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All Journal Jurnal Paradigma Ekonomika Formatif: Jurnal Ilmiah Pendidikan MIPA JISTech (Journal of Islamic Science and Technology) Journal on Education GERVASI: Jurnal Pengabdian kepada Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat FARABI: Jurnal Matematika dan Pendidikan Matematika Berdikari : Jurnal Ekonomi dan Statistik Indonesia Jurnal Engineering Jurnal Inovasi Pembangunan Journal Of Human And Education (JAHE) Journal of Applied Agricultural Science and Technology Jurnal Riset Mahasiswa Matematika Innovative: Journal Of Social Science Research Multi Proximity: Jurnal Statistika Universitas Jambi Global Education Journal (JUMPER) SEWAGATI: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat dan Riset Pendidikan International Assulta of Research and Engagement Journal of The Indonesian Society of Integrated Chemistry INTAN CENDEKIA: JURNAL PENGABDIAN MASYARAKAT EDUJAVARE: International Journal of Educational Research Jurnal Ekonomi, Manajemen, Akuntansi Journal of Conflict and Social Class (JCSC)
Mardhotillah, Bunga
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Segmentasi Provinsi di Indonesia Menggunakan Metode K-Means Berdasarkan Tujuan Mengakses Internet Tahun 2024 Nabila, Anugrah Putri; Mardhotillah, Bunga
Jurnal Riset Mahasiswa Matematika Vol 5, No 2 (2025): Jurnal Riset Mahasiswa Matematika
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/jrmm.v5i2.38985

Abstract

Kesenjangan digital dan pemahaman tentang cara masyarakat di daerah menggunakan internet sangat penting dalam membuat kebijakan pembangunan yang tepat sasaran di Indonesia. Penelitian ini bertujuan untuk mengelompokkan provinsi ke dalam kelompok-kelompok yang memiliki karakteristik serupa, berdasarkan persentase penduduk yang mengakses internet untuk tujuan tertentu pada tahun 2024. Metode yang digunakan adalah K-Means Clustering, dengan data yang sudah diatur agar mudah dibandingkan. Jumlah kelompok terbaik ditentukan melalui metode Elbow. Penelitian menemukan lima kelompok yang mewakili perilaku pengguna internet yang berbeda, mulai dari daerah yang cenderung hanya mengakses internet secara pasif hingga wilayah yang menjadi pusat aktivitas digital. Contohnya, Kelompok 3 dikenal sebagai pusat ekonomi digital karena tingkat penggunaan internet yang tinggi untuk keperluan jual beli, bekerja dari rumah, dan belajar online. Sementara itu, Kelompok 1 memiliki kesenjangan digital yang tinggi karena adopsi internet rendah di semua aspek. Hasil pemilahan kelompok ini memberikan dasar analisis yang solid dan berdasarkan fakta untuk pemerintah dalam merancang kebijakan yang tepat, seperti meningkatkan literasi digital, membangun infrastruktur, atau melatih tenaga ahli, sesuai dengan kebutuhan masing-masing kelompok.
Pendampingan dan Workshop untuk Penggiat Lingkungan: Pemanfaatan Vizly (AI – Powered Data Analysis) dalam Analisis Statistik Lingkungan Hidup Mardhotillah, Bunga; Shally Yanova; Bambang Irawan; Ade Adriadi; Lailal Gusri; Edi Saputra; Ade Nurdin; Tri Syukria Putra
Journal of Conflict and Social Class (JCSC) Vol. 3 No. 01 (2026): Journal of Conflict and Social Class (JCSC)
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This mentorship and workshop aimed to enhance the capacity of environmental activists to understand and apply statistical analysis to environmental issues. Through the use of Vizly (AI-Powered Data Analysis), participants were introduced to an artificial intelligence-based approach that simplifies data processing, visualization, and interpretation of results. The workshop method included intensive mentoring, theoretical presentations, and hands-on practice using relevant environmental data, such as air quality, waste management, and renewable energy utilization. The workshop was conducted in a systematic manner: identifying participant needs, introducing basic statistical analysis concepts, simulating the use of Vizly, and post-workshop mentoring to ensure continued understanding. The results demonstrated improved skills among participants in processing environmental data more quickly, accurately, and evidence-based. Vizly has been proven to assist environmental activists in producing analyses that can support decision-making, policy advocacy, and environmental program planning. The implications of this activity include facilitating the integration of AI technology into environmental work, while also opening up opportunities for collaboration between academics, government, and communities.
Prediction of Renewable Energy Potential to Prevent Greenflation Using Bayesian Structural Time Series: BSTS with JASP Software to Predict PLTMH Potential Mardhotillah, Bunga; Yanova, Shally; Manab, Abdul; Hais, Yosi Riduas; Saputra, Edi; Adriadi, Ade; Nurdin, Ade
International Assulta of Research and Engagement (IARE) Vol. 4 No. 1 (2026): International Assulta of Research and Engagement (IARE)
Publisher : Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/iare.v4i1.1101

Abstract

The global transition toward renewable energy is increasingly urgent to mitigate climate change and reduce dependence on fossil fuels; however, it also introduces economic risks such as greenflation, driven by rising demand for green commodities. In Indonesia, renewable energy development has become a national priority, with Jambi Province identified as a strategic region due to its significant micro-hydropower (PLTMH) potential. This study aims to predict PLTMH potential as a means of supporting energy transition planning and preventing greenflation through data-driven policy decisions. The research employs a Bayesian Structural Time Series (BSTS) approach using JASP software, integrating Kalman Filter, spike-and-slab regression, and Bayesian Model Averaging. Time series data from 2008–2024 were analyzed with 2,000 MCMC draws and a 1% burn-in to ensure estimation stability. The results demonstrate a strong upward trend in PLTMH capacity, with high model accuracy indicated by an R² value of 0.991, low residual standard deviation, and acceptable prediction uncertainty. Forecasts suggest continued growth in PLTMH capacity over the next two decades before reaching a steady state. The study concludes that BSTS is a robust and reliable method for predicting renewable energy potential and supporting counterfactual policy analysis. This research contributes empirically to applied Bayesian time series modeling and practically to renewable energy policy planning, offering evidence-based insights to enhance energy security and mitigate greenflation risks.
Pengelompokan Provinsi Berdasarkan Dinamika Nasabah-Debitur BPR Syariah Mubarak, Fadhlul; Mardhotillah, Bunga; Sundara, Vinny Yuliani; Germansah, Germansah; Jiblathar, Panji
EKOMA : Jurnal Ekonomi, Manajemen, Akuntansi Vol. 5 No. 3: Maret 2026
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/ekoma.v5i3.14569

Abstract

Penelitian ini bertujuan untuk mengelompokkan provinsi di Indonesia berdasarkan dinamika jumlah nasabah dan debitur Bank Pembiayaan Rakyat Syariah (BPRS) selama periode Februari-Oktober 2025. Data bersumber dari Otoritas Jasa Keuangan (OJK) dan dianalisis menggunakan metode K-Means Clustering dengan dua variabel utama, yaitu rata-rata jumlah nasabah dan debitur per provinsi. Proses analisis meliputi standardisasi data, penentuan jumlah klaster optimal melalui metode Elbow dan Silhouette, serta visualisasi hasil pengelompokan. Hasil penelitian menunjukkan terbentuknya tiga klaster: (i) klaster dengan aktivitas BPRS tinggi (Jawa Barat dan Jawa Timur), (ii) klaster dengan aktivitas rendah yang mencakup sebagian besar provinsi, dan (iii) klaster menengah dengan rasio debitur/nasabah relatif tinggi seperti Nusa Tenggara Barat dan Kepulauan Riau. Temuan ini mengindikasikan adanya heterogenitas antarwilayah yang signifikan, sehingga kebijakan pengembangan BPRS perlu disesuaikan dengan karakteristik masing-masing klaster. Penelitian ini memberikan kontribusi dalam perumusan strategi segmentasi berbasis data untuk meningkatkan inklusi keuangan syariah di Indonesia.
Co-Authors Abd Fatah, Rahmat Abdul Manab Ade Adriadi Ade Nurdin Adilah, Silvia Nur Adne Sagita Panjaitan Affan Malik Affan Malik Affan, Affan Afreni Hamidah Afrianda, Vionica Agustina, Ti’ah Alfarez, Dzaki Ade Alim, Khairul Alisyahbana, Iman Utoya Amanda, Tasya Arif Arif Asfahani, Asfahani Auqi B. B., S. Farrel Azizah, Suci Midsyahri Bambang Haryadi Bambang Irawan Basayarahil, S. Farrel Auqi Baswara Corry Sormin CUT MULTAHADAH Damris Muhammad Dewi Iriani Ditya Ismi Budiarti Edi Saputra Edi Saputra EFENDI Elisa, Edi Fadli, Amril Feriana, Rina Fernando Mersa Putra Fuldiaratman Germansah, Germansah Gusmanely Z Gusmanely Z, Gusmanely Z Gusmi Kholijah Gusri, Lailal Haikal, Ibnu Hambali, Jhoni Hadi Harahap, Subur Hermanetty Hermanetty Hilmiah Hilmiah, Hilmiah I Gede Wiratmaja Ira Galih Prabasari Jiblathar, Panji Julistia, Andrini Kamid, Kamid kevin, kevin panjaitan Khaira, Ulfa kholijah, gusmi Komang Ariyanto M Rafly Maretha M. RIZKY RAMADHAN Maharani, Cindy Maria Risnawati Mubarak, Fadhlul Multahadah, Cut Nabila, Anugrah Putri Nainggolan, Hermin Ngatijo Ngatijo Nizlel Huda Nurhadi, Miranda Sukma Olvin Prasetia Pangesti, Zahwa Rifsya Prakoso, Maliki Aji Prananingrum, Dwi Kartika Putri, Desfita Eka Putri, Nabilah Shahada Putrie, Rena Augia Rahmawati, Rahmawati Ramadhan, Afif Kurnia rarasati, niken Rayandra Asyhar Rena Augia Putrie Revis Asra Reza, Aidini Desfa Rijaya, Candra Riyan Hidayat Rizqa Raaiqa Bintana Rodhiyah, Zuli Sa'diyah, Sa'diyah Safitri, Yuliana Sarmada, Sarmada Seeletse, Solly Matshonisa Sherly, Issaura Sihombing, Febriana Sihotang, Wanti Perinduri Sipni, Dawam Mussurur Sormin, Corry Sufri Sufri Sufri Sufri Sundara, Vinny Yuliani Susilawati Susilawati Suzanti, Sriliah Syahrul Syahrul Syamsyida Rozi Tamrin Fathoni Tedjo Sukmono Tri Syukria Putra Trinata, Ario Surya Ulfa Khaira, Ulfa Wardi Syafmen Wardi Syafmen Wibowo, Salsa Dyvia Wijaya, Untung Yanova, Shally Yosi Riduas Hais Yuniati, Triyana Yurinanda, Sherli Yurinanda, Sherly Yusnidar Yusnidar Z, Gusmanely Zurweni Zurweni Zurweni