Garuda - Garba Rujukan Digital

PEMODELAN ARIMA-GARCH UNTUK VOLATILIAS DAN VALUE AT RISK PADA SAHAM PT. GUDANG GARAM TBK Rosi Ramayanti; Dodi Devianto; Delvia Alhusna
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.373

Investment is one of the development factors in economic activity, there are two basic things that investor must know before making investment decisions, namely: returns and risk. One of the statistical methods to calculate the maximum loss in investment is Value at Risk (VaR). this study aims to calculate VaR on the closing stock price data of Pt. Gudang Garam TBK for the daily period starting from 4 January 2021 to 30 December 2021. Log return data is model by ARIMA. The ARIMA model contains a heteroscedasticity effect so it is inadequate for modelling, one of the models that can overcome the heteroscedasticity problem is the ARCH-GARCH model. Forecasting the volatility of the data is done using the ARCH-GARCH model. The results show that the GARCH (1,1) is the best model for predicting volatility. Volatility is predicted for the next 30 days, after the volatility forecasting results are obtained, the VaR calculation can be continued. Based on the results, it shows that volatility increases over time, which means that the risk that investor will accept will be higher and the returns will also be greater

Integer Linear Programming In Production Profit Optimization Problems Using Branch And Bound Methods & Gomory Cutting Plane Nurweni putri; Maya Sari Syahrul; Rosi Ramayanti
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 3 (2024): May 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i3.32888

Integer Linear Programming is a mathematical model that allows the results of solving cases in linear programming in the form of integers. Methods to solve Integer Programming problems include the Branch and Bound Method and the Gomory Cutting Plane Method. Both of these methods have certain rules for adding new constraint functions until an optimal solution to an integer is obtained. The purpose of this study is to optimize the profits of the production of UMKM Capal Classic Shoes Kab. Agam by using the Branch and Bound method and the Gomory Cutting Plane method and analyzing the comparison of optimal results resulting from the two methods. The data used in the study are data on raw materials for making classic sandals and profit data. The results obtained by these two methods produce the same maximum profit, namely RP. 664,000 with each producing 15 pairs of men's sandals and 13 pairs of women's sandals. But in its completion, the Branch and Bound method requires many iterations and a longer time compared to the Gumory Cutting plane method.

Penerapan Logika Fuzzy Menggunakan Metode Tahani Untuk Pengambilan Keputusan Kenaikan Jabatan Di PT. Prioritas Outlet Bukittinggi Rina, Iswan; Syahrul, Maya Sari; Ramayanti, Rosi
Jurnal Penelitian Dan Pengkajian Ilmiah Eksakta Vol 3 No 1 (2024): Jurnal Hasi Penelitian Dan Pengkajian Ilmiah Eksakta - JPPIE
Publisher : LPPM Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jppie.v3i1.1397

Kenaikan jabatan merupakan suatu faktor yang sangat penting bagi perencanaan karir karyawan, dan juga menjadi dorongan untuk seseorang untuk maju menjadi lebih baik. Seringkali proses kenaikan jabatan dilakukan secara manual, atau secara objektif yang mengakibatkan kecemburuan atau kesenjangan sosial antar karyawan, dan dalam mengambil keputusan kenaikan jabatan banyak melibatkan aspek-aspek yang berupa himpunan samar (alamiah), sementara data hasil penilain masih berupa nilai pasti. Hal ini tentunya memakan banyak waktu untuk mengkonversi dari nilai pasti tersebut kedalam himpunan samar apabila dilakukan secara manual. Untuk itu dalam membatu mengambil kepututsan di PT Prioritas Outlet Bukittinggi dapat menggunakan Logika Fuzzy dengan Metode Tahani agar mendapatkan hasil yang akurat. Promotion is a very important factor for employee career planning, and is also an encouragement for someone to progress to become better. Often the process of promotion is carried out manually, or objectively, which results in jealousy or social inequality between employees, and in making decisions about promotion involves many aspects that are in the form of a vague (natural) set, while the assessment result data is still in the form of definite values. This of course takes a lot of time to convert the exact values into a vague set if done manually. For this reason, to help make decisions at PT Prioritas Outlet Bukittinggi, you can use Fuzzy Logic with the Tahani Method to get accurate results.

Penerapan Minimum Spanning Tree Dalam Menentukan Rute Terpendek Pada Pemasangan Jaringan PT.PLN (Persero) Di Kecamatan Padang Utara Kota Padang Rina, Iswan; Ramayanti, Rosi; Putri, Nurweni
Jurnal Penelitian Dan Pengkajian Ilmiah Eksakta Vol 3 No 2 (2024): Jurnal Hasi Penelitian Dan Pengkajian Ilmiah Eksakta - JPPIE
Publisher : LPPM Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jppie.v3i2.1659

Pada tulisan ini akan ditunjukkan penyelesaian data PLN dengan meminimumkan jarak atau menentukan jarak terpendek dari data PLN, dengan kata lain mencari minimum spanning tree dari model tree yang terbentuk. In this article, we will show how to solve PLN data by minimizing the distance or determining the shortest distance from PLN data, in other words looking for the minimum spanning tree from the tree model formed.

Perbandingan SARIMA dan Dekomposisi pada Peramalan Wisatawan Mancanegara di Sumatera Barat Rosi Ramayanti; Harifa Hananti; Nur Khasanah; Beni Gusman
Lattice Journal : Journal of Mathematics Education and Applied Vol. 5 No. 2 (2025): Desember 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/lattice.v5i2.10290

Tourism is a major driver of global economic growth, contributing over 10% of world GDP and generating employment for millions. West Sumatra, Indonesia, offers outstanding natural scenery and rich culture, but international tourist arrivals remain volatile. In January 2024, arrivals reached 4,689, increased to 7,107 in May 2024, and then dropped to 4,631 in June 2024. This variability makes dependable forecasting essential for tourism planning, including promotional programs, service capacity, and destination management. The projections can also support marketing targets, budget allocation, and infrastructure readiness for better policy decisions. This study forecasts international tourist arrivals to West Sumatra using two time-series approaches: Seasonal Autoregressive Integrated Moving Average (SARIMA) and a decomposition method. The best model is selected using Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE). Monthly data are taken from Statistics Indonesia (BPS) for West Sumatra covering January 2010 to December 2024. Results show SARIMA is more accurate, with a MAPE of 1.91%, while decomposition yields 15%. Forecasts for 2025 indicate a peak in September at 10,686 visitors and a trough in March at 5,430 visitors. Pariwisata merupakan motor penting ekonomi global karena menyumbang lebih dari 10% PDB dunia serta menciptakan lapangan kerja bagi jutaan orang. Provinsi Sumatera Barat memiliki daya tarik alam dan budaya yang kuat, namun kunjungan wisatawan mancanegara masih berfluktuasi. Pada Januari 2024 tercatat 4.689 kunjungan, meningkat hingga 7.107 pada Mei 2024, kemudian turun lagi menjadi 4.631 pada Juni 2024. Fluktuasi ini menuntut peramalan yang andal agar pemerintah dan pelaku usaha dapat menyusun program promosi, kapasitas layanan, dan pengelolaan destinasi secara tepat. Temuan ini dapat membantu penentuan target pemasaran, alokasi anggaran, dan kesiapan infrastruktur pariwisata daerah. Penelitian ini memprediksi jumlah kunjungan wisatawan mancanegara ke Sumatera Barat menggunakan dua metode deret waktu, yaitu Seasonal Autoregressive Integrated Moving Average (SARIMA) dan metode dekomposisi, lalu membandingkan kinerja model berdasarkan Mean Absolute Percentage Error (MAPE) dan Root Mean Squared Error (RMSE). Data berasal dari Badan Pusat Statistik Sumatera Barat periode Januari 2010–Desember 2024. Hasilnya, SARIMA lebih akurat dengan MAPE 1,91% dibanding dekomposisi 15%. Prediksi 2025 menunjukkan puncak pada September 10.686 wisatawan dan terendah pada Maret 5.430 wisatawan.

Utilizing Sales Data to Optimize Digital Marketing Strategies for Beauty Products in Padangsidimpuan City Rosi Ramayanti; Ihdi Syahputra
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 2 (2025): December 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/balqis.v1i2.10114

This study presents a data-driven framework for optimizing digital marketing strategies of beauty products in Padangsidimpuan. Motivated by the dominance of the Y.O.U brand (47.8% portfolio share) and an average store/BA target achievement rate of 43.7% with a 55.5% revenue gap, the research aims to integrate product portfolio analytics (price, margin, segmentation, brand) with sales performance analysis (target vs. actual). A quantitative descriptive approach was employed using secondary internal data—1,297 SKUs with sell-in/out prices and margin metrics, and monthly targets and achievements for 27 stores and 25 beauty advisors (August 2025)—supported by library research on digital marketing literature. Data analysis included descriptive statistics, price segmentation, brand distribution, margin analysis by segment, and performance gap assessment. Findings reveal a portfolio concentration in the mid-price segment (30k–60k, 38.6%) with an average margin of 31.3%, while only 14.2% of SKUs exceed 40% margin. The average achievement rate of 43.7% (range 0–91.1%) underscores the need for targeted digital interventions. The proposed framework prioritizes high-margin SKUs for paid media, SEO for mid-range products, cross-category bundling, live streaming, personalized content, and RACE-based KPI governance. Implementation is expected to close revenue gaps and raise the achievement rate above 60% within 1–2 quarters. The framework is adaptable to similar regional markets. Keywords: sales data, digital marketing, price segmentation, beauty products, RACE framework.

Utilizing Sales Data to Optimize Digital Marketing Strategies for Beauty Products in Padangsidimpuan City Rosi Ramayanti; Ihdi Syahputra
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 2 (2025): December 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/balqis.v1i2.10114

This study presents a data-driven framework for optimizing digital marketing strategies of beauty products in Padangsidimpuan. Motivated by the dominance of the Y.O.U brand (47.8% portfolio share) and an average store/BA target achievement rate of 43.7% with a 55.5% revenue gap, the research aims to integrate product portfolio analytics (price, margin, segmentation, brand) with sales performance analysis (target vs. actual). A quantitative descriptive approach was employed using secondary internal data—1,297 SKUs with sell-in/out prices and margin metrics, and monthly targets and achievements for 27 stores and 25 beauty advisors (August 2025)—supported by library research on digital marketing literature. Data analysis included descriptive statistics, price segmentation, brand distribution, margin analysis by segment, and performance gap assessment. Findings reveal a portfolio concentration in the mid-price segment (30k–60k, 38.6%) with an average margin of 31.3%, while only 14.2% of SKUs exceed 40% margin. The average achievement rate of 43.7% (range 0–91.1%) underscores the need for targeted digital interventions. The proposed framework prioritizes high-margin SKUs for paid media, SEO for mid-range products, cross-category bundling, live streaming, personalized content, and RACE-based KPI governance. Implementation is expected to close revenue gaps and raise the achievement rate above 60% within 1–2 quarters. The framework is adaptable to similar regional markets. Keywords: sales data, digital marketing, price segmentation, beauty products, RACE framework.

Utilizing Sales Data to Optimize Digital Marketing Strategies for Beauty Products in Padangsidimpuan City Rosi Ramayanti; Ihdi Syahputra
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 2 (2025): December 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/balqis.v1i2.10114

This study presents a data-driven framework for optimizing digital marketing strategies of beauty products in Padangsidimpuan. Motivated by the dominance of the Y.O.U brand (47.8% portfolio share) and an average store/BA target achievement rate of 43.7% with a 55.5% revenue gap, the research aims to integrate product portfolio analytics (price, margin, segmentation, brand) with sales performance analysis (target vs. actual). A quantitative descriptive approach was employed using secondary internal data—1,297 SKUs with sell-in/out prices and margin metrics, and monthly targets and achievements for 27 stores and 25 beauty advisors (August 2025)—supported by library research on digital marketing literature. Data analysis included descriptive statistics, price segmentation, brand distribution, margin analysis by segment, and performance gap assessment. Findings reveal a portfolio concentration in the mid-price segment (30k–60k, 38.6%) with an average margin of 31.3%, while only 14.2% of SKUs exceed 40% margin. The average achievement rate of 43.7% (range 0–91.1%) underscores the need for targeted digital interventions. The proposed framework prioritizes high-margin SKUs for paid media, SEO for mid-range products, cross-category bundling, live streaming, personalized content, and RACE-based KPI governance. Implementation is expected to close revenue gaps and raise the achievement rate above 60% within 1–2 quarters. The framework is adaptable to similar regional markets. Keywords: sales data, digital marketing, price segmentation, beauty products, RACE framework.

Title

Found 8 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 8 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 8 Documents
Search