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All Journal Excellent Jurnal Mirai Management Asia-Pacific Management and Business Application Syntax Literate: Jurnal Ilmiah Indonesia Scientific Journal of Reflection : Economic, Accounting, Management and Business JURNAL PENDIDIKAN TAMBUSAI Jurnal Manajemen Strategi dan Aplikasi Bisnis Aptisi Transactions on Management Jurnal Menara Ekonomi : Penelitian dan Kajian Ilmiah Bidang Ekonomi EKONOMI BISNIS Jurnal Sains dan Teknologi JATI (Jurnal Mahasiswa Teknik Informatika) Emerging Markets : Business and Management Studies Journal Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal MSDA (Manajemen Sumber Daya Aparatur) JOURNAL OF BUSINESS AND ECONOMICS RESEARCH (JBE) BUDGETING : Journal of Business, Management and Accounting Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) Journal of Advanced Multidisciplinary Research Journal of Economics and Business UBS AKSELERASI: Jurnal Ilmiah Nasional CENDEKIA : Jurnal Ilmu Pengetahuan Jurnal Ekonomi Bisnis, Manajemen dan Akuntansi (JEBMA) International Journal of Applied Finance and Business Studies Co-Value : Jurnal Ekonomi, Koperasi & Kewirausahaan AKADEMIK: Jurnal Mahasiswa Ekonomi & Bisnis AKADEMIK: Jurnal Mahasiswa Humanis Jurnal Locus Penelitian dan Pengabdian KNOWLEDGE: Jurnal Inovasi Hasil Penelitian dan Pengembangan Jurnal Ekonomika Dan Bisnis Economic Reviews Journal Asean International Journal of Business JRAP (Jurnal Riset Akuntansi dan Perpajakan) Jurnal Ekonomika Manajemen Dan Bisnis Jurnal Indonesia Sosial Sains Jurnal Pendidikan Indonesia (Japendi) Cerdika: Jurnal Ilmiah Indonesia Indonesia Accounting Research Journal Indonesian Research Journal on Education Innovative: Journal Of Social Science Research Indo-Fintech Intellectuals: Journal of Economics and Business Business and Investment Review Jurnal Informatika Ekonomi Bisnis Al-Tasyree: Jurnal Bisnis, Keuangan dan Ekonomi Syariah IIJSE Jurnal Sistem Informasi dan Manajemen Jurnal Akuntansi Sektor Publik Jurnal Media Akademik (JMA) Sainteks: Jurnal Sain dan Teknik Jurnal Multidisiplin Indonesia Adpebi International Journal of Multidisciplinary Sciences International Journal of Indonesian Business Review International Journal of Management and Business Applied Agrinus: Jurnal Agro Marin Nusantara Jurnal Cendekia Ilmiah
Heikal, Jerry
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Analyzing the Use of Klik XYZ Application by Members of Koperasi XYZ with the Binary Logistic Regression Method Syarah, Irra Siti; Heikal, Jerry
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research (Special Issue)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.15677

Abstract

Advances in technology and the internet allow users to conduct transactions through mobile applications, including bill payments and product purchases. Koperasi XYZ has developed the Klik XYZ application to improve the efficiency and convenience of its members in shopping. This study aims to analyze the factors that influence the use of Klik XYZ application by cooperative members using binary logistic regression method. The variables analyzed include age, gender, frequency of access, and customer satisfaction. The analysis results show that age, gender, and customer satisfaction have a significant influence on purchasing decisions. The binary logistic regression model built has an overall accuracy rate of 89.3%, with a prediction accuracy of 90.7% for purchase behavior and 87.6% for non-purchase behavior. The findings can be used by XYZ to develop more effective marketing strategies by targeting members based on their age, gender, and satisfaction level. In addition, improving service quality and user experience can increase customer satisfaction, which in turn can increase purchase rates. By implementing the right marketing strategy, it is expected to improve XYZ's sales performance in the future and assist the cooperative in providing optimal service to its members.
Application of Binary Logistic Regression Method Using Python to Analyze the Effect of Ease of Use, Administrative Costs and Preferences on the Probability of Student Decisions Choosing Payment Channels for Course Registration Using Bank Mandiri Suryani, Rahmah; Praditya, Rizqy Gumilar; Sembodo, Giry; Heikal, Jerry
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research (Special Issue)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.15679

Abstract

This study analyzes the factors that influence Open University students' decision to choose Bank Mandiri payment channel for course registration. Using binary logistic regression method with Python, this study explores the influence of ease of use, administrative costs, and student preference on the probability of choosing Bank Mandiri. Data from 200 students were analyzed using variables such as age, gender, ease of use of mobile banking application, transaction fees, and student preference. Model evaluation using confusion matrix and ROC curve showed good performance with Area Under the Curve (AUC) 0.84. This study revealed that factors such as ease of use and transaction fees strongly influence students' decisions in choosing payment channels. The results show that the model has 78% accuracy with three significant variables with values below 5%: ease of use, transaction costs, and student preferences. Evaluation using ROC curves showed good model performance with an AUC of 0.84. This research aims to improve UT and Bank Mandiri payment services and provide insight into the adoption of financial technology in the education sector.
Customer Renewal Prediction for Motor Vehicle Insurance Using Binary Logistic Regression in PT XYZ Insurance Hendrawan, Erwan; Zakaria, Dzaki; Salwa, Elja; Heikal, Jerry
Innovative: Journal Of Social Science Research Vol. 4 No. 6 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i6.16478

Abstract

Asuransi kendaraan bermotor merupakan salah satu produk asuransi yang banyak diminati oleh masyarakat. Namun, mempertahankan pelanggan untuk terus memperpanjang polis asuransi mereka merupakan tantangan yang signifikan bagi perusahaan asuransi. Penelitian ini bertujuan untuk melihat prediksi pembelian berulang (second purchase/renewal) poduk asuransi kendaraan di PT XYZ Insurance serta mengidentifikasi dan menganalisis faktor-faktor yang mempengaruhi keputusan perpanjangan polis asuransi kendaraan bermotor dengan menggunakan model regresi logistik biner. Model ini dipilih karena kemampuannya dalam memprediksi probabilitas terjadinya suatu peristiwa berdasarkan variabel independen yang ada. Variabel-variabel independen yang diteliti dalam penelitian ini meliputi usia nasabah, jenis produk, premi, pembayaran dan tenor polis. Hasil analisis menunjukkan bahwa model regresi binari logistik ini mampu mengidentifikasi variabel independen yang signifikan berpengaruh terhadap keputusan pembelian berulang produk asuransi kendaraan. Secara khusus, usia nasabah memiliki pengaruh signifikan dengan koefisien 0.19, sementara tenor memiliki pengaruh yang sangat signifikan dengan p-value <0.01. Dari seluruh data nasabah yang dianalisis, model ini memprediksi bahwa 15% nasabah akan melakukan pembelian berulang (renewal) terhadap produk asuransi kendaraan. Di sisi lain, diprediksi bahwa 75% nasabah tidak akan melakukan pembelian berulang. Hasil ini menunjukkan bahwa variabel usia dan tenor memiliki peran penting dalam menentukan keputusan pembelian berulang nasabah asuransi kendaraan. Temuan ini dapat memberikan implikasi praktis bagi perusahaan asuransi dalam merancang strategi pemasaran dan retensi pelanggan yang lebih efektif, dengan fokus pada segmen usia tertentu dan pengelolaan tenor asuransi yang lebih optimal. Penelitian lebih lanjut disarankan untuk mengeksplorasi variabel lain yang mungkin berpengaruh dan menggunakan metode analisis yang berbeda untuk memperkuat prediksi perpanjangan pelanggan asuransi kendaraan bermotor.
FACTORS OF USING CASHLESS TRANSACTIONS IN RETAIL BUSINESS USING GROUNDED THEORY Givianty, Vasya Theodora; Kurinawan, Haby; Julian, Ahmad; Heikal, Jerry
AKSELERASI: Jurnal Ilmiah Nasional Vol 6 No 1 (2024): AKSELERASI: JURNAL ILMIAH NASIONAL
Publisher : GoAcademica Research dan Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54783/jin.v6i1.909

Abstract

Today's technological developments have been able to influence almost all business sectors so that business actors inevitably have to be able to keep up with these technological developments if they want to survive in the business world. One sector that is very dynamic following these developments is the banking sector. Developments in this sector have a domino effect on other sectors because banking acts like a bridge between business actors. The product results from this sector which can be said to be one of the factors changing consumer behavior is e-banking which encourages the creation of cashless (non-cash) transactions. Apart from that, the increasing type and number of smartphones has contributed to the growth of transactions via e-banking. This research uses qualitative techniques with a grounded theory approach. The author conducted direct interviews with several business actors in the retail sector to determine the influence of e-banking in increasing transactions. Based on the research results, it was found that the coding scheme consisted of 17 codes which formed 7 categories and gave rise to 3 themes with a total frequencies of 25. The highest frequency in coding was 12 on the theme of ease of transactions and 10 on the theme of security so that the factors that influence the use of cashless e-banking are making it easier. buying and selling transactions of business actors in the retail sector and reducing the risk of fraud during transactions compared to increasing transaction volume.
Decision-Making Techniques using LSTM on Antam Mining Shares before and during the COVID-19 Pandemic in Indonesia Badri, Ahmad Kamal; Heikal, Jerry; Nurjaman, Deden Roni; Terah, Yochebed Anggraini
APTISI Transactions on Management (ATM) Vol 6 No 2 (2022): ATM (APTISI Transactions on Management: July)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v6i2.1776

Abstract

Stocks, apart from having volatile and chaotic characteristics, also have various kinds of noise, non-linear and non-stationary movements, making them difficult to predict accurately. Therefore, the risk of investing in stocks depends on the skills of investors or traders in making judgments and decisions. This study aims to use Long Short-Term Memory (LSTM) as a decision-making technique with historical stock prices as the sole predictor, then implement it in conditions before and during the COVID-19 pandemic. The study results concluded that Long Short-Term Memory (LSTM) could be used as a decision-making technique in conditions before and during the COVID-19 pandemic with historical price inputs as the sole predictor. Based on the research that has been done, the following conclusions can be drawn: The LSTM model can predict stock prices well using historical stock prices as the sole predictor. The LSTM model can be used as a trading decision-making technique for day traders. The risk of stock prediction using the LSTM method in 2019 before the COVID pandemic was proven to be lower than in 2020 during the COVID pandemic. For further research, researchers can conduct more in-depth research on the risk criteria for making trading decisions as an essential reference that can be used to select the LSTM model.
Application Of Artificial Intelligence (Ai) In Television Industry Management Strategy Using Grounded Theory Analysis: A Case Study On Tvone Ridwan, Dadang; Heikal, Jerry
Jurnal Pendidikan Indonesia Vol. 4 No. 9 (2023): Jurnal Pendidikan Indonesia (Japendi)
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v4i9.2196

Abstract

The television industry has undergone many changes over time, especially with ever-increasing technological advances. One technology that has had a significant impact on this industry is artificial intelligence (AI). The purpose of this research is to understand the application of artificial intelligence (AI) in the television industry management strategy with a case study on tvOne. This study utilised qualitative methods to understand and describe the situation that takes place in the research environment. The sample in this study were five respondents from tvOne’s top management. The analysis began with the coding stage of the data derived from the results of the interviews which had been transcribed into text using a grounded theory approach. The conclusion of this study is that the opportunity provided by AI for the television industry is content production. Opportunities for implementing AI technology at tvOne, through the integration of AI in content production, are directed at increasing the efficiency and quality of program production by utilising more sophisticated data analysis and automation. Then, the challenges faced in implementing AI in the television industry are resources. The challenge of implementing AI technology at tvOne is in terms of human resources and physical resources needed, which include the necessary technical expertise and the availability of adequate financial resources and infrastructure.
SEGMENTASI PELANGGAN MENGGUNAKAN K-MEANS CLUSTERING STUDI KASUS PELANGGAN UHT MILK GREENFIELD Ariati, Ira; Norsa, Reza Nugraha; Akhsan, Lurinjani; Heikal, Jerry
Cerdika: Jurnal Ilmiah Indonesia Vol. 3 No. 7 (2023): Cerdika : Jurnal Ilmiah Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/cerdika.v3i7.639

Abstract

Penelitian ini bertujuan untuk melakukan segmentasi pelanggan menggunakan metode K-Means Clustering dalam kasus pelanggan susu UHT Greenfield. Segmentasi pelanggan penting untuk memahami preferensi, kebutuhan, dan karakteristik pelanggan yang berbeda, sehingga perusahaan dapat mengarahkan upaya pemasaran dengan lebih efektif. Metode K-Means Clustering digunakan untuk mengelompokkan pelanggan berdasarkan atribut tertentu, seperti preferensi rasa, alamat pengiriman, dan depot penjualan. Data pelanggan Greenfield UHT Milk dikumpulkan, termasuk variabel seperti frekuensi pembelian, volume pembelian, dan preferensi rasa. Data penelitian dianalisis menggunakan analisis K-Means Clustering. Hasil penelitian dikategorikan menjadi 3 klaster, yaitu: 1. Klaster Premium : Pengiriman terbanyak ke Pamengkasan, produk terbanyak yang dibeli adalah Greenfield UHT full cream 250 ml, Meskipun kuantitas pembelian tidak terlalu tinggi, mereka menghasilkan penjualan yang signifikan, karena mereka menyukai kemasan minuman tunggal yang lebih besar yaitu 250 ml2. Cluster Sedang: Pengiriman terbanyak ke Jembrana, produk yang paling banyak dibeli adalah Greenfield UHT full cream 125 ml, Jumlah penjualan yang sedikit, produk yang dibeli dengan ukuran terkecil, membuat cluster ini memberikan penjualan terkecil di antara cluster lainnya dan mereka fokus pada harga dalam pembelian mereka3. Cluster Curah Pengiriman terbanyak ke Jember, Produk yang banyak dibeli adalah Greenfield UHT full cream 250 ml, Intensitas pembelian mereka kecil tetapi jumlah pembelian mereka sangat besar sehingga menghasilkan nilai jual yang signifikan.
THE CHANGES IN FINANCIAL PERFORMANCE SEGMENTATION USING FINANCIAL RATIOS PHARMACEUTICAL COMPANIES IN INDONESIA Soviatun, Nuria; Heikal, Jerry
Cerdika: Jurnal Ilmiah Indonesia Vol. 3 No. 08 (2023): Cerdika : Jurnal Ilmiah Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/cerdika.v3i08.688

Abstract

The purpose of this study is to analyze the financial condition of pharmaceutical companies in Indonesia listed on the IDX. This study measures the ratios, namely net profit margin, debt to equity ratio, and return on equity based on financial reports as of June 2022 and June 2023. Data processing in this study used IBM SPSS software with K-means clustering analysis.From the clustering results, there were 5 clusters with 5 personas, namely Very Good (A), Good (B), Fair (C), Bad (D), and Very Bad. Persona grouping based on the ratio of NPM, ROE, and DER. There has been a change in financial performance segmentation from 2022 to 2023, where most of the pharmaceutical companies in Indonesia have experienced a decline in performance in 2023.From the results of the comparison above, it can be concluded that PT Pyridam Farma Tbk shows the most significant change in financial performance segmentation, from poor performance (D) in 2022 to very good (A) performance in 2023. Meanwhile, the financial performance of PT Indofarma Tbk from 2022 and 2023 has not experienced a change in segmentation, remains in a very bad position (E). The authors conclude that PT Pyridam Farma Tbk has the potential to become a company that will acquire PT Indofarma Tbk.
Financial Performance Segmentation Changes on Indonesian Insurance Companies Tonggo, Andohar; Rachman Zarkasih, Aditya; Heikal, Jerry
Economic Reviews Journal Vol. 3 No. 4 (2024): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v3i4.398

Abstract

Company acquisition is one of the strategies for developing and maintaining the company's survival, especially if unforeseen situations occur that are detrimental to a company, for example in the insurance industry during the Covid-19 pandemic. The purpose of this study is to determine changes in the performance of financial ratios of insurance companies from 2021 to 2022 which can be used as consideration for making acquisitions. The method used is quantitative using k-mean clustering in SPSS software and ranking is made based on DER, ROE, NPM and RBC analysis. Based on the data above, it can be seen that there are companies that have changed from 2021 to 2022. There are 7 companies that have experienced an increase in status, 5 companies that have experienced a decline and 5 companies that have not experienced a change. The most recommended company for acquisition is Lippo General Insurance Tbk and the recommended company for acquisition is Panin Financial Tbk and dan Panininvest Tbk.
PENERAPAN METODE REGRESI LOGISTIK BINER DENGAN MENGGUNAKAN PHYTON UNTUK MENGANALISA PENGGUNA MEDIA SOSIAL TERHADAP PROBABILITAS PEMBUKAAN REKENING PADA BANK X Riyani, Sari; Kristianto, Fajar; Wulandari, Rayuli; Heikal, Jerry
SCIENTIFIC JOURNAL OF REFLECTION : Economic, Accounting, Management and Business Vol. 7 No. 2 (2024): SCIENTIFIC JOURNAL OF REFLECTION: Economic, Accounting, Management, & Business
Publisher : Sekolah Menengah Kejuruan (SMK) Pustek

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37481/sjr.v7i2.840

Abstract

In the rapidly developing digital era, financial institutions, such as Bank X, can utilize social media to understand consumer behavior and expand their customer base. This research uses a binary logistic regression method with social media user data to analyze the relationship between online activity and the decision to open an account at the bank X. The aim of this research is to assess the influence of user activity on social media platforms (Instagram, TikTok, Facebook, Twitter and YouTube) on the decision to open an account at the Bank X as well as analyze and identify key variables that influence the decision to open an account, based on media activity data. social. Results show that Instagram has a significant influence, with the combination of social media platforms increasing the probability of opening an account. TikTok and Facebook also have a positive impact, while Twitter and YouTube have a lower impact. Recommended marketing strategy to focus more on Instagram, with an emphasis on a combination of other social media platforms. From the results of the scenario interpretation, Instagram has a significant positive influence on the decision to open an account, with the highest probability among other individual platforms. TikTok, Facebook, and Twitter also have a positive impact, although their probabilities tend to be similar. Meanwhile, YouTube's influence on the decision to open an account seems to be lower than other social media platforms.
Co-Authors Agus Siswanto Akhsan, Lurinjani Alam, Taris Zakira Aldyah, Tika Alghifari Suhardi, Fitra Ali Wafa Amelia, Dona Andi Saputro Anjarsari, Rosita Anne, Lisye Ira Apriani, Asti Arda, Edvidel Ardanesworo, Muhammad Feyzel Khalfani Putra Ardiansyah, Giri Teguh Ardianto, Andi Ariati, Ira Arrafi, Risa Eka Arthanugraha, Adam Awalludin Awalludin, Awalludin Ayu Pradina, Dinda Ayu Wulandari Ayu, Cita Azkia, Nayla Azwar , Tasrika Azwar, Meiriza Azwar, Tasrika Azzuhri, Muhammad Basyar Badri, Ahmad Kamal Budi Setiawan Chairani, Metha Erzha Chandra, Jimmy Chandra, Jon Hendra Saputra Chitra, Jimmi Chow, Sayuti Darma Tenaya, I Putu Risky Daswirman, Daswirman Daulay, Risma Yanti Dawam, Khaerud Deden Nurjaman Desmalina, Desmalina Deswita, Riyan Yulmi Devi, Rizky Feliana Diah Utami, Diah Dilla Sistesya Doni Magat Harahap Dwi Ramadona, Dasatry Dwirahmawati, Retno Dzulqornain, Muhammad Edison, Alva Elfira, Renti Enny Enny Enny Widawati Erwan Erwan, Erwan Esvandiary Iswari, Neisya Fadhilah, Savira Maghfiratul Fadilla, Triana Gustiani Faisal Faisal Fajarini, Nurfahma Fauzan, Heri Fazarullah , Dwirizky Finnia Ayu Kirana, Astried Fitria, Yossa Gelvi, Gelvi Givianty, Vasya Theodora Gunawan, William Ben Gusmeri, Gusmeri Hanifeliza, Rury Hardiyanti Hardiyanti Hariandja, E N Budiyanto Harsemarozi, Harsemarozi Hartanti, Sandra Dewi Hasahatan, Alex Fernando Hendrawan, Erwan Herdiany, Gita Amira Hindrawan, Dimas Humaira, Putri Syifa Hutabarat, Berman Hutabarat, Berman J Jaya, Hamka Putra Julian, Ahmad Kamaratih F, Yositalida Kettipusem, Sri Polya Kevry Ramdany kharisma, Gilang Kornela, Andhini Kristianto, Fajar Kurinawan, Haby Kurniawati, Yuni Kusumaningrum, Indah Liestiani, Annisa Mafatir Romadhon, Damar Maharani, Sella Sakilla Mangkuto, Shidiq Umar Mardiyanto, Joko Marlina Marlina Moh. Masnur Muhammad Farhan Muhammad Ikhsan Muhammad, Tegar Mulyo, Iksan Adityo Mulyono, Rynto Muzakkar, Milastri Nazmi, Fittria Ningsih, Andria Nisa, Khairi Norsa, Reza Nugraha Nugrahmi, Lidya Nugroho, Septiadi Nugroho, Yusuf Wahyu Nur Aulia, Reza Nurlia, Siti Adinda Nurrela, Nisa Nurseha, Muhammad Ikhsan Nurviriana, Savira Octavianson, Dave Nathanael Oki, Helzulmita Oktarini, Dwi Indah Olivia Olivia Osthar, Fidy Rachman Pamadia, Era Pambudi, Adhy Priyo Pangestuti, Intan Passalaras, Raja Aulia Payoka, Netty Perdana, Gemilang Adi Perdhana, Rizkita Bagus Permadiyansach, Bambang Prabowo, Heru Pradina, Dinda Ayu Praditya , Rizqy Gumilar Praditya, Rizqy Gumilar Pramono Hadi Prasasti, Ferdania Pratama, Renaldo Pratiwi Pratiwi Purwanto, Muhammad Rizki Puspita Dewi, Puspita Puspita, Angela Candra Puteri, Cita Ayu Riyadi Putra Jaya, Hamka Putra, Abhiyoga Deyandra Putra, Rahmad Yunendri Putri, Annisa Nurwanda Putri, Juandela Herina Putri, Maya Seruni Rachman Zarkasih, Aditya Rachmawatie, Srie Juli Rafanio, Kevin Raharjo, Bangkit Widhi Rahmadeni Rahmadeni Rahmawati, Nurmalinda Rahmi, Mutia Ramadhan, Andi Ramadhan, Andika Ramadhan, Yufiansyah Wahyu Reynaldi, Jaka Rica Rica, Rica Ridwan, Dadang Riyani, Sari Safangati, Ainun Safira, Alika Salim, Susan Ratna Salwa, Elja Samsul Arifin Samudra Wicaksono, Muhammad Haston Sani, Fitroh Baherudin Santosa, Suhari Saputra, Tubagus Chandra Saraswati, Iska Sari, Irma Ratna Sari, Nimas Indah Fatimah Saumananda Suroso, Nurinda Savitri, Fania Mutiara Sayuti Sayuti Sekar Ndini, Ayu Sembodo, Giri Sembodo, Giry Shabrina, Andi sirya, Damara Siswanto, Fajar Hartanto Sitinjak, Jeklin Soviatun, Nuria Sri Mulyaningsih Sri Nugroho, Amanda Sri Utami Sugino, Agus Suhardi, Fitra Alghifari Sukmayanti, Andini Wulan Suryani, Rahmah Suududdin, Suududdin Syafer, Erdimen Syam, Syahrul Syarah, Irra Siti Syarifudin Syarifudin Syarrah, Ira Siti Syawaldi Afwan, Ahmad Syawaludin, Rahmat Taufiqillah, Rizal Teguh Widodo Terah, Yochebed Anggraini Threezardi, Ricki Tonggo, Andohar Triesna Ratulina Tuwindar, Tuwindar Wahyuningsih, Nia Watugilang, Ageng Wicaksono, Muhammad Haston Samudra Widya Handayani Wulan, Mutia Karunia Antap Wulandari, Rayuli Yakub, Isnendi Yohana, Kesia Yudi Nugraha Bahar Zakaria, Dzaki Zulfahmi, Muhammad Riko Yohansyah