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All Journal Aptisi Transactions on Technopreneurship (ATT) Inovasi: Jurnal Ilmiah Ilmu Manajemen Dinasti International Journal of Digital Business Management Jurnal Manajemen Bisnis Eka Prasetya Journal Informatic, Education and Management (JIEM) Jurnal Scientia Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Journal of Management and Bussines (JOMB) Jurnal Sosial dan Teknologi Jurnal Studi Islam Lintas Negara (Journal of Cross-Border Islamic Studies) Jurnal Akuntansi, Manajemen Dan Ekonomi Islam (JAM-EKIS) Journal of Social And Economics Research Jurnal Multidisiplin Sahombu IIJSE Al-Zayn: Jurnal Ilmu Sosial & Hukum Jurnal Media Akademik (JMA) Adpebi Science Series Management Analysis Journal Journal of Business Economics and Management journal of social and economic research J-CEKI Menulis: Jurnal Penelitian Nusantara Neraca: Jurnal Ekonomi, Manajemen dan Akuntansi
Jerry Heikal
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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K-Means Clustering: Customer Data Analysis in B2C Model at PT SCG Readymix Indonesia Lisdayanti, Dewi; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 3: April 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i3.7571

Abstract

PT SCG Readymix Indonesia merupakan perusahaan beton siap pakai dengan jaringan 33 batching plant yang tersebar di tiga wilayah utama Indonesia: West, Central, dan East. Perusahaan menyediakan beton dengan berbagai mutu, dari K150 hingga K450, serta produk khusus yang melayani empat segmen utama: residensial, komersial, infrastruktur, dan industrial. Untuk meningkatkan layanan, perusahaan menggunakan platform digital yaitu aplikasi Betonku dan e-commerce Tokopedia. Penelitian ini menggunakan algoritma K-Means Clustering untuk menganalisis data dari 100 pelanggan B2C di aplikasi Betonku dan Tokopedia guna mengelompokkan pelanggan berdasarkan karakteristik seperti usia, jenis kelamin, domisili, jenis proyek, nilai transaksi, dan metode pembayaran. Hasil analisa mengidentifikasi empat cluster utama, di mana Cluster 1 mendominasi segmen komersial dan residensial dengan rata-rata transaksi Rp. 67 juta, sementara Cluster 4 fokus pada proyek residensial dengan nilai transaksi Rp. 39 juta. Berdasarkan hasil yang didapatkan, online value proposition yang dapat direkomendasikan yaitu Monitoring Pengiriman Real-Time, One-Click Order, dan program loyalitas berbasis diskon. Integrasi teknologi Augmented Reality (AR) juga disarankan untuk membantu pelanggan memvisualisasikan lokasi proyek. Analisa ini membantu PT SCG Readymix Indonesia dalam mengembangkan layanan berbasis data, meningkatkan kepuasan pelanggan, dan memperluas pangsa pasar
Analysis of Factors Influencing the Decision to Resubscribe to Spotify Premium Using Binary Logistic Regression Method Indah Nur Syamsi Aguston; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 3: April 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i3.8107

Abstract

Keputusan untuk kembali berlangganan (resubscribe) layanan Spotify Premium merupakan tantangan yang menarik untuk dianalisis, terutama dalam memahami faktor-faktor yang memengaruhi perilaku konsumen. Penelitian ini bertujuan untuk mengidentifikasi faktor- faktor utama yang memengaruhi keputusan resubscribe Spotify Premium menggunakan pendekatan Marketing 8P (Product, Price, Place, Promotion, People, Process, Physical Evidence, dan Partnership) sebagai kerangka analisis. Metode penelitian yang digunakan adalah regresi logistik biner dengan bantuan perangkat lunak SPSS. Data dikumpulkan melalui survei terhadap 102 konsumen Spotify yang dipilih secara acak. Variabel independen meliputi berbagai aspek seperti kualitas audio, fitur, promosi, harga, dan kemitraan, sementara variabel dependen adalah keputusan pembelian ulang. Data survei diolah menggunakan Microsoft Excel, dinormalisasi, dan variabel berbentuk teks seperti "YA" dan "TIDAK" dikonversi menjadi nilai biner (1 dan 0). Hasil penelitian menunjukkan bahwa faktor yang berpengaruh signifikan terhadap keputusan pembelian ulang adalah kualitas audio Spotify yang memuaskan dan paket bundling dengan provider telekomunikasi. Faktor lainnya tidak memiliki pengaruh signifikan terhadap keputusan pembelian ulang. Berdasarkan analisis terhadap 102 responden, model regresi logistik berhasil memprediksi bahwa sebanyak 99 konsumen akan melakukan pembelian ulang dan 3 konsumen tidak akan melakukannya, dengan tingkat akurasi model sebesar 86,3%. Penelitian ini memberikan wawasan penting bagi Spotify dan penyedia layanan serupa untuk memfokuskan strategi pemasaran pada kualitas layanan dan kemitraan strategis guna meningkatkan retensi pelanggan.
Mobile Phone Preferences Segmentation Using The K-Means Clustering in Indonesia Annisa Nurwanda Putri; Pratiwi, Pratiwi; Putri Syifa Humaira; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 3: April 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i3.8123

Abstract

This study investigates consumer preferences for mobile phones in Indonesia using the K- Means Clustering method. Data from 114 respondents were analyzed to identify key characteristics and preferences, focusing on variables such as age, gender, income, brand, and features like storage, connectivity, design, and accessories. The results revealed six distinct clusters, each representing unique consumer segments, such as Tech-Savvy Seekers, Secure Tech Enthusiasts, Performance Prioritizers, Security-Centric Pragmatists, Style-Savvy Connectors, and Endurance Seekers. The segmentation process highlights significant differences in consumer behavior, with some clusters emphasizing high performance and advanced connectivity features, while others prioritize affordability, security, and design. Based on the STP (Segmentation, Targeting, Positioning) framework, two target segments were identified: Tech-Savvy Seekers and Endurance Seekers. These segments were selected due to their high purchasing power and strong demand for premium mobile phone features, including long battery life and powerful performance. The proposed value proposition for these target segments is "Empower Your Mobile Experience with High-End Performance and Unmatched Battery Life," emphasizing key product features that align with their preferences. Additionally, this study incorporates the 7Ps marketing mix to offer practical recommendations on product development, pricing strategies, distribution channels, promotional efforts, customer service, purchasing processes, and physical evidence. These findings provide valuable insights for businesses to develop targeted marketing strategies that better address the diverse needs of Indonesian mobile phone consumers.
Analysis of Factors Influencing Consumers in using Loyalty Rewards Programs in Indonesian Convenience Stores using Binary Logistic Regression Method Putri Syifa Humaira; Annisa Nurwanda Putri; Pratiwi, Pratiwi; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 3: April 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i3.8124

Abstract

This research aims to analyze the factors that influence consumers in using loyalty rewards programs at minimarket retailers in Indonesia. With the backdrop of intense competition in the retail sector, loyalty rewards programs have become one of the main strategies to enhance customer loyalty. This study adopts a quantitative approach using binary logistic regression method to evaluate the influence of the Product, Price, Promotion, and Process variables from the 7P marketing concept on consumer participation. Data were obtained through an online survey of 148 respondents who are consumers of minimarkets with access to the loyalty rewards program. The analysis results show that the Price variable (represented by psychological loyalty), Promotion (represented by product information), and Process (represented by user-friendliness and repeat purchase) have a significant influence on the use of the program. The resulting regression model shows an accuracy of 81.8%, with these variables being the main predictors. The conclusion of this research emphasizes the importance of developing strategies that strengthen the emotional value of the program, optimize promotions, and simplify the program usage process to enhance the effectiveness of the loyalty rewards program. Practical recommendations include exclusive offers for loyal customers, promotions using various digital channels, and integrating the Loyalty Rewards program with digital applications or payment systems to make it easier for consumers to monitor and redeem points, in order to create sustainable added value for both customers and the company.
Cultural Wedding Rituals Among Batak Toba Millennials and Gen Z: Perceptions in the Modern Era - An Ethnographic Study Tiyanda Hanti Arum Kusuma; Rizki Agung Ramadani; Rinta Agustiani Dwiputri; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 3: April 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i3.8140

Abstract

Indonesia has many different ethnic groups. Among them, the Batak people stand out. Batak weddings are known for being long and elaborate, but with modern times, things are changing. Modernization has made Batak wedding ceremonies more convenient and has changed the way people think, with many preferring practicality. This study explores the perspectives and experiences of the Batak community regarding the traditional Batak wedding ceremony and its relevance in modern times. A qualitative research method with an Ethnography approach was employed. Through five interview questions, the study aims to understand whether the Batak wedding rituals are perceived as challenges or advantages, whether the process remains relevant, and how individuals respond to the idea of shorter and more practical wedding ceremonies. Purposive sampling was used to select Generation Millennial and Generation Z respondents for in-depth interviews.The interview results from four respondents indicate that despite the complex and time-consuming nature of the Batak wedding rituals, the Batak community still regards them as a sacred cultural heritage. Respondents believe that the lengthy process brings benefits such as a deeper appreciation for marriage and lower divorce rates. The two generations share the same views on traditional marriage, with shared values of the sacredness of marriage and preserving cultural heritage. Overall, this study highlights the importance of preserving and passing down Batak wedding traditions while accommodating societal changes.
Exploring the Staycation Phenomenon After COVID-19: A Grounded Theory Approach Desy Maya Indriana; Indah Nur Syamsi Aguston; Maysheilla Chandra; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 4: Juni 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i4.8550

Abstract

The staycation phenomenon has received significant attention in recent years, especially during the pandemic, as more and more people choose to spend their free time close to home. However, the staycation phenomenon does not necessarily disappear when the pandemic ends, as many people, especially urban dwellers, still choose to do staycations as an alternative vacation. The continuous interest in staycations underscores the need for a deeper exploration of the motivations, experiences, and implications associated with this recreational trend. Therefore, this research employs a grounded theory approach to delve into aspects of the staycation phenomenon, aiming to provide a comprehensive understanding of its dynamics and impacts. Researchers conducted direct interviews with several millennial participants (aged 27 – 37 years old), seeking to uncover the fundamental factors driving individuals’ decisions to choose staycations. By elucidating the determinants of staycation choice, this study is expected to contribute to the fields of recreation studies, and tourism, and provide fresh insights that can be utilized by the hospitality industry or related associations to enhance their services, thus ensuring that staycations remain a sustainable and inclusive recreational option for diverse populations. Based on the research results, the researchers obtained coding results of 42 from 9 respondents which were then classified into 19 categories and 13 themes: Location, Reviews, Price, Facility, Services, Proximity to the culinary / souvenir area, Healing, Cozy Place, Quality, Activity in Hotel, Me-time, Looking for New Atmosphere, Bonding. The highest scores that drive individual decisions in choosing a staycation is Healing.
Customer Segmentation Using K-Means Clustering on Top of 4 Platform Streaming in Indonesia Syakina, Syakina; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 4: Juni 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i4.8584

Abstract

Platform streaming adalah layanan media yang ditawarkan langsung kepada penonton melalui Internet. Layanan streaming biasanya dapat diakses melalui situs web di komputer pribadi, serta melalui aplikasi di perangkat seluler (seperti ponsel pintar dan tablet), pemutar media digital (termasuk konsol permainan), atau televisi dengan platform Smart TV terintegrasi. Youtube, Netflix, Disney+, dan Viu merupakan 4 platform streaming yang paling sering digunakan oleh masyarakat Indonesia. Tujuan penelitian ini untuk mengetahui segmentasi pengguna platform streaming berdasarkan preferensi, karakteristik, dan rekomendasi paket langganan yang sering digunakan. Metode K-Means Clustering digunakan untuk mengelompokkan pengguna platform streaming berdasarkan atribut tertentu, seperti preferensi film, aspek prilaku pengguna, dan kenyamanan dari paket langganan yang ditawarkan. Jumlah responden pada penelitian ini 107 orang yang tersebar di seluruh Indonesia, dimana data yang diperoleh 3 cluster yang memiliki persona dengan karakteristik dan preferensi yang berbeda. Hasil dari penelitian ini menunjukan 3 cluster yang berbeda yaitu Middle Productive Age of Netflix User, Early Productive Age of Viu User, dan Middle Productive Age of Disney+ User. Walaupun Cluster 1: Middle Productive Age of Netflix User bukanlah cluster terbesar yang hanya memiliki nilai 31% dari total populitas akan tetapi Netflix dapat menargetkan cluster 1 dan melakukan positioning seperti menyesuaikan keinginan dari cutomer yaitu mengembangkan paket langganan loyalitas serta menggunakan online platform dalam melakukan marketing.
Identifying Key Drivers of Repurchase Intentions for Sari Roti Products Using Binary Logistic Regression Analysis Annisa Liestiani; Ayu Wulandari; E. N. Budiyanto Hariandja; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 4: Juni 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i4.8716

Abstract

This study aims to analyze various factors that influence the repurchase decision of Sari Roti products. The method used in this research is binary logistic regression using the SPSS tool. A sample of 156 consumers was randomly selected. Data was collected through a survey filled out by 156 Sari Roti consumers. The survey results were entered into Microsoft Excel and then normalized. For Independent Variable and Dependent Variable data in the form of text "Yes" or "No", it will be converted into binary numbers, meaning it is represented by the numbers 1 (one) and 0 (zero). Independent Variable data consists of Durability, Reliable Quality, Well-Known Brand, Prestigious Brand, Interested In New Flavors, New And Innovative Products, Sufficiently Many Variants, Affordable Price, Competitive Price, Price Matches The Quality, Value For Money, Promotion Via Facebook, Promotion Via Instagram, Promotion Via Twitter, Promotion Via YouTube, and Promotion Via Website, Influencer Recommendation, Family Recommendation, Friend Recommendation, Good Memory Or Experience, Easily Accessible Store Location, Always Available, Satisfied With Customer Service, Good Reputation, Easy-To-Remember Brand, Good Packaging Condition. While, the Dependent Variable is the Repurchase Intentions. From the research results, it can be concluded that the factors that significantly influence the repurchase decision are Prestigious Brand, Sufficiently Many Variants, and Affordable Price. Other variables do not significantly affect the decision to repurchase Sari Roti products. Based on the binary logistic regression analysis of 156 Sari Roti consumers, it was predicted that 140 consumers would repurchase, and 16 consumers would not, with a data accuracy of 83.3%.
Identifying Customer Segmentation and Persona of Online Transportation Companies in Jabodetabek Using K-Means Clustering Analysis for a More Effective Marketing Strategy E. N. Budiyanto Hariandja; Annisa Liestiani; Ayu Wulandari; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 4: Juni 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i4.8717

Abstract

The demand for online transportation services in Jabodetabek has surged in recent years, driven by urbanization and the need for efficient mobility. This study aims to identify market segmentation through clustering, enabling online transportation companies to uncover detailed consumer personas and develop precise value propositions. Data was collected from 413 respondents via an online survey within the Jabodetabek area and processed with KNIME software. The analysis identified three (3) distinct user groups/clusters: The Minimum Budget Conscious Users, Value-Seeking Occasional Users, and The Established Loyalist Gentleman. Among these, The Established Loyalist Gentleman, characterized by higher income levels and frequent service usage, emerged as the ideal target segment. To attract this segment, personalized marketing strategies focusing on part of the 4Ps marketing mix are proposed. Key initiatives include Comfort and Safety Assurance, offering premium vehicles that are safe, clean, and well-maintained, along with professional drivers for a superior travel experience. Enhanced App Features include advanced safety tools like real-time trip tracking, emergency buttons, and driver identity verification to increase user trust. Ease of Booking ensures a user-friendly app interface with one-click booking and saved routes for convenience. Flexible payment methods and Special Premium Services, such as exclusive discounts for frequent or long-distance trips, further enhance loyalty. These strategies cater to the preferences of this high-value segment, fostering stronger engagement and driving long-term growth in the competitive online transportation market.
Customer Segmentation Using K-Means Clustering Analysis (Case Study on Amazon Prime Video Userbase) Heidi Yanti Anggraeni Putri; Pratama Hadi Saputra; Resman Yohanes Doloksaribu; Jerry Heikal
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 4: Juni 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i4.8860

Abstract

Layanan streaming Amazon Prime Video telah berkembang secara signifikan dan telah menjadi salah satu pemain kunci dalam industri streaming yang kompetitif. Penelitian ini bertujuan untuk menjelaskan tren dan pola mendasar yang membentuk kesuksesan Amazon Prime Video dalam menghadapi tantangan industri. Dengan mengelompokkan pelanggan berdasarkan perilaku dan preferensi mereka, penelitian ini akan memberikan wawasan mendalam mengenai cara memenuhi kebutuhan spesifik setiap segmen. Dengan memahami preferensi dan perilaku pengguna, Amazon Prime Video dapat merancang strategi konten yang lebih terarah dan relevan. Penelitian ini menggunakan dataset Amazon Prime Userbase yang terdiri dari 2.500 responden untuk mengidentifikasi segmen pasar melalui analisis cluster K-means. Hasilnya, empat cluster pelanggan yang berbeda teridentifikasi: Cluster 1 (Mid-age Female User), Cluster 2 (Senior Male User), Cluster 3 (Young Male User), dan Cluster 4 (Senior Female User). Cluster 1, yang didominasi oleh wanita berusia 36-49 tahunyang didominasi oleh wanita berusia 36-49 tahun dan memiliki aktivitas interaksi tertinggi, kami pilih sebagai target segmen pasar yang utama bagi Amazon Prime Video. Cluster ini menunjukkan preferensi yang kuat terhadap genre drama dan aksi serta penggunaan perangkat Smart TV dan smartphone, menciptakan peluang untuk meningkatkan pengalaman menonton yang berkualitas tinggi. Value proposition yang diusulkan mencakup penambahan konten eksklusif, pengembangan fitur interaktif seperti komentar real-time, program loyalitas untuk pengguna aktif, serta acara nonton bersama dan kampanye media sosial yang meningkatkan keterlibatan. Menyasar Cluster 1 dapat memperkuat posisi Amazon Prime Video dalam mengadaptasi layanan yang relevan dan personal bagi pelanggan, sekaligus memberikan wawasan untuk penelitian lebih lanjut dalam memahami perilaku konsumen dalam segmen ini. Penelitian ini diharapkan dapat memberikan kontribusi bagi Amazon Prime Video terhadap strategi pemasaran yang lebih efektif dan peningkatan kepuasan pelanggan di industri streaming yang kompetitif.
Co-Authors Abhiyoga Deyandra Putra Achmad Ichsan Adevi, Isye Rahayu Adhy Priyo Adi Setiawan Aditya Rachman Zarkasih ADRIAN PRATAMA Agung Ibrahim Agung Pribadi Agus Sugiono Ahmad Ilham Bachrie Harahap Alex Fernando Hasahatan Ali Sudrajat Andara Rahma Danurisa Andi Mardhotilla Anggini, Dewi Anjar Asmara Putra Annisa Liestiani Annisa Nurwanda Putri Antoni Irawan AYU WULANDARI Bachrie Harahap, Ahmad Ilham Bambang Permadiyansach Berman J Hutabarat Budiyanto Hariandja Desy Maya Indriana Dewi Anggini Dewi Lisdayanti Dimas Hindrawan Diny Claudia Doni Magat Harahap Dzaki Zakaria E. N. Budiyanto Hariandja Edoward N. Budiyanto Elisa Purnawati Elja Salwa Enny Enny Erni Susanty Erwan Hendrawan Fajar Hartanto Siswanto Fajar Kristianto Fanjili Gratia Mamonto Fetri Nelfa Ganang Kartiko Aji Gilang Kharisma Ramadhan Ibrahim Gulfi Oktariani Heidi Yanti Anggraeni Putri Helga Meilany Ign Agus Supriyono Indah Nur Syamsi Aguston Irma Nur Wanty Isfan Ferli jeffry kurniawan Lisdayanti, Dewi Lisdyanto Lucia Rainy Betari Marc Giulio Richard Marlina Maysheilla Chandra Mega Yunita Gayo Metta Karunia Michael Milastri Muzakkar Moh Masnur Monica Pongsibidang Mufti Kusuma Firdaus Muhammad Feyzel Khalfani Putra Ardanesworo Muhammad Ikhsan Nurseha MUHAMMAD YUSUF Mutia Karunia Antap Wulan Nandi Andrian Kurnia Putra Nayla Azkia Nurul Intan Permanasari Oci Citra Maharani Panka Gumilang Ponjo Utomo Pratama Hadi Saputra Pratama, Renaldo Pratiwi Pratiwi Pratiwi Putri kirana Putri Syifa Humaira Raden Maart Adi Waskita Tjahjono Rafyon Sani Rayuli Wulandari Resman Yohanes Dolok Saribu Resman Yohanes Doloksaribu Retno Santoro Richard, Marc Giulio Rifko Sinaga Rinta Agustiani Dwiputri Riri Yunita Rivelino, Deva Rizki Agung Ramadani Rizky Feliana Devi Rudi Setiari samsul arifin Sari Riyani Satriya Perdana Savira Nurviriana Sayuti Shera Fanesha Siti Wulansari Sri Polya Kettipusem Susan Ratna Susan Ratna Salim Susi Suheni Suududdin, Suududdin Syakina Syakina, Syakina Tampi, Mia Tika Aldyah Tiyanda Hanti Arum Kusuma Vitto Rialialie Zahwa Nur Syahda Zahwa Nursyahda