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All Journal Journal of Comprehensive Science Eduvest - Journal of Universal Studies Jurnal Ekonomi, Manajemen, Akuntansi
Germansah, Germansah
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Aerospace Engineering Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Neuroscience Social Sciences

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Geometric Brownian Motion in Analyzing Seasonality of Gold Derivative Prices Germansah, Germansah; Tjahjana, R. H.; Herdiana, Ratna
Eduvest - Journal of Universal Studies Vol. 3 No. 8 (2023): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v3i8.892

Abstract

Complex financial markets, influenced by complex and interconnected factors, require proper decision making. Gold derivatives, as an increasingly popular trading instrument, have experienced significant growth. However, with high profit potential also comes significant risk. Market analysis, including technical analysis and leveraging seasonality, can be an important tool in reducing risk and making smart decisions. This research aims to assess the effectiveness of the Geometric Brownian Motion (GBM) model in predicting Gold Derivative prices through the application of the Mean Absolute Percentage Error (MAPE) test.In this study, the Brownian Motion Geometric Method and Simple Moving Average are combined to analyze the seasonality of gold derivative prices to provide a view of price movement patterns. The results showed that the Brownian Motion Geometric Method was effective in predicting the price of gold derivatives, with a low error rate. In addition, seasonality analysis reveals monthly price movement patterns that can be a guide for traders and investors. This research provides valuable insights for decision making in gold derivatives trading in dynamic and complex financial markets.
Model Regresi Logistik Biner: Faktor-Faktor yang Mempengaruhi Kepemilikan akun Keuangan di Indonesia Jiblathar, Panji; Germansah, Germansah; Mubarak, Fadhlul
Journal of Comprehensive Science Vol. 4 No. 12 (2025): Journal of Comprehensive Science
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/jcs.v4i12.3852

Abstract

Penelitian ini menganalisis determinan kepemilikan akun keuangan formal di Indonesia pasca-pandemi menggunakan regresi logistik biner pada data Global Findex 2024 (N = 1.067). Variabel independen mencakup usia, pendidikan, pendapatan (quintile), gender, domisili, dan status ketenagakerjaan. Hasil menunjukkan pendidikan tinggi meningkatkan odds kepemilikan sebesar 412% (OR = 5,12; 95% CI = 2,18–14,10; p < 0,001), diikuti pendidikan menengah (OR = 2,43) dan quintile terkaya (OR = 2,22). Gender gap signifikan: perempuan memiliki odds 25% lebih rendah (OR = 0,750; p = 0,042). Status pengangguran menurunkan odds hingga 51% (OR = 0,487). Domisili pedesaan tidak signifikan (p = 0,624), menandakan konvergensi urban-rural akibat digitalisasi. Model valid (VIF < 1,3; Hosmer-Lemeshow p = 0,653; AUC = 0,716). Penelitian ini merekomendasikan intervensi berbasis odds ratio bagi OJK untuk mencapai inklusi 90% pada 2029.
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 Herdiana, Ratna Jiblathar, Panji Mardhotillah, Bunga Mubarak, Fadhlul Sundara, Vinny Yuliani Tjahjana, R. H.