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Integra: Journal of Integrated Mathematics and Computer Science
Published by Universitas Lampung
ISSN : -     EISSN : 31091792     DOI : https://doi.org/10.26554/integrajimcs
Core Subject : Science, Education,
Computer Science & IT Mathematics
Integra : Journal of Integrated Mathematics and Computer Science is the international journal in the field of Mathematics and Computer Science. Integra : Journal of Integrated Mathematics and Computer Science publish original research work both in a full article or in a short communication form, review article, and technical article in the field of Mathematics and Computer Science. Scope of this journal is : Mathematics Applied Mathematics Statistics Applied Statistics Data Science Computer Science
Arjuna Subject : Matematika - Matematika Komputer
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 2 (2025): July" : 5 Documents clear
Multidimensional Log-Linear Modeling (Case Study: Gender, Age, Head Circumference, and Nutritional Status Among Early Childhood Children) Yoka, Ranara Athalla; Usman, Mustofa; Chasanah, Siti Laelatul; Widiarti; Handayani, Vitri Aprilla
Integra: Journal of Integrated Mathematics and Computer Science Vol. 2 No. 2 (2025): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20252228

Abstract

Poor nutritional status tends to increase the risk of morbidity and mortality among children in developing countries. Therefore, data on these rates can be an important indicator in describing the condition of undernutrition in a community. Log-linear model analysis can be used to categorize data on nutritional status. Based on data obtained from the Rajabasa Indah Health Center area, Rajabasa Subdistrict, Bandar Lampung City, there are 418 children who have examined at the Posyandu. The analysis model conducted in this study involves four variables, each variable is categorized into several categories according to predetermined criteria. Gender with two categories (male and female), age with two categories (1-12 months and 13-60 months), head circumference with two categories (normal and abnormal), and nutritional status with three categories (undernourished, well-nourished, and overnourished). This study aims to determine the best model using log-linear analysis that can explain the relationship between the four variables. The results obtained are the best model for the data involved in the [UG][LG][J] structure, the structure describes the interaction between age and nutritional status and head circumference and nutritional status.
Jordan Derivation on the Polynomial Ring R[x] Sitompul, Desi Elena; Fitriani; Chasanah, Siti Laelatul; Faisol, Ahmad
Integra: Journal of Integrated Mathematics and Computer Science Vol. 2 No. 2 (2025): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20252229

Abstract

Given a ring R. An additive mapping δ: R → R is called a Jordan derivation if δ(a²) = δ(a)a + aδ(a) for every a in R. Jordan derivation is one of the special forms of derivation. In this study, we investigate the Jordan derivation on the polynomial ring R[x] and examine its properties. This study begins by constructing the Jordan derivation on the polynomial ring R[x], followed by investigating its characteristics, including the relationship between the Jordan derivation on the ring R and on the polynomial ring R[x]. In addition, several concrete examples are presented to illustrate the main results obtained. This research is expected to contribute to a deeper understanding of the properties of Jordan derivations on polynomial rings.
Integrating VAR and CNN Models for Accurate Forecasting of Money Supply in Indonesia Warsono; Sulandra, Ardelia Maharani; Kurniasari, Dian; Usman, Mustofa; Susetyo, Budi
Integra: Journal of Integrated Mathematics and Computer Science Vol. 2 No. 2 (2025): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20252230

Abstract

Economic forecasting serves as a fundamental element in supporting decision-making processes across multiple sectors. One of the main areas of interest in this field is the estimation of the money supply within an economy. The Vector Autoregressive (VAR) model is a commonly applied method for forecasting; however, it often encounters limitations when processing data with nonlinear patterns. Convolutional Neural Networks (CNNs) offer an alternative approach, particularly effective in identifying nonlinear structures that are not adequately captured by VAR models. A hybrid VAR-CNN model is therefore proposed, combining the respective strengths of both techniques to improve the accuracy of predictions. This research applies to the hybrid VAR-CNN model to forecast economic variables for the period from July 2022 to June 2023. The model consists of two main components: the first utilizes forecasted values generated by the VAR model, while the second processes the residuals from the VAR output using a CNN. With 80% of the data allocated for training and 20% for testing, the hybrid VAR-CNN model demonstrates improved performance over alternative forecasting methods. Evaluation based on Mean Absolute Percentage Error (MAPE), supremum (D) values, and p-values confirms the effectiveness of this hybrid approach.
Comparative Analysis of CIH and Christofides Algorithms for Optimal Tourist Route Planning in West Java Hadi, Nur Wafiqoh; Nurfabella, Rehsya; Wamiliana; Mustika, Mira
Integra: Journal of Integrated Mathematics and Computer Science Vol. 2 No. 2 (2025): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20252231

Abstract

Efficient route planning plays a crucial role in supporting tourism development, particularly in regions with numerous scattered attractions such as West Java, Indonesia. This study addresses the Traveling Salesman Problem (TSP) by comparing two algorithmic approaches: the Cheapest Insertion Heuristic (CIH) and the Christofides algorithm, to determine the shortest tour among 20 selected tourist sites. Using travel time data obtained from Google Maps, both algorithms were implemented manually and using Python language programming. The manual application of the CIH algorithm resulted in a total travel time of 813 minutes, which was later optimized to 764 minutes after adjustments to eliminate intersecting paths. Meanwhile, the CIH algorithm implemented in Python provided a final route of 717 minutes. In contrast, the Christofides algorithm yielded consistent results for both manual and Python-based calculations, producing a tour with a total travel time of 746 minutes. The findings suggest that the CIH algorithm using Python language offers the most efficient route in this case study. This research contributes to the development of intelligent tour planning systems and can be a valuable reference for optimizing regional tourism logistics.
IoT-Based Air Conditioner Monitoring and Control at PT XYZ: A Prototype Approach Utilizing Node MCU ESP8266, Relay Modules, and DHT11 Temperature Sensors Innaya, Thalia Gemi; Junaidi, Akmal; Alfikri, Fadli; Kurniawan, Didik; Iqbal, Muhammad
Integra: Journal of Integrated Mathematics and Computer Science Vol. 2 No. 2 (2025): July
Publisher : Magister Program of Mathematics, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/integrajimcs.20252237

Abstract

This study presents the development and implementation of an IoT-based monitoring and control system for air conditioners (AC) at PT XYZ. Leveraging the capabilities of Node MCU ESP8266, relay modules, and DHT11 temperature sensors, the proposed system enables real-time monitoring of AC status and room temperature. It also facilitates control over individual and multiple AC units, thereby enhancing operational efficiency. The system’s design focuses on energy efficiency, aiming to reduce unnecessary power consumption by ensuring that AC units are active only when needed. The system includes features for monitoring the AC’s on/off status and providing historical temperature data through graphical charts. This real-time data display allows users to track temperature trends and make informed decisions regarding AC operation. The prototype approach employed in this research involves several stages: communication with stakeholders, planning, modeling, prototype development, deployment, and iterative feedback. Testing results indicate that the system effectively meets the research objectives by providing accurate temperature readings and reliable AC control. Compared to existing solutions, this system offers enhanced functionality and integration, contributing to energy savings and improved management of AC units. This research contributes to the field by addressing gaps identified in previous studies and demonstrating the practical application of IoT technology in energy management for air conditioning systems.

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