Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

25.173

P-Index

This Author published in this journals

Muhammad Arifin

Universitas Muria Kudus

Author-ID : 2473690

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

Published : 266 Documents Claim Missing Document

Claim Missing Document

Articles

23 24 25 26 27

PENERAPAN ALGORITMA MACHINE LEARNING UNTUK PENGELOMPOKAN SISWA BERDASARKAN ASPEK AKADEMIK DAN NON-AKADEMIK Hesti Sabrila Aulia; Muhammad Arifin; Diana Laily Fithri
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7249

This study aims to develop a student potential clustering system as a strategy to address the limitations of academic identification processes that have traditionally been conducted manually, subjectively, and are prone to observational bias. The K-Means Clustering and K-Medoids algorithms were applied to a dataset consisting of 1,023 student records from SMP Negeri 2 Jekulo Kudus and SMP Negeri 3 Jekulo Kudus, using variables such as semester report card grades, core subjects including Mathematics, Science, and Indonesian Language, overall average scores, attitude assessments, and participation in extracurricular activities. The study employed a cluster number of (k = 3), representing High, Medium, and Low student potential categories for educational mapping purposes. The data preprocessing stage included missing value imputation using mean values and normalization of numerical features using RobustScaler to minimize the influence of outliers without removing student data. The evaluation results indicate that the K-Means algorithm achieved better clustering performance than K-Medoids based on evaluation metrics, with a Silhouette score of 0.529 and a Davies–Bouldin Index of 0.879, making it more suitable for the characteristics of the student dataset used. The system was subsequently implemented as an interactive web-based application developed in Python using the Flask framework and a MySQL database, enabling centralized data management, real-time access, and visualization of clustering results through a user-friendly interface. With this system, schools are expected to be able to map student potential more objectively, efficiently, and in a data-driven manner, thereby supporting learning strategy planning, intervention programs, and more targeted and inclusive educational decision-making.

KLASIFIKASI KEPUASAN PELANGGAN BERDASARKAN DATA HASIL SURVEI PADA ISP ERATEL MENGGUNAKAN MACHINE LEARNING: CUSTOMER SATISFACTION CLASSIFICATION BASED ON SURVEY DATA AT ISP ERATEL USING MACHINE LEARNING Muhammad Ary Sanjaya Putra Ary; Arif Setiawan; Muhammad Arifin
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7937

Customer satisfaction is a critical factor in the sustainability of internet service providers (ISP). This study aims to compare the performance of Naïve Bayes, Support Vector Machine (SVM), and Random Forest algorithms in classifying customer satisfaction levels at ISP Eratel based on questionnaire survey data. Data were collected by distributing questionnaires to 301 respondents of Eratel customers with 10 question items on a Likert scale of 1–4 using convenience sampling technique. The research stages include data collection, preprocessing, labeling using the class interval method, stratified dataset splitting with an 80:20 ratio, classification model training, and web dashboard implementation. The labeling process produced three classes: Satisfied (54.82%), Fairly Satisfied (41.20%), and Dissatisfied (3.99%). Based on single split evaluation, the Naïve Bayes and SVM algorithms achieved the same accuracy of 90.16%, with Naïve Bayes showing slightly better performance in recognizing the minority class with a precision of 90.15%, recall of 90.16%, and f1-score of 90.05%, compared to SVM with precision of 87.29%, recall of 90.16%, and f1-score of 88.50%. Meanwhile, Random Forest achieved an accuracy of 86.89% with an f1-score of 86.25%, with a notable advantage in precision for the Dissatisfied class at 100% but a lower recall of 50%. Overall, Naïve Bayes emerged as the best-performing algorithm based on single split evaluation. The classification models were subsequently implemented into a Streamlit-based web dashboard that allows users to upload survey data in Excel (.xlsx) format, display interactive visualizations of customer satisfaction distribution, and spatially map classification results per sub-district in Kudus Regency in real-time. This study concludes that all three algorithms are capable of classifying customer satisfaction effectively, with Naïve Bayes demonstrating the best overall performance based on single split evaluation. Keyword: Customer Satisfaction, Naïve Bayes, Support Vector Machine, Classification, ISP.

PENGELOMPOKAN BAHAN BAKU BERDASARKAN TINGKAT PENGGUNAAN BERBASIS ALGORITMA CLUSTERING PADA SELARAS COFFEE & SPACE Bayu Samudro Fadhilah; Muhammad Arifin; Rhoedy Setiawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8008

Inventory management in the food and beverage business requires a measurable approach to reduce the risk of stock shortages and excess inventory. Selaras Coffee & Space has operational kitchen raw material data that can be utilized to identify usage patterns more objectively. This study aims to group raw materials based on usage levels by comparing K-Means, Hierarchical Clustering, and K-Medoids algorithms. The data were obtained from kitchen raw material stock opname and purchase order records for February 2026, using stock_fisik, min_stock, and qty_po as clustering attributes. The research stages included data collection, preprocessing, unique item aggregation, Min-Max normalization, clustering algorithm implementation, evaluation using Sum of Squared Errors (SSE) and Silhouette Score, and implementation of the results into a web-based system. The initial dataset consisted of 3,080 rows and was aggregated into 110 unique items. The evaluation results showed that K-Means and Hierarchical Clustering achieved an SSE value of 4.630818 and a Silhouette Score of 0.781801, indicating a strong cluster structure. K-Medoids obtained an SSE value of 11.022485 and a Silhouette Score of 0.470763. K-Means was selected as the best algorithm because it achieved optimal evaluation performance and is simpler to implement in the system. The clustering results showed that 6 items were categorized as High Usage, 7 items as Medium Usage, and 97 items as Low Usage. The results can assist management in understanding raw material usage levels as a basis for more effective inventory control.

KLASTERING LAGU BERBASIS AKTIVITAS PENDENGAR MENGGUNAKAN ALGORITMA SELF ORGANIZING MAP BERDASARKAN FITUR AUDIO SPOTIFY: ACTIVITY BASED SONG CLUSTERING USING THE SELF ORGANIZING MAP ALGORITHM BASED ON SPOTIFY AUDIO FEATURES Ridho Agiel Syahputra Siallagan; Muhammad Arifin; Pratomo Setiaji
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8017

This study aims to cluster songs based on listener activities using the Self Organizing Map (SOM) algorithm with Spotify audio features. The dataset used in this study was obtained from Kaggle with a total of 20,718 songs. The variables used include Danceability, Energy, Valence, and Acousticness. The research stages consist of data pre-processing, searching for the best SOM parameters using Grid Search, SOM clustering, clustering evaluation using Silhouette Score and Davies-Bouldin Index (DBI), activity labeling, and implementation of a Streamlit-based web dashboard. The results show that the best SOM parameters were obtained using a 2x3 grid, 3000 iterations, sigma 1.0, and learning rate 0.5 with a Silhouette Score of 0.2348 and a DBI value of 1.2894. The Silhouette Score indicates that the separation between clusters is moderate but not perfect, which is reasonable because music data often have continuous and overlapping audio characteristics. Meanwhile, the DBI value indicates that the similarity between clusters is still relatively high, although the clusters can still be interpreted based on their dominant audio characteristics. The clustering process produced six activity clusters, namely Workout, Dancing, Gaming, Sleeping, Studying, and Hanging Out. The Gaming cluster became the largest cluster with 31.35% of the data, while the Workout cluster became the smallest with 9.53%. The web dashboard implementation successfully visualized clustering results, music activity distributions, cluster characteristics, and music recommendations based on listener activities. The study concludes that the SOM algorithm is capable of clustering songs based on Spotify audio feature similarities at a moderate level and can be implemented in activity-based music recommendation systems.

ANALISIS SENTIMEN TERHADAP PROGRAM MAKAN BERGIZI GRATIS DI MEDIA SOSIAL X BERBASIS PEMBELAJARAN MESIN aufa hanif; Muhammad Arifin; Yudie Irawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8035

Social media X provides many public responses to the Free Nutritious Meal Program (MBG), including support, questions, criticism, and neutral information. This study processes 6,000 tweets related to MBG to identify the direction of public opinion using a machine learning approach. The research flow consists of sentiment labeling, text cleaning, TF-IDF weighting, and model testing using Naive Bayes, Random Forest, and Support Vector Machine. The sentiment distribution shows 3,087 positive tweets, 2,213 neutral tweets, and 700 negative tweets. Model testing shows that Random Forest produced the strongest result with 94.75% accuracy, 95.66% precision, 94.75% recall, and 94.93% F1-score. These findings indicate that Random Forest is more suitable for recognizing sentiment patterns in the MBG tweet dataset than the other two models. The study also presents the analysis through a web-based system containing dashboard, dataset import, sentiment data, preprocessing, training, evaluation, and new opinion classification features.

Expert System for Detecting Academic Burnout Levels among University Students Using the Certainty Factor Method Zahrotul Khoiriyah; Arif Setiawan; Muhammad Arifin
INOVTEK Polbeng - Seri Informatika Vol. 11 No. 3 (2026): August
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/mdwyhb15

Academic burnout is a condition of physical, emotional, and mental exhaustion resulting from prolonged academic demands and may negatively affect students' learning and well-being. This study aimed to develop a web-based expert system to support the preliminary identification of academic burnout among university students using the Certainty Factor method. The system knowledge was constructed through a literature review and a structured knowledge acquisition process involving a psychology expert before being represented in the knowledge base. The system was developed using the Waterfall model with PHP, the CodeIgniter framework, and MySQL. Functional evaluation using black-box testing showed that all system features operated as expected. In addition, User Acceptance Testing (UAT) involving 102 students of Universitas Muria Kudus achieved an overall acceptance score of 83.92%, indicating a Very Good level of user acceptance. The developed system was able to classify consultation results into mild, moderate, and severe academic burnout categories based on the implemented Certainty Factor inference process. Therefore, the proposed expert system may serve as a supporting tool for the preliminary identification of academic burnout. Further validation using standardised psychological instruments or professional psychological assessments is recommended in future studies.

Penerapan Algoritma K-Means untuk Segmentasi Pemilih Berdasarkan Kelompok Usia (Studi Kasus: DPT Desa Kesambi) Intan Nur Alisa, Firda; Dea Anggi Maharani, Nanda; Nur Amandasari, Canes; Nur Maulani, Anggita; Arifin, Muhammad
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 6 No 3 (2026): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v6i3.1961

Partisipasi pemilih merupakan salah satu indikator penting dalam keberhasilan penyelenggaraan pemilu di tingkat desa. Namun, pendekatan sosialisasi yang bersifat seragam tanpa mempertimbangkan karakteristik demografis pemilih seringkali kurang efektif. Penelitian ini bertujuan untuk melakukan segmentasi pemilih berdasarkan kelompok usia menggunakan algoritma K-Means Clustering pada data Daftar Pemilih Tetap (DPT) Desa Kesambi. Variabel yang digunakan dalam proses clustering adalah usia dan jenis kelamin. Data yang digunakan berjumlah 1.465 rekod setelah melalui tahap preprocessing. Penentuan jumlah cluster optimal dilakukan menggunakan Elbow Method, yang menghasilkan nilai k = 3 sebagai jumlah cluster terbaik. Hasil clustering membagi pemilih ke dalam tiga kelompok, yaitu Pemilih Muda (usia 17–34 tahun) sebanyak 509 pemilih (34,7%), Usia Produktif (usia 35–53 tahun) sebanyak 592 pemilih (40,4%), dan Lansia (usia 54–93 tahun) sebanyak 364 pemilih (24,8%). Evaluasi menggunakan Silhouette Score menghasilkan nilai 0,5698 yang menunjukkan kualitas clustering dalam kategori cukup baik. Hasil penelitian ini dapat dimanfaatkan sebagai dasar pengambilan keputusan dalam merancang strategi sosialisasi dan pendekatan kampanye yang lebih tepat sasaran sesuai dengan karakteristik demografis masing-masing kelompok pemilih.

Persepsi Ulama Dayah Terhadap Konversi Bank Konvensional (Studi Kasus Di Kota Banda Aceh) Arifin, Muhammad; Usman, Ismuadi; Fadhillah, Alfatan
JIMEBIS: Scientific Journal of Students Islamic Economics and Business Vol. 4 No. 2 (2023): JIMEBIS
Publisher : Fakultas Ekonomi dan Bisnis Islam, Universitas Islam Negeri Ar-Raniry Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/jimebis.v4i2.422

After the conversion of conventional banks to sharia banks, people still think that there are no significant differences in the operational system of sharia banks except just changing the name, changing the term interest to profit sharing and several other small things that are not significant. This research aims to analyze the perceptions of ulama regarding the conversion of conventional banks to sharia banks in Banda Aceh. This research uses descriptive qualitative methods. Data was obtained by interviewing related parties such as ulama and community leaders. The research results show that according to the perception of ulama, the conversion of conventional banks to sharia banks is in accordance with the Islamic banking system because there is a Sharia Supervisory Board, although it still requires improvement. According to them, this conversion is the right thing and indeed should be carried out considering the existence of the Qanun on Sharia Financial Institutions in Aceh.

Pelatihan Sistem Informasi Stock Opname Berbasis Web pada DPMD Kabupaten Kudus Tasa Tasa; Muhammad Arifin
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 2 (2026): Mei
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/h2qd9764

Pengelolaan persediaan yang masih dilakukan secara manual pada Dinas Pemberdayaan Masyarakat dan Desa (DPMD) Kabupaten Kudus menimbulkan berbagai permasalahan, seperti kesalahan pencatatan, keterlambatan pelaporan, serta rendahnya efisiensi kerja. Kegiatan ini bertujuan untuk meningkatkan kemampuan pegawai dalam mengelola persediaan melalui pelatihan sistem informasi stock opname berbasis web. Metode pelaksanaan menggunakan pendekatan community-based melalui workshop yang meliputi penyampaian materi, diskusi, praktik langsung, dan pendampingan dengan memanfaatkan data riil. Tahapan kegiatan meliputi analisis kebutuhan, persiapan materi, implementasi sistem, pelatihan, dan evaluasi secara deskriptif melalui observasi dan wawancara. Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan keterampilan peserta dalam mengoperasikan sistem, mulai dari input data barang, pencatatan transaksi, hingga pembuatan laporan secara otomatis. Selain itu, terjadi peningkatan efisiensi waktu, akurasi data, serta kemudahan dalam akses dan pengelolaan informasi persediaan. Dampak dari kegiatan ini adalah mendukung proses digitalisasi pengelolaan persediaan serta meningkatkan kinerja pegawai dalam penyajian informasi yang lebih cepat dan akurat atau terlalu panjang.

Comparative Study of Machine Learning Algorithms for Student Performance Prediction in Islamic Boarding Schools Ari Adaninggar; Muhammad Arifin; Diana Laily Fithri
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 10 No. 1 (2026): Issues July 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v10i1.18673

Al-Manshurin Ar-Rikzan Jepara Islamic Boarding School faces challenges in the early detection of potential declines in student achievement because the evaluation process still relies on manual recording. This study aims to design an interactive website-based Early Warning System to predict the final performance predicate of students by integrating academic data and non-academic behavior (mutabaah yaumiyah). The methodology used refers to the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. This study compares three classification algorithms: Decision Tree (C4.5), Naïve Bayes, and K-Nearest Neighbor (K-NN). To address class imbalance in the 210 original data records, the Synthetic Minority Over-sampling Technique (SMOTE) was applied to generate 450 balanced records, which were then evaluated using 10-Fold Cross Validation. The test results show that the Decision Tree (C4.5) algorithm produces the most superior performance with an Accuracy of 97.62%, Precision of 97.96%, and Recall of 97.62%. This superiority is driven by the decision tree structure's ability to map non-linear conditional rules relevant to the pesantren's absolute rules. As an applicative output, the best model is extracted into a Streamlit-based dashboard equipped with expert recommendations (feature importances). This system automatically highlights the variables contributing the highest risk, enabling administrators to formulate accurate intervention and mentoring steps before the semester evaluation ends.

Co-Authors 'Amala A., Ahsanu - Supriyono Abbas, Aries Abd. Faishol Abdul Manan Abdul Rauf Chaerudin Abdullah Muttaqin Abiyyi, Al Ghossan Abthal Ade Budi Setiawan Aditya Taufik Ismail Adlian Jefiza Adzkar, Fadhlika Afif, Faisal Afriana, Bs Monica Afrianda, Gusti Afridon, M Afriyanti Afriyanti, Afriyanti Afriza Akhid Khoiruddin Agung Mahardiono, Novan Agus Trianto Ahmad Afifuddin Ahmad Hariyadi Ahmad Zidan Nur Rizqi Aina, Asri Nur Aji, A. Damar Aji, Muji Handoyo Akmal Riza Akrim, Akrim Al-Fatah, Sopi Nurul Alamsyah, Tedi Alamul Huda, Alamul Alaydrus, S. Ali Jadid Alfina Chintya Bella Alif Fadhillah Laili Putri Alif Fadhillah Laili Putri Alifa Marsha Rahmania Aliya Aszava Alwani, Yazid Alya, Kharisma Rahmadhani Alya, Nabila Ulamy Amalia, Nadra Amanatillah, Dara Amanda Putri Cheryl Andhika Ikhwal Fadhil Ferdian Andre , Lesis Andrian, Nawang Alan Andrianti, Rini Andy Lasmana Angga Wahyu Wibowo Anita Rahmawati Annisa Nurrachmawati Annisa, Dewi Sry Anteng Widodo Aprilia, Wa Ode Intan Apriliana Sari Arbani, Hayaadilah Rizqi Ardhana Januar Mahardhani Ari Adaninggar Ariansyah, Rafi Ariesta, Ria Arif Harjanto Arif Rahman Hakim Arif Setiawan Arina Fawaida Arini Zulfaida Aristianty, Dian Sari Arono Arono Arum Kusuma Wardhany Ary Kania Sya'diah Arya Subastian Asmoro, Novian Wely Aspira, Muizatul Atsna Rifqi Habibur Rahman aufa hanif Aulia Happy Salma Aulia, Farhan Aulia, Ismi Aulia, Riza Azzahro, Fatimah Bagus Sujarwo Bahtiar, Adhi Baiti Rahman Bakti Nendra Khurrohim Bambang Hariyadi Bambang Widjanarko, Bambang Widjanarko Batubara, Oktia Elfriza Bayu Samudro Fadhilah Berkahi, Alrezqio Meykhara Aqbel Bilqis, Adilla Boer, Dara Cantika Putriadin Budiana, Budiana Budiono, Ragil Catur Wuragil, Irfan Chandra Ayu Fatikasari Chaniago, Edi Salim Christoper Ade Immanuel Cut Intan Hayati Dafa, Yori Hayyan Damanik, Ricardo Fransiskus Damar Aji Gurowo Daniah Darmnato, Eko Dea Anggi Maharani, Nanda Delismasari, Delismasari Deni Mahdiana Deshinta Dewi Maharani Destarina, Dea Devi Mutiara Khoirun Nisa, Asti Dewantari Nasution, Nurul Annisa Dhani Miftahul Abid Dhohiri, Daud Dian Asriningati Dian Eka Chandra Wardhana, Dian Eka Chandra Diana Laily Fithri Diana Laily Fithri Diana Laily Fithri Diana Layli Fithri Diki Eka Gunawan Dita Amelia Putri, Dita Amelia Djarot Winoto, Djarot Winoto Dodi Candra Kurniawan Dongoran, Indra Pilianti Durrotun Nafisah Dwi Kurnia Putri Eko Darmanto Eko Darmnato Elsa Violina Damayanti Elyza Dewi Fortuna Endah Wahyutri Endhito Hafiz Meifaza Eni Mayasari Entin Hidayah Eny Enawaty Era Wulandari Erlina Erlina Esti Wijayanti Esti Wijayanti, Esti Evi Maryanti F.A., Moch Hazmi Fachry Abda El Rahman Fadhillah, Alfatan Fahmiyudin, Muhamad Fahri, Muhammad Yazid Fajar Nugraha Farhan Wildan Darmawan Farid Noor Romadlon Farida, Elis Anita Faris Ahmad Farhan Farhan Faris Widhiarta Farma, Junia Fathon, Ulil fathurrahman, fajar Febriana Permatasari Fery Ariyana Fithri, Diana Layli Fitri, Rosiana Fitri, Saudatul Fitriyani, Laili Fitriyanti Nakul Futra, Asrizal Deri Gafur, Syahrul Ghufron Tamami Gumono Gumono, Gumono Gunawan, Erli Gurning, Jhon Pedrik Haedar Akib Handayani, Listy Hapsari, Rini Tri Harahap, Santi Evalia hasanah, kamalia Henandra Eka Putra, Dias Hendro HS., R. Hendy Hendy Hendro Hadi Sridjono Hendy Hendro Sajono Herawati, Yuke Elvin Heri Susanto Herlina, Yekti Heru Sabputro Hery Purwosusanto Hesti Sabrila Aulia Hidayat, Hilmi Bayu Hidayat, Muhammad Taufiq Hikhmah, Fitria Nurul Husna, Atina Ifriany, A. Ihyani Malik Ihza, Andika Ika Karlina Laila Nur Suciningtyas Ike Anggraeni Ilham Dwi Pranoto Imam Kusyairi, Imam Imaroh, Rachel Tinezia Zaitul Ina Kusumawardani Alina Fakhri Indahsari, Susi Insani, Muhammad Fitrah Intan Firdausatul Salsabilla Intan Hayati Intan Hayati Intan Nur Alisa, Firda Ipaludin, Muhammad Irfan Santiko Irwan Purnama Irwanto Zarma Putra Ishak, Safrizal Iskandar Iskandar Iskandar Iskandar Ismail Ismail Ismi Alfina Ayu Azzahra Iswahyu Pranawukir Ivonita Simbolon, Artha Jafarudin, Sesy Dwi Prinita Jalilah Jalilah Jamhari Jamhari Jasmawati, Jasmawati Jayanti, Nur Ivo JUNAIDI Karima, Mafaza Karimuna, Siti Rabbani Kejora Rizka Amanda Khairani, Suci Khairudin Syah Khairul Amri Khilal Arlisna Rahmadani Khoirun Nisa', Dwi Susanti Khoiruz Zahro Ksrisya, Vira Clarissa Kurniawan, Moh Adi Kurniawan, Muhammad David Lailatus Sa’diah, Najwa Lailatussaadah M Nur, Lailatussaadah Laily Fithri, Diana Latifah, Noor Lilis Puspitawati Liza, Risko Lubis, Muhammad Rasyid lutfi, Attabik Lu’lu’il Laili M. Alvino Bintang P M. Yogi Riyantama Isjoni Magdalena, Melani Maria Maharani, Adelia Maharani, Ria Maharani, Vanessa MAHARINI, MAHARINI Mahendra, Prionaka Luthfi Mahpuz Maimun Maimun Majid, Akmal Abdul Malyani, Fitri Manurung, Lastiur Marbun, Egricana Marchella, Intan Mardasela, Tery Marpaung, Maria Magdalena Martina MARTINA, ANGGUN Marzuarman, Marzuarman Masriani . Maulida Zakiah, Diana Maulidah, Hana Mutialif Maulidiawati, Chyntia Meri, Rita Misyanto Moch Naufal Ardiyansyah Moch Zainuddin Qomari Mohammad Fathoni Mohammad Maulana Afriza Mohzana Monika, Dezetty Muchlas Muchlas Mudrikah, Mudrikah Muham, Novia Angelia Br Muhamad Davin Tanzila Ramdani Muhamad Yuwanda Muhammad Alvino Bintang Adi Pradana Muhammad Ardi Hermansyah Muhammad Ary Sanjaya Putra Ary Muhammad Azka Latif Muhammad Fajar Maulana Muhammad Hidayat Muhammad Khaeruddin Hamsin, Muhammad Muhammad Khoirul Anam Muhammad Muhammad Muhammad Mursyid Muhammad Nanang Qosim Muhammad Rizqi Ijlal Tsani Muhammad Tahir Muhammad Tegar Sirri Arrafi Muhammad Vikri Mustafa Muhammad Wasil Muhammad Yamin Muhazir, Achmad Muksal Muksal Muksin, Muksin Mumu Zainal Mutaqin Munirul Abidin Musfiroh, Aam Mutia, Sri Muzakkir Muzakkir Myllikha Putri Izza Nadhrah Wivanius, Nadhrah Nadiya, Ulfah Nafar Ja’far Ashidiqi Naibaho, Sisilia Hotrepiyanti Br Najwa Hanindya Putri Nalendra Cahaya Heraditya Nanda Bagus Yulianto Nanda Lutfi Rizqiyanto Nandalisa Lisa Fa’ati Rahmawati Nariyah, Ahlun Nasution, Nurul Izzah Nasution, Ummi Fadillah Naufal renanda Nava Azahra Nazar Nazar, Nazar Nazila, Tasya Nisa, Nabila Mataun Noermanzah, Noermanzah Noor Azizah Noor Latifah Noprianti, Dini Noviyanto Firmansyah, Heru Novrian, David Saldomi Nugraha, Gilang Try Nur Amandasari, Canes Nur Ivo Jayanti Nur Maulani, Anggita Nur Rohmah Nurasiah Nurasiah Nurdin Nurhidayah, Josanti Nurmala, Sinta Nurmulya, Wa Ode Sitti NURUL AZIZAH Nuzula Fitranti, Avin Palahudin Pebrinda, Else perma sari, rose intan Permadi, Luchyto Chandra Pohan, Putri Amanda Pradani, Rizky Fitriyanti Prasaja Wikanta Prasidarini, Rifka Ilma Pratama, Wildan Pratomo Setiaji Pratomo Setiaji Primadiarta, Ari Sam Primawanti, Henike Prionaka Luthfi Mahendra Priyambodo, Ragil Putra, Debi Kumala Putra, Edo Putri Kurnia Handayani Putri, Sarah Athaullah Wenna Putri, Shasha Ramadhani Putri, Sylvia Octa Putri, Yohana Shavira Qomaruddin R Rhoedy Setiawan Rachmi Meutia Rafli Zudha Sasongko Rafly Channan Assegaf Ragil Budiono Rahmatullah, Zaid Hidayat Rahmawati, Amelia Ramadanil, Farid Ramadhan, Fathjri Ramadhan, M. Zaki Nawaf Ramadhani, Silvia Ramadlan As'ari, Wahyu Ratna Wati Regizka Ayu Mega Saputri RESTIN MEILINA Retno Widyastuti, Retno Revanda Putri Rahmadani Ridho Agiel Syahputra Siallagan Ridwan Rini Ekayati Rini Muharini Rino Sardanto Ritonga, Din Aswan Amran Riyan Hadi Prabowo Riyan Sisiawan Putra Rizal Maulana Rizal Maulana, Rizal Rizal Setiawan Rizka, Fithria Rizky Adisaputra Rizky Ferdiansyah Rizky Muhammad Rizky Maulana Rochim, Galuh Nur Rohadi, Melia Pradita Romdoni, Moh Fahmi Sabputro, Heru Sadali, Muhamad Safera, Asywila Huda Sahputra, Rahmat Saidun Basyar, Aminun Fais Salamah, Ummi Salma Elsa Widyadhana Salma Hayati Salsabila, Cut Sarah Athiyah Samudi Santy, Nawal Ari Saputra, Hasar Sarjana Sarjana Saruran, Michelin Alfa Seila Desy Maulia Selamet Ahmad Faisal Sembiring, Oscar Fredriek Setiyoadi, Amanda Diyas Sety, La Ode Muhamad Shahadah, Dewi Faridah Nur Shasha Ramadhani Putri Shofiani Dwi Natalia Siahaan, Gorga Josua Chrisvandoli Sihombing, Ahmad Gunawan Sihotang, Yohana Silitonga, Alfredo Jonathan Simangunsong, Agustina Simanjorang, R. Mahdalena Simarmata, Ruth Ana Magdalena Br Simatupang, Linda E M Sinaga, Zulkani Sintiana, Indah Siregar, Fathia Siregar, Putri Bungsu Sirullah, Mohammad Fajar Siti Aminah Siti Ifa Septiana Siti Nurfadilah H Siti Raihanah Sitompul, Adravia Lisbeth Claudia Soni Adiyono Sri Utami Sudarsono Sugiartono, Endro Sukarmi Sukinah, Endang Sukma Wijayanti Sulung, Bagus Putra Supriadi Supriyono Supriyono Supriyono Supriyono Supriyono Suryo Hadi Kusumo Susanto, Gito Aru Susanto, Gito Aru Syafiul Muzid Syahrul Bagus Andreyan Syahwa Mutiara Putri Syaputa, Muhammad Rioardian Syauqi, Gutti Zaidan Syifa Amalia Syindau Abdillah, M. Andrian Tampubolon, Rijal Tampubolon, Sandy Donni Tarigan, Jenni Parlopes Br Tarigan, Tiodora Br Tasa Tasa Tasa Taufiq Hidayat Tauran, Rina Teddy Octa Prabowo Tihadanah, Tihadanah Tirta Nita Togatorop, Inneke MF Tri Danang Kurniawan Tri Dina Fitria Tria Yanuarsih Triwahyuni, Dewi Tsirwatun Nisail Khasanah Tunnazia, Aqilla Ubaidillah, Jainul Ukun, Ukun Kurnia Ulan Ullul Azmie, Fadila Umar, U Usman, Ismuadi Utama, Bima Satria Utami, Mauliddina Utami, Yulia Verdinand, Rhenal Vinsensia, Desi Virgie Andrian Noval Vita Nurus Salamah Wahyu Dhani Prayoga Wahyu Wibowo, Angga Wandari, Kameilia Wardhana, Fahriy Aulia Widany, Chelyn Audya Widya Rika Puspita Widyantoro, Murwan Wijaya, Cindy Ari Wijiyanto, Dwi Wirahmi, Nori Wiwik Yunarni Widiarti Wiwit Agus Triyanto Yasmin, Dhira Fijri Yudie Irawan Yulfitra, Yulfitra Yuniarsi Rahayu Yunira, Yuli Yusuf Sabilu, Yusuf Zaenal Arifin Zahra, Nadhira Fitria Zahrotul Khoiriyah Zakiiya, Ghulaman Zessicha Belliana Putri Zoningsih, Meta Yupitri Zubdatu Zahrati, Zubdatu Zahrati Zulaika Zuliyanto, Muhammad Zuliyati Zuliyati

Title

Found 266 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 266 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 266 Documents
Search