Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

1.907

P-Index

This Author published in this journals

All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer dan 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

Agus Zainal Arifin

Departemen Teknik Informatika Institut Teknologi Sepuluh Nopember Surabaya

Author-ID : 221631

Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 99 Documents Claim Missing Document

Claim Missing Document

Articles

6 7 8 9 10

Semantic Rule Labeling dan Sentence Information Density Dalam Pemilihan Kalimat Representatif Cluster Pada Peringkasan Multi-Dokumen Gus Nanang Syaifuddiin; Agus Zainal Arifin; Diana Purwitasari
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol 6, No 1 (2016): Jurnal Inspiration Volume 6 Issue 1
Publisher : STMIK AKBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v6i1.86

Coverage dan salient merupakan masalah utama yang menjadi perhatian para peneliti dalam peringkasan dokumen. Pendekatan clustering mampu memberikan coverage yang baik terhadap semua topik namun tidak memiliki informasi-informasi yang bisa mewakili kalimat-kalimat lain (salience sentence).Salience dapat digali dengan melihat hubungan dari satu kalimat dengan kalimat lain yang dibangun dengan pendekatan position text graph, namun position text graph hanya mampu menggali hubungan antar kalimat tanpa memperhatikan peran semantik kata (“who” did “what” to “whom”, “where”, “when”, and “how”) dalam kalimat yang dibandingkan.Pada paper ini kami mengusulkan sebuah metode baru strategi pemilihan kalimat representatif cluster dengan pendekatan sentence information density dan Semantic Rule labeling. Hasil uji coba menunjukkan metode yang metode yang diusulkan mampu memilih kalimat ringkasan lebih baik dari metode Sentence Information Density (SID) dengan rata-rata nilai Rouge-1 0.32511.

Computer-aided diagnosis for osteoporosis based on trabecular bone analysis using panoramic radiographs Agus Zainal Arifin; Anny Yuniarti; Lutfiani Ratna Dewi; Akira Asano; Akira Taguchi; Takashi Nakamoto; Arifzan Razak; Hudan Studiawan
Dental Journal (Majalah Kedokteran Gigi) Vol. 43 No. 3 (2010): September 2010
Publisher : Faculty of Dental Medicine, Universitas Airlangga https://fkg.unair.ac.id/en

Background: Mandibular bone on panoramic radiographs has been proven to be useful for identifying postmenopausal women with low skeletal bone mineral density. One of the important parts of mandibular bone is trabecular bone. Trabecular bone architecture is one of the factors that governs bone strength and may be categorized as a contributor to bone quality. Purpose: The purposes of this study were to develop a computer-aided system for measuring trabecular bone line strength on panoramic radiographs in identifying postmenopausal women with osteoporosis and to clarify the diagnostic efficacy of the system. Methods: Reduction and expansion of trabecular bone sample images using a two level Gaussian pyramid for removing noises and small segments were first introduced. Then, line strength at each pixel was calculated based on its existence on the trabecular bone with emphasizes line segment which has similar orientation with the root of tooth. The density was measured with respect to line strength of segment structure which has similar orientation with the root of tooth, either on the left and the right in the mandibular bone. Number of pixels in the line segment area was compared with a threshold value to determine whether normal or osteoporosis. Results: From experiment on 100 data, the accuracy of 88%, sensitivity of 92%, and specificity of 86.7% were achieved. Conclusion: The computer-aided system of trabecular bone analysis may be useful for detecting osteoporosis using panoramic radiographs.Latar belakang: Tulang mandibula pada panoramik radiografi telah banyak diteliti dan terbukti mampu digunakan untuk mengidentifikasi wanita pasca menopause dengan menggunakan bone mineral density rendah. Salah satu bagian tulang mandibula yang penting adalah tulang trabekula. Arsitektur tulang trabekula merupakan salah satu dari faktor-faktor yang mempengaruhi kekuatan tulang dan dapat digolongkan sebagai kontributor bagi kualitas tulang. Tujuan: Penelitian ini bertujuan untuk membangun sebuah sistem dengan bantuan komputer untuk mengukur kekuatan garis pada tulang trabekula dan menggunakannya untuk mendeteksi osteoporosis pada wanita postmenopause. Metode: Dilakukan sampling pada sebagian tulang mandibular yang menghasilkan sebuah sampel citra. Sampel citra ini selanjutnya diperbaiki dari derau (noise) dengan menggunakan piramida Gaussian dua level. Kekuatan garis pada tiap piksel dihitung berdasarkan orientasi segmen garis tulang trabekula yang sejajar dengan akar gigi. Setelah dilakukan binerisasi, luasan segmen yang dihasilkan dihitung dan dibandingkan dengan sebuah nilai ambang. Bila luasan melebihi nilai threshold maka dikategorikan sebagai normal. Sebaliknya bila luasan dibawah nilai threshold, dikategorikan sebagai osteoporosis. Hasil: Berdasarkan eksperimen terhadap 100 data, sistem mampu mencapai akurasi identifikasi sebesar 88%, sensitivitas 92%, dan spesifisitas 86,7%. Kesimpulan: Sistem analisa trabecular bone dengan bantuan komputer ini dapat digunakan oleh para dokter gigi untuk mendeteksi osteoporosis menggunakan panoramik radiografi.

Ultrafuzziness Optimization Based on Type II Fuzzy Sets for Image Thresholding Agus Zainal Arifin; Aidila Fitri Fitri Heddyanna; Hudan Studiawan
Journal of ICT Research and Applications Vol. 4 No. 2 (2010)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.2010.4.2.2

Image thresholding is one of the processing techniques to provide high quality preprocessed image. Image vagueness and bad illumination are common obstacles yielding in a poor image thresholding output. By assuming image as fuzzy sets, several different fuzzy thresholding techniques have been proposed to remove these obstacles during threshold selection. In this paper, we proposed an algorithm for thresholding image using ultrafuzziness optimization to decrease uncertainty in fuzzy system by common fuzzy sets like type II fuzzy sets. Optimization was conducted by involving ultrafuzziness measurement for background and object fuzzy sets separately. Experimental results demonstrated that the proposed image thresholding method had good performances for images with high vagueness, low level contrast, and grayscale ambiguity.

PEMBANGUNAN DAN MANAJEMEN APLIKASI UJIAN ONLINE BAGI MADRASAH SEBAGAI SOLUSI BERBAGAI PROBLEM YANG MUNCUL SAAT EVALUASI KEGIATAN BELAJAR MENGAJAR SISWA (Studi Kasus pada Madrasah Aliyah Negeri Kota Blitar dan Madrasah Aliyah Matholi'ul Anwar Karanggeneng Arya Yudhi Wijaya; Agus Zainal Arifin
JPM17: Jurnal Pengabdian Masyarakat Vol 2 No 01 (2016)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jpm17.v2i01.779

One aspect of measuring the quality of teaching and learning is the processof students evaluation. During this process, teachers in secondary schools,especially madrasah which is identical to the conventional education systemcompared with public schools, have difficulty in performing the test especiallyin the correction process and cheating prevention. The proposed solution in thisservice is to build an online exam application in the computer laboratory formadrasah. With the application of this online system, the exam can beconducted in a computer network and can prevent cheating because thequestions and answers were randomized. In addition, the online exam is alsoeasier for the teacher to evaluate since there is a statistical report of testresults. Experimental results using online exam application at partner schoolhas shown some benefits, i.e. accelerating the implementation of exams forstudents, ensuring confidentiality matter, facilitate the supervision of the testimplementation, speed up the process of getting value without havingpreoccupied with the correction manually, speeding up the analysis of dailytests and questions analysis, and minimize the possibility of cheating. We stillfound obstacles in the field, namely the lack of quality infrastructure to supportthe use of online exams.Keyword: Computer Based Test, Online Test

Pemodelan Topik dengan LDA untuk Temu Kembali Informasi dalam Rekomendasi Tugas Akhir Diana Purwitasari; Aida Muflichah; Novrindah Alvi Hasanah; Agus Zainal Arifin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Undergraduate thesis as the final project, or in Indonesian called as Tugas Akhir, for each undergraduate student is a pre-requisite before student graduation and the successfulness in finishing the project becomes as one of learning outcomes among others. Determining the topic of the final project according to the ability of students is an important thing. One strategy to decide the topic is reading some literatures but it takes up more time. There is a need for a recommendation system to help students in determining the topic according to their abilities or subject understanding which is based on their academic transcripts. This study focused on a system for final project topic recommendations based on evaluating competencies in previous academic transcripts of graduated students. Collected data of previous final projects, namely titles and abstracts weighted by term occurences of TF-IDF (term frequency–inverse document frequency) and grouped by using K-Means Clustering. From each cluster result, we prepared candidates for recommended topics using Latent Dirichlet Allocation (LDA) with Gibbs Sampling that focusing on the word distribution of each topic in the cluster. Some evaluations were performed to evaluate the optimal cluster number, topic number and then made more thorough exploration on the recommendation results. Our experiments showed that the proposed system could recommend final project topic ideas based on student competence represented in their academic transcripts.

KLASIFIKASI KATEGORI DOKUMEN BERITA BERBAHASA INDONESIA DENGAN METODE KATEGORISASI MULTI-LABEL BERBASIS DOMAIN SPECIFIC ONTOLOGY Pangestu Widodo; Januar Adi Putra; Suwanto Afiadi; Agus Zainal Arifin; Darlis Herumurti
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 2 No. 2 (2016)
Publisher : Universitas Widyatama

[Id]Sebuah dokumen berita seringkali terkait lebih dari satu kategori, untuk itu diperlukan pemanfaatan metode kategorisasi yang tidak hanya cepat tetapi juga dapat mengelompokkan sebuah berita kedalam banyak kategori. Banyak metode yang dapat digunakan untuk mengkategorisasi dokumen berita, salah satunya adalah ontologi. Pendekatan ontologi dalam kategorisasi sebuah dokumen berita didasarkan pada kemiripan fitur yang ada di dokumen dengan fitur yang ada di ontologi. Penggunaan ontologi dalam kategorisasi yang hanya didasarkan pada kemunculan term dalam menghitung relevansi dokumen menyebabkan banyak kemunculan fitur lain yang sebenarnya sangat terkait menjadi tidak terdeteksi. Dalam? paper ini diusulkan? metode baru untuk kategorisasi dokumen berita? yang terkait dengan banyak kategori, metode ini berbasis domain specific ontology yang perhitungan relevansi dokumen terhadap ontologinya tidak hanya didasarkan pada kemunculan term tetapi juga memperhitungkan relasi antar term yang terbentuk. Uji coba dilakukan pada dokumen berita berbahasa indonesia dengan 2 kategori yaitu olahraga dan teknologi. Hasil uji coba menunjukkan nilai rata-rata akurasi yang cukup tinggi yaitu kategori olahraga adalah 93,85% sedangkan pada kategori teknologi adalah 96,32%.Kata Kunci: Dokumen berita, kategorisasi, multi-label, ontologi,? domain-spesifik.[En]A news document often related? to more than one category,? necessary for utilization? the method of categorization that is not only fast but also able to Classify a news into many categories. Many methods can be used to categorize the news documents, one of which is an ontology. Ontology approach in the categorization of a document is based on the similarity of news features in documents with features that exist in the ontology. The use of ontologies in categorization that just based on the occurance of the term in calculating the relevance of the document, led to the emergence of many other fea-tures that are actually very relevant is undetectable. This paper proposed a new method for categorizing news documents are related with many categories, the method is based on a specific domain ontology and for document relevance calculation is not only based on the occurrence of the term but also take into account the relationships between terms that are formed. Tests performed on the Indonesian language news document with? two categories: sports and technology. The trial results show the value of the average accuracy is high, that the sports category was 93,85% and the technology category is 96,32%.Keywords : News document, ?categorization, multi-label, Ontology, domain-specific.

PEMBOBOTAN KATA BERDASARKAN KLASTER PADA OPTIMISASI COVERAGE, DIVERSITY DAN COHERENCE UNTUK PERINGKASAN MULTI DOKUMEN Ryfial Azhar; Muhammad Machmud; Hanif Affandi Hartanto; Agus Zainal Arifin; Diana Purwitasari
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 2 No. 3 (2016)
Publisher : Universitas Widyatama

[Id]Peringkasan yang baik dapat diperoleh dengan coverage, diversity dan coherence yang optimal. Namun, terkadang sub-sub topik yang terkandug dalam dokumen tidak terekstrak dengan baik, sehingga keterwakilan setiap sub-sub topik tersebut tidak ada dalam hasil peringkasan dokumen. Pada paper ini diusulkan metode baru pembobotan kata berdasarkan klaster pada optimisasi coverage, diversity dan coherence untuk peringkasan multi-dokumen. Metode optimasi yang digunakan ialah self-adaptive differential evolution (SaDE) dengan penambahan pembobotan kata berdasarkan hasil dari pembentukan cluster dengan metode Similarity Based Histogram Clustering (SHC). Metode SHC digunakan untuk mengklaster kalimat sehingga setiap sub-topik pada dokumen bisa terwakili dalam hasil peringkasan. Metode SaDE digunakan untuk mencari solusi hasil ringkasan yang memiliki tingkat coverage, diversity, dan coherence paling tinggi. Uji coba dilakukan pada 15 topik dataset Text Analysis Conference (TAC) 2008. Hasil uji coba menunjukkan bahwa metode yang diusulkan dapat menghasilkan ringkasan skor ROUGE-1 sebesar 0.6704, ROUGE-2 sebesar 0.2051, ROUGE-L sebesar 0.6271 dan ROUGE-SU sebesar 0.3951.Kata kunci : peringkasan multi dokumen, similarity based histogram clustering, coverage, diversity, coherence[En]Good summary can be obtained with optimizing coverage, diversity, and coherence. Nevertheless, sometime sub-topics wich is contained in the document is not extracted well, so that the representation of each sub-topic is appear in docment summarizarion result. In this paper, we propose new of term weighting based on? cluster in optimizing coverage, diversity, and coherence for multi-document summarization. Optimization method which is used is self-adaptive differential evolution (SaDE) with additional term weighting based on clustering result with Similarity Based Histogram Clustering (SHC). SHC is used to cluster sentence so that every sub-topic in the document can be represented in summarization result. SaDE is used to search summarization result solution which has high coverage, diversity, and coherence level. Experiment is done on 15 topics in Text Analysis Conference (TAC) 2008 dataset. Experimental results show that this proposed method can produce summarization score? ROUGE-1 0.6704, ROUGE-2 0.2051, ROUGE-L 0.6271 and ROUGE-SU 0.3951.Keywords: multy-document summarization, similarity based histogram clustering, coverage, diversity, coherence.

Seleksi Fitur Dua Tahap Menggunakan Information Gain dan Artificial Bee Colony untuk Kategorisasi Teks Berbasis Support Vector Machine Khalid Khalid; Bagus Setya Rintyarna; Agus Zainal Arifin
Systemic: Information System and Informatics Journal Vol. 1 No. 2 (2015): Desember
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Salah satu problem yang dihadapi dalam kategorisasi teks adalah dimensi data yang besar yang menyebabkan terjadinya inefisiensi dalam aspek waktu komputasi. Untuk mengatasi hal tersebut, salah satu hal yang bisa dilakukan adalah seleksi fitur pada tahap pre- processing. Pada penelitian ini diusulkan seleksi fitur dua tahap dengan Information Gain dan Artificial Bee Colony. Kategorisasi teks dilakukan dengan Support Vector Machine. Hasil uji coba pada Dataset Reuter21578 menunjukkan adanya peningkatan Precision sebesar rata-rata 15% dan Recall sebesar rata-rata 13% dibandingkan metode pembanding yaitu PSO-SVM.

EFISIENSI PHRASE SUFFIX TREE DENGAN SINGLE PASS CLUSTERING UNTUK PENGELOMPOKAN DOKUMEN WEB BERBAHASA INDONESIA Desmin Tuwohingide; Mika Parwita; Agus Zainal Arifin
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 8 No 2 Februari 2016
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/technoscientia.v8i2.162

The number of indonesian documents which available on internet is growing very rapidly. Automatic documents clustering shown to improving the relevant documents search results of many found documents. Suffix tree is one of documents clustering method that developed, because it is proven to increase precision. In this paper, we propose a new method to clustering indonesian web documents based on phrase efficiency in the choice process of base cluster with the combination of documents frequency and term frequency calculation on the phrase with a single pass clustering algorithm (SPC). Every phrase that is considered as the base cluster will be vectored then calculate of the term frequency and document frequency. Furthermore, the documents will be calculate their similarity based on the tf-idf weighted using the cosine similarity and documents clustering is done by using a single pass clustering algorithm. The proposed method is tested on 6 dataset with number of different document 10, 20, 30, 40, 50 and 60 documents. The experiment result show that the proposed method succeeded clustering indonesian web documents by reducing the leaf node with no derivative and produces the F-measure an average of 0.78 while STC traditional produces the F-measure an average of 0.55.This result prove that the efficiency of phrase by phrase choice on internal nodes and leaf nodes that have derivative, and a combination of term frequency and document frequency calculation on the base cluster, gives a significant impact on the process of clustering documents.

Segmentasi Multi Proyeksi pada Citra Cone Beam Computed Tomography Gigi Menggunakan Metode Level Set Fahmi Syuhada; Rarasmaya Indraswari; Agus Zainal Arifin; Dini Adni Navastara
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 2 (2021): December 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i2.413

Segmentation of dental Cone-beam computed tomography (CBCT) images based on Boundary Tracking has been widely used in recent decades. Generally, the process only uses axial projection data of CBCT where the slices image that representing the tip of the tooth object have decreased in contrast which impact to difficult to distinguish with background or other elements. In this paper we propose the multi-projection segmentation method by combining the level set segmentation result on three projections to detect the tooth object more optimally. Multiprojection is performed by decomposing CBCT data which produces three projections called axial, sagittal and coronal projections. Then, the segmentation based on the set level method is implemented on the slices image in the three projections. The results of the three projections are combined to get the final result of this method. This proposed method obtains evaluation results of accuracy, sensitivity, specificity with values of 97.18%, 88.62%, and 97.61%, 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 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 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 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 Lafnidita Farosanti Laili Cahyani Lutfiani Ratna Dewi Luthfi Atikah M. Ali Fauzi Mamluatul Hani’ah Maulana, Hendra Maulana, Hendra Mika Parwita Moch Zawaruddin Abdullah 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 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 Yudhi Diputra Yufis Azhar Yulia Niza Yunianto, Dika R. Zainal Abidin Zakiya Azizah Cahyaningtyas

Title

Found 99 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 99 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 99 Documents
Search