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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer dan Informasi Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmu Komputer Jurnal Teknik ITS Majalah Kedokteran Bandung IPTEK The Journal for Technology and Science CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Kursor Jurnal technoscientia Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications REKAYASA JPM17: Jurnal Pengabdian Masyarakat POROS TEKNIK Annual Research Seminar Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology Jurnal Inspiration Dental Journal (Majalah Kedokteran Gigi) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal ULTIMATICS Journal of Computer Science and Informatics Engineering (J-Cosine) Systemic: Information System and Informatics Journal Specta Journal of Technology EPI International Journal of Engineering ILKOMNIKA: Journal of Computer Science and Applied Informatics Indonesian Journal of Electrical Engineering and Computer Science JURNAL TEKNOLOGI TECHNOSCIENTIA Makara Journal of Technology Sewagati Nusantara Journal of Computers and its Applications Jurnal INFOTEL
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Analisis Metode Representasi Teks Untuk Deteksi Interelasi Kitab Hadis: Systematic Literature Review Amelia Devi Putri Ariyanto; Chastine fatichah; Agus Zainal Arifin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (359.814 KB) | DOI: 10.29207/resti.v5i5.3499

Abstract

Hadith is the second source of reference for Islamic law after the Qur'an, which explains the sentences in the Qur'an which are still global by referring to the provisions of the Prophet Muhammad SAW. Classification of text documents can also be used to overcome the problem of interrelation between the Qur'an and hadith. The problem of interrelation between books of hadith needs to be done because some hadiths in certain hadith books have the same meaning as other hadith books. This study aims to analyze the development of text representation and classification methods suitable to overcome similarity meaning problems in detecting interrelationships between hadith books. The research method used is Systematic Literature Review (SLR) sourced from Google Scholar, Science Direct, and IEEE. There are 42 pieces of literature that have been studied successfully. The results showed that contextual embedding as the newest text representation method considered word context and sentence meaning better than static embedding. As a classification method, the ensemble method has better performance in classifying text documents than using only a single classifier model. Thus, future research can consider using a combination of contextual embedding and ensemble methods to detect interrelationships between books of hadith.
Sistem Informasi Absensi Haul Berbasis Web di Pondok Pesantren Muhyiddin Surabaya Jannah, Erliyah Nurul; Arifin, Agus Zainal
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 1, No 1 (2015): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v1i1.405

Abstract

Teknologi informasi saat ini telah menjadi kebutuhan bagi hampir semua instansi, baik pemerintah maupun swasta. Tak terkecuali pondok pesantren, khususnya Pondok Pesantren Muhyiddin Surabaya. Berbagai permasalahan di pondok pesantren membutuhkan bantuan teknologi informasi dalam penyelesaiannya. Salah satunya adalah permasalahan pencatatan kehadiran peserta dalam suatu acara tertentu seperti acara Haul. Haul merupakan acara tahunan yang bertujuan untuk memperingati hari lahirnya Nabi Muhammad SAW. Acara Haul di PP. Muhyiddin mendatangkan lebih dari seribu peserta yang merupakan penghafal Quran. Panitia Haul harus mengabsen peserta satu persatu serta menempatkannya ke majelis-majelis berdasarkan urutan kedatangan dan kota asal. Sistem informasi absensi yang ada masih berbasis desktop dan hanya mampu digunakan untuk mengabsen peserta saja. Sistem tersebut belum mampu melakukan pembagian majelis peserta secara otomatis. Padahal proses pembagian majelis inilah yang menyebabkan proses absensi memakan waktu lama. Oleh sebab itu, dibuatlah sebuah Sistem Informasi Absensi Haul yang berbasis web. Sistem ini diharapkan mampu untuk membuat proses absensi pada acara Haul menjadi lebih efisien. Dari hasil pengujian sistem yang telah dilakukan, dalam satu menit sistem dapat digunakan untuk mengabsen sepuluh peserta, membagi peserta tersebut ke majelis-majelis, dan mencetak kartu peserta Haul.
Query Expansion menggunakan Word Embedding dan Pseudo Relevance Feedback Tanuwijaya, Evan; Adam, Safri; Anggris, Mohammad Fatoni; Arifin, Agus Zainal
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 5, No 1 (2019): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v5i1.1385

Abstract

Kata kunci merupakan hal terpenting dalam mencari sebuah informasi. Penggunaan kata kunci yang tepat menghasilkan informasi yang relevan. Saat penggunaannya sebagai query, pengguna menggunakan bahasa yang alami, sehingga terdapat kata di luar dokumen jawaban yang telah disiapkan oleh sistem. Sistem tidak dapat memproses bahasa alami secara langsung yang dimasukkan oleh pengguna, sehingga diperlukan proses untuk mengolah kata-kata tersebut dengan mengekspansi setiap kata yang dimasukkan pengguna yang dikenal dengan Query Expansion (QE). Metode QE pada penelitian ini menggunakan Word Embedding karena hasil dari Word Embedding dapat memberikan kata-kata yang sering muncul bersama dengan kata-kata dalam query. Hasil dari word embedding dipakai sebagai masukan pada pseudo relevance feedback untuk diperkaya berdasarkan dokumen jawaban yang telah ada. Metode QE diterapkan dan diuji coba pada aplikasi chatbot. Hasil dari uji coba metode QE yang diterapkan pada chatbot didapatkan nilai recall, precision, dan F-measure masing-masing 100%; 70% dan 82,35 %. Hasil tersebut meningkat 1,49% daripada chatbot tanpa menggunakan QE yang pernah dilakukan sebelumnya yang hanya meraih akurasi sebesar 68,51%. Berdasarkan hasil pengukuran tersebut, QE menggunakan word embedding dan pseudo relevance feedback pada chatbot dapat mengatasi query masukan dari pengguna yang ambigu dan alami, sehingga dapat memberikan jawaban yang relevan kepada pengguna.  Keywords are the most important words and phrases used to obtain relevant information on content. Although users make use of natural languages, keywords are processed as queries by the system due to its inability to process. The language directly entered by the user is known as query expansion (QE). The proposed QE in this research uses word embedding owing to its ability to provide words that often appear along with those in the query. The results are used as inputs to the pseudo relevance feedback to be enriched based on the existing documents. This method is also applied to the chatbot application and precision, and F-measure values of the results obtained were 100%, 70%, 82.35% respectively. The results are 1.49% better than chatbot without using QE with 68.51% accuracy. Based on the results of these measurements, QE using word embedding and pseudo which gave relevance feedback in chatbots can resolve ambiguous and natural user’s input queries thereby enabling the system retrieve relevant answers.
Ambiguitas Machine Translation pada Cross Language Chatbot Bea Cukai Al Haromainy, Muhammad Muharrom; Setyawan, Dimas Ari; Waluya, Onny Kartika; Arifin, Agus Zainal
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 5, No 1 (2019): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v5i1.1387

Abstract

Sistem Information Retrieval (IR) maupun chatbot semakin banyak dikembangkan. Salah satu bagian yang banyak diteliti adalah cross language. Masalah pada pengembangan cross language yaitu terjadinya kesalahan pada hasil terjemahan mesin translasi yang memberikan arti tidak sesuai dengan bahasa natural, sehingga pengguna tidak mendapatkan jawaban yang semestinya, bahkan tidak jarang pula pengguna tidak menemukan jawaban. Penelitian ini mengusulkan skema baru mesin translasi yang bertujuan meningkatkan performa dalam masalah ambiguitas. Mesin translasi bekerja dengan cek kebenaran kata kunci, kemudian melakukan Part-of-Speech (POS) Tagging pada kata benda (noun). Kemudian, setiap kata benda yang terdeteksi akan dicari sinonimnya. Lalu, sinonim yang didapatkan akan ditambahkan dan menjadi alternatif kueri baru. Kueri yang mempunyai nilai confident tertinggi diasumsikan sebagai kueri yang paling sesuai. Pada hasil yang didapatkan setelah dilakukan uji coba, melalui penambahan metode yang kami usulkan pada machine translation, dapat meningkatkan akurasi chatbot dibandingkan tanpa menggunakan skema yang diusulkan. Hasil akurasi bertambah 5%, dari yang semula 73% menjadi 77%.  Information retrieval and chatbot systems are increasingly being developed with its language part mostly studied. However, the problem associated with its development is the occurrence of errors in the translation machine resulting in inaccurate answers not in accordance with the natural language, thereby providing users with wrong answers. This study proposes a new translation machine scheme that aims to improve performance while translating ambiguous terms. Translation machines functions by checking the correctness of keywords, and carrying out Part-of-Speech (POS) Tagging on nouns (noun). The synonyms of any detected noun are searched for and obtained added to become alternative new queries. Those with the highest confident value are assumed to be the most appropriate. The results obtained after testing, through the addition of the method proposed in machine translation, can improve the accuracy of the chatbot compared to not using the proposed scheme. The results of the accuracy increased from the original 73% to 77%.
Deteksi Bot Spammer Twitter Berbasis Time Interval Entropy dan Global Vectors for Word Representations Tweet’s Hashtag Priyatno, Arif Mudi; Muttaqi, Muhammad Mirza; Syuhada, Fahmi; Arifin, Agus Zainal
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 5, No 1 (2019): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v5i1.1382

Abstract

Bot spammer merupakan penyalahgunaan user dalam menggunakan Twitter untuk menyebarkan pesan spam sesuai dengan keinginan user. Tujuan spam mencapai trending topik yang ingin dibuatnya. Penelitian ini mengusulkan deteksi bot spammer pada Twitter berbasis Time Interval Entropy dan global vectors for word representations (Glove). Time Interval Entropy digunakan untuk mengklasifikasi akun bot berdasarkan deret waktu pembuatan tweet. Glove digunakan untuk melihat co-occurrence kata tweet yang disertai Hashtag untuk proses klasifikasi menggunakan Convolutional Neural Network (CNN). Penelitian ini menggunakan data API Twitter dari 18 akun bot dan 14 akun legitimasi dengan 1.000 tweet per akunnya. Hasil terbaik recall, precision, dan f-measure yang didapatkan yaitu 100%; 100%, dan 100%. Hal ini membuktikan bahwa Glove dan Time Interval Entropy sukses mendeteksi bot spammer dengan sangat baik. Hashtag memiliki pengaruh untuk meningkatkan deteksi bot spammer.  Spam spammers are users' misuse of using Twitter to spread spam messages in accordance with user wishes. The purpose of spam is to reach the required trending topic. This study proposes detection of bot spammers on Twitter based on Time Interval Entropy and global vectors for word representations (Glove). Time Interval Entropy is used to classify bot accounts based on the tweet's time series, while glove views the co-occurrence of tweet words with Hashtags for classification processes using the Convolutional Neural Network (CNN). This study uses Twitter API data from 18 bot accounts and 14 legitimacy accounts with 1000 tweets per account. The best results of recall, precision, and f-measure were 100%respectively. This proves that Glove and Time Interval Entropy successfully detects spams, with Hash tags able to increase the detection of bot spammers.
Pola Posisi Berbasis Fuzzy dalam Domain Frekuensi dan Pseudopolar Fourier Transform untuk Identifikasi Bintang Baru Cahyani, Laili; Arifin, Agus Zainal; Wijaya, Arya Yudhi
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol 5, No 2 (2015): Jurnal Inspiration Volume 5 Issue 2
Publisher : STMIK AKBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v5i2.66

Abstract

Identifikasi bintang diperlukan dalam penelusuran bintang. Namun, adanya bintang baru dapat mempengaruhi stabilitas bintang di sekitarnya. Hal itu dapat menyebabkan kesalahan dalam penelurusan bintang. Maka, diperlukan sebuah aplikasi yang mampu melakukan identifikasi bintang baru. Salah satu cara untuk melakukan identifikasi bintang baru adalah dengan membandingkan citra masukan terhadap citra database. Permasalahan terjadi ketika pengambilan citra bintang dilakukan pada waktu atau kondisi yang berbeda. Sehingga penelitian ini melakukan identifikasi bintang baru dengan mengintegrasikan metode pola posisi berbasis Fuzzy dalam domain frekuensi dan Pseudopolar Fourier Transform. Metode pola posisi berbasis Fuzzy telah mampu mengidentifikasi kemiripan bintang meskipun terdapat bintang tetangga hilang. Sedangkan, metode Pseudopolar Fourier Transform mampu mengidentifikasi besarnya perubahan kondisi citra. Selanjutnya, bintang baru dapat diidentifikasi melalui pengurangan koordinat posisi bintang pada citra masukan dan koordinat posisi bintang pada citra database. Kinerja sistem dapat ditunjukkan setelah melakukan pengujian terhadap 172 data dari aplikasi Stellarium, yaitu dengan tingkat akurasi sebesar 72,67%.
Arabic Book Retrieval using Class and Book Index Based Term Weighting M. Ali Fauzi; Agus Zainal Arifin; Anny Yuniarti
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (421.466 KB) | DOI: 10.11591/ijece.v7i6.pp3705-3710

Abstract

One of the most common issue in information retrieval is documents ranking. Documents ranking system collects search terms from the user and orderly retrieves documents based on the relevance. Vector space models based on TF.IDF term weighting is the most common method for this topic. In this study, we are concerned with the study of automatic retrieval of Islamic Fiqh (Law) book collection. This collection contains many books, each of which has tens to hundreds of pages. Each page of the book is treated as a document that will be ranked based on the user query. We developed class-based indexing method called inverse class frequency (ICF) and book-based indexing method inverse book frequency (IBF) for this Arabic information retrieval. Those method then been incorporated with the previous method so that it becomes TF.IDF.ICF.IBF. The term weighting method also used for feature selection due to high dimensionality of the feature space. This novel method was tested using a dataset from 13 Arabic Fiqh e-books. The experimental results showed that the proposed method have the highest precision, recall, and F-Measure than the other three methods at variations of feature selection. The best performance of this method was obtained when using best 1000 features by precision value of 76%, recall value of 74%, and F-Measure value of 75%.
Fuzzy Region Merging using Fuzzy Similarity Measurement on Image Segmentation Wawan Gunawan; Agus Zainal Arifin; Rarasmaya Indraswari; Dini Adni Navastara
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (748.683 KB) | DOI: 10.11591/ijece.v7i6.pp3402-3410

Abstract

Some image’s regions have unbalance information, such as blurred contour, shade, and uneven brightness. Those regions are called as ambiguous regions. Ambiguous region cause problem during region merging process in interactive image segmentation because that region has double information, both as object and background. We proposed a new region merging strategy using fuzzy similarity measurement for image segmentation. The proposed method has four steps; the first step is initial segmentation using mean-shift algorithm. The second step is giving markers manually to indicate the object and background region. The third step is determining the fuzzy region or ambiguous region in the images. The last step is fuzzy region merging using fuzzy similarity measurement. The experimental results demonstrated that the proposed method is able to segment natural images and dental panoramic images successfully with the average value of misclassification error (ME) 1.96% and 5.47%, respectively.
Incorporating Index of Fuzziness and Adaptive Thresholding for Image Segmentation Umi Salamah; Riyanarto Sarno; Agus Zainal Arifin; Anto Satriyo Nugroho; Ismail Eko Prayitno Rozi; Puji Budi Setia Asih
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1192.007 KB) | DOI: 10.11591/ijece.v8i4.pp2406-2418

Abstract

Binary Segmentation of an image played an important role in many image processing application. An image that was having no bimodal (or nearly) histogram accompanied by low-contrast was still a challenging segmentation problem to address. In this paper, we proposed a new segmentation strategy to images with very irregular histogram and had not significant contrast using index of fuzziness and adaptive thresholding. Index of fuzziness was used to determine the initial threshold, while adaptive thresholding was used to refine the coarse segmentation results. The used data were grayscale images from related papers previously. Moreover, the proposed method would be tested on the grayscale images of malaria parasite candidates from thickblood smear that had the same problem with this research. The experimental results showed that the proposed method achieved higher segmentation accuracy and lower estimation error than other methods. The method also effective proven to segment malaria parasite candidates from thickblood smears image.
Automatic image slice marking propagation on segmentation of dental CBCT Agus Zainal Arifin; Evan Tanuwijaya; Baskoro Nugroho; Arif Mudi Priyatno; Rarasmaya Indraswari; Eha Renwi Astuti; Dini Adni Navastara
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 6: December 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i6.13220

Abstract

Cone Beam Computed Tomography (CBCT) is a radiographic technique that has been commonly used to help doctors provide more detailed information for further examination. Teeth segmentation on CBCT image has many challenges such as low contrast, blurred teeth boundary and irregular contour of the teeth. In addition, because the CBCT produces a lot of slices, in which the neighboring slices have related information, the semi-automatic image segmentation method, that needs manual marking from the user, becomes exhaustive and inefficient. In this research, we propose an automatic image slice marking propagation on segmentation of dental CBCT. The segmentation result of the first slice will be propagated as the marker for the segmentation of the next slices. The experimental results show that the proposed method is successful in segmenting the teeth on CBCT images with the value of Misclassification Error (ME) and Relative Foreground Area Error (RAE) of 0.112 and 0.478, respectively.
Co-Authors - Azhari AA Sudharmawan, AA Adenuar Purnomo Adhi Nurilham Adi Guna, I Gusti Agung Socrates Afrizal Laksita Akbar Ahmad Afiif Naufal Ahmad Reza Musthafa, Ahmad Reza Ahmad Syauqi Aida Muflichah Aidila Fitri Fitri Heddyanna Akira Asano Akira Taguchi Akwila Feliciano Alhaji Sheku Sankoh, Alhaji Sheku Alif Akbar Fitrawan, Alif Akbar Alifia Puspaningrum Alqis Rausanfita Amelia Devi Putri Ariyanto Aminul Wahib Aminul Wahib Aminul Wahib Ana Tsalitsatun Ni'mah Andi Baso Kaswar Andi Baso Kaswar Anindhita Sigit Nugroho Anindita Sigit Nugroho Anny Yunairti Anny Yuniarti Anto Satriyo Nugroho Arif Fadllullah Arif Mudi Priyatno Arifin, M. Jainal Arifzan Razak Arini Rosyadi Arrie Kurniawardhani Arya Widyadhana Arya Yudhi Wijaya Bagus Satria Wiguna Bagus Setya Rintyarna Baskoro Nugroho Bilqis Amaliah Chandranegara, Didih Rizki Chastine Fatichah Christian Sri kusuma Aditya, Christian Sri kusuma Cinthia Vairra Hudiyanti Cornelius Bagus Purnama Putra Daniel Sugianto Daniel Swanjaya Darlis Herumurti Dasrit Debora Kamudi Desepta Isna Ulumi Desmin Tuwohingide Dhian Kartika Diana Purwitasari Didih Rizki Chandranegara Dika Rizky Yunianto Dimas Fanny Hebrasianto Permadi Dini Adni Navastara, Dini Adni Dinial Utami Nurul Qomariah Dwi Ari Suryaningrum Dyah S. Rahayu Eha Renwi Astuti Endang Juliastuti Erliyah Nurul Jannah, Erliyah Nurul Ery Permana Yudha Eva Firdayanti Bisono Evan Tanuwijaya Evelyn Sierra Fahmi Syuhada Fahmi Syuhada Fandy Kuncoro Adianto Fathoni, Kholid Fiqey Indriati Eka Sari Gosario, Sony Gulpi Qorik Oktagalu Pratamasunu Gus Nanang Syaifuddiin Handayani Tjandrasa Hanif Affandi Hartanto Hudan Studiawan Humaira, Fitrah Maharani Humaira, Fitrah Maharani I Guna Adi Socrates I Gusti Agung Socrates Adi Guna I Made Widiartha I Putu Gede Hendra Suputra Indra Lukmana Irna Dwi Anggraeni, Irna Dwi Ismail Eko Prayitno Rozi Januar Adi Putra Kevin Christian Hadinata Khadijah F. Hayati Khairiyyah Nur Aisyah Khairiyyah Nur Aisyah, Khairiyyah Nur Khalid Khalid Khoirul Umam Kholid Fathoni Lafnidita Farosanti Laili Cahyani Lutfiani Ratna Dewi Luthfi Atikah M. Ali Fauzi M. Jainal Arifin Mamluatul Hani’ah Maulana, Hendra Maulana, Hendra Mika Parwita Moch Zawaruddin Abdullah Moh. Zikky Moh. Zikky, Moh. Mohammad Fatoni Anggris, Mohammad Fatoni Mohammad Sonhaji Akbar Muhamad Nasir Muhammad Bahrul Subkhi Muhammad Fikri Sunandar Muhammad Imron Rosadi Muhammad Imron Rosadi Muhammad Machmud Muhammad Mirza Muttaqi Muhammad Muharrom Al Haromainy Munjiah Nur Saadah Muttaqi, Muhammad Mirza Nahya Nur Nanang Fakhrur Rozi Nanik Suciati Nina Kadaritna Nova Hadi Lestriandoko Novi Nur Putriwijaya Novrindah Alvi Hasanah Nur, Nahya Nuraisa Novia Hidayati Nursanti Novi Arisa Nursuci Putri Husain Ozzy Secio Riza Pangestu Widodo, Pangestu Pasnur Pasnur Pasnur Pasnur Puji Budi Setia Asih Putri Damayanti Putri Nur Rahayu Putu Praba Santika Rangga Kusuma Dinata Rarasmaya Indraswari Ratri Enggar Pawening Renest Danardono Resti Ludviani Rigga Widar Atmagi Riyanarto Sarno Riza, Ozzy Secio Rizka Sholikah Rizka Wakhidatus Sholikah Rizqa Raaiqa Bintana Rizqi Okta Ekoputris Rosyadi, Ahmad Wahyu Ryfial Azhar, Ryfial Safhira Maharani Safri Adam Saiful Bahri Musa Salim Bin Usman Saputra, Wahyu Syaifullah Jauharis Satrio Verdianto Satrio Verdianto Setyawan, Dimas Ari Sherly Rosa Anggraeni Siprianus Septian Manek Sonny Christiano Gosaria Sugiyanto, Sugiyanto Suprijanto Suprijanto Suwanto Afiadi Syadza Anggraini Syuhada, Fahmi Takashi Nakamoto Tegar Palyus Fiqar Tesa Eranti Putri Tio Darmawan Umi Salamah Undang Rosidin Verdianto, Satrio Waluya, Onny Kartika Wanvy Arifha Saputra Wardhana, Septiyawan R. Wawan Gunawan Wawan Gunawan Wawan Gunawan Wawan Gunawan Wijayanti Nurul Khotimah Wiwik Dyah Septiana Kurniati Yudhi Diputra Yufis Azhar Yulia Niza Yunianto, Dika R. Zainal Abidin Zakiya Azizah Cahyaningtyas