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All Journal Jurnal Pengabdian UNDIKMA Journal of Mathematics, Computation and Statistics (JMATHCOS) Scripta Economica: Journal of Economics, Management, and Accounting
Dewi Leonita Sari
Institut Teknologi Kalimantan
Religion Agriculture, Biological Sciences & Forestry Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Empowering Local MSMEs through Branding, Product Design, and Digital Marketing: A Community Engagement Program at Pringgondani Market, Balikpapan Mega Silfiani; Irma Fitria; Hairul Irawan; Rianto Padli; Dewi Leonita Sari; Nur Annisa; Nadya Alivia Raaph; Kayla Salbina Zahra; M. Daffa Rivaldy Darwis; Sunrie Kristella Lastiur; Michell Patricia
Jurnal Pengabdian UNDIKMA Vol. 7 No. 1 (2026): February
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v7i1.18166

Abstract

This community service program aims to strengthen the capacity of micro, small, and medium enterprises (MSMEs) in branding, product design, and digital marketing in order to enhance their business competitiveness. The program was implemented through a series of training sessions and mentoring activities involving 57 MSME participants. It consisted of three main components: (1) branding and business preparation, (2) product and packaging design using simple digital tools, and (3) social media–based marketing for digital promotion. Evaluation was conducted using pre- and post-training tests, structured questionnaires, and visual documentation of product packaging. The data were analyzed using descriptive statistics and comparative analyses of participants’ test scores and design outputs. The results indicate substantial improvements in participants’ understanding of branding principles, design aesthetics, and digital literacy. Quantitatively, the average test score increased from 9.1 in the pre-test to 10.0 in the post-test, and many participants successfully redesigned their product packaging and began using social media more systematically for promotional purposes. As a result, MSME owners developed clearer product identities, more attractive packaging, and more consistent online engagement. Overall, the program demonstrates that short-term, community-based interventions can effectively enhance MSME competitiveness and digital readiness while supporting sustainable local economic growth. These findings underscore the importance of integrating creativity, technology, and community participation in MSME empowerment initiatives.
Peran Inovasi dalam Menghubungkan dan Memperkuat Hubungan Manajemen Risiko Perusahaan dengan Kinerja UMKM di Indonesia Ferdiansyah Pratama; Nia Lorenza Br Sinuhaji; Dewi Leonita Sari; Alvianus Kristian Sumual
Journal of Economics, Management, and Accounting Vol 1 No 1 (2025): July: Scripta Economica: Journal of Economics, Management, and Accounting
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65310/7chb4p65

Abstract

Piutang merupakan salah satu akun krusial dalam laporan keuangan perguruan tinggi karena berasal dari biaya pendidikan, layanan akademik, dan kerja sama institusional yang apabila tidak dikelola secara efektif dapat meningkatkan risiko ketidakwajaran saldo serta menyebabkan salah saji material. Penelitian ini bertujuan menganalisis prosedur audit atas ketidakwajaran piutang pada perguruan tinggi melalui studi kasus pada Kantor Akuntan Publik (KAP) Ramdany guna menggambarkan langkah-langkah audit dalam memastikan kewajaran penyajian akun piutang. Penelitian menggunakan metode deskriptif eksploratif dengan teknik pengumpulan data berupa observasi langsung proses audit serta telaah dokumen audit, laporan keuangan, dan kertas kerja pemeriksaan, kemudian dianalisis secara kualitatif. Hasil penelitian menunjukkan bahwa KAP Ramdany menerapkan prosedur audit substantif dan analitis untuk menguji asersi eksistensi, kelengkapan, hak dan kewajiban, penilaian, serta penyajian piutang dan menemukan ketidakwajaran pada saldo piutang mahasiswa nonaktif yang belum dicadangkan maupun diklasifikasikan secara tepat sehingga menimbulkan overstatement aset lancar. Atas temuan tersebut auditor memberikan opini wajar dengan pengecualian dan merekomendasikan penguatan sistem pengendalian internal, pembaruan kebijakan pencadangan piutang, peningkatan efektivitas penagihan, dan digitalisasi sistem pencatatan.
Comparative Modelling of Sharia-Compliant Stock Returns and Volatility Using GRU–GARCH and DES–GARCH: Evidence from Telkom Indonesia Indrawan Indrawan; Fadeli Muhammad Habibie; Magdalena Effendi; Nurul Hidayat; Dewi Leonita Sari; Jesselyn Nixie Amadea; Nabela Ariyaninda Budi Astutik
Journal of Mathematics, Computations and Statistics Vol. 9 No. 3 (2026): Volume 09 Issue 03 (September 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/5yr4h156

Abstract

The integration of deep learning and econometric models has become an active research direction in modern computational finance, particularly for capturing the nonlinear dynamics and time-varying volatility that characterize equity markets. In the Islamic capital market, reliable modeling of return and volatility matters for risk assessment and for investment decisions that stay consistent with Sharia principles. This study compares two hybrid models, GRU–GARCH and DES–GARCH, for jointly modeling the return and conditional volatility of PT Telekomunikasi Indonesia Tbk (TLKM), a highly liquid Sharia-compliant stock. A Gated Recurrent Unit (GRU) network and Double Exponential Smoothing (DES) were each used to model the conditional mean of the daily log returns, while the residuals of both were modeled with a GARCH specification to capture volatility clustering. The analysis drew on 2,463 daily observations from March 2016 to March 2026, split into 80% training and 20% testing data, with model selection based on validation performance and information criteria. Forecast accuracy was measured with the scale-independent Mean Absolute Scaled Error (MASE), complemented by the QLIKE loss for the variance forecasts, the Diebold–Mariano test for pairwise comparison, and a Kupiec backtest for Value-at-Risk. Both hybrids beat a naïve benchmark, and a GARCH(1,1) model with Student-t innovations adequately described the strong volatility persistence (about 0.98) and the heavy tails found in the return series. Contrary to the common expectation that deep learning improves accuracy, the parsimonious DES–GARCH model produced a lower MASE (0.914 against 0.983) and a lower QLIKE (2.68 against 2.83) than GRU–GARCH, and the gap in mean-forecast accuracy was statistically significant under the Diebold–Mariano test. DES–GARCH also delivered better-calibrated Value-at-Risk, passing the Kupiec test at both confidence levels while GRU–GARCH did not. These results suggest that, for daily Sharia-stock returns whose predictable component is small, a simpler smoothing-based mean model can match or exceed a deep learning model, and that a strong classical baseline should be established before more complex architectures are adopted for operational risk work.
Co-Authors Alvianus Kristian Sumual Fadeli Muhammad Habibie Ferdiansyah Pratama Hairul Irawan Indrawan Irma Fitria Jesselyn Nixie Amadea Kayla Salbina Zahra M. Daffa Rivaldy Darwis Magdalena Effendi Mega Silfiani Michell Patricia Nabela Ariyaninda Budi Astutik Nadya Alivia Raaph Nia Lorenza Br Sinuhaji Nur Annisa Nurul Hidayat Rianto Padli Sunrie Kristella Lastiur