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Pengaruh Sertifikat Halal Terhadap Pendapatan Usaha dan Halal Awareness UMKM di Sektor Halal Food (Studi Pada Pelaku Usaha UMKM Kecamatan Cihideung Kota Tasikmalaya) Muiz, Aris Nurul; Damayanti, Aulia; Indra, Regina; Marlina, Lina
J-Alif : Jurnal Penelitian Hukum Ekonomi Syariah dan Budaya Islam Vol 8, No 2 (2023): J-Alif, Volume 8, Nomor 2, November 2023
Publisher : Fakultas Agama Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jalif.v8i2.4829

Abstract

Produk halal kini telah menjadi tren dunia karena memiliki pasar yang potensial bahkan dengan adanya peningkatan industri halal, sektor pertumbuhan ekonomi mengalami kemajuan, kesadaran tentang konsep halal mulai meningkat, dan banyaknya perusahaan di bidang produk dan layanan mulai merespon kebutuhan konsumen. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh variabel sertifikat halal terhadap variabel pendapatan usaha dan halal awareness UMKM. Jenis penelitian ini menggunakan metode deskriptif kuantitatif. Data yang digunakan dalam penelitian ini adalah data primer. Jumlah data yang diperoleh sebanyak 27 responden yang tersebar di daerah Kecamatan Cihideung, Kota Tasikmalaya. Hasil pengolahan data yang diolah menggunakan SPSS 23 dengan regresi linier berganda yang menunjukan bahwa variabel sertifikat halal berpengaruh secara signifikan terhadap pendapatan penjualan usaha, hal ini dapat dilihat dari signifikasi sertifikat halal sebesar 0,064 yang berarti lebih besar dari tingkat signifikasi yang digunakan yaitu 0,05 atau 5%. Berdasarkan hasil pengolahan data peneliti menunjukkan bahwa variabel sertifikat halal berpengaruh signifikan terhadap halal awareness UMKM, hal ini dapat dilihat dari signifikasi halal awareness sebesar 0,093 yang berarti lebih besar dari tingkat signifikasi yang digunakan yaitu 0,05 atau 5%.
ANALISIS PENGENDALIAN INTERNAL ORGANISASI PENGELOLA ZAKAT (OPZ) PADA LAZNAS “X” DI SURABAYA DALAM RANGKA MENINGKATKAN EFEKTIVITAS DAN EFISIENSI ORGANISASI Damayanti, Aulia; Harindahyani, Senny
CALYPTRA Vol. 7 No. 1 (2018): Calyptra : Jurnal Ilmiah Mahasiswa Universitas Surabaya (September)
Publisher : Perpustakaan Universitas Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.782 KB)

Abstract

Penelitian ini bertujuan untuk mengetahui kelima komponen pengendalian internal yang diterapkan dalam Organisasi Pengelola Zakat (OPZ) dalam ketiga aktivitas pada LAZNAS “X” yang ada di Surabaya. Penelitian ini secara khusus ingin mengetahui bagaimana penerapan pengendalian internal yang baik untuk OPZ sehingga dapat meningkatkan efektivitas dan efisiensi dari organisasi. Jenis penelitian yang digunakan adalah applied research dengan metode pendekatan kualitatif. Dalam penelitian ini disebutkan rekomendasi bagi LAZNAS “X” agar dapat meningkatkan pengendalian internalnya dalam menjalankan aktivitas OPZ. Hasil penelitian menemukan bahwa perlu adanya peningkatan dari pengendalian internal yang diterapkan dalam masing-masing aktivitas. Peningkatan diperlukan sebab pengendalian internal yang masih lemah di salah satu komponen. Peningkatan pengendalian internal dalam aktivitas OPZ mampu meningkatkan efektivitas dan efisiensi organisasi.
Voice-Based Emotion Identification Based on Mel Frequency Cepstral Coefficient Feature Extraction Using Self-Organized Maps and Radial Basis Function Nikmah, Asrivatun; Damayanti, Auli; Winarko, Edi
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 1 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i1.68246

Abstract

Speech recognition is one of the most popular research fields, one of which is about emotion identification. Voice-based emotion identification is carried out to determine the pattern of emotions using the depth analysis mechanism of voice signal development and feature extraction that carries the emotional characteristic parameters of the speaker's voice. Furthermore, the emotional characteristics of the speaker's voice are classified using an artificial neural network method to recognize patterns. In this study, emotion identification from voice signal data is classified into angry, sad, happy, and neutral emotions. The stages of voice-based emotion identification, including the feature extraction stage using the mel frequency cepstral coefficient, produce coefficient values, which will be used in the identification stage using the Self Organized Maps method on the Radial Basis Function.
ANALISIS RASIO LIKUIDITAS, PROFITABILITAS DAN SOLVABILITAS UNTUK MENGUKUR KINERJA KEUANGAN PADA PT AKR CORPORINDO TBK PERIODE 2014-2023 Damayanti, Aulia; Mardiana, Sri
JIAR : Journal Of International Accounting Research Vol 4 No 01 (2025): JIAR : Journal Of International Accounting Research
Publisher : Pusat Studi Ekonomi Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/jiar.v4i01.1701

Abstract

Penelitian ini bertujuan untuk mengetahui bagaimana kinerja keuangan PT AKR Corporindo Tbk periode 2014-2023 dengan menggunakan Rasio Likuiditas, Rasio Profitabilitas, dan Rasio Solvabilitas. Penelitian ini menggunakan metode deskriptif asosiatif yang berdasarkan laporan keuangan PT AKR Corporindo Tbk periode 2014-2023. Berdasarkan dari hasil perhitungan Rasio Likuiditas yang menggunakan Current Ratio, Cash Ratio, dan Quick Ratio dalam menilai kinerja keuangan PT AKR Corporindo Tbk periode 2014-2023, diperoleh nilai Current Ratio dinyatakan “Kurang Baik”, nilai Cash Ratio dinyatakan “Kurang Baik” dan Quick Ratio dinyatakan “Kurang Baik”. Hasil perhitungan Return On Assets yaitu “Kurang Baik”, Return On Equity dinyatakan “Kurang Baik”, dan Net Profit Margin dinyatakan “Kurang Baik”. Sedangkan perhitungan Debt to Assets Ratio dinyatakan “Kurang Baik”, perhitungan Debt to Equity Ratio dinyatakan “Kurang Baik” dan Long Term Debt to Equity Ratio dinyatakan “Sangat Baik”.
Pengaruh media sosial terhadap sosialisasi remaja di era digital Damayanti, Aulia; Khasanah, Nur
Jurnal Pendidikan Agama Islam Vol 2 No 2 (2025): Jurnal Pendidikan Agama Islam
Publisher : Sekolah Tinggi Agama Islam (STAI) AL-IKHLAS DAIRI SIDIKALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64677/ppai.v2i2.200

Abstract

This research seeks to examine how social affects the socialization process of adolescent in the contemporary digital age. The rapid advancement of information technology has transformed patterns of social communication, especially among teenagers who are active social media users. This research employs a library research method by reviewing relevant academic literature. The findings indicate that social media exerts a dual influence on adolescent socialization. Positively, it expands social networks, enhances creativity, and serves as a medium for learning and character development. Conversely, excessive use may lead to psychological disorders, reduced face-to-face interactions, and deviant behaviors such as cyberbullying and hedonism. Efforts to optimize adolescent socialization in the digital era can be achieved through parental supervision, digital literacy education in schools, and the cultivation of responsible online ethics.
Strengthening Women’s Roles Through Banking Support for Sustianable Maritime Sector Development Agustuty, Lasty; Ramlah, St.; Damayanti, Aulia; Patimah, Patimah
Al-Buhuts Vol. 21 No. 2 (2025): Al-Buhuts
Publisher : Institute Agama Islam Negeri (IAIN) Sultan Amai Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30603/ab.v21i2.6887

Abstract

This study aims to analyze the factors influencing business credit disbursement by banks and their impact on increasing the capacity of MSMEs and sustainable economic growth. The sample in this study was women entrepreneurs in the coastal tourist area of Bulukumba Regency. The analytical method used was a mixed-method approach, with quantitative measures using path analysis and qualitative measures using a hermeneutic approach. The results indicate that the credit security system banks offer is an essential factor in entrepreneurs' credit decision-making. Furthermore, the results also demonstrate the influence of bank credit disbursement on increasing the capacity of MSMEs, both in terms of income and capability. This increase in business capacity can ultimately impact the country's economic growth
Cryptocurrency Price Prediction Using Long Short Term Memory Algorithm and Moving Average Convergence Divergence Abiyyu Dicky Pratama; Auli Damayanti; Edi Winarko
Contemporary Mathematics and Applications (ConMathA) Vol. 8 No. 1 (2026)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v8i1.76496

Abstract

Cryptocurrency is one of the digital assets that is increasingly popular for investment in Indonesia. However, the price movements of cryptocurrencies tend to be volatile, as prices can change at any time and are not easy to predict. This study aims to predict cryptocurrency price movements using the Long Short-Term Memory Algorithm (LSTM) and Moving Average Convergence Divergence (MACD). LSTM is an algorithm used to generate optimal weights and biases in modeling cryptocurrency data, while MACD is used to analyze trends and momentum in cryptocurrency prices. The data used consists of daily closing prices of Bitcoin (BTC), totaling 809 data points. The data is divided into 70% (566 data) for the training process and 30% (243 data) for the testing process. From this data, patterns are formed with five inputs and one output, resulting in 561 patterns for the training process and 238 patterns for the testing process. The LSTM and MACD processes for predicting cryptocurrency include procedures for data input, data division, parameter initialization, LSTM calculation, average error evaluation, and MACD calculation. Based on the program implementation, with several parameter values, the average error difference obtained during the training stage is 0.0695 and 0.0303 during the testing stage. Because the average error difference obtained is relatively small, this indicates that LSTM-MACD is capable of recognizing data patterns and predicting data effectively.