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All Journal Excellent Jurnal Mirai Management JURNAL PENDIDIKAN TAMBUSAI Jurnal Riset Akuntansi Aksioma 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 MSDA (Manajemen Sumber Daya Aparatur) JOURNAL OF BUSINESS AND ECONOMICS RESEARCH (JBE) BUDGETING : Journal of Business, Management and Accounting Journal of Advanced Multidisciplinary Research International Journal of Applied Finance and Business Studies 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 JRAP (Jurnal Riset Akuntansi dan Perpajakan) Jurnal Ekonomika Manajemen Dan Bisnis Jurnal Indonesia Sosial Sains Indonesia Accounting Research Journal 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 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 J-CEKI
Heikal, Jerry
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Customer Segmentation Using K-Means Clustering with SPSS Program in a Case Study of Consumer Interest in Current Coffee Shop Daulay, Risma Yanti; Passalaras, Raja Aulia; Heikal, Jerry
BUDGETING : Journal of Business, Management and Accounting Vol 5 No 2 (2024): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v5i2.9288

Abstract

This research aims to segment customers using the K-Means Clustering method in a case study of consumer interest in current coffee shops such as Kopi Kenangan, Kopi Janji Jiwa, Tomoro Coffee, Fore Coffee and Fami Cafe. Customer segmentation is useful for knowing consumer preferences such as interests, background, lifestyle, service quality and consumer characteristics that are useful for knowing the right persona and marketing strategy as well as the value proposition, especially at the Kopi Kenangan, Janji Jiwa, Tomoro Coffee, Fore Coffee and Fami Cafe coffee shops. The analytical method used in this research is data collection by distributing questionnaires to respondents with predetermined criteria in the Jakarta area and outside Jakarta. The questionnaire was distributed in November 2023. The survey results were analyzed using the K-Means Clustering method in the SPSS 23 program to group consumers based on certain attributes such as age, education, domicile, income, occupation, frequently used social media and most popular coffee shop preferences. such as coffee and non-coffee variants, price, service quality and recommending it to other people. Based on the results of K-Means Clustering data processing, there are 3 clusters, namely cluster 1 (Consumptive Customer), cluster 2 (Standard Young Customer), cluster 3 (Potential Customer) which can be concluded that cluster 3 is a potential cluster that is the target of this research, where cluster 3 consists of respondents who are coffee fans and don't like coffee but are very active in using social media and have made online food transactions and always dine in when making transactions at coffee shops. So it can be seen that cluster 3 can be explored and used as a marketing target by carrying out promotions on various social media applications by offering various choices of coffee and non-coffee variants in order to attract customers who don't like coffee so they are interested and want to try the products offered. . The value proposition for current coffee shops is to give the impression of Coffee Vibes and focus on providing a unique and unforgettable coffee experience by presenting innovative flavor variants and creative coffee presentations, exploring new flavors and offering premium quality that can be enjoyed by all groups and creating an atmosphere comfortable and Instagram- worthy to provide a pleasant customer experience that fits the rhythm of modern life. Keywords: Cluster Analysis, Current Coffee, Customer Segmentation, K-Means SPSS,.
Mendorong Pertumbuhan Pangsa Pasar B2B untuk Sektor Ride-Hailing Menggunakan Segmentasi Pasar Strategis Kamaratih F, Yositalida; Perdhana, Rizkita Bagus; Nugroho, Yusuf Wahyu; Heikal, Jerry
BUDGETING : Journal of Business, Management and Accounting Vol 5 No 2 (2024): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v5i2.9609

Abstract

The expansion of Indonesia's ride-hailing sector has been considerable, fueled by technological advancements and the widespread embrace of smartphones. Despite its swift growth, the industry faces difficulties concerning long-term viability, safety issues, and compliance with governmental regulations. Nevertheless, the integration of advanced technologies and strategic plans for service expansion into new regions presents significant opportunities. The competitive environment in Indonesia's ride-hailing market not only stimulates innovation but also shapes a lively and evolving market atmosphere. Originally designed for consumers, the ride-hailing sector has evolved into a versatile transportation solution for various business needs, including employee transportation and goods delivery. These services offer advantages for companies, such as enhanced operational efficiency and reduced logistics costs. Recognizing the diversity of the business market, segmentation becomes vital in comprehending customer needs. Through tailored marketing approaches, companies can deliver more pertinent solutions, boosting competitiveness and enlarging B2B market share. By using K-means clustering, it yields 5 clusters, namely cluster 1: Tech Innovators and Financial Players, cluster 2: Logistics Singular Focus, cluster 3: Logistics, Retail, and Automotive Synergy, cluster 4: Culinary, Logistics, and Travel Dynamics, cluster 5: Tech Titans, Healthcare Giants, and Financial Leaders. The analysis of user clusters on the B2B Ride Hailing Indonesia platform provides useful insights that guide strategic recommendations for improving service offerings, refining marketing strategies, and optimizing business operations. Targeting the millennial demographic through digital channels and influencers, examining marginal costs for high-traffic clusters to identify optimization opportunities, exploring expansion possibilities in clusters with growth potential, and tailoring business solutions for clusters with unique needs are among the recommendations. Keywords: K-means Clustering, Market Innovation, Market Share Expansion, Ride-Hailing Sector, Segmentation, Strategic Decisions.
Customer Segmentation of Pabuaran Store on Shopee E-Commerce Using RFM Model Analysis (Case Study of H&M Brand Sales Products) Arthanugraha, Adam; Azzuhri, Muhammad Basyar; Ramadhan, Yufiansyah Wahyu; Heikal, Jerry
BUDGETING : Journal of Business, Management and Accounting Vol 5 No 2 (2024): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v5i2.9724

Abstract

E-Commerce creates business activities that make it easier for people to be more effective because business transactions between sellers and buyers are not limited by space and time. Pabuaran store is one of the personal shopper service providers which started its business in 2019, the marketplace phenomenon in that year has increased massively and online business players in one of the marketplaces have also reached 7 (seven) million in 2019. Product graph seen in the Pabuaran Store's Services business tends to decline, this requires business actors to take strategic steps to maintain their existence in the business world. This is used encouraged service business owners to gain profits in the midst of the phenomenon that is occurring. In determining the variables, the general model used to group customers is the RFM (Recency, Frequency, Monetary) Model, which groups customers based on the time interval of the customer's last visit, frequency of visits, and the amount of value issued as company royalties(1). The recency value can determine the time span since the customer's last transaction. The frequency value can indicate how many transactions each customer conducts with the company. Additionally, the monetary value can reveal the amount of expenditure made by each customer in each transaction with Pabuaran Store on Shopee. The three segments have different campaign strategies. For Segment 1, a reactivation campaign is implemented, such as conducting live videos on Shopee. In Segment 2, a broadcast retention message is delivered to customers who have previously purchased products from Pabuaran Store. As for Segment 3, where loyal customers are identified, a loyalty point system is introduced to keep these customers engaged. Keywords: E-Commerce, Frequency, Monetary, Personal shopper, Recency.
Food Stall Owners’ Strategies in Response to Rice Price Surges: a Grounded Theory Analysis Pratiwi, Pratiwi; Humaira, Putri Syifa; Putri, Annisa Nurwanda; Heikal, Jerry
BUDGETING : Journal of Business, Management and Accounting Vol 6 No 1 (2024): BUDGETING : Journal of Business, Management and Accounting
Publisher : Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/budgeting.v6i1.10395

Abstract

The contemporary rice price surges are affected by several factors including natural, production-related, and even political factors. Food stall business owners affected by these surges need to make optimal decisions and strategies to ensure their business survival. This research aimed at identifying the strategies adopted by the affected food stall business owners. The study used a qualitative method with a Grounded Theory approach by conducting interviews with 6 respondents consisting of food stall owners in Jakarta. Based on the findings, 22 codes forming 5 categories were identified. This identification concluded 3 strategical themes: Price Adjustments, Substitution, and Omni-Channel totalling 24 points. The most common strategy applied by the participants is Price Adjustments as common as 21 points. This strategy is adopted to mitigate the impact of rising rice prices and maintain operations by focusing on price adjustments (13 points), portion sizes (5 points), and rice quality (3 points). Keywords: Food Stall Business Strategy, Grounded Theory, Rice Price Surges.
Segmentation, targeting and positioning analysis using k-means clustering model: A case study of the laptop market in Indonesia Saputra, Tubagus Chandra; Fadhilah, Savira Maghfiratul; Mangkuto, Shidiq Umar; Heikal, Jerry
International Journal of Applied Finance and Business Studies Vol. 12 No. 2 (2024): September: Applied Finance and Business Studies
Publisher : Trigin Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijafibs.v12i2.313

Abstract

In Indonesia's rapidly evolving laptop market, understanding consumer preferences is crucial for maintaining competitiveness. This study employs the K-Means Clustering algorithm to segment the laptop market based on variables such as age, income, expenditure, laptop price, main usage, and selection criteria. Data were collected from 271 respondents in the Jabodetabek area through an online survey. The analysis identified six distinct customer clusters: Edu-Tech Enthusiasts, Executive Civil Servants, Gov-Corp Society, Steady State Officials, Corporate Climbers, and Emerging Entrepreneurs. Each cluster exhibits unique characteristics and preferences, including preferred brands and price ranges. The findings emphasize the importance of targeted marketing strategies tailored to the specific needs of each segment. By leveraging these insights, laptop producers can optimize product offerings, pricing strategies, and promotional campaigns to enhance market share, customer loyalty, and profitability in Indonesia's competitive laptop industry.
The Reassessment of CAPM Relative Accuracy Comparative Study with Actual Price Movement in Indonesian (2019-2022) Fajarini, Nurfahma; Heikal, Jerry
International Journal of Management and Business Applied Vol. 3 No. 1 (2024)
Publisher : Asosiasi Dosen Peneliti Ilmu Ekonomi dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54099/ijmba.v3i1.743

Abstract

This study aims to investigate the accuracy of the Capital Asset Pricing Model (CAPM) in predicting stock returns on the Indonesian Stock Exchange (IDX) during the period of 2019 to 2022. The objectives of the research are to benefit the individuals and communities such as enhancing individuals’ decision-making in predicting stock returns, advancing community understanding of financial markets, and contributing new investment insight for societal benefits. The sample comprises 45 selected stocks out of more than 700 stocks, using K-Means Clustering to ensure a diverse and representative dataset. The study compared CAPM’s predictions with the Moving Average (MA) method. Findings show CAPM’s decisions align 87% with MA-analyzed price movements, underscoring CAPM’s effectiveness and the value of using multiple methods for financial predictions. While CAPM proves robust during economic recovery, further analysis is needed for optimal investment strategies. This study’s results challenge some arguments against CAPM’s accuracy.
The Influence of Offering Equity, Brand Equity, and Relationship Equity on Customer Satisfaction and Customer Loyalty Awalludin, Awalludin; Heikal, Jerry
International Journal of Management and Business Applied Vol. 3 No. 2 (2024)
Publisher : Asosiasi Dosen Peneliti Ilmu Ekonomi dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54099/ijmba.v3i2.1083

Abstract

The rapid growth of the information technology industry has driven the demand for high-quality IT training. Intensive bootcamp IT programs have increasingly become the primary choice for individuals seeking to enter this industry. Through effective IT bootcamps, individuals can acquire skills that align with the rapidly evolving job market demands, while organizations can attract digitally skilled talent ready to face the challenges of Industry 4.0. As the demand for IT training increases, so does the number of IT bootcamps offering a variety of educational products to meet labor market needs. One of the prominent providers is Hacktiv8 Indonesia. Since its establishment in 2016, Hacktiv8 has faced numerous challenges, one of which is maintaining customer engagement to ensure continued use of its services. This research aims to analyze the influence of Offering Equity, Brand Equity, and Relationship Equity on Customer Satisfaction and Customer Loyalty among participants in Hacktiv8 Indonesia’s IT Bootcamp, with a focus on a case study of Hacktiv8. The research method used is Structural Equation Modeling-Partial Least Squares (SEM-PLS), and the data was collected through an online survey of 150 participants who are currently enrolled or about to enroll in Hacktiv8’s IT Bootcamp. The analysis results are expected to provide better insights into the factors affecting customer satisfaction and loyalty within the context of IT bootcamp training. The practical implications of these findings are anticipated to assist educational and training institutions in enhancing their offering strategies, brand management, and customer relationship building to improve customer satisfaction and loyalty in the future.
STRATEGI SEGMENTASI PELANGGAN MANJA BEAUTY SKINCARE DENGAN MENGGUNAKAN ANALISA RFM MODEL Nisa, Khairi; Heikal, Jerry
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 6 No. 1 (2022): JATI Vol. 6 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v6i1.4558

Abstract

Persaingan semakin ketat di bidang usaha memotivasi sebuah usaha kecil dan menengah (UKM) untuk mengelola pelayanan terhadap konsumen tetap (pelanggan) secara maksimal .Menaikkan kesetiaan pelanggan dengan mengelompokkan pelanggan menjadi beberapa kelompok dan menentukan taktik pemasaran yang tepat serta efektif untuk setiap kelompok. Segmentasi pelanggan dapat dilakukan melalui metode clustering. Penelitian ini bertujuan untuk menganalisis Recency, Frequency dan Monetary (RFM) pelanggan pada Manja Beauty Skincare. Analisis yang digunakan meliputi analisis deksriptif dimana data yang digunakan berupa data primer. Teknik pengumpulan data digunakan yaitu metode observasi (pengamatan), wawancara. Hasil penelitian menunjukkan bahwa ada pelanggan yang memperoleh predikat terbaik, predikat cukup baik, dan predikat kurang baik. Predikat terbaik merupakan pelanggan yang wajib di pertahankan, sementara pelanggan cukup baik bisa di berikan stimulus kepada pelanggan seperti discount harga atau penawaran yang menarik lainnya kepada pelanggan yang memiliki loyal card.
Analysis of Global Bank’s Financial Performance with the Clustering K-Means Model Santosa, Suhari; Heikal, Jerry
JRAP (Jurnal Riset Akuntansi dan Perpajakan) Vol 11 No 2 (2024): July - December
Publisher : Magister Akuntansi Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35838/jrap.2024.011.02.22

Abstract

Purpose: The purpose of this study is to find out the financial performance of global banks in each cluster for the years 2019 and 2023. In addition, this study is also to find out the position of Indonesia's banks compared to global and ASEAN banks in 2019 and 2023. Methodology: The analysis model used is that the formation of clusters is based on the ratio of CAR, LDR, NIM, ROA and ROE. Testing was carried out with the K-Means model using SPSS. Findings: The results of the study show that in general, global banking performance in 2023 is better than in 2019 in 4 clusters out of 5 clusters. However, the number of banks in the Very Good and Good cluster has decreased in 2023 compared to 2019. In addition, the number of banks in the Very Bad cluster also increased in 2023 compared to 2019. Implication: The increase in the number of banks in the Very Bad cluster needs to be a concern, because the improvement in performance is not as good as other global banks. Local bank supervisory authorities, including the Financial Services Authority in Indonesia, need to pay attention to the performance of banks in the Very Poor cluster. Originality: This study provides additional information about the condition of banks compared to their peers in 2019 and 2023 at the global, ASEAN and Indonesia levels for bank management, investors and also authorities.
Analisis Prediksi financial Distress Perusahaan Industri Kimia Dasar Zulfahmi, Muhammad Riko Yohansyah; Heikal, Jerry
Jurnal Mirai Management Vol 9, No 1 (2024)
Publisher : STIE AMKOP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/mirai.v9i1.6560

Abstract

Tujuan penelitian ini adalah untuk mengetahui analisis rasio keuangan terhadap financial distress. Financial distress merupakan variabel dependen yang diukur dengan interest coverage ratio. Variabel independen dalam penelitian ini diukur dengan debt-equity rasio, return on asset, return on equity, dan net profit margin. Penelitian ini menggunakan metode kuantitatif. Populasi dalam penelitian ini adalah perusahaan manufaktur sektor industri kimia dan dasar yang terdaftar di Idx.co.id pada bulan November 2022. Berdasarkan metode purposive sampling, diperoleh 95 perusahaan yang menjadi sampel penelitian. Data yang digunakan merupakan data sekunder yang diperoleh dari Idx.co.id pada perusahaan manufaktur sektor kimia dan industri dasar pada bulan November 2022. Teknik analisis data yang digunakan adalah analisis regresi Binary Logistic. Hasil penelitian menunjukkan pengaruh yang signifikan terhadap financial distress. Dari 35 perusahaan tersebut dalam kondisi baik, 5 perusahaan mengambil risiko dan 57 perusahaan diprediksi bangkrut. Kata Kunci: Financial distress, financial Rasio, Binary Logistic
Co-Authors Aldyah, Tika Amelia, Dona Andi Saputro Anjarsari, Rosita Arda, Edvidel Ardanesworo, Muhammad Feyzel Khalfani Putra Ardianto, Andi Arthanugraha, Adam Arum Kusuma, Tiyanda Hanti Awalludin Awalludin, Awalludin Ayu Pradina, Dinda Ayu Wulandari Azkia, Nayla Azwar , Tasrika Azwar, Meiriza Azwar, Tasrika Azzuhri, Muhammad Basyar Chitra, Jimmi Chow, Sayuti Darma Tenaya, I Putu Risky Daswirman, Daswirman Daulay, Risma Yanti Dawam, Khaerud Desmalina, Desmalina Devi, Rizky Feliana Dilla Sistesya Doni Magat Harahap Dwi Ramadona, Dasatry Dwiputri, Rinta Agustiani Dzulqornain, Muhammad Edison, Alva Elfira, Renti Enny Enny Erwan Erwan, Erwan Fadhilah, Savira Maghfiratul Faisal Faisal Fajarini, Nurfahma Ferli, Isfan Fitria, Yossa Gandhi, Ayu Gelvi, Gelvi Gunawan, William Ben Gusmeri, Gusmeri Hanifeliza, Rury Hariandja, E N Budiyanto Harsemarozi, Harsemarozi Hasahatan, Alex Fernando Heswara, Faisal Hindrawan, Dimas Humaira, Putri Syifa Hutabarat, Berman Hutabarat, Berman J Jaya, Hamka Putra Kamaratih F, Yositalida Kettipusem, Sri Polya Kevry Ramdany Kurniawati, Yuni Kusumaningrum, Indah Liestiani, Annisa Mamonto, Fanjili Gratia Mangkuto, Shidiq Umar Marlina Marlina Muhammad Farhan Muhammad Ikhsan Muhammad, Tegar Mulyo, Iksan Adityo Muzakkar, Milastri Nazmi, Fittria Ningsih, Andria Nisa, Khairi Nugrahmi, Lidya Nugroho, Septiadi Nugroho, Yusuf Wahyu Nurviriana, Savira Octavianson, Dave Nathanael Oki, Helzulmita Oktariani, Gulfi 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 Pratama, Renaldo Pratiwi Pratiwi Purwanto, Muhammad Rizki Puspita Dewi, Puspita Putra, Abhiyoga Deyandra Putra, Rahmad Yunendri Putri, Annisa Nurwanda Putri, Juandela Herina Putri, Maya Seruni Rafanio, Kevin Raharjo, Bangkit Widhi Rahmadeni Rahmadeni Rahmawati, Nurmalinda Rahmi, Mutia Ramadani, Rizki Agung Ramadhan, Andika Ramadhan, Yufiansyah Wahyu Rica Rica, Rica Safangati, Ainun Samsul Arifin Santosa, Suhari Saputra, Tubagus Chandra Saraswati, Iska Sari, Irma Ratna Saumananda Suroso, Nurinda Savitri, Fania Mutiara Sayuti Sayuti Shabrina, Andi sirya, Damara Siswanto, Fajar Hartanto Sitinjak, Jeklin Sodikin Sodikin Sri Nugroho, Amanda Sri Utami Sugino, Agus Suhardi, Fitra Alghifari Sukmayanti, Andini Wulan Sutama, Aditya Suududdin, Suududdin Syafer, Erdimen Syarifudin Syarifudin Syarrah, Ira Siti Syawaldi Afwan, Ahmad Syawaludin, Rahmat Teguh Widodo Triesna Ratulina Tuwindar, Tuwindar Wahyuningsih, Nia Wicaksono, Muhammad Haston Samudra Widiyanta, Antonius Hendri Wulan, Mutia Karunia Antap Yakub, Isnendi Yohana, Kesia Yumarsa, Imam YUNI KURNIAWATI Zulfahmi, Muhammad Riko Yohansyah