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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal F. Teknik : RESULTAN Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Komputer AMIK BSI Cakrawala : Jurnal Humaniora Bina Sarana Informatika Paradigma Jurnal Ilmiah FIFO Bina Insani ICT Journal Jurnal Pilar Nusa Mandiri Information System for Educators and Professionals : Journal of Information System Jurnal Mahasiswa Bina Insani Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) Jurnal Teknik Informatika STMIK Antar Bangsa Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Komtika (Komputasi dan Informatika) IKRA-ITH EKONOMIKA Jurnal ICT : Information Communication & Technology JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Kajian Ilmiah Jurnal Sistem Informasi Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Journal of Students‘ Research in Computer Science (JSRCS) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Pengabdian Masyarakat Information Technology (JPM ITech) Journal of Computer Science Contributions (Jucosco) Jurnal Kecerdasan Buatan dan Teknologi Informasi Jurnal Komtika (Komputasi dan Informatika) Journal of Intelligent Systems for Community Development (JISCoDe)
Herlawati Herlawati
Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Other

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Penentuan Pola Frekuensi Jenis Perawatan Kecantikan Berbasis Web Menggunakan Algoritma Apriori (Studi Kasus: Peterson Salon Bekasi) Herlawati Herlawati; Rahmadya Trias Handayanto; Sri Rejeki; Wowon Priatna; Prima Dina Atika; Syahbaniar Rofiah; Endang Retnoningsih; Faisal Adi Saputra; Galih Apriansha Pradana
Journal of Students‘ Research in Computer Science Vol. 3 No. 2 (2022): November 2022
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jsrcs.v3i2.1381

Abstract

Currently, technology can affect services in any field, both in areas such as salon services and sales of clothing products. How to plan a marketing strategy using the web based on service transaction data and products that are most often chosen by customers. Therefore, an information system for determining frequency patterns is needed using the website-based Apriori Algorithm method. The results of research on salons based on the type of beauty treatment obtained for the type of treatment with a minimum confidence = 70%, the first confidence value is 63% if the customer chooses to wash (shampoo), the customer chooses scissors, the second the confidence value is 100%, if the customer chooses to blow then chooses also cut, and the third confidence value is 86% if the customer chooses creambath then the customer chooses to cut too. Meanwhile at the shop clothes determining the frequency pattern of types of clothes with a minimum value of confidence = 70% so that the results include if a customer buys a veil, the customer buys a robe with a confidence value of 71.43% and if a customer buys khimar then the customer will also buy a robe with a confidence value of 78, 57%. With these results salon and clothing store owners can determine marketing strategies by providing the right product and service recommendations to customers. Keywords: Apriori Algorithm, Beauty Care, Recommendations, Sales   Abstrak Saat ini teknologi dapat mempengaruhi pelayanan dalam bidang apapun seperti jasa salon maupun penjualan produk pakaian. Bagaimana merencanakan strategi pemasaran menggunakan web berdasarkan data transaksi layanan dan produk yang paling sering dipilih oleh pelanggan. Oleh karena itu dibutuhkan sistem informasi penentuan pola frekuensi menggunakan metode Algoritma Apriori berbasis website. Hasil penelitian pada salon berdasarkan jenis perawatan kecantikan diperoleh untuk jenis perawatan dengan minimum confidence=70% yang pertama nilai confidence sebesar 63% jika pelanggan memilih cuci (keramas) maka pelanggan memilih gunting, yang kedua nilai confidence sebesar 100% jika pelanggan memilih blow maka memilih digunting juga, dan yang ketiga nilai confidence 86% jika pelanggan memilih creambath maka pelanggan memilih digunting juga. Sedangkan pada toko pakaian penentuan pola frekuensi jenis baju dengan nilai minimum confidence= 70% sehingga mendapatkan hasil diantaranya jika pelanggan membeli kerudung maka pelanggan membeli gamis dengan nilai confidence sebesar 71,43%  dan  jika  pelanggan  membeli  khimar maka pelanggan juga akan membeli gamis dengan nilai confidence sebesar 78,57%. Dengan hasil tersebut pemilik salon dan toko pakaian dapat menentukan strategi pemasaran dengan memberikan rekomendasi jasa dan produk yang tepat kepada pelanggan. Kata kunci: Algoritma Apriori, Penjualan, Perawatan Kecantikan, Rekomendasi
Modification of SqueezeNet for Devices with Limited Computational Resources Rahmadya Trias Handayanto; Herlawati
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4446

Abstract

In recent years, the computational approach has shifted from a statistical basis to deep neural network architectures which process the input without explicit knowledge that underlies the model. Many models with high accuracy have been proposed by training the datasets using high performance computing devices. However, only a few studies have examined its use on non-high-performance computers. In fact, most users, who are mostly researchers in certain fields (medical, geography, economics, etc.) sometimes need computers with limited computational resources to process datasets, from notebooks, personal computers, to mobile processor-based devices. This study proposes a basic model with good accuracy and can run lightly on the average computer so that it remains lightweight when used as a basis for advanced deep neural networks models, e.g., U-Net, SegNet, PSPNet, DeepLab, etc. Using several well-known basic methods as a baseline (SqueezeNet, ShuffleNet, GoogleNet, MobileNetV2, and ResNet), a model combining SqueezeNet with ResNet, termed Res-SqueezeNet, was formed. Testing results show that the proposed method has accuracy and inference time of 84.59% and 8.46 second, respectively, which has an accuracy of 2% higher than the SqueezeNet (82.53%) and is close to the accuracy of other baseline methods (from 84.93% to 0.88.01%) while still maintaining the inference speed (below nine second). In addition, residual part of the proposed method can be used to avoid vanishing gradient, hence, it can be implemented to solve more advanced problems which need a lot of layers, e.g., semantic segmentation, time-series prediction, etc.
Identification of Website-Based Product Sales Frequency Patterns using Apriori Algorithms and Eclat Algorithms at Rio Food in Bekasi Salwa Nabiila Pramuhesti; Herlawati Herlawati; Tyastuti Sri Lestari
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 11 No 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.5941

Abstract

Sales reports that are not managed automatically may hinder businesses from accurately determining their progress in the short or long term. With increasing community needs for a product, business owners have an opportunity to market their products to a larger audience. The abundance of data highlights the need for information to produce patterns that can be used as a reference for making decisions in buying products on the website. Data mining algorithms can provide support for analysis, which can help avoid inaccurate business progress reports. In this study, the Apriori and Eclat algorithms were applied to analyze frequent itemsets in association rule mining. The dataset used in this study consists of 20 transaction data from frozen food sales. The results showed that the combination of Nugget and Chicken Sausage itemsets were the most frequent, with higher support, confidence, and lift ratio values than the others. These results can be used as product recommendations that are most in demand by customers.
Pencarian Stasiun Kereta Terdekat dengan Algoritma A Star Berbasis Android di Area Stasiun Wilayah Bekasi Ikhsan Dwikurniawan; Herlawati .; Robertus Suraji
Jurnal ICT: Information Communication & Technology Vol. 21 No. 2 (2021): JICT-IKMI, Desember 2021
Publisher : LPPM STMIK IKMI Cirebon

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

Abstract

Transportasi telah menjadi salah satu kebutuhan yang sangat penting dalam kegiatan sehari-hari di kehidupan bermasyarakat. Kemajuan teknologi informasi yang ada saat ini, dapat digunakan sebagai sarana untuk meningkatkan pelayanan umum, salah satunya adalah di bidang perkeretaapian. Dengan adanya kemajuan teknologi informasi dapat memudahkan masyarakat untuk mengetahui informasi secara cepat dan mudah, tetapi masih ada beberapa kendala yaitu kurangnya informasi mengenai rute stasiun terdekat. Penelitian ini bertujuan untuk membuat aplikasi pencarian Stasiun terdekat berbasis android dengan rute terpendek menuju Stasiun tujuan dengan menggunakan Algoritma A-STAR. Algoritma A-STAR ialah algoritma yang mencari rute terpendek untuk mencapai tujuan yang diharapkan. Tahapannya yaitu 1) Memasukkan node awal ke open list. 2) Melakukan looping. 3) Simpan rute secara backward, urutkan mulai dari node goal ke parent-nya sampai ke node awal bersamaan menyimpan node-nya ke dalam sebuah array. Pada penelitian ini Stasiun Kranji, Stasiun Bekasi, Stasiun Bekasi Timur, Stasiun Tambun, Stasiun Cibitung, Stasiun Telaga Murni, Stasiun Cikarang. Pengujian pada penelitian ini dilakukan dengan pengujian black box testing dan pengujian perbandingan antara algoritma A-STAR dengan Google Map, hasilnya diperoleh menunjukan lebih banyak algoritma A-STAR berhasil dengan jarak terpendek, walaupun ada Algoritma A-STAR yang hasil sama dengan Google Maps, dan algoritma A-STAR ada juga yang menunjukkan jarak yang lebih jauh dibandingkan Google Maps
Learning Vector Quantization, Hebbian Learning, and Self-Organizing Map for Classification Herlawati Herlawati
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 11 No 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.6942

Abstract

Deep Learning has been rapidly developed. Almost all proposed methods already have very high accuracy. Most of these methods still use techniques from the past with some modifications to adapt to existing modules. Sometimes it is necessary to understand past methods to produce new methods. Therefore, this research examines past models that have the potential to improve the performance of existing deep learning models. The methods to be examined include Learning Vector Quantization (LVQ), Hebbian learning, and Self-Organizing Map (SOM). The iris dataset available on Scikit-learn (SKlearn) is used here for testing in cases of supervised learning and unsupervised learning (especially SOM). The results show that LVQ has a good accuracy of 93%, while Hebbian learning has an accuracy of 56%. SOM fluctuates between 88% and 93%. Although the accuracy of SOM does not exceed LVQ, this model does not require labels in its training process.
Perubahan Kerapatan Vegetasi dan Penutup Lahan Terhadap Urban Heat Island (UHI) di Kota Bekasi Rahmadya Trias Handayanto; Haryono; Herlawati
Journal of Students‘ Research in Computer Science Vol. 4 No. 1 (2023): Mei 2023
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jsrcs.v4i1.2655

Abstract

The replacement of vegetation by roads, buildings, and other structures leads to increased absorption and reflection of solar heat, resulting in elevated surface temperatures in urban areas. This leads to the formation of more hotspots, triggering changes in weather and climate, which are key indicators of the Urban Heat Island (UHI) phenomenon. UHI refers to the phenomenon where urban areas experience higher temperatures compared to their surrounding areas. The primary factor influencing UHI is the conversion of vegetated land cover into developed areas due to urban growth. This causes an increase in surface temperatures due to a reduction in vegetation density and an increase in building density. Changes in land cover within the study area can be identified using unsupervised classification analysis, followed by the analysis of the Normalized Difference Vegetation Index (NDVI) to assess the vegetation index's impact on Land Surface Temperature (LST) and determine the surface temperature of Bekasi city. Accordingly, the objective of this research is to analyze the Urban Heat Island in Bekasi city using a quantitative approach that utilizes Landsat satellite imagery. The results indicate that the temperature in Bekasi city ranges from 25 to 31 degrees Celsius.  Keywords: Landsat-8, Land Surface Temperature, Land Use, NDVI, USGS   Abstrak Pergantian vegetasi oleh jalan, bangunan, dan struktur lainnya menyebabkan peningkatan penyerapan dan pantulan panas matahari, yang mengakibatkan kenaikan suhu permukaan di kota. Akibatnya, terbentuk lebih banyak titik panas yang memicu perubahan cuaca dan iklim, yang menjadi pemicu terjadinya Urban Heat Island (UHI). UHI adalah fenomena di mana wilayah perkotaan mengalami suhu yang lebih tinggi dibandingkan dengan wilayah sekitarnya. Faktor utama yang mempengaruhi terjadinya UHI adalah konversi lahan vegetasi menjadi area perkotaan akibat pembangunan kota. Hal ini menyebabkan peningkatan suhu permukaan karena berkurangnya kerapatan vegetasi dan peningkatan kerapatan bangunan. Perubahan tutupan lahan di dalam area penelitian dapat diidentifikasi melalui analisis klasifikasi tak terbimbing, diikuti oleh analisis Indeks Vegetasi Perbedaan Ternormalisasi (NDVI) untuk mengetahui pengaruh indeks vegetasi terhadap Suhu Permukaan Tanah (LST) dan menentukan suhu permukaan kota Bekasi. Dengan demikian, tujuan penelitian adalah untuk menganalisis Urban Heat Island di kota Bekasi dengan pendekatan kuantitatif yang menggunakan citra satelit Landsat. Hasil penelitian menunjukkan bahwa suhu kota Bekasi berkisar antara 25 hingga 31 derajat Celsius. Kata kunci: Landsat-8, Land Surface Temperatur, NDVI, Tata Guna Lahan, USGS
PENINGKATAN PENGEMBANGAN UMKM BERKELANJUTAN DI ERA DIGITAL DAN GO GREEN PASCA PANDEMI COVID-19 Herlawati Herlawati; Bayu Andriansyah; Ajie Prasetya; Handry Hartino; Ivan Nur Firdaus; Juandika Shevani; Muhammad Zidan Al Faiq; Raihan Nurfaidzi
Jurnal Pengabdian Masyarakat Information Technology Vol 2 No 1 (2023): Jurnal Pengabdian Masyarakat Information Technology - Maret 2023
Publisher : Teknik Informatika dan Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jpm_itech.v2i1.2312

Abstract

Pelaksanaan Pengabdian kepada Masyarakat (PkM) dalam bentuk Kuliah Kerja Nyata (KKN) oleh Mahasiswa serta Dosen dari Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya diadakan pada Perumahan Mustika Karangsatria RW 14 Tambun Utara Kabupaten Bekasi yang ditujukan untuk pelaku UMKM. Adapun tujuan dari pelaksanaan kegiatan ini yaitu agar pelaku UMKM yang termasuk pengurus pada RW 14 dapat: i) Memahami peranan penting digitalisasi terhadap data dari pelaku UMKM, dan ii) Memahami seberapa penting Go Green di lingkungan RW 14 setelah melewati pandemi Covid-19. Kegiatan KKN ini diharapkan dapat memberikan solusi permasalahan yang dialami oleh pelaku UMKM serta pengurus RW 14 yang termasuk ke dalam mitra kegiatan ini yaitu data pelaku UMKM di daerah tersebut belum tersusun dengan rapi, sehingga salah satunya dibuatlah sebuah aplikasi untuk menyimpan data tersebut berbasis website. Pada pelaksanaan kegiatan PKM ini, tim menerapkan pendekatan bidang edukasi (pendidikan) yang secara berkelanjutan. Metode pelaksanaan pada pelaksanaan kegiatan KKN ini yaitu a) Metode sosialisasi, b) Metode pengembangan, c) Metode penyuluhan serta d) Metode Pembelajaran. Hasil yang diperoleh dari pelaksanaan kegiatan ini berupa aplikasi yang dapat digunakan untuk proses pendataan pelaku UMKM untuk diolah serta memberikan bantuan kepada pengurus yang berada di sekitaran RW 14. Selain itu, itu diperoleh kondisi lingkungan yang hijau pada wilayah lapangan RW 14 pada sisi Go Green dengan melakukan penanaman kembali beberapa tanaman hijau
Sentiment Analysis of On-Demand Ride-Hailing Systems using Support Vector Machine and Naïve Bayes Bhagaskara Farhan Wiguna; Herlawati Herlawati; Ajif Yunizar Pratama Yusuf
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol 11 No 2 (2023): September 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i2.7384

Abstract

Gojek is one of Indonesia's most popular online transportation, founded in 2010. The Gojek application has been downloaded one hundred forty-two million times with more than two million drivers and four hundred thousand partners in food delivery services. Due to the increasing use of the Gojek application and the importance of knowing user views about the services provided by the application. In this research, the sentiment analysis is using Support Vector Machine and the Naïve Bayes method to classify positive sentiment and negative sentiment. The target label focus on positive and negative labels to aims avoid the bias that exists in neutrally labeled reviews on the Gojek Application. The research process includes data collection, pre-processing the data, weighting with Term Frequency-Invers Document Frequency, Support Vector Machine, and Naïve Bayes training by dividing the data into 90% training data and 10% testing data and then evaluating the results using a confusion matrix. The results of testing using the Support Vector Machine algorithm resulted in 90% accuracy, 94% recall, 91% precision, and 94% f1-score, therefore the Naïve Bayes algorithm produces 77% accuracy, 96% recall, 77% precision, and 85% f1-score.
SIX SIGMA STATISTIK DENGAN MINITAB DAN EXCEL Herlawati Herlawati
Paradigma Vol 10, No 1 (2008): Periode Januari 2008
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v10i1.17050

Abstract

Most companies, nowadays, are applying the six sigma approach to support the quality control of their products. The term six sigma is taken from statistic terms six and sigma. Six means number 6 and sigma means a symbol for a standard deviation. In other words, the standard deviation in use is 6s, meaning that to produce products with 0.002 per one million defect opportunity; the accepted limit of tolerance is 6 times as much as the standard deviation. The existence of noise factor theory which causes shift of mean to the right about 1.5s with 4.4 per one million defect opportunity (DPMO), initiate a number of practitioners to change the term six sigma with 3.4 DPMO, even though it is still controversial. Since most six sigma users are industries with great amount of products, which requires high level of accuracy and speed, thus the use of computer is inevitable. The most common six sigma software programs are Minitab and Excel. Nonetheless, software is only a means. IT is important to understand the essence of statistics so that not only enterprises (industry, trade, and the kind) but also service provider (education, medical, consultant, and etcetera) can apply it for quality control.
Pengoptimalan Penggunaan Smartphone Sebagai Digital Marketing Pada SMAN 14 Bekasi Prima Dina Atika; Fata Nidaul Khasanah; Herlawati; Rafika Sari; Endang Retnoningsih; Rahmadya Trias Handayanto; Tyastuti Sri Lestari
Journal Of Computer Science Contributions (JUCOSCO) Vol. 1 No. 2 (2021): Juli 2021
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jucosco.v1i2.698

Abstract

Penggunaan internet untuk aktivitas transaksi bisnis dikenal dengan istilah Electronic Commerce (E-commerce). Hal ini ditandai dengan meningkatnya jumlah pengusaha yang menggunakan e-commerce dalam perusahaannya. Digital marketing memudahkan pebisnis memantau dan menyediakan segala kebutuhan dan keinginan calon konsumen, di sisi lain calon konsumen juga bisa mencari dan mendapatkan informasi produk hanya dengan cara menjelajah dunia maya sehingga mempermudah proses pencariannya. Mitra dari kegiatan pengabdian kepada masyarakat yaitu guru SMA Negeri 14 Bekasi. Hal ini dilakukan sebagai upaya pengenalan dalam pengoptimalan penggunaan smartphone yang tidak hanya digunakan untuk sekedar menulis pesan, melakukan panggilan dan bersosial media saja, namun dapat juga dijadikan sebagai media yang mampu mendukung kegiatan usaha atau bisnis yang dimiliki oleh beberapa Guru. Pelaksanaannya materi yang dipaparkan mengenai pengantar digital marketing dan teknis penggunaan salah satu ­e-commerce Shopee. Metode pelaksanaan kegiatan ini dimulai dari penyuluhan, pelatihan dan evaluasi. Hasil dari kegiatan pelatihan menunjukkan para peserta antusias dengan adanya kegiatan ini dan menganggap materi yang dipaparkan sangat menarik dan bermanfaat.
Co-Authors A.A. Ketut Agung Cahyawan W Abd Rohman Abdu Malik AlHakim Abdul Kholis Acah Acah Achmad Noe’man Achmad Wira Wiguna Adam Adam Adam Fajariansyah Adi Muhajirin Adi Supriyatna admin admin Aera Santiana Afina Putri Dzulqiyana Agus Hidayat Agus Hidayat Ajie Prasetya Ajif Yunizar Pratama Yusuf Al Ihsan Fauzi Ardilla Andy Achmad Hendhar Setiawan Andy Achmad Hendharsetiawan Andy Achmad Hendharsetiawan Andy Achmad Hendharsetiawan Anggaini, Meri Anindita Septiarini, Anindita Anis Athifah Anisa Feby Yana Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anton Anton Ardiansyah, Muhamad Asmoro Bangun Priambodo Atika , Prima Dina Ayu Afidarisa Rahma Bangga Tua Siregar Bayu Andriansyah Ben Rahman Beno Aditya Sanusi Beno Aditya Sanusi Benrahman Bertnardo Mario Uskono Bhagaskara Farhan Wiguna Binu Nuryadi Budi Santoso Bunga Pratiwi Caroline Julyana Magdalena Christhover , Robbie Dadan Irwan Dani Dani Daniel Jhon Rosinton Hutauruk Desi Puspasari Diah Putri Ramadhani Diah Putri Ramadhani Diah Putri Ramadhani Dicki Rizki Amarullah Didik Setiyadi Dinda Mutiara Hanum Dwi Budi Santoso Dwi Budi Srisulistiowati Dzulqiyana, Afina Putri Eka Puspita Sari Eka Suryani Pratiwi Ekawati, Inna Endang Retnoningsih Erene Gernaria Sihombing, Erene Gernaria Ervan Dwi Kurniawan Fachrullyanta Adi Saputra Fachrullyanta Adi Saputra Fahrika, Andi Ika Faisal Adi Saputra Fata Nidaul Khasanah Feni Meilan Tasiba Firyal Rosiana Dita Frieyadie Galih Apriansha Pradana Gedhe Hilman Wakhid Gilby Lionska Wenas Handry Hartino Haris, Syamsul Alam Harviansyah, Muhammad Haryono Haryono Haryono Hendharsetiawan , Andy Achmad Hendharsetiawan, Andy Achmad Heri Prabowo Hero Suhartono Hero Suhartono, Hero Hutauruk , Daniel Jhon Rosinton I Komang Arya Trisumeikra Icah Fitri Yani Ikhsan Dwikurniawan Ikhsan Dwikurniawan Intan Cahya Syahfitri Intan Cahya Syahfitri Ira Wardani Irham Cahya Nugraha Irwan Raharja Ivan Nur Firdaus Izdihar, Zalfa Jaja Jaja Jaja Jaja Joko Dwi Hartanto Juandika Shevani Julaiwa, Siti Hawa Karnita Afnisari, Karnita Krisendo Setiawan Kukuh Dwi Prasetyo Kurniawan, Ervan Dwi Kustanto , Prio Ladyana Suciani Syafitri Laila Salsabilla Hanifa Lubis, Riski Aditya Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah Malikus Sumadyo Marsyanda Salsa Nabila Mayora Lolly Ishimora Media Anugerah Ayu, Media Anugerah Merza Dheo Prakoso Mirza Cahya Ningrum Mochamad Galih Pradipta Muhamad Ardiansyah Muhammad Gymnastiar Muhammad Harviansyah Muhammad Muharrom Muhammad Reinaldy Santoso Muhammad Riky Sudrajat Muhammad Zidan Al Faiq Nabila Ramadhani Sari Naufal Arif Fadilah Naufal Eka Wicaksono Nida Rachmatin Nita Merlina Nita Merlina, Nita Nitin Kumar Tripathi Nitin Kumar Tripathi Noer Hikmah Novaldi Nur Pratama Novianto, Krisna Nunung Hidayatun Nur Amanda Pratiwi Nurchayati Nurchayati Nurcholis Nurcholis Oriza Sativa Dinauni Silaen Pahrizal Pahrizal Popy Purnamasari Wahid Suyitno Pradana , Galih Apriansha Pramod Kumar Priatna , Wowon Prihatin, Sandy Satyo Prilia Hashifah Syafina Prima Dina Atika Purnomo, Rakhmat Purnomo, Rakhmat Purwanti, Santi Putra Aldi Purnama Rafika Sari RAFIKA SARI Rafly Fandiansyah Rahmadanti, Regita Ari Rahmadya Trias Handayanto Rahmadya Trias Handayanto Rahmadya Trias Handayanto rahmadya trias handayanto Rahmadya Trias Handayanto Rahmadya Trias Handayanto Raihan Nurfaidzi Raka Rismayana Rakhmat Purnomo Rakhmat Purnomo Ramadhan, Sahara Ramadhani, Diah Putri Rasim Rasim Rejeki , Sri Retno Nugroho Whidhiasih Retno Sari Riska Utami Dewi Riski Aditya Lubis Rizki Aulianita, Rizki Rizky Maulana Arrasyid Robbie Christhover Robertus Suraji Rosliana, Siti Rusdiansyah Rusdiansyah Sahara Ramadhan Salwa Nabiila Pramuhesti Samsiana , Seta Sandy Satyo Prihatin Sanusi, Beno Aditya Saputra , Faisal Adi Saputra, Fachrullyanta Adi Sari , Rafika SATRIYAS ILYAS Septi Eka Hardyana Septia, Dwi Yoga Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Setyowati Srie Gunarti, Anita Shadriyah , Shadriyah Silaen, Oriza Sativa Dinauni Siti Hawa Julaiwa Siti Masripah Siti Rosliana Siti Setiawati Sohee Minsun Kim Solikin Solikin Solikin Solikin Sri Rejeki Sri Sureni Sugeng Murdowo Sugiyatno , Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sultan Ahmad Rizki Badani Sunandar Sunandar Syadhaffa Gedriyansah Syafira Cessa Agustin Syahbaniar Rofiah Syahfitri, Intan Cahya Syamsul Alam Haris Tambun, Jerisman Jhon Wesli Tata Arya Cahyaaty Teddy Mantoro Tia Monisya Afriyanti Tumbur Togu Tyastuti Sri Lestari Tyastuti Sri Lestari Umi Salamah Umi Salamah Wida Prima Mustika Yana, Anisa Feby Yessi Rahmawati Yugo Bhekti Utomo Yusuf, Ajif Yunizar Pratama