesian, this can be the best approach for machine translation of Indonesian to Madurese.
PENCEGAHAN PERUNDUNGAN DARING BAGI PESERTA DIDIK TINGKAT SEKOLAH MENENGAH PERTAMA (SMP) Mega Oktaviana; Didik Dwi Prasetya; Natalina Wahyu Siswijayanti
Jurnal Ekonomi, Bisnis dan Pendidikan Vol. 4 No. 1 (2024)
Publisher : Universitas Negeri Malang

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

Abstract

Di era digital teknologi informasi dan komunikasi khususnya media sosial meningkat secara signifikan, namun dalam perkembangnya terdapat dampak negatif yang menyertainya salah satunya adalah perundungan daring. Perundungan daring di kalangan remaja SMP merupakan salah satu permasalahan serius yang perlu dicegah guna meminimalisir kerugian bagi korban di masa mendatang. Bentuk penelitian yang diterapkan dalam artikel ini merupakan penelitian berbasis tinjauan literasi, data yang digunakan berupa data yang berasal dari informasi teks yang diperoleh dari basis data Google Scholar yang dipublikasikan antara tahun 2019 hingga tahun 2024. Hasil penelitian mengidentifikasi faktor-faktor penyebab perundungan daring berupa faktor dalam diri (internal) dan faktor lingkungan (eksternal). Selain itu diperlukan berbagai langkah dalam mencegah perundungan daring bagi peserta didik di tingkat SMP, merupakan tugas bagi seluruh lapisan masyarakat agar dapat lebih bijak dalam menggunakan media sosial dan mencipatakan lingkungan yang lebih positif sehingga perundungan daring dapat diminimalisir secara signifikan. Perundungan daring bukanlah masalah yang dapat diabaikan agar menciptakan lingkungan digital yang aman dan nyaman bagi semua pengguna.
PEMANFAATAN PANEL SURYA UNTUK SISTEM PINTU AKSES OTOMATIS BERBASIS RFID DAN IOT PADA LABORATORIUM TEKNIK ELEKTRO UNIVERSITAS TULUNGAGUNG bagaskoro; Hafiizh, Muhammad; Didik Dwi Prasetya
Jurnal Pengabdian Kepada Masyarakat Vol 7 No 2 (2024): At-Tamkin - Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Islam Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/attamkin.v7i2.5783

Abstract

Laboratorium Teknik Elektro Universitas Tulungagung masih menggunakan sistem akses pintu manual dengan kunci konvensional yang memiliki beberapa kelemahan dalam hal keamanan dan efisiensi pemantauan. Pengabdian masyarakat ini bertujuan untuk mengimplementasikan sistem pintu akses otomatis berbasis RFID (Radio Frequency Identification) dan IoT (Internet of Things) dengan sumber energi panel surya. Metode pelaksanaan meliputi survei lokasi, desain dan pembuatan TTG (Teknologi Tepat Guna), implementasi sistem yang terdiri dari instalasi dan pengujian di lapangan, serta pelatihan penggunaan sistem kepada pengelola laboratorium. Sistem yang dikembangkan mengintegrasikan tiga teknologi utama: (1) RFID untuk identifikasi pengguna yang berhak mengakses laboratorium, (2) IoT untuk pemantauan dan pengendalian jarak jauh melalui aplikasi smart phone, dan (3) panel surya sebagai sumber energi terbarukan. Hasil pengabdian menunjukkan bahwa sistem yang diimplementasikan dapat meningkatkan aspek keamanan melalui pembatasan akses menggunakan kartu RFID, memudahkan pemantauan aktivitas keluar-masuk laboratorium secara real-time, serta mendukung efisiensi energi melalui pemanfaatan panel surya. Sistem ini juga mendukung visi Universitas Tulungagung menuju smart campus yang ramah lingkungan dengan memanfaatkan teknologi informasi terkini.
Integrasi Teknologi Mobile Untuk Pembelajaran Dasar Desain Grafis: Pengembangan E-Modul Berbasis Proyek Untuk SMK Yusril Imamuddin; Didik Dwi Prasetya; Tuwoso
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 4 No. 1: MARET 2024
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v4i1.253

Abstract

Salah satu permasalahan utama yang dihadapi adalah pembelajaran dasar desain grafis yang masih mengandalkan modul konvensional dan media presentasi, yang kurang efektif dalam membantu siswa memahami konsep, khususnya terkait penerapan gambar vektor. Disamping itu penelitian mengenai penerapan teknologi mobile untuk mengembangkan e-modul berbasis proyek dengan tujuan meningkatkan pemahaman dan partisipasi siswa dalam pembelajaran dasar desain grafis di SMK masih jarang dilakukan. Sehingga tujuan penelitian ini adalah mengembangkan Mobile E-Module untuk siswa kelas X DKV SMK Negeri 1 Kalitengah berbasis project-based learning pada materi dasar desain grafis untuk penerapan pembuatan gambar vektor. Untuk mengevaluasi e-modul, pendidik, praktisi lapangan, ahli media, ahli materi, dan 34 siswa berpartisipasi dalam proyek penelitian dan pengembangan. Wawancara, observasi, dan kuesioner adalah beberapa prosedur pengumpulan data, sedangkan metode kualitatif dan kuantitatif digunakan untuk pengolahan data. Penelitian ini berhasil mengembangkan e-modul Android berbasis PjBL yang valid, praktis dan layak digunakan. Berdasarkan uji keefektifan, skor N-gain dalam kategori tinggi dan peningkatan skor pre-test dan post-test merupakan indikator kebermanfaatan e-modul ini. Dengan demikian, pembelajaran desain grafis di SMK dapat memberikan siswa pengalaman belajar yang menyenangkan, interaktif, dan beragam serta meningkatkan kualitas pengajaran. Keberhasilan penerapan teknologi seluler ini menunjukkan kemungkinan besar untuk menggabungkan teknologi terkait di bidang kurikulum SMK lainnya.
Design and Development of Online Collaborative Learning Platform of Kit-Build Concept Map Pinandito, Aryo; Prasetya, Didik Dwi; Az-zahra, Hanifah Muslimah; Wardhono, Wibisono Sukmo; Hayashi, Yusuke; Hirashima, Tsukasa
Journal of Information Technology and Computer Science Vol. 6 No. 1: April 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (680.051 KB) | DOI: 10.25126/jitecs.202161294

Abstract

A concept map is deemed a useful teaching and learning tool. It offers many potential advantages over just representing the students’ knowledge and understanding during learning, and have been widely used to support learning. Kit-Build concept map is one learning framework that incorporate digital concept map for its learning activities. Learning with Kit-Build concept map has been found to have better learning effects towards students' understanding and knowledge retention. Incorporating Kit-Build concept map into collaborative learning have been reported to have better outcome than the traditional collaborative learning. However, collaborative learning with Kit-Build concept map cannot be accomodated with the current Kit-Build system where learning activity is conducted online. This study presents the design and development of online collaborative learning platform of Kit-Build Concept Map. A prototype of the collaboration system to support collaborative learning with Kit-Build concept map is developed and be evaluated to portray its potential usability for further development and practical use. The result suggested that incorporating Socket.IO as a real-time communication middleware is effective to deliver online collaborative learning features into the Kit-Build system. Preliminary evaluation to the system also suggested that the system has the potential for actual use in supporting distant collaborative learning with Kit-Build concept map.
Student Dropout Prediction Using Random Forest and XGBoost Method Putra, Lalu Ganda Rady; Prasetya, Didik Dwi; Mayadi, Mayadi
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 1 (2025): February 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i1.21191

Abstract

Background: The increasing dropout rate in Indonesia poses significant challenges to the education system, particularly as students advance through higher education levels. Predicting student attrition accurately can help institutions implement timely interventions to improve retention. Objective: This study aims to evaluate the effectiveness of the Random Forest and XGBoost algorithms in predicting student attrition based on demographic, socioeconomic, and academic performance factors. Methods: A quantitative study was conducted using a dataset of 4,424 instances with 34 attributes, categorized into Dropout, Graduate, and Enrolled. The performance of Random Forest and XGBoost was compared based on accuracy, specificity, and sensitivity. Results: Random Forest achieved the highest accuracy at 80.56%, with a specificity of 76.41% and sensitivity of 72.42%, outperforming XGBoost. While XGBoost was slightly less accurate, it remained a competitive approach for student attrition prediction. Conclusion: The findings highlight Random Forest's robustness in handling extensive datasets with diverse attributes, making it a reliable tool for identifying at-risk students. This study underscores the potential of machine learning in addressing educational challenges. Future research should explore advanced ensemble techniques, such as the Ensemble Voting Classifier, or deep learning models to further enhance prediction accuracy and scalability. 
Anatomy of Sentiment Analysis in Ontological, Epistemological, and Axiological Perspectives Fadli Hidayat, M. Noer; Dwi Prasetya, Didik; Widiyaningtyas, Triyanna; Patmanthara, Syaad
JOIN (Jurnal Online Informatika) Vol 10 No 1 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i1.1228

Abstract

The aim of this article was to examine sentiment analysis methods from the perspective of the philosophy of science with three approaches, ontological, epistemological and axiological. This research used a qualitative research method (descriptive-analysis) with an ontological, epistemological and axiological approach that uses library research and document studies of previous research results. Data collection was carried out through books and reputable scientific journals on Scopus, ScienceDirect, IEEEXplore and Springer Link. The results of this research showed that sentiment analysis from an ontological perspective describes the definition, development and relationship of sentiment with social reality. Meanwhile, from an epistemological perspective, sentiment analysis is viewed from how the source of knowledge is obtained, explaining the production of sentiment analysis knowledge, and several ways of working that can be applied in studies. Axiologically, sentiment analysis can see the function and value resulting from sentiment analysis, as well as discussing the results of interpretation from sentiment analysis studies. These findings showed the development of sentiment analysis in answering various problems to improve the quality of sustainable services in various fields.
An enhanced pivot-based neural machine translation for low-resource languages Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almuíini
International Journal of Advances in Intelligent Informatics Vol 11, No 2 (2025): May 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i2.2115

Abstract

This study examines the efficacy of employing Indonesian as an intermediary language to improve the quality of translations from Javanese to Madurese through a pivot-based approach utilizing neural machine translation (NMT). The principal objective of this research is to enhance translation precision and uniformity among these low-resource languages, hence advancing machine translation models for underrepresented languages. The data collecting approach entailed extracting parallel texts from internet sources, followed by pre-processing through tokenization, normalization, and stop-word elimination algorithms. The prepared datasets were utilized to train and assess the NMT models. An intermediary phase utilizing Indonesian is implemented in the translation process to enhance the accuracy and consistency of translations between Javanese and Madurese. Parallel text corpora were created by collecting and preprocessing data, thereafter, utilized to train and assess the NMT models. The pivot-based strategy regularly surpassed direct translation regarding BLEU scores for all n-grams (BLEU-1 to BLEU-4). The enhanced BLEU ratings signify increased precision in vocabulary selection, preservation of context, and overall comprehensibility. This study significantly enhances the current literature in machine translation and computational linguistics, especially for low-resource languages, by illustrating the practical effectiveness of a pivot-based method for augmenting translation precision. The method's dependability and efficacy in producing genuine translations were proved through numerous studies. The pivot-based technique enhances translation quality, although it possesses limitations, including the risk of error propagation and bias originating from the pivot language. Further research is necessary to examine the integration of named entity recognition (NER) to improve accuracy and optimize the intermediate translation process. This project advances the domains of machine translation and the preservation of low-resource languages, with practical implications for multilingual communities, language education resources, and cultural conservation.
Co-Authors Abdul Karim Abdul Wafi Abdullah Iskandar Syah Achmad Afif Irwansyah Adi Wahyu Wardani Ahmad Fajruddin Syauqi Ahmad Reza Adrian Ahmad Yusuf Setiawan Ainun Nur Baiti Aji P Wibawa Aji Prasetya Wibawa Akbar, Asna Isyarotul Andika Dwiyanto, Felix Andrew Nafalski Anik Nur Handayani Anjar Dwi Rahmawati Arifiati Fitri Anggraini Aripriharta - Aryo Pinandito Ashar, Muhammad Azhar Ahmad Smaragdina Azlan Mohd Zain Bagaskoro Biantoro, Yudhi Bintang Romadhon Cakir, Gulsun Kurubacak Danang Arbian Sulistyo Denis Eka Cahyani Dwi Widiyasari Dyah Ayu Langening Tyas Ella Amelia Widodo Enggie Hendrawan Saputra F.ti Ayyu Sayyidul Laily Fadhli Almu’iini Ahda Fadli Hidayat, M. Noer Fathan Alfariel Adhyaksa Fatrisna Salsabila, Reni Febrianto Alqodri Firdaus, Nabilah Zakiyah Salmaa Frendy Rumambi Gradiyanto Radityo Kusumo Hafid, Ahmad Hairani Hairani Hakkun Elmunsyah Hanif Rifai Adha Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haq, Salsabila Thifal Nabil Hariyanto Hariyanto Hayashi, Yusuke Hirasama, Tsukasa Hirashima, Tsukasa I Made Wirawan I Nyoman Gede Arya Astawa Ilham Ari Elbaith Zaeni Intan Sulistyaningrum Sakkinah Jevri Tri Ardiansyah Kalifatullah, M. Ajie Khoirul Anwar KHOIRUL ANWAR Kusumo, Gradiyanto Radityo Laily, F.ti Ayyu Sayyidul Lalu Ganda Rady Putra Langlang Gumilar Lismi Animatul Chisbiyah Luqman Affandi Lutfi Budi Ilmawan, Lutfi Budi M. Ajie Kalifatullah Marsono Marsono Marsono Marsono Maskur Maskur Maskur Maskur Mayadi Mayadi Mega Oktaviana Moh. Nur Zamzami Moh. Zainul Falah Moh. Zulfiqar Naufal Maulana Muhammad Arief Nugroho Muhammad Aris Ichwanto muhammad hafiizh, muhammad Muhammad Jauharul Fuady Muhammad Mushawwir Muhammad Zaki Wiryawan Muhammad Zidni Ridlo Mukhamad Angga Gumilang Muladi Nadiah Alma Ratnaduhita Nadindra Dwi Ariyanta Nafalski, Andrew Nanscy Evi Wardani Natalina Wahyu Siswijayanti Nena Erviana Nunung Nurjanah Nur Hidayat, Wahyu Nuryakin, Mokhamad Perkasa, Gigih Prasetya, Luhur Adi Prasetyo, Muchamad Wahyu Prihandicha, Adiftya Bayu Putro, Maulana Nur Antoro Ratnaduhita, Nadiah Alma Reni Fatrisna Salsabila Reo Wicaksono Ridlo, Muhammad Zidni Rismayanti, Nurul Rofiudin, Amir Rumambi, Frendy Rocky Ryan Kurniawan Samodra, Joko Setiadi Cahyono Putro Setiawan, Ahmad Yusuf Setyani, Ida Agus Shafelbilyunazra, Alvalen Sigit Perdana Siti Sendari Sofiya Anggraini Sri Sumanti, Endang Sucipto Sucipto Sucipto Sucipto Sucipto Sucipto Sulistyo, Danang Arbian Sumanti, Endang Sri Syaad Patmanthara Syaichul Fitrian Akbar Syamsul Arifin Triyanna Widiyaningtyas Triyanna Widyaningtyas Triyanna Widyaningtyas, Triyanna Tsukasa Hirashima Tsukasa Hirashima Tsukasa Hirashima Tuwoso Usman Nurhasan Usman Nurhasan Utama, Agung Bella Putra Utomo Pujianto Wahfi, Muhammad Fikri Wahyu Sakti Gunawan Irianto Wahyu Styo Pratama Wahyu Tri Handoko Wahyudi, Erlik Prasetyo Wardani, Adi Wahyu Welly Antonius Wibawa, Aji P Wibisono Sukmo Wardhono, Wibisono Sukmo Widiyanti Widiyanti, Widiyanti Yana Andayani Yusril Imamuddin Zaeni, Ilham Ari Elbaith Zainul Falah, Moh.