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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 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 Sosial dan Teknologi 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 Journal Research of Social Science, Economics, and Management 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 Jurnal Multidisiplin Indonesia Adpebi International Journal of Multidisciplinary Sciences International Journal of Indonesian Business Review International Journal of Management and Business Applied Jurnal Abdimas Peradaban Agrinus: Jurnal Agro Marin Nusantara Jurnal Cendekia Ilmiah
Heikal, Jerry
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Analisis Pengaruh Karakteristik Produk terhadap Niat Beli Ulang Pelanggan menggunakan Metode Regresi Logistik Biner Faisal, Faisal; Sari, Irma Ratna; Saraswati, Iska; Heikal, Jerry
AKADEMIK: Jurnal Mahasiswa Humanis Vol. 4 No. 3 (2024): AKADEMIK: Jurnal Mahasiswa Humanis
Publisher : Perhimpunan Sarjana Ekonomi dan Bisnis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37481/jmh.v4i3.1064

Abstract

The internet and television have become an inseparable part of the daily life of modern society. The function of the internet covers various aspects, from communication, entertainment, education, to work. On the other hand, television remains a medium of entertainment and information for many people. This study aims to identify dependent variables and determine the accuracy of the model used by data processing using the SPSS program to find out whether customers will make a repeat purchase or not. Based on the above reasons, the analysis will be conducted to assess the influence of product characteristics on the customer's desire to repurchase the add-on or upgrade the product currently in use, in an internet and TV service company and to identify and analyze the product characteristics that most significantly affect the customer's decision to purchase the same product again in the future. The method used is binary logistic regression. The results of the study showed a significant influence between the independent variable (X) internet speed used, the type of product used, and the type of network used on the dependent variable (Y) of the decision to rebuy (add on). For the results of the binary logistic regression classification table, it is known that the results of prediction and observation are 325 customers who do not Rebuy (add on), while those who are predicted and observed do Rebuy (add on) as many as 293 customers. The remaining 214 and 168 customers produced differences between prediction and observation, so that the percentage accuracy of the regression model in this study was obtained of 61.8%. Based on the results of binary regression analysis, we found that internet speed is a very influential factor for customers in purchasing additional products. Creating variations of additional products for internet speed upgrades is crucial and should be better considered by the product team. The right variations of speed upgrades are a solution to increasing the sales of additional products.
Grounded Theory Analysis on IT Consultant Company Survival Strategy in The Vuca Era Fauzan, Heri; Heikal, Jerry
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 7 No 2 (2024): Sharia Economics
Publisher : Sharia Economics Department Universitas KH. Abdul Chalim, Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v7i2.4784

Abstract

This research was focused on how IT Consulting Companies can survive during the VUCA era (within scope 2020-2023). This research revealed the challenges during the VUCA Era and strategies to tackle the challenges. This research was conducted using grounded theory analysis, interviewing process, and gap analysis with the current theories. All methods are compiled together as a qualitative research approach. In this research, purposeful sampling was used to choose relevant respondents with minimum classification as a director level in an IT Consulting Company who knew about the company strategy and business environment during the in-scoped period. The coding process was done twice, the first coding process to map the challenges in the VUCA era and the second one to find out the strategy for VUCA challenges in the first coding results. The coding process gathered 23 codes for challenges in VUCA which were categorized into 9 categories and then became 5 themes. The result concludes that the top challenge in the VUCA era is customer engagement. The second coding process found the 23 strategies from all interviews and categorized them into 5 categories and then 4 themes. It concludes that the top priority strategy to survive during VUCA is a customer-driven approach strategy with many variations.
Enhancing Customer Segmentation in Online Transportation Services: A Comprehensive Approach Using K-Means Clustering and RFM Model Perdhana, Rizkita Bagus; Heikal, Jerry
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 7 No 2 (2024): Sharia Economics
Publisher : Sharia Economics Department Universitas KH. Abdul Chalim, Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v7i2.4851

Abstract

In the rapidly evolving landscape of online transportation services, companies face complex challenges to maintain and expand their market positions. Understanding customer dynamics has become crucial for success, extending beyond mere acquisition to encompass retention. This study presents a comprehensive approach to customer segmentation in online transportation services using K-Means Clustering and the RFM Model. K-Means Clustering categorizes customers based on behavioral patterns, while the RFM Model provides a detailed insight into customer engagement in acquisition activities. The integration of these methodologies aims to enable companies to tailor services, enhance customer experiences, and formulate targeted marketing strategies. The analysis identifies 5 diverse customer groups: (1) Urban Luxury Commuters, (2) Non-Motorized Urban Users, (3) Tech-Savvy Urban Commuters, (4) Diverse Urban Commuters, and (5) Budget-Conscious Urban Commuters. Among these groups, the (2) Non-Motorized Urban Users group is the focus due to its high monetary value and the second-highest frequency level. Users in this cluster tend to transact frequently, indicating consistent and recent engagement with transportation services. Factors such as high transaction frequency and total transaction value underscore the importance of this cluster in generating overall revenue. Additionally, the research will consider additional factors such as user demographics, travel purposes, and promotional activities to further understand user behavior patterns in this cluster. The goal is to formulate targeted strategies to enhance user satisfaction, engagement, and potential revenue growth for transportation service providers. This study also introduces an RFM-based marketing program targeting different customer segments, such as (1) Platinum Membership, (2) Rush Hour Bonanza, (3) Bundle Extravaganza, (4) Revive and Thrive Offer, and (5) Back in the Saddle Campaign. Furthermore, the Refer-a-Friend Program encompasses all RFM segments, encouraging users to expand the network of online transportation service users. The seamless integration between customer segmentation and RFM-based initiatives has the potential to enhance customer retention, drive revenue growth, and improve operational efficiency, contributing significantly to adaptive business strategies in the dynamic online transportation services sector.
Digital Marketing Analysis of Mie Gacoan Customer at Jakarta Using RFM and K-Means Clustering Methode Alghifari Suhardi, Fitra; Saputro, Andi; Sri Nugroho, Amanda; Heikal, Jerry
Journal of Economics and Business UBS Vol. 13 No. 2 (2024): Regular Issue
Publisher : Cv. Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52644/joeb.v13i2.312

Abstract

PT. Pesta Pora Abadi or Mie Gacoan is an Indonesian company within the Food and Beverages industry that produces food using noodles. Mie Gacoan is currently thriving with hype and sales, and with those momentum supporting them, they want to take advantage of this moment to expand their business by analysing their customer to market more their products, but they still don’t know Segmentasi is a process of knowing customer characteristics to get profitable customers for the company. Segmentasi will be done by grouping the customers into x categories. This study aims to combine K-means clustering and RFM to analyze the customer segmentation of Mie Gacoan. This customer characteristics will help Mie Gacoan in decision making to prioritize their energy and resources to potential customers or profitable customers.
Identifying Customer Segmentation and Persona of Soft Drink Industry in India: An Approach Using K-Means Clustering Samudra Wicaksono, Muhammad Haston; Heikal, Jerry
Co-Value Jurnal Ekonomi Koperasi dan kewirausahaan Vol. 15 No. 3 (2024): Co-Value: Jurnal Ekonomi, Koperasi & Kewirausahaan
Publisher : Program Studi Manajemen Institut Manajemen Koperasi Indonesia Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/covalue.v15i3.4671

Abstract

Perkembangan industri makanan dan minuman terus maju dengan dukungan teknologi dan berbagai inovasi terbaru. Dalam kategori minuman ringan (soft drink), semakin banyak varian jenis dan penambahan rasa yang dibuat untuk menarik perhatian masyarakat. Pertumbuhan industri minuman ringan diperkirakan akan terus meningkat. Minuman ringan (soft drink) adalah minuman yang tidak mengandung alkohol, biasanya berbentuk bubuk atau cairan yang mengandung bahan makanan atau bahan tambahan lainnya, baik alami maupun sintesis, dan dikemas dalam kemasan siap konsumsi. Perusahaan minuman ringan dalam menentukan langkah untuk meningkatkan keuntungan, perlu memiliki strategi meningkatkan penjualan dengan mengetahui target konsumen supaya tidak kehilangan pelanggan potensial dan memiliki biaya iklan yang efektif dengan melakukan customer segmentation. Metode yang digunakan pada penelitian ini untuk melakukan segmentasi adalah dengan menggunakan Metode Kmeans clustering. Metode ini adalah salah satu algoritma pembelajaran tanpa pengawasan (unsupervised learning). K-Means berfungsi untuk mengelompokkan data ke dalam data kluster. Dataset pada penelitian ini menggunakan 1000 populasi transaksi minuman ringan di India. Hasil penelitian menunjukkan 7 kluster berbeda yaitu middle productive age of gangster softdrink lovers, Early Productive Age of Sky9 and CodeX Softdrink Lovers, Cocacola & Pepsi lovers, Pepsi Softdrink Lovers, middle productive age of Cocacola softdrink lovers, Early Productive Age of Cocacola Softdrink Lovers, dan Bluebull Softdrink Lovers. Cluster 6: Early Productive Age of Cocacola Softdrink Lovers merupakan kluster terbesar senilai 19% dari total populasi. Dengan ini maka perusahaan cocacola yang menargetkan Cluster 6 dapat melakukan positioning seperti menyesuaikan keinginan dari cutomer yang yaitu mengembangkan produk less sugar serta menggunakan online platform dalam melakukan marketing.
K-Means Clustering Using Principal Component Analysis (PCA) Indonesia Multi-Finance Industry Performance Before and During Covid-19 Mulyaningsih, Sri; Heikal, Jerry
APMBA (Asia Pacific Management and Business Application) Vol. 11 No. 2 (2022)
Publisher : Department of Management, Faculty of Economics and Business, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.apmba.2022.011.02.1

Abstract

The cluster analysis within specific industry such as in multi finance indsutries is designed to be a tool for accelerating investment decisions, such as whether to buy, sell, or hold stocks in a way to construct an optimized portfolio. The purpose of the study was to apply cluster analysis on multi-finance stock data listed on the Indonesia Stock Exchange in the years 2019 and 2021, before and during Covid-19, using the PCA (Principal Component Analysis) K-means algorithm. The objective of this study is to classify stocks based on PCAs in order to assist investors in segmenting a multi-finance stocks cluster. The clustering is done on the 16 stocks registered in ISE using two-time windows: 2019 data where Covid-19 has not yet occurred and 2021 data where Covid-19 is still ongoing, and the firm is still in the recovery stage. The cluster analysis results show 12 companies worth investing in because they performed well. There is finding that  company that have unfavorable Covid-19 externalities since this cluster has worsening performance and is thus not advised as a stock investment. Meanwhile, the others company has neutral externalities because it remains in the same cluster in 2019 and 2021.
Binary Logistic Regression Analysis on Financial Performance of State-Owned Enterprises (Telkom and PLN): Case Study on NPM Change Based on ROA and TATO Maharani, Sella Sakilla; Nurrela, Nisa; Utami, Diah; Heikal, Jerry
Dinasti International Journal of Economics, Finance & Accounting Vol. 6 No. 6 (2026): Dinasti International Journal of Economics, Finance & Accounting (January - Feb
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v6i6.5775

Abstract

This research investigates the effect of Return on Assets (ROA) and Total Asset Turnover (TATO) on the likelihood of Net Profit Margin (NPM) change in PT Telkom Indonesia (Persero) Tbk and PT Perusahaan Listrik Negara (Persero) over Semester II 2015 to Semester I 2024. Using binary logistic regression, the dependent variable, which increases NPM, is defined as a binary outcome (1 = increase, 0 = no increase), with ROA and TATO as independent variables. The analysis includes 34 valid cases from company financial reports. Regression results show ROA significantly predicts NPM growth (B = 0.609, p = 0.015), boosting the odds of increases, especially in Telkom’s asset-efficient operations. TATO is also significant (B = -0.213, p = 0.006), but its negative coefficient indicates that higher turnover may hinder NPM growth due to rising costs, particularly in PLN’s capital-intensive sector. The classification table reports 76.47% accuracy, with 73.68% correct predictions for non-increasing NPM (0) and 80% for increasing NPM (1). These findings reveal sector-specific patterns Telkom’s strength in asset utilization versus PLN’s operational cost challenges offering valuable insights for optimizing profitability and informing strategic financial decisions in the state-owned enterprises.
The Influence of Digital Service Quality and Customer Experience on User Satisfaction and Loyalty of Shopee in Indonesia Using SEM–PLS Dinar Fasya, Diva; Herdianto, Herdianto; Ahtisya, Syauqi; Heikal, Jerry
Economic Reviews Journal Vol. 4 No. 4 (2025): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v5i1.983

Abstract

This study aims to analyze the influence of digital service quality and customer experience on user satisfaction and loyalty among Shopee users in Indonesia using the Structural Equation Modeling–Partial Least Squares (SEM–PLS) approach. Digital transformation has reshaped consumer behavior, positioning service quality and customer experience as key success factors in e-commerce. Data were collected through an online survey using a Likert scale from active Shopee users. The results indicate that customer experience has the most dominant influence on satisfaction, while digital service quality acts as a fundamental factor shaping users’ positive perceptions of the platform. Customer satisfaction is proven to be a significant mediating variable linking service quality and customer loyalty. Users who experience positive and consistent interactions tend to be more satisfied and demonstrate stronger long-term loyalty to Shopee. These findings highlight the importance of enhancing digital experiences that are both engaging and personalized to sustain customer loyalty in an increasingly competitive e-commerce environment.
Analyzing the Influence of Promotion on Consumer Purchase Decisions Using a Binary Logistic Regression Model in Car Salon Services Ahtisya, Syauqi; Herdianto, Herdianto; Fasya, Diva Dinar; Heikal, Jerry
Economic Reviews Journal Vol. 4 No. 4 (2025): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v5i1.984

Abstract

This study aims to analyze the influence of promotion on consumer purchasing decisions for car salon services using the binary logistic regression model. Promotion plays a crucial role in marketing strategy, particularly in service industries, as it helps build awareness and stimulates consumer decisions. Data were collected from 150 respondents who had been exposed to promotional activities conducted by car salon businesses. The independent variables examined in this research include promotion, price, brand switching, and prior experience, while the dependent variable is the consumer’s purchase decision. The data were analyzed using the binary logistic regression method with IBM SPSS 25 software. The results show that promotion and customer experience have a positive and significant effect on purchasing decisions, whereas price and brand switching have a significant negative effect. The final model achieved a classification accuracy of 74,0%, indicating that the selected variables can effectively explain consumer decision-making behavior. These findings highlight that effective promotional strategies and positive customer experiences significantly increase the likelihood of purchase, while high price perceptions and brand-switching tendencies reduce it. This study provides managerial implications for car salon service providers to enhance promotional effectiveness and improve customer satisfaction to foster long-term loyalty.
The Influence of Product Quality, Price, and Service on Customer Satisfaction and Loyalty at Goodtry Burger Outlets Using SEM-PLS Mardiyanto, Joko; Heikal, Jerry
Jurnal Indonesia Sosial Sains Vol. 6 No. 12 (2025): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v6i12.2142

Abstract

This study aims to examine the influence of product quality, price, and service on customer satisfaction and customer loyalty at GOODTRY burger outlets using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The research investigations five key variables: product quality, price, service, customer satisfaction, and customer loyalty. Data were collected from 46 respondents through an online questionnaire distributed to active customers. The results show that price and service significantly affect customer satisfaction, with coefficients of 0.306 (p = 0.029) and 0.349 (p = 0.018), respectively. Additionally, price has a strong and significant impact on customer loyalty (coefficient = 0.570, p = 0.000). In contrast, product quality does not have a statistically significant effect on either satisfaction (p = 0.077) or loyalty (p = 0.369), and service has no significant direct effect on loyalty (p = 0.057). These findings highlights the critical role of pricing strategies and service quality in fostering customer satisfaction and loyalty in the fast-food sector.
Co-Authors Agus Siswanto Ahtisya, Syauqi Akhsan, Lurinjani Alam, Taris Zakira Aldyah, Tika Alghifari Suhardi, Fitra Ali Wafa Amelia, Dona Andi Saputro Anindyarta Adi Wardhana 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 Dinar Fasya, Diva Doni Magat Harahap Dwi Ramadona, Dasatry 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 Fasya, Diva Dinar Fauzan, Heri Fazarullah , Dwirizky 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 Herdianto Herdianto, Herdianto Herdiany, Gita Amira Herry K, Raras 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 Mulyani, Sarah Mulyanto, Imam Arie 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 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 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 Setiawan, Dolis 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 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 Widya Handayani Wulan, Mutia Karunia Antap Wulandari, Rayuli Wuryantadi, Dwi Yakub, Isnendi Yohana, Kesia Yudi Nugraha Bahar YUNI KURNIAWATI Zakaria, Dzaki Zulfahmi, Muhammad Riko Yohansyah