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INSTALL: Information System and Technology Journal
Published by Universitas Sari Mulia
ISSN : -     EISSN : 30481597     DOI : https://doi.org/ 10.33859/install
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Education
The Focus and Scope of this Journal is related to : Information system Information Technology Business commerce Management technology Business Technology
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 18 Documents
 1   2 
The Regression Analysis Data for E-Sport Athletes Prediction using OSEMN Framework: Analisis Regresi Data Prediksi Atlet E-Sport Menggunakan Kerangka OSEMN Septyan Eka Prastya; Musyfia Adla; Bayu Nugraha; Yuslena Sari
INSTALL: Information System and Technology Journal Vol 1 No 1 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i1.542

Abstract

In the fast-growing E-Sports industry, athlete performance is the key to achieving success and winning. Therefore, analyzing the factors that contribute to the performance of E-Sports athletes is essential in order to optimize their performance in competition. This study aims to analyze the relationship between age, number of training hours, and experience playing in competition with rank, kill death ratio (KDA), and the number of wins of E-Sports athletes using the OSEMN approach (Obtain, Scrub, Explore, Model, Interpret, and Communicate). The data was obtained from 300 professional or non-professional E- Sports athletes, over the past three years who were involved in various competitions. Independent variables included age, number of training hours, and experience playing in competitions, while the dependent variables included rank, KDA, and number of wins. Data was collected, processed and explored and then analyzed using multiple linear regression methods. This study succeeded in applying the regression analysis method using the OSEMN framework, identifying relevant variables, and developing effective data collection and processing methods. This model has the potential to provide accurate predictions of E- Sport athlete performance data. However, it is still important to consider other factors such as business context, comparison with other models, and cross- validation to confirm the reliability of the prediction results.
A Exploratory Data Analysis (EDA) of Social Aid Recipients in Murung Raya District Central Kalimantan Province with Machine Learning Approach: Analisis Data Eksplorasi (EDA) Penerima Bantuan Sosial di Kabupaten Murung Raya Provinsi Kalimantan Tengah dengan Pendekatan Machine Learning Regina; M. Riko Anshori Prasetya; Ahmad Hidayat
INSTALL: Information System and Technology Journal Vol 1 No 1 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i1.543

Abstract

Various kinds of problems often occur in programs implemented by the government, one of which is the problem that often arises is the uneven distribution of social assistance carried out to people with low economic levels, poverty is the main problem being faced by all countries in the world, including Indonesia. The purpose of implementing the dataset of social assistance recipients using EDA. To find the correlation of 4 variables, namely Number of Population, Number of Recipients, Occupation, and Age in the dataset of social assistance recipients in Murung Raya District, Central Kalimantan Province, with a machine learning approach. Then the research method used here is quantitative methods and experiments with machine learning approaches. So by using the EDA method on data on social assistance recipients in Murung Raya Regency, Central Kalimantan Province, it can be seen that the variable Number of population has.
The Image Segmentation Of Ornamental Plants Typical Of South Kalimantan Using The Convolutional Neural Network Method: Segmentasi Citra Tanaman Hias Khusus Kalimantan Selatan Menggunakan Metode Convolutional Neural Network Lufila Lufila; Septyan Eka Prastya; Finki Dona Marleny
INSTALL: Information System and Technology Journal Vol 1 No 1 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i1.544

Abstract

One of the very important processes in the recognition of visually presented objects. Image segmentation is one of the important topics in computer science, especially in the field of digital image processing. The research method used is image segmentation using the Convolutional Neural Network (CNN) method; the results obtained in this study are accurate to the image of plants selected as the sample of this study. The dataset in this study used pictures or objects of ornamental plants, namely Black Orchids, Betel Lurih, and Aglonema Tri-Color. As for the samples used in this study, namely for these three types of objects, 50 pictures were taken for each object used. By using epochs of 15, researchers have determined to reduce system performance time and by epoch times of 17s, 18s, and 24s. The number of epochs that will be used also affects the time that will be taken by modeling training. Due to the increasing number of epochs, the time that will be required for training will be longer. Then, the accuracy value of the data trained is 0.7667 with a loss value of 0.4039, and the val_loss value is 0.4611 with a val_accuracy of 0.7333. The segmentation results obtained using the convolutional neural network model have a fairly good accuracy level of 0.7667 and a validation accuracy of 0.7333.
The Clustering Of Sapodilla Fruit (Manilkara Zapota) Maturity Levels Based On Color Using K-Means Clustering Method: Clustering Tingkat Kematangan Buah Sapodilla (Manilkara Zapota) Berdasarkan Warna Menggunakan Metode K-Means Clustering Wayan Bayu Sumadika; Muhammad Syahid Pebriadi
INSTALL: Information System and Technology Journal Vol 1 No 1 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i1.546

Abstract

The study aimed to evaluate the accuracy of determining sapodilla fruit maturity using the K-Means Clustering algorithm, a method that partitions data into clusters of similar characteristics; by applying K-Means Clustering on data samples obtained from Kaggle, and using Matlab for pixel value calculation, the algorithm effectively classified 150 sapodilla fruit samples into two clusters—75 mature and 75 raw—with an accuracy of 92.2% for mature sapodilla and 94.5% for raw sapodilla, demonstrating that K-Means Clustering, a straightforward and user-friendly algorithm, is highly effective in distinguishing sapodilla fruit maturity levels.
A Naïve Bayes Approach to Understanding Students’ Pychological Well-Being : Pendekatan Naïve Bayes untuk Memahami Kesejahteraan Psikologis Siswa Febria Sera Darnefi; M. Riko Anshori Prasetya
INSTALL: Information System and Technology Journal Vol 1 No 1 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i1.547

Abstract

High levels of stress and depression among Indonesian students are significant issues that demand special attention. According to data from the National Crime Information Center (Pusiknas) of the Indonesian National Police (Polri), there were 971 cases of suicide related to the mental health of students from January to October 18, 2023. This study utilizes an open dataset from Kaggle, which includes information on students' mental health conditions, and applies the Naive Bayes algorithm to determine accuracy, precision, and recall values. The Naive Bayes approach is employed to classify the mental health status of students and identify those who require special assistance. The results indicate that the Naive Bayes algorithm is effective in identifying students needing special help, with a high accuracy rate. Testing with RapidMiner yielded an accuracy of 90.00%, a recall rate of 89.66% for the 'No' class and 100.00% for the 'Yes' class. Precision for the 'No' label was 100.00%, while for the 'Yes' label, it was 25.00%. This approach can aid campuses, families, and professionals in identifying students who need special attention.
The Diabetes Prediction Using Flask and Decision Tree Classifier with Cross-Validation: Prediksi Diabetes Menggunakan Flask dan Decision Tree Classifier dengan Validasi Silang Nor Anisa; Anggara Kurniawan
INSTALL: Information System and Technology Journal Vol 1 No 1 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i1.548

Abstract

Diabetes is a chronic medical condition that impairs the body's ability to process blood sugar, leading to elevated levels of glucose in the blood. This condition can cause serious health complications if not managed properly. Early detection and intervention are crucial in preventing these complications. This study aims to develop a user-friendly web application using Flask, a lightweight Python web framework, to predict the type of diabetes based on symptoms reported by users. The Machine Learning model utilized for this purpose is the Decision Tree Classifier, chosen for its simplicity and interpretability. The model's performance was evaluated through cross-validation to ensure reliability and accuracy. The results demonstrate that the developed application can effectively predict the type of diabetes, providing valuable insights and assisting users in seeking timely medical advice. This tool has the potential to enhance public awareness about diabetes and facilitate early diagnosis, ultimately contributing to better health outcomes for individuals at risk of this condition.
Planning of Information Systems Needs for Parking Space in Private Colleges of Banjarmasin City: Perencanaan Kebutuhan Sistem Informasi Ruang Parkir di Perguruan Tinggi Swasta Kota Banjarmasin Anugrah Bakti Sitanggang; Nurhaeni; M.Riko Anshori Prasetya
INSTALL: Information System and Technology Journal Vol 1 No 2 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i2.595

Abstract

Parking is one of the components or integral aspects of transportation system needs, as any journey with a private vehicle usually starts and ends at the parking lot. The study was developed using a system planning method with a functional approach described using UML Tools (Unified Modelling Language). The aim of the study is to make a plan for parking in the private college environment of Banjarmasin city using UML Tools. The study is basically a quantitative observational research that is a measured research design. System design is done using UML Tools as a modeling tool to describe how the system will work and make it easier for the system to be designed to be understood. This research is expected to be beneficial to the parking lot providers in order to create efficiency for the riders in searching for parker land not to waste time, improve security, facilitate access and minimize the occurrence of parking lot clashes with other riders seeing the number of vehicles increasing as the student mobility increases.
Exploratory Data Analysis (EDA) of Marriage Patterns in Kabupaten Banjar Using Machine Learning Approaches Husna Karima; Mambang; Subhan Panji Cipta; Muhammad Zulfadhilah
INSTALL: Information System and Technology Journal Vol 1 No 2 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i2.629

Abstract

Marriage is a sacred moment that has a significant impact on the social, economic and demographic structure of a region. This research aims to implement a marriage dataset in Banjar Regency and find a correlation between the number of marriages, education level and age of the bride and groom using Exploratory Data Analysis (EDA) techniques and machine learning approaches. The method used is a quantitative method with observation and analysis using EDA and machine learning. The research results show that there is a strong correlation between the number of marriages and the age of the bride and groom (r = 0.99) and between the number of marriages and the education level of the bride and groom (r = 0.99). In addition, a perfect correlation was found between the ages of the groom and the bride (r= 0.99) as well as between the educational levels of the groom and the bride (r = 1). This analysis provides a better understanding of marriage patterns in Banjar Regency and shows that couples aged 21-30 years have a high positive correlation with the number of marriages. It is hoped that these results can become the basis for social policies and educational programs related to marriage.
Dropshipper Hijab Haven: A Solution for Stylish and Comfortable Hijabs Nurul Fahmi; Nor Anisa
INSTALL: Information System and Technology Journal Vol 1 No 3 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i3.746

Abstract

Hijab Haven is an innovative startup that aims to provide hijab collections with fashionable, comfortable, and functional designs to fulfill the needs of modern Muslim women. Through a technology-based approach and digital marketing, the startup offers solutions that not only improve customer experience but also support more efficient business management. This research uses a descriptive method with a qualitative approach to evaluate digital marketing strategies, optimization of stock management, and user-friendly e-commerce interface design. Results show that the combination of social media strategy, use of cloud-based technology, and business management training significantly improved Hijab Haven's competitiveness as well as sustainability in the Muslim fashion market. The findings provide important insights into how MSMEs can leverage technology to achieve sustainable growth in the digital age. This research recommends further development in product innovation and the use of artificial intelligence for market trend analysis to improve service personalization.
Auto Lavaggio: Innovation and Digitalization in the Car Wash Industry Fajar Adha; Muhammad Fitri Saputra; Nor Anisa
INSTALL: Information System and Technology Journal Vol 1 No 2 (2024): INSTALL : Information System and Technology Journal
Publisher : LPPM Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/install.v1i2.747

Abstract

The car wash industry continues to grow with the adoption of digital technology to improve operational efficiency and service quality. This study aims to develop a digital application that supports the auto lavaggio business with key features such as online reservations, service process automation, and data-based performance reporting. This application was developed using the Django framework for the backend and Flutter for the user interface, with testing carried out using the black-box testing method. The results of the study show that this application has succeeded in increasing service efficiency by up to 40%, reducing customer waiting time, and providing ease of transactions through the integration of a digital payment system. In addition, the reporting dashboard feature provided allows business owners to monitor business performance in real-time, increasing transparency and making more informed decisions. Although this application has succeeded in providing significant benefits, challenges such as payment API integration and user adaptation to new technologies remain. The solutions implemented include system optimization and the addition of tutorial features for new users. Overall, this application provides an innovative solution in improving the services and operations of the auto lavaggio business, while opening up opportunities for further development, such as the use of artificial intelligence (AI) and the expansion of environmentally friendly services.

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