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FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT MENABUNG DI BANK SYARIAH : (STUDI KASUS di BSI EX BSM ) Maharani, Renita; Supriyanto, Trisiladi; Rahmi, Mira
JURNAL SYARIKAH : JURNAL EKONOMI ISLAM Vol. 7 No. 2 (2021): Jurnal Syarikah
Publisher : Program Studi Ekonomi Islam FEI UNIDA Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/jsei.v7i2.4483

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh dari religiusitas, pengetahuan produk, kualitas pelayanan, lokasi, dan biaya administrasi terhadap minat menabung di Bank BSI Ex BSM Jakarta Timur. Populasi yang dipilih dalam penelitian ini yaitu nasabah yang memiliki minat menabung di Bank BSI Ex BSM Jakarta Timur. Teknik pengumpulan sampel yang digunakan probability sampling dengan jenis simple random sampling. Sumber data dalam penelitian ini didapatkan dari penyebaran kuesioner kepada 130 responden. Teknik analisis data pada penelitian ini menggunakan SmartPLS 3.0. Hasil yang didapat dari penelitian ini menyatakan bahwa religiusitas dan pengetahuan produk berpengaruh signifikan terhadap minat menabung, sedangkan kualitas pelayanan, lokasi, dan biaya admisnitrasi tidak berpengaruh signifikan terhadap minat menabung.  
Study on Crystal Structure, Surface Area, and Energy Gap Behaviors of Nanotitania Polymorphs Prepared Using Monoethanolamine Manurung, Posman; Maharani, Renita; Rahmayanti, Dita; Yulianti, Yanti; Junaidi; Marjunus, Ronius
Science and Technology Indonesia Vol. 9 No. 2 (2024): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.2.345-353

Abstract

Polymorphous nanotitania samples were prepared from titanium butoxide (TTB) as a precursor using sol-gel processing in ethanol as a solvent, without and with monoethanolamine (MEA). The experiments used 5.25 mL TTB and MEA with varied volumes of 0.5, 1.0, 1.5, and 2.0 mL. The sample without MEA was specified as sample A, and the samples produced using MEA were specified as samples B, C, D, and E, respectively. All samples were calcined at 500 °C for 4 h and then collected data by X-ray Diffraction (XRD), the Brunauer-Emmett-Teller (BET) method used to analyze Surface Area Analyzer (SAA), Transmission Electron Microscopy (TEM), Raman Spectroscopy, and UV-Visible Diffuse Reflectance Spectroscopy (UV-Vis DRS). The results of XRD characterization indicate that samples A and B form anatase phase, while samples C and D are composed of anatase, brookite, and rutile phases, and sample E is consisted of anatase and brookite phases with weight percentages of (94.53 ± 1.72) % and (5.47 ± 0.36) %, respectively. The presence of the three phases of titania is also confirmed by Raman spectroscopy analysis, which showed anatase peaks at 146, 197, 398, and 513 cm-1, brookite peaks at 245 and 402 cm-1, and rutile peaks at 319, 436, and 612 cm-1. According to XRD, the samples have the particle size in the range of 14-19 nm. A representative sample (sample C) was also characterized using TEM, revealing a particle size of 16.0 ± 0.3 nm. This representative sample revealed the largest surface area of 172.2 m2/g, as seen by BET, and the lowest energy gap of 3.03 eV.
Penerapan Diagram Kendali Shewhart pada Model ARMA-GARCH dalam Memantau Proses Keuangan di Pasar Modal Indonesia Maharani, Renita; Suwanda
Bandung Conference Series: Statistics Vol. 5 No. 2 (2025): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v5i2.20556

Abstract

Abstract. The capital market has significant potential to drive the country's economic growth. The Indonesian capital market is inseparable from market uncertainty which influences risk considerations in investing. Financial data modeling using time series methods is effective in modeling stock market returns and volatility. The ARMA model is unable to handle the problem of non-constant residual variance, requiring advanced modeling, namely ARMA-GARCH. However, this model has limitations in monitoring the stability of financial processes. Therefore, a statistical method capable of monitoring financial process stability, namely the Shewhart control chart, is applied. This study uses the ARMA-GARCH model and the Shewhart control chart to model returns and volatility with statistical control tools useful for providing an overview of investment risk in the Indonesian capital market. This study uses data from the Jakarta Composite Index for the period January 2000 to December 2024, totaling 6,089 observations. The results show that the ARMA (1,2) - GARCH (2,1) model is the best model with the smallest AIC and SIC values. The Shewhart control chart for the ARMA (1,2) - GARCH (2,1) model shows 101 uncontrolled signals. This indicates that there were at least 101 market volatility shocks in the Indonesian capital market from January 2000 to December 2024. Abstrak. Pasar modal memiliki potensi besar menjadi motor penggerak pertumbuhan ekonomi negara. Pasar modal Indonesia tidak terlepas dari ketidakpastian pasar yang berpengaruh pada pertimbangan risiko dalam berinvestasi. Pemodelan data keuangan menggunakan metode deret waktu sangat efektif dalam memodelkan return dan volatilitas pasar saham. Model ARMA tidak mampu menangani masalah ragam sisaan yang tidak konstan sehingga diperlukan pemodelan lanjutan yaitu ARMA-GARCH. Namun, model ini memiliki keterbatasan dalam memantau stabilitas proses keuangan. Maka diterapkan metode statistik yang mampu memantau stabilitas proses keuangan yaitu diagram kendali Shewhart. Penelitian ini menggunakan model ARMA-GARCH dan diagram kendali Shewhart untuk memodelkan return dan volatilitas dengan alat kontrol statistik yang berguna untuk memberikan gambaran risiko investasi di pasar modal Indonesia. Penelitian ini menggunakan data Indeks Harga Saham Gabungan (IHSG) periode Januari 2000 sampai Desember 2024 sebanyak 6.089 pengamatan. Hasil penelitian menunjukkan bahwa model ARMA (1,2) – GARCH (2,1) merupakan model terbaik dengan nilai AIC dan SIC terkecil. Diagram kendali Shewhart pada model ARMA (1,2) – GARCH (2,1) menunjukkan sinyal yang tidak terkendali sebanyak 101 kali. Hal ini menandakan bahwa sepanjang periode Januari 2000 sampai Desember 2024 terjadi setidaknya 101 kali guncangan (market volatility) di pasar modal Indonesia.