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All Journal Nusa: Jurnal Ilmu Bahasa dan Sastra Jurnal sistem informasi, Teknologi informasi dan komputer JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) JSiI (Jurnal Sistem Informasi) JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknik Informatika (JUTIF) Journal La Multiapp JURNAL ILMIAH GLOBAL EDUCATION Economicus: Jurnal Ekonomi dan Manajemen Jurnal Manajemen Informatika dan Bisnis Digital Wicara Jurnal Informatika: Jurnal Pengembangan IT

Khothibul Umam

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Author-ID : 407634

Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Gaya Bahasa Lirik Lagu "untuk hati yang terluka", "ragu Semesta", dan "Sikap Dunawi" pada Album LEXICON Isyana Sarasvati (Sebuah Kajian Stilistika) Puspita, Yonanda Dera; Muzakka, Moh; Umam, Khothibul
Wicara: Jurnal Sastra, Bahasa, dan Budaya Vol 1, No 2: Oktober 2022
Publisher : Program Studi Sastra Indonesia, Fakultas Ilmu Budaya, Universitas Diponegoro

AbstrakPenelitian ini bertujuan untuk menjelaskan gaya bahasa dalam lirik lagu “untuk hati yang terluka”, “ragu Semesta”, dan “Sikap Duniawi” yang dianalisis dari segi gaya bahasa dalam bunyi, gaya bahasa dalam kata, gaya kalimat, dan gaya wacana menggunakan kajian stilistika. Penelitian ini menggunakan teori struktur puisi, teori stilistika, dan teori gaya bahasa. Pendekatan yang digunakan dalam penelitian ini adalah kualitatif deskriptif dan metode yang digunakan adalah metode stilistika yang menitikberatkan pada pengkajian mengenai gaya bahasa objek material penelitian yang mencakup: (1) teknik pengumpulan data; (2) teknik analisis data; (3) tahap penyajian hasil analisis data. Hasil dari penelitian ini adalah, gaya bahasa dalam bunyi pada lirik lagu “untuk hati yang terluka” dan “ragu Semesta” menunjukkan bunyi kakafoni yang mengisyaratkan makna yang memiliki nuansa sedih, sedangkan pada lirik lagu “Sikap Duniawi” menujukkan bunyi efoni yang mengisyaratkan makna dan nuansa bahagia. Gaya bahasa dalam kata pada ketiga objek material penelitian ini menggunakan bahasa keseharian namun dari segi tata bahasa dikemas secara implisit untuk memberikan nilai puitis. Gaya kalimat pada lirik lagu “untuk hati yang terluka” meliputi gaya bahasa aferesis sebanyak sebelas (11) data, repetisi, alegori, metafora, hiperbola masing-masing sebanyak dua (2) data, dan personifikasi sejumlah satu (1) data. Pada lirik lagu “ragu Semesta” meliputi gaya bahasa aferesis sebanyak dua belas (12) data, simile, personifikasi, dan repetisi masing-masing sebanyak sati (1) data, dan metafora sebanyak tiga (3) data. Dan gaya bahasa pada lirik lagu “Sikap Duniawi” meliputi gaya bahasa aferesis sebanyak dua (2) data, retoris dan ironi masing-masing sebanyak satu (1) data, metafora sebanyak enam (6) data, dan repetisi sebanyak tiga (3) data. Gaya wacana pada ketiga objek material penelitian merupakan wacana yang saling terhubung dan padu.Kata kunci: “untuk hati yang terluka”, “ragu Semesta”, “Sikap Duniawi”, Album LEXICON, Stilistika.

Lima Mode Fantasi dalam Novel The Bliss Bakery Karya Kathryn Littlewood Terjemahan Nadia Mirzha: Kajian Teori Fantasi Rosemary Jackson Widyasari, Sherly Gratia; Umam, Khothibul; Komariya, Siti
Wicara: Jurnal Sastra, Bahasa, dan Budaya Vol 3, No 2: Oktober 2024
Publisher : Program Studi Sastra Indonesia, Fakultas Ilmu Budaya, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/wjsbb.2024.22741

Novel The Bliss Bakery karya Kathryn Littlewood merupakan novel terjemahan bergenre fantasi yang berisi tentang perjalanan Rosemary Bliss dalam membuat roti ajaib. Setiap pembuatan roti dapat memperlihatkan keajaiban sehingga memberikan gambaran semesta fantasi buatan pengarang. Roti ajaib dibuat sesuai dengan tujuannya dalam menyelesaikan masalah. Penelitian ini ditujukan untuk mengungkapkan dunia fantasi buatan pengarang. Objek formal dalam penelitian berfokus pada unsur-unsur fantasi yang terdapat di dalam novel. Kajian teori yang digunakan untuk menganalisis berdasarkan pemikiran Rosemary Jackson. Metode penelitian yang digunakan, yaitu metode deskriptif kualitatif. Pendekatan analisis yang dipakai yaitu pendekatan mimetik. Pendekatan mimetik digunakan untuk membandingkan dunia fantasi dengan dunia nyata untuk mempermudah analisis unsur-unsur mode fantasi. Hasil analisis menunjukkan bahwa unsur-unsur fantasi dalam novel The Bliss Bakery karya Kathryn Littlewood memiliki lima mode fantasi sesuai teori Rosemary Jackson, yaitu imajinasi dalam pengasingan (penaklukan badai, halilintar, awan, bahan ajaib, penulisan resep, tatanan kehidupan yang terbalik); yang nyata di bawah pengawasan (makanan pokok, takaran resep, bahan-bahan pembuatan roti biasa, perebutan warisan, bencana badai, dan hubungan sosial); luar biasa, mimetik, dan fantastis (anak yang sedang kritis, kisah cinta Mr. Bastable dan Miss Thistle, serta pembalik keadaan seutuhnya); tidak signifikan (badai, kilat, dan awan); serta topografi (dataran rendah, dataran tinggi, bentuk kunci pintu, tata letak barang-barang di gudang, dan bangunan rahasia), tema (kepahlawanan), dan mitos (dongeng, abad pertengahan, dan kepercayaan).

Nilai Perjuangan Tokoh Utama dalam Cerpen Kabut di Teras Senja Karya Sutini Izzuddin, Zufar Wahyu; Martini, Laura Andri Retno; Umam, Khothibul
Wicara: Jurnal Sastra, Bahasa, dan Budaya Vol 2, No 1: April 2023
Publisher : Program Studi Sastra Indonesia, Fakultas Ilmu Budaya, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/wjsbb.2023.17217

Penelitian ini bertujuan untuk mengetahui nilai perjuangan yang terdapat dalam kumpulan cerpen Kabut di Teras Senja karya Sutini. Teknik dalam penelitian ini menggunakan teknik pengumpulan data yang berupa kajian pustaka, teknikanalisis data yang terdiri tiga tahap yaitu reduksi data,sajian data, kesimpulan dan sumber data penelitian yang menggunakan kumpulan cerpen Kabut di Teras Senja karya Sutini. Hasil penelitian ini mengungkapkan unsur struktur fiksi selalu berkaitan dengan tokoh, penokohan, latar, alur, sudut pandang dan amanat. Latar cerpen Kabut di Teras Senja terbagi menjadi dua bagian yaitu latar netral dan latar tipikal. Kedua latar ini terdapat pada cerpen ‘’ Kabut di Teras senja’’, ‘’Bukan sepatu cindrella’’, ‘’Korban Bucin’’, ‘’Arisan Jodoh’’, dan ‘’Bersahabat Ombak’’. Hubungan antar unsur struktur fiksi ttersebut menghasilkan pesan moral tertenu. Pesan moral yang ingin disampaikan kepada pembaca yaitu pesan moral berupa nilai perjuangan. Nilai perjuangan tersebut adalah pantang menyerah, sabar, bekerja sama, dan rela berkorban.

Analisis Lima Dimensi Religius dalam Film Qodrat Karya Charles Gozali: Kajian Sosiologi Sastra Tambunan, Rieke Dinda Laila; Umam, Khothibul; Khurosan, Herpin Nopiandi
Wicara: Jurnal Sastra, Bahasa, dan Budaya Vol 4, No 1: April 2025
Publisher : Program Studi Sastra Indonesia, Fakultas Ilmu Budaya, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/wjsbb.2025.26918

AbstractThis study uses a material object in the form of Charles Gozali's Qodrat film. Charles Gozali's Qodrat film has a unique aspect in its religiosity. This study uses narrative film theory, literary sociology theory and religiosity which are explained using descriptive methods. The purpose of this study is to explain the narrative structure of the film contained in Charles Gozali's Qodrat film. The theory of narrative structure is used to describe the story and plot, the relationship between narrative and space, the relationship between narrative and time, and the main elements of the narrative (characters, problems and conflicts, and goals), and themes in the Qodrat film. Meanwhile, to eliminate the value of religiosity in the film Qodrat by Charles Gozali, the author uses the theory of the dimensions of religiosity of Glock and Stack. The results of the analysis of the narrative structure of the film Qodrat by Charles Gozali. The results of the analysis of the narrative structure of the film Qodrat by Charles Gozali are the discovery of several developments in the character's faith through analysis of the story and plot, the relationship between narrative and space, the relationship between narrative and time, the main elements of the narrative and theme. The results of the analysis obtained are that the film Qodrat meets the five aspects of the theory of religiosity of Glock and Stack. The five dimensions consist of five dimensions of religiosity, namely the dimensions of belief (belief/belief), practice (ritual/religious practice), knowledge (knowledge), experience (experience), and consequences (consequences), Belief in the existence of God, understanding of the help and protection given by God, religious rituals performed to God such as prayer, ruqyah and fasting, knowledge of religion, ability to read the holy verses of the Qur'an, understand the science of rukiah, and be able to fight against jinn disturbances, spiritual experiences, mystical disturbances, and receive help from God, the dimension of consequences includes the end that will be obtained from the actions taken, in the form of good and bad.Keywords: Qodrat film, sociology of literature, dimensions of religiosity, Glock and Stark IntisariPenelitian ini menggunakan objek material berupa film Qodrat karya Charles Gozali. Film Qodrat karya Charles Gozali memiliki keunikan pada aspek religiusitasnya. Penelitian ini menggunakan teori naratif film, teori sosiologi sastra dan religiusitas yang dijelaskan dengan metode deskriptif. Tujuan penelitian ini adalah untuk menjelaskan struktur naratif film yang terdapat dalam film Qodrat karya Charles Gozali. Teori struktur naratif digunakan untuk mendeskripsikan cerita dan plot, hubungan naratif dengan ruang, hubungan naratif dengan waktu, serta elemen pokok naratif (pelaku cerita/tokoh, permasalahan dan konflik, dan tujuan), serta tema dalam film Qodrat. Sedangkan untuk menganalisis nilai religiusitas dalam film Qodrat karya Charles Gozali, pengarang menggunakan teori dimensi religiusitas Glock dan Stack. Hasil analisis struktur naratif film Qodrat karya Charles Gozali. Hasil analisis struktur naratif film Qodrat karya Charles Gozali ini adalah ditemukannya beberapa perkembangan keimanan tokoh melalui analisis cerita dan plot, hubungan naratif dengan ruang, hubungan naratif dengan waktu, elemen pokok naratif dan tema. Adapun hasil analisis yang didapatkan bahwa film Qodrat memenuhi lima aspek teori religiusitas Glock dan Stack. Lima dimensi tersebut, terdiri dari lima dimensi religiusitas yaitu dimensi belief (kepercayaan/keyakinan), practice (ritual/praktik keagamaan), knowledge (pengetahuan), experience (pengalaman), dan consequences (konsekuensi), Keyakinan terhadap adanya Tuhan, keyakinan terhadap pertolongan dan perlindungan yang diberikan Tuhan, ritual keagamaan yang dilakukan kepada Tuhan seperti sholat, ruqyah serta berpuasa , pengetahuan tentang agama, kemampuan dalam membaca ayat suci al-Qur’an, memahami ilmu rukiah, serta mampu melawan gangguan jin, pengalaman-pengalaman spiritual, gangguan-gangguan mistis, serta mendapat pertolongan dari Tuhan, dimensi akibat meliputi akhir yang akan diperoleh atas tindakan yang dilakukan, berupa baik dan buruk.Kata kunci: film Qodrat, sosiologi sastra, dimensi religiusitas, Glock dan Stark

Modeling Political Discourse in Indonesia’s 2024 Election Using Unsupervised Machine Learning Malikhatul Ibriza; Maya Rini Handayani; Wenty Dwi Yuniarti; Khothibul Umam
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 2 (2025): MEY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i2.2359

The 2024 General Election in Indonesia has generated a large volume of diverse and unstructured digital political discourse, necessitating a machine learning-based analytical approach for efficient, objective, and scalable data processing. This study aims to map political discourse from 14,813 text data collected from the open-source "Indonesian Election 2024" dataset on the Hugging Face platform, encompassing social media posts (e.g., Twitter) and online news content from January to March 2024. This research integrates three core methods: Principal Component Analysis (PCA) for dimensionality reduction, K-Means for clustering, and Latent Dirichlet Allocation (LDA) for topic extraction. This combination represents an original approach in Indonesian political discourse studies, leveraging unsupervised learning techniques to enhance topic mapping efficiency compared to single-method approaches in prior research. The analysis identified three primary clusters electoral technical issues, candidate figures, and official agendas yielding a Silhouette Score of 0.51 (a clustering quality metric) and a top topic coherence score of 0.51. Validation was conducted both quantitatively and qualitatively by content experts. This approach not only demonstrates strong analytical capability in uncovering thematic patterns but also offers practical applications for institutions such as the General Elections Commission (KPU), Election Supervisory Body (Bawaslu), and the media in monitoring strategic issues and detecting potential disinformation in the lead-up to the election.

HANA: An AI Chatbot for Islamic Jurisprudence on Menstruation using SBERT and TF-IDF Masuzzahra, Tsaura Rafah; Khothibul Umam; Hery Mustofa; Maya Rini Handayani
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9449

The advancement of Artificial Intelligence (AI), particularly in Natural Language Processing (NLP), has opened new opportunities for religious technological innovation, especially in addressing practical Islamic jurisprudence issues such as menstruation (fiqh haid). This research proposes and implements HANA, an AI chatbot developed for Telegram, utilizing a hybrid approach combining Term Frequency-Inverse Document Frequency (TF-IDF) and Sentence-BERT (SBERT) models. A curated dataset of over 1000 question-answer pairs from classical and contemporary Islamic literature was used, primarily based on the Shafi'i school of thought. The chatbot matches user queries through a two-stage retrieval: initial keyword matching via TF-IDF and deeper semantic matching via SBERT embeddings. Evaluations were conducted by comparing TF-IDF, SBERT, and hybrid approaches using cosine similarity, precision, recall, and F1-score metrics, focused on top-1 retrieval accuracy. HANA achieved an average cosine similarity score of 0.6581 and a semantic relevance rating of 87% based on expert validation, while User Acceptance Testing (UAT) involving 15 respondents indicated 86.7% satisfaction. Although the system is deployed as a proof-of-concept on Google Colab without persistent hosting, it demonstrates the viability of lightweight AI chatbots for Shariah consultation services. Future improvements include multi-turn conversation handling and integration with large language models for better context understanding. This research contributes to expanding NLP applications within techno-dakwah initiatives, providing a scalable approach to enhance women's access to Islamic jurisprudence knowledge.

Comparative Study of SVM, KNN, and Naïve Bayes for Sentiment Analysis of Religious Application Reviews Heti Aprilianti; Khothibul Umam; Maya Rini Handayani
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9482

This study aims to evaluate and compare the performance of three machine learning algorithms—Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), and Naïve Bayes—for sentiment classification of user reviews on the NU Online application in the Google Play Store. NU Online is a religious digital platform providing Islamic content such as articles, prayers, and worship schedules. A total of 1,500 user reviews were collected using web scraping, and 1,491 were retained after data cleaning. Preprocessing steps included punctuation removal, case folding, normalization, stopword removal, stemming, and tokenization. Sentiment labels (positive or negative) were automatically assigned using a lexicon-based approach. The performance of the models was assessed using accuracy, precision, recall, and F1-score, calculated via confusion matrix with a training-testing data split. The results show that the SVM with a linear kernel achieved the best accuracy (81.6%), followed by Naïve Bayes (73.2%) and K-NN (66.9%). These findings indicate that SVM is the most effective algorithm in this context, providing practical contributions for developers of the NU Online digital religious platform and contributing to research in Indonesian natural language processing.

Detecting Fake Reviews in E-Commerce: A Case Study on Shopee Using Support Vector Machine and Random Forest Khoirotulmuadiba Purifyregalia; Khothibul Umam; Nur Cahyo Hendro Wibowo; Maya Rini Handayani
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9514

The increasing popularity of online shopping, particularly on platforms such as Shopee, has made product reviews a significant factor influencing consumer purchasing decisions. However, the presence of fake reviews generated by non-human agents undermines consumer trust and affects platform credibility. This study aims to detect fake reviews on Shopee by applying a text classification approach using Random Forest and Support Vector Machine (SVM) algorithms. A dataset consisting of 3,686 Shopee product reviews was collected and underwent preprocessing steps including data cleaning, normalization, tokenization, and TF-IDF weighting. Review labeling was performed automatically through the Latent Dirichlet Allocation (LDA) method, categorizing reviews into Original (OR) and Computer-Generated (CG). Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. Experimental results show that the SVM algorithm achieved the highest accuracy at 88.84%, outperforming Random Forest which obtained 80.39%. These findings highlight the effectiveness of SVM in handling high-dimensional text data for fake review detection. The study contributes to the application of automated topic modeling (LDA) for labeling e-commerce reviews in the Indonesian context and opens opportunities for further enhancement using larger datasets and deep learning-based models to improve classification accuracy and scalability.

Performance of Machine Learning Algorithms on Imbalanced Sentiment Datasets Without Balancing Techniques Dina Wulan Yekti rahayu; Khothibul Umam; Maya Rini Handayani
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9584

This study explores the performance of five sentiment classification algorithms—Naïve Bayes, Logistic Regression, Support Vector Machine, Decision Tree, and Random Forest—on an imbalanced sentiment dataset, with the SMOTE technique applied as a comparison. The research follows the Knowledge Discovery in Databases (KDD) framework, which includes data selection, preprocessing, transformation, data mining, and evaluation. The evaluation uses metrics such as accuracy, precision, recall, F1-score, and macro average F1-score. Initial results show that all five algorithms performed fairly well even without using a balancing technique, with Naïve Bayes achieving the highest F1-score of 0.84 and recall of 0.81. After applying SMOTE, only small improvements were observed in some models, such as Random Forest (F1-score increased from 0.81 to 0.85), while other models like Naïve Bayes experienced a decrease in performance, dropping to 0.77. This suggests that the effect of balancing techniques like SMOTE can vary depending on the algorithm. Thus, this study provides empirical contributions that highlight the importance of selecting appropriate approaches and the need for a deep understanding of each algorithm's behavior in the context of imbalanced data. Researchers are encouraged to carefully consider these aspects when designing experiments and interpreting results.

Deteksi Dark patterns Biaya Layanan E-commerce Berdasarkan Perspektif Konsumen Menggunakan Algoritma Support Vector Machine Salmalina, Divana Taricha; Umam, Khothibul; Handayani, Maya Rini
Jurnal Sistem Komputer dan Informatika (JSON) Vol 6, No 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8563

Perkembangan industri e-commerce di Indonesia belakangan ini dibayangkan pada fenomena meningkatnya keluhan konsumen terkait kebijakan biaya layanan yang dinilai kurang transparan, termasuk indikasi adanya praktik pola gelap . Penelitian ini bertujuan mengkaji persepsi konsumen terhadap isu tersebut melalui pendekatan analisis sentimen berbasis machine learning dan deteksi pola manipulatif. Data penelitian diperoleh dari ulasan pengguna di platform media sosial X yang kemudian diproses melalui serangkaian tahapan text mining meliputi pembersihan data, tokenisasi, stopword removal , dan stemming . Analisis sentimen menggunakan algoritma Support Vector Machine (SVM) menunjukkan hasil yang signifikan, dimana 55-78% ulasan di platform ketiga e-commerce (Shopee, Tokopedia, Lazada) tergolong negatif. Analisis TF-IDF mengidentifikasi kata kunci seperti "biaya", "layan" (layanan), dan "mahal" sebagai istilah paling dominan dalam ulasan negatif. Model SVM menunjukkan kinerja yang cukup baik dengan akurasi mencapai 87% dalam mengklasifikasikan sentimen negatif. Lebih lanjut, analisis tematik terhadap ulasan negatif berhasil mengidentifikasi indikasi pola gelap , khususnya dalam kategori biaya tersembunyi (biaya tersembunyi) dan menyelinap ke keranjang (penambahan produk tanpa disadari) yang muncul secara konsisten di semua platform. Temuan ini tidak hanya menegaskan adanya pola manipulatif yang berulang dalam industri e-commerce Indonesia, tetapi juga menegaskan urgensi bagi para pelaku industri untuk meningkatkan transparansi dalam kebijakan biaya. Secara praktis, hasil penelitian ini dapat menjadi bahan pertimbangan penting bagi regulator dalam merumuskan kebijakan perlindungan konsumen di era digital yang lebih komprehensif.

Co-Authors Azziizah, Almira Farradinda Dewi, Fiashintha Dina Wulan Yekti rahayu Dwi Yuni Saraswati Dwi Yuniarti, Wenty Endang Supriyati Fadhilah, Mohamad Agung Faruq, Muhammad Kholfan Fastabiqul Khusna Febrianto, Bagus Haryanti, Novia Heti Aprilianti Imtias, Muhamad Bunan Izzuddin, Zufar Wahyu Jinan, Muhammad Syifaaul Khoirotulmuadiba Purifyregalia Komariya, Siti Lailatus Sa’adah Laura Andri Retno Martini Limparu, Stella Lasverina Mahfudh, Adzhal Arwani Maizaliyanti, Annisa Malikhatul Ibriza Manurung, Gregorius Tri Hendrawan Masuzzahra, Tsaura Rafah Masy Ari Ulinuha Maya Rini Handayani Moh Muzakka, Moh Mokhamad Iklil Mustofa Muhammad Rafid Pratama Mustofa, Hery Mustofa, Mokhammad Iklil Nur Cahyo Hendro Wibowo Nur Cahyo Hendro Wibowo, Nur Cahyo Hendro Pramesti, Arfiana Diah Prasilda, Dina Rahma Puspita, Yonanda Dera Putri, Amiliya Putri, Indira Alifia Qonita, Nuurun Najmi Rahmadani, Nurul REDYANTO NOOR Rini Handayani, Maya Sabilillah, Muhsin Safitri, Sindy Eka Sajmira, Danita Divka Salmalina, Divana Taricha Sanjaya, Tegar Saputra, Adika Kaka Sa’adah, Lailatus Sa’adah, Siti Miftahus Septyorini, Talitha Dwi Siti Nur'aini Subowo, Moh Hadi Sukarjo Waluyo Syafiqa, Luthfia Rahmati Tambunan, Rieke Dinda Laila Tri Listyorini Wenty Dwi Yuniarti Wenty Dwi Yuniarti, Wenty Dwi Widyasari, Lia Widyasari, Sherly Gratia Yuniardi Fadilah Zaman, Farkhan Nuruz

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