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All Journal Dinamis : Journal of Islamic Management and Bussiness JURNAL PENDIDIKAN TAMBUSAI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Perak Malahayati : Pengabdian Kepada Masyarakat PETITA Sinomika Journal: Publikasi Ilmiah Bidang Ekonomi dan Akuntansi Jurnal Sains Informatika Terapan (JSIT) Liaison Journal of BEST JURNAL ILMIAH GEMA PERENCANA Edukasi
Affandi, Muhammad
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Nursing Public Health Social Sciences Other

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Product Differentiation and Monopolistic Market Competition in the Retail Coffee Industry in Indonesia: A Review of Sharia Compliance and Its Impact on Consumer Choices Nurbaeti, Feby; Affandi, Muhammad; Safri, Rahmat; Mukti, Titania
Dinamis : Journal of Islamic Management and Bussiness Vol. 8 No. 2 (2025): Oktober : Journal of Islamic Management and Business
Publisher : Institut Agama Islam Negeri Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/dinamis.v8i2.7142

Abstract

The modern coffee industry in Indonesia has grown rapidly with the emergence of popular brands such as Kopi Kenangan, Janji Jiwa, and Fore Coffee. These brands operate in a monopolistic competition market structure, characterized by many sellers offering similar but differentiated products. This study aims to analyze the market structure, differentiation strategies, and the nature of competition among leading coffee brands, as well as to examine their alignment with Islamic economic principles, such as fairness, transparency, and the prohibition of unhealthy competition. This research employs a descriptive qualitative method by collecting secondary data and conducting limited interviews with consumers and business actors. The results indicate that while the competition is generally fair, aggressive promotional strategies and market dominance by larger brands may create imbalances that warrant further ethical evaluation from an Islamic economic perspective.
ANALISIS TINGKAT KEPARAHAN COVID-19 DI SUATU NEGARA MENGGUNAKAN METODE K-MEDOID CLUSTERING Amelia, Syahputri; Yusri, Eldo; Irwansyah, Bambang; Andira, Ayu; Sukri, Muhammad; Yafi, Muhammad Fauzan; Affandi, Muhammad
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5787

Abstract

Abstract: This study aims to classify the severity of COVID-19 cases based on patient and region data using the K-Medoid Clustering method. COVID-19 has varying degrees of symptom severity, requiring cluster analysis to identify severity patterns to support decision-making in healthcare resource allocation and policy formulation. The data used included the number of positive cases, recovered cases, deaths, the average age of patients, and comorbidity levels. The results showed that the K-Medoid method was able to effectively cluster the data. In the raw dataset, the percentage of patients not infected with COVID-19 was 62.62%, while the percentage of infected patients was 37.38%. Based on sample characteristics, non-obese patients accounted for 74.54%, obese patients 25.46%, and patients with a combination of obesity and cardiovascular disease 0.57%. Keywords: Covid-19, Severity, K-Medoid Clustering, Data Mining Abstrak: Penelitian ini bertujuan untuk mengelompokkan tingkat keparahan kasus COVID-19 berdasarkan data pasien dan wilayah menggunakan metode K-Medoid Clustering. COVID-19 memiliki variasi tingkat keparahan gejala, sehingga diperlukan analisis klaster untuk mengidentifikasi pola keparahan yang mendukung pengambilan keputusan dalam alokasi sumber daya kesehatan dan perumusan kebijakan. Data yang digunakan meliputi jumlah kasus positif, kasus sembuh, kasus meninggal, usia rata-rata pasien, serta tingkat komorbiditas. Hasil penelitian menunjukkan bahwa metode K-Medoid mampu melakukan pengelompokan data secara efektif. Pada dataset mentah, persentase pasien tidak terjangkit COVID-19 sebesar 62,62%, sedangkan pasien terjangkit sebesar 37,38%. Berdasarkan karakteristik sampel, pasien non-obesitas memiliki persentase 74,54%, pasien obesitas 25,46%, dan pasien dengan kombinasi obesitas serta penyakit kardiovaskular sebesar 0,57%. Kata Kunci : Covid-19, Tingkat Keparahan, K-Medoid Clustering, Data Mining
Co-Authors Adna, Alfira Amelia, Syahputri Ayu Andira Br Dalimunthe, Henny Herawaty E, Muhammad Yusuf Ash Sidiq Emy Hajar Abra Fatik Rahayu Givandi, Muhammad Hadiyanti , Puji IRVANSYAH, ADI Irwansyah, Bambang Muhammad Sukri Mukti, Titania Nurbaeti, Feby Prasetya, Bustamil Ibnu ratna wijayanti, ra afera Safri, Rahmat Sasmita, Karta Shandy Aditya, Shandy soewandi, verena Soimah, Fitri Suherman, Suherman Ulandari, Putri wijayanti, ra afera ratna Yafi, Muhammad Fauzan Yulendasari, Rika Yusri, Eldo