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All Journal Jurnal Sains dan Seni ITS E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Matematika Sains dan Teknologi BENTANG : Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil JMM (Jurnal Masyarakat Mandiri) EIGEN MATHEMATICS JOURNAL Variance : Journal of Statistics and Its Applications Specta Journal of Technology Jurnal Pengabdian UNDIKMA Buletin Statistika dan Aplikasi Terkini JOMPA ABDI: Jurnal Pengabdian Masyarakat Jurnal Statistika dan Komputasi (STATKOM) PIKAT JPNM : Jurnal Pustaka Nusantara Multidisiplin Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi Equiva International Journal of Computing Science and Applied Mathematics-IJCSAM
Mega Silfiani
Institut Teknologi Kalimantan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Transportation Other

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Empowering New Capital Zones: East Kalimantan’s Economic District Outlooks Using Location Quotient and Cluster Analysis Mega Silfiani; Diana Nurlaily; Irma Fitria
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 10 No. 2 (2024)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v10i2.4613

Abstract

This research focuses on investigating the economy of the new capital buffer zone by identifying and clustering its leading sectors in GRDP (Gross Regional Domestic Product) of East Kalimantan. The identification of a region’s leading sector through LQ (Location Quotient) index has proven to be effective. In addition, k-means clustering and Self-Organizing Maps (SOM) are adopted to provide comprehensive insights. The results show that LQ index quickly identifies the main sectors in each district of East Kalimantan. In addition, the kmeans clustering has better performance than SOM based on the Silhouette coefficient. This meticulous analysis confirms the existence of two distinct clusters, one including eight members and the other consisting of only two. Anticipating future research endeavours, the exploration of various approaches for constructing clusters, encompassing both hierarchical and non-hierarchical approaches, provides the potential to enhance the performance of clusters. By investigating this structure, a more comprehensive comprehension of the economic framework of East Kalimantan can be achieved, as well as its potential role as a buffer for the capital region.
Prediksi Jarak Luncur Longsoran Berdasarkan Parameter Geometri Lereng dan Tipe Batuan: Landslide Distance Prediction Based on Slope Geometry and Rock Type Parameters Dyah Wahyu Apriani; Aulia Putri Salsabila; Christianto Credidi Khala; Mega Silfiani
Bentang : Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil Vol 11 No 2 (2023): BENTANG Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil (Juli 2023)
Publisher : Universitas Islam 45

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/bentang.v11i2.6950

Abstract

landslide disaster. Based on this fact, a method is needed to predict the range of landslides to minimize the impact of disaster losses. The empirical statistical method is one of the methods that can be used to predict landslides by taking input data from the history of previous landslide events. This research aims to find the best modeling form for sliding distance prediction and which parameters influence a landslide's sliding distance prediction. This study used multiple linear regression methods. The data used in this study are geometric slope parameters in the form of slope height (H), original slope (θ), landslide area (A), and rock type (RT). The data was taken from the 2015-2021 PVMBG landslide investigation report and used the Google Earth and Global Mapper program. Based on the analysis of the best empirical model that can predict the sliding distance of a landslide log Lmax = 0,387 – 0,097 RT + 0,230 log H + 0,458 log A – 0,220 tan θ with an R2 value of 0,94 and an average estimated error of 31,56%. The parameter that has the most influence on the prediction of sliding distance is the area affected by the landslide (A).
Pengembangan UMKM bagi Masyarakat di Kawasan Wisata Pasar Tumpah Pringgondani Silfiani, Mega; Fitria, Irma; Irawan, Hairul; Padli, Rianto; Sari, Dewi Leonita; Annisa, Nur; Raaph, Nadya Alivia; Zahra, Kayla Salbina; Darwis, M Daffa Rivaldy; Lastiur, Sunrie Kristella; Patricia, Michell
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 17, No 1 (2026): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v17i1.26698

Abstract

Pasar tradisional memegang peran penting dalam mendukung aktivitas ekonomi kerakyatan dan menjadi pusat perputaran ekonomi lokal, terutama bagi pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) di Indonesia. Keberadaan pasar tradisional tidak hanya sebagai tempat transaksi, tetapi juga sebagai ruang tumbuhnya wirausaha lokal. Namun, di tengah pesatnya perkembangan teknologi digital, pelaku UMKM dituntut untuk beradaptasi, khususnya dalam hal strategi promosi dan pengembangan produk agar tetap kompetitif. Kegiatan Pengabdian kepada Masyarakat ini dilaksanakan di Pasar Tumpah Pringgondani, Balikpapan, dengan tujuan utama meningkatkan kapasitas pelaku UMKM dalam aspek desain produk dan strategi branding yang efektif melalui pemanfaatan media sosial. Rangkaian kegiatan diawali dengan proses identifikasi kebutuhan peserta melalui penyebaran kuesioner untuk merancang pendekatan pelatihan yang tepat sasaran. Selanjutnya, dilakukan pelatihan pengolahan pangan berbasis potensi lokal, yaitu sari nanas dan rumput laut, yang dirancang untuk meningkatkan keterampilan praktis, nilai tambah produk, serta daya tarik visual. Pelatihan ini juga mendorong kreativitas dan inovasi pelaku UMKM dalam menghasilkan produk unggulan. Diharapkan, melalui program ini, pelaku UMKM dapat meningkatkan daya saing, memperluas jangkauan pemasaran secara digital, serta memberikan kontribusi nyata terhadap pertumbuhan ekonomi lokal yang berkelanjutan.
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.
Comparison of Several Univariate Time Series Methods for Inflation Rate Forecasting Salfina Salfina; Yunissa Hernanda; Mega Silfiani
Eigen Mathematics Journal Vol 7 No 2 (2024): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i2.200

Abstract

Forecasting inflation is very crucial for a country because inflation is one of indicator to measure development of the country. This study aims to evaluate the effectiveness of three univariate time series methods i.e., ARIMA (Autoregressive Integrated Moving Average), Double Exponential Smoothing (DES), and Trend Projection (TP), in forecasting Indonesia’s monthly inflation rates using data from 2018 to 2022. The analysis identifies DES as the most accurate method, evidenced by its lowest Root Mean Square Error (RMSE) value of 2.9296, outperforming ARIMA and TP, which have RMSE values of 13.1479 and 3.47053, respectively. Consequently, DES was selected as the preferred model for forecasting inflation over the next 36 month, with the forecasts indicating a consistent downward trend in inflation throughout the year. While these findings highlight DES's effectiveness, the study also acknowledges limitations, including its reliance on univariate models that do not incorporate other economic variables, and the potential limitations of the dataset’s specific time frame. To address these limitations, future research should consider multivariate models, integrate machine learning techniques, and conduct scenario analyses to improve forecast accuracy and robustness. Despite these constraints, the study provides valuable insights into inflation forecasting in Indonesia, offering a practical tool for policymakers and contributing to more informed economic decision-making.
Co-Authors Agung Prabowo Akbar Taufik Amrullah Aprilianti, Dwi Savira Aulia Putri Salsabila Aulia, Aleyda Kania Farra Azka, Muhammad Christianto Credidi Khala Darwis, M Daffa Rivaldy Dewi Leonita Sari Diana Nurlaily Diana Nurlaily Dyah Wahyu Apriani Dyah Wahyu Apriani Farida Nur Hayati Ferdy Novri Firdaus, Andi Adam Fitria, Irma Fitria, Irma Fitriani, Yustina Hairul Irawan Hanifatuzzuhro, Retno Lelly Winda Hariyadi, Fahri Dwi Hermayanti, Naura Attya Irawan, Hairul Irma Fitria Kayla Salbina Zahra Khoiriyah, Nurhastivania Sohifatul Lastiur, Sunrie Kristella Lembang, Gebryani Rante Lumintang, Indah Ayu M. Daffa Rivaldy Darwis Magh Heryan Tudaan Michell Patricia Muhammad Iqbal Nadya Alivia Raaph Novelinda, Resti Nur Annisa Nur Annisa Nurlaily, Diana Padli, Rianto Patricia, Michell Raaph, Nadya Alivia Rama, Luthfy Ahmad Rezki, Surya Muhammad Rianto Padli S, Hadiyyan Falakha Salfina Salfina Sari, Dewi Leonita Sembiring, Brema Suhartono Suhartono Sunrie Kristella Lastiur Surya Puspita Sari, Surya Puspita Wijayanti, Anis Fadillah Winda, Retno Lelly Yunissa Hernanda Zahra, Kayla Salbina