Article Per Year (5 Year)
p-Index From 2021 - 2026
0.751
P-Index
This Author published in this journals
All Journal Respati Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Paradigma Journal of Intelligent Software Systems
Dini Fakta Sari, Dini Fakta
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Journal of Intelligent Software Systems

 1 
BUSINESS INTELLIGENCE FOR DETERMINING PROMOTIONAL MEDIA Alvianingrum, Ante Wahyu; Sari, Dini Fakta; Syadziliy, Abil Hasan Ali Asy; Supriatin, Supriatin; Nur’aini, Nur’aini
Journal of Intelligent Software Systems Vol 3, No 2 (2024): December 2024
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v3i2.1505

Abstract

Abstract—In 2021-2022, SMK Dirgantara Putra Bangsa experienced a decrease in the number of prospective students who registered. This condition encourages schools to innovate and be creative in choosing effective promotional media in disseminating information on New Student Admissions (PPDB) to the public widely and routinely, with the aim of attracting more new students. This promotional effort involves the use of various types of promotional media. Business intelligence plays a role in processing organizational data into useful information to improve performance, by analyzing historical data which is then used to support decision making and planning. The K-Means algorithm is one of the clustering methods that is often used because of its ease of implementation and its ability to minimize the sum of squared error (SSE) value between data and the specified centroid. The collaboration between Business Intelligence and K-Means clustering is expected to help SMK Dirgantara Putra Bangsa in choosing the right promotional media and creating new innovations in disseminating PPDB information to the public.Keywords— PPDB, Business intelligence, K-Means clustering, Media Promosi
SALES PREDICTION OF VEGETABLE SEED PRODUCTS USING SIMPLE LINEAR REGRESSION Sari, Dini Fakta; Sofian, Muhammad Ali; Nurcahyo, Agung Wilis; Wiharyanto, Kelik; Pereira, Elisabet da Conceição
Journal of Intelligent Software Systems Vol 4, No 1 (2025): Juli 2025
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v4i1.2001

Abstract

The growth of the modern agricultural sector drives the need for an accurate sales prediction system, especially for vegetable seed products that are highly dependent on the season and market demand. An imbalance between stock and demand can cause losses, either in the form of overstock or undersupply. This condition requires a data-based planning strategy to ensure stock availability according to actual needs in the field. A historical data-based sales prediction approach is a relevant solution to optimize the distribution and procurement process. This study aims to apply a simple linear regression method in predicting vegetable seed sales based on historical data for one year. The prediction model is built using the time variable (month) as the independent variable and the number of seed requests as the dependent variable. This technique was chosen because of its ability to identify linear relationship patterns between time and sales trends in a simple but effective way. The data used comes from internal records of farmers and distributors, which are then classified into two main categories: leafy vegetable seeds (spinach, kale, mustard greens) and fruit vegetable seeds (tomatoes, chilies, eggplants). The results of the study showed that simple linear regression was able to provide fairly accurate predictive results. This model can be used as a basis for decision making in production planning, supply chain management, and seed inventory management, thus supporting the efficiency of farming businesses and reducing potential losses due to mismatches between demand and supply.
Co-Authors A, Azanuddin Alvianingrum, Ante Wahyu Asyahri Hadi Nasyuha Danny Kriestanto, Danny Edi Iskandar, Edi Khoiri, Muhammad Hafidz Ady Muhammad Rivai Nurcahyo, Agung Wilis Nur’aini, Nur’aini Pereira, Elisabet da Conceição Sofian, Muhammad Ali Supriatin Supriatin, Supriatin Syadziliy, Abil Hasan Ali Asy Totok Mujiono, Totok Wiharyanto, Kelik