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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 Riset Akuntansi Aksioma Jurnal Menara Ekonomi : Penelitian dan Kajian Ilmiah Bidang Ekonomi Dinasti International Journal of Education Management and Social Science 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 Jurnal Fokus Manajemen Bisnis 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 Eduvest - Journal of Universal Studies Applied Quantitative Analysis (AQA) Innovative: Journal Of Social Science Research Indo-Fintech Intellectuals: Journal of Economics and Business Business and Investment Review Jurnal Informatika Ekonomi Bisnis Enrichment: Journal of Multidisciplinary Research and Development 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 Journal of Innovative and Creativity 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 J-CEKI
Heikal, Jerry
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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.
Customer Segmentation Based on Rfm Analysis as The Basis of Marketing Strategy Case Study of Crude Palm Oil Product in Palm Oil Industry Syahfitri, Fenny; Heikal, Jerry
Enrichment: Journal of Multidisciplinary Research and Development Vol. 2 No. 8 (2024): ENRICHMENT: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v2i8.186

Abstract

Nowadays so many palm oil companies sell the product to potential buyer to maximize their revenue, so they need to understand the customer's data better in all aspects. Segmenting the customers according to their data became extrem important in this context. This study aims to explore customer segmentation using RFM (Recency, Frequency, and Monetary) analysis as a basis for developing an effective marketing strategy for Crude Palm Oil (CPO) products in the palm oil industry. In this paper, i used data of crude palm oil sales database that obtained from digital platform named Customer Relationship Management (CRM) System and Auction by E-commerce involving 56 buyers by 2.499 transactions. After the scoring and data processing, the number of customers for each RFM Score is obtained, then the Monetary group is segmented which is divided into 27 Labels and grouping to 11 (eleven) Labels of Buyer’s Company, Engaged (8), Loyal (9), Potential (9), Affair (14), Broke Up (3), No Hurt Feeling (1), Disappointed (2), Agony (1), Broken Heart (3), Hurt Feeling (3) and Lost Feeling (3). By using RFM analysis, it can effectively creating a marketing strategy to increase the status of potential customer to the loyal customer to increase the corporate’s revenue and to improve corporate’s value added.
Analysis Of Student’s Participation in Extracurricular Class at Sekolah Citamulia Using RFM Model Firdaus, Aulia; Heikal, Jerry
Enrichment: Journal of Multidisciplinary Research and Development Vol. 2 No. 8 (2024): ENRICHMENT: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v2i8.187

Abstract

The cognitive development of children, as well as the academic performance of students, can be influenced by various factors. One of these factors is students' active involvement in extracurricular activities outside the classroom. These activities are supplementary programs designed to facilitate students' interests and talents in specific fields. It is crucial to maintain a high level of student participation because active participation significantly impacts cognitive and academic improvement. The objective of this study is to assess the level of active student participation by categorizing students based on their engagement using the RFM (Recency, Frequency, Monetary) method. The second objective is that, once the student engagement mapping is established, it will allow for targeted programs and policies tailored to each group, thereby enhancing overall student participation in extracurricular activities. In this RFM method, recency represents the date of the student’s most recent attendance at an activity. Frequency represents the total number of student attendances, and monetary represents the total nominal amount spent. The data was collected from January to September 2024, involving 250 students participating in extracurricular activities. Generally, the RFM output reveals student segmentation based on activity can be categorized into seven groups, which are Ashamed, Nice Tried, Bored, Initiative, Committed, Excited, and Passionate. Based on these results, several policies can be formulated according to the conditions of each student.
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.
Segmentation of Students Using K-Means Clustering Case Study of Sekolah Dasar Tahfizh Quran (SDTQ) Citamulia Firdaus, Aulia; Heikal, Jerry
Jurnal Pendidikan Indonesia Vol. 5 No. 11 (2024): Jurnal Pendidikan Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v5i11.5922

Abstract

This study aims to determine consumer segmentation using K-Means Clustering in the case of SDTQ Cita Mulia elementary school students. The results of the study can be useful for preparing marketing strategies and sharpening the school's competitive advantages. The process consists of grouping consumer data based on several variables, which are student’s gender, distance from home to school, age of student parents, parents' occupation and income, parents' education and the curriculum used by the previous school. After grouping the data, the initialization stage is carried out by giving an initial number. Then the clustering process is carried out. The resulting cluster will be analyzed to see the current Student profile. By studying the clusters formed, it helps us to determine school development policies, especially how marketing strategies can attract consumers in the middle cluster, namely those who have not joined us much but have the potential to be interested in our products. The result of the process there are four clusters with each cluster has specific persona name as follows: The first Cluster is the reachable distance with 5-6 km distance from the school, the second cluster in The long distance with 6 up to 28 Km distance from the school, the third cluster is the neighbor with just 3-4 km from school, and the forth cluster is the have this cluster persona has the highest parents income with the distance from school is 5-6 Km. The largest distribution of members is cluster 3 followed by cluster 4. Meanwhile, cluster 1 is not too big yet but still looks potential, and the lowest is cluster 2, so from this data the target persona is in cluster 3, the Neighbor persona.
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.
MERGERS AND ACQUISITIONS VALUATION FOR THE ACQUISITION OF PT LIPPO KARAWACI TBK BY PT BUMI SERPONG DAMAI TBK Wuryantadi, Dwi; Heikal, Jerry
Cerdika: Jurnal Ilmiah Indonesia Vol. 3 No. 10 (2023): Cerdika : Jurnal Ilmiah Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/cerdika.v3i10.691

Abstract

The purpose of this study is to determine mergers and acquisitions valuation for the acquisition One of the strategic objectives aimed at enhancing performance is product diversification. By acquiring PT Lipo Karawaci Tbk (LPKR), PT Bumi Serpong Damai Tbk (BSDE) aspires to expand its product portfolio by incorporating the existing offerings of LPKR. The method use quantitative methodology, characterized by the collection of numerical data and subsequent analysis by statistical tools. The primary objective of this study is to quantitatively quantify and provide an objective analysis of various eventsThe successful execution of this corporate activity necessitates meticulous calculation to effectively enhance the performance of the purchasing company, hence accomplishing its primary objective. One of the research objectives is to ascertain the valuation of PT Lippo Karawaci Tbk (LPKR) as a firm. The free cash flow method, often known as FCFF, is a viable approach for conducting assessments within the context of corporations. The aforementioned are financial concepts and measures employed for the purpose of quantifying the quantity of cash created by a corporate entity. In order to ascertain the post-acquisition predictions of the company for the subsequent five-year period (2023-2027), an analysis of the financial report data of both entities from 2020 to 2027 is required.
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 Arum Kusuma, Tiyanda Hanti 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 Dwiputri, Rinta Agustiani Dwirahmawati, Retno Dzulqornain, Muhammad Edison, Alva Elfira, Renti Enny Enny Enny Widawati Erwan Erwan, Erwan Esvandiary Iswari, Neisya Fachry Abda El Rahman Fadhilah, Savira Maghfiratul Fadilla, Triana Gustiani Faisal Faisal Fajarini, Nurfahma Fauzan, Heri Fazarullah , Dwirizky Ferli, Isfan Finnia Ayu Kirana, Astried Firdaus, Aulia Fitria, Yossa Gandhi, Ayu Gelvi, Gelvi Givianty, Vasya Theodora Gunawan, William Ben Gusmeri, Gusmeri Hanifeliza, Rury Hardiyanti Hardiyanti Hariandja, E N Budiyanto Harsemarozi, Harsemarozi Hasahatan, Alex Fernando Hasibuan, Muhammad Satir Hendrawan, Erwan Herdiany, Gita Amira Heswara, Faisal 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 Mamonto, Fanjili Gratia Mangkuto, Shidiq Umar 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 Nurviriana, Savira Octavianson, Dave Nathanael Oki, Helzulmita Oktariani, Gulfi Oktarini, Dwi Indah Olivia Olivia Osthar, Fidy Rachman Pamadia, Era Pambudi, Adhy Priyo Pangestuti, Intan Panka Gumilang 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 Ramadani, Rizki Agung Ramadhan, Andi Ramadhan, Andika Ramadhan, Yufiansyah Wahyu Reynaldi, Jaka Rica Rica, Rica Ridwan, Dadang Riyani, Sari Safangati, Ainun 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 Sodikin Sodikin Soviatun, Nuria Sri Mulyaningsih Sri Nugroho, Amanda Sri Utami Sugino, Agus Suhardi, Fitra Alghifari Sukmayanti, Andini Wulan Suryani, Rahmah Sutama, Aditya Suududdin, Suududdin Syafer, Erdimen Syahfitri, Fenny 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 Widiyanta, Antonius Hendri Widya Handayani Wulan, Mutia Karunia Antap Wulandari, Rayuli Wuryantadi, Dwi Yakub, Isnendi Yohana, Kesia Yudi Nugraha Bahar Yumarsa, Imam YUNI KURNIAWATI Zakaria, Dzaki Zulfahmi, Muhammad Riko Yohansyah