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Informatics and Software Engineering (ISE)
Published by Santoso Academy Network
ISSN : 29882818     EISSN : 29882222     DOI : https://doi.org/10.58777/ise
Core Subject : Science,
Computer Science & IT
The Informatics and Software Engineering is an open-access and peer-reviewed journal that publishes theoretical and empirical research articles, review papers, and case studies on all major Informatics and Software Engineering topics. The journals mission is to offer a forum for the growing amount of scholarly research on Information Technology and Software Engineering in which it operates. The journal emphasizes theoretical advancements, their application, and empirical, practical, and policy research in global IT technology. The journal provides a platform for professionals in the field of IT to exchange their expertise and experiences. It aims to promote discussions on the design, development, implementation, management, and assessment of diverse IT applications among practitioners, researchers, managers, and IT policymakers. The journals goal is to promote communication and collaboration between and among academic and other research groups, as well as the founder of start-up and technology decision-makers at private and public institutions, national and global, and their regulators.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 2 (2024): December 2024" : 5 Documents clear
Object-Oriented Analysis in Software Engineering: A Systematic Review of the Literature Maulana, Rizqi Mustafa; Husna, Miftahul; Yuni Sugiarti
Informatics and Software Engineering Vol. 2 No. 2 (2024): December 2024
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v2i2.254

Abstract

This study examines the impact of the application of Object-Oriented Analysis (OOA) in software development on software quality improvement. Using the Systematic Literature Review (SLR) method covering the period from 2019 to 2024, this study identifies key methodologies and practices that contribute to improved software design, component reutilization, flexibility, and scalability. The research methodology involved collecting and evaluating relevant journal articles, with a focus on the use of Unified Modeling Language (UML), design patterns, and refactoring techniques in software development. The results show that the implementation of the OOA significantly improves the modularity of the software, allows for component reutilization, and improves the flexibility and scalability of the system. These findings highlight that the main success factors in the implementation of OO include competence of the development team, effective project management, adequate availability of tools and technology, and good communication and collaboration within the team.   Penulisan ini bertujuan untuk mengkaji dampak penerapan analisis berorientasi objek (OOA) dalam pengembangan perangkat lunak terhadap peningkatan kualitas perangkat lunak. Dengan menggunakan metode tinjauan pustaka sistematis (SLR) yang mencakup periode 2019 hingga 2024, penulisan ini mengidentifikasi metodologi dan praktik kunci yang berkontribusi terhadap peningkatan desain perangkat lunak, kegunaan kembali komponen, fleksibilitas, dan skalabilitas. Metodologi penelitian melibatkan pengumpulan dan evaluasi artikel jurnal yang relevan dengan fokus pada penggunaan Unified Modeling Language (UML), pola desain, dan teknik refaktoring dalam pengembangan perangkat lunak. Hasil penelitian menunjukkan bahwa penerapan analisis berorientasi objek secara signifikan meningkatkan modularitas perangkat lunak, memungkinkan kegunaan kembali komponen, dan meningkatkan fleksibilitas serta skalabilitas sistem. Temuan ini menyoroti bahwa faktor kesuksesan utama dalam penerapan OOA termasuk kompetensi tim pengembang, manajemen proyek yang efektif, ketersediaan alat dan teknologi yang memadai, serta komunikasi dan kolaborasi yang baik dalam tim. Penelitian ini memberikan wawasan berharga bagi pengembang perangkat lunak dan organisasi dalam merencanakan dan mengimplementasikan proyek pengembangan perangkat lunak yang lebih efektif dan efisien, dengan fokus pada peningkatan kualitas perangkat lunak melalui penggunaan OOA. Keterbatasan penelitian ini mencakup cakupan literatur yang ditinjau dan generalisabilitas temuan di berbagai konteks pengembangan perangkat lunak.
Assessing the Predictive Performance of Machine Learning Algorithms: DBNs, Fuzzy ARTMAP, and SVMs Kim, Daehyon
Informatics and Software Engineering Vol. 2 No. 2 (2024): December 2024
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v2i2.255

Abstract

The field of machine learning is rapidly advancing, and selecting the most suitable algorithm for predictive tasks remains a critical challenge. This study evaluates the predictive performance of three prominent machine learning algorithms: Deep Belief Networks (DBNs), Fuzzy ARTMAP, and Support Vector Machines (SVMs). Experiments on pattern recognition using image data from construction sites showed that DBNs achieved the highest predictive accuracy. In this study, experiments were conducted on a pattern recognition problem using image data from construction sites. The experimental results demonstrated that DBNs exhibited the highest predictive accuracy with the data used in this study. Algorithms such as DBNs, Fuzzy ARTMAP, and SVMs are representative models of machine learning methods, and their predictive power can vary depending on the type of data and the problem context. Therefore, future research should incorporate extended analyses with more diverse datasets and problem domains. Nonetheless, the findings of this study provide valuable guidelines for selecting appropriate algorithms for practical problem-solving and offer practical insights for practitioners aiming to optimize predictive accuracy across various machine learning applications.   Bidang pembelajaran mesin berkembang pesat, dan memilih algoritma yang paling sesuai untuk tugas-tugas prediktif masih merupakan tantangan penting. Studi ini memberikan evaluasi komprehensif terhadap kinerja prediktif dari tiga algoritma pembelajaran mesin terkemuka: Deep Belief Networks (DBNs), Fuzzy Adaptive Resonance Theory Mapping (FuzzyARTMAP), dan Support Vector Machines (SVMs). Dalam penelitian ini, percobaan dilakukan pada masalah pengenalan pola menggunakan data gambar dari lokasi konstruksi. Hasil eksperimen menunjukkan bahwa DBN menunjukkan akurasi prediksi tertinggi dibandingkan data yang digunakan dalam penelitian ini. Algoritma seperti DBN, FuzzyARTMAP, dan SVM merupakan model representatif dari metode pembelajaran mesin, dan kekuatan prediksinya dapat bervariasi bergantung pada jenis data dan konteks masalah. Oleh karena itu, penelitian di masa depan harus menggabungkan analisis yang diperluas dengan kumpulan data dan domain masalah yang lebih beragam. Meskipun demikian, temuan penelitian ini memberikan pedoman berharga dalam memilih algoritma yang tepat untuk pemecahan masalah praktis dan menawarkan wawasan praktis bagi para praktisi yang ingin mengoptimalkan akurasi prediksi di berbagai aplikasi pembelajaran mesin.
BRI Mobile M-Banking User Satisfaction Analysis using Technology Acceptance Model Putra, Bayu Prasetya
Informatics and Software Engineering Vol. 2 No. 2 (2024): December 2024
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v2i2.268

Abstract

In early February 2019, PT Bank Rakyat Indonesia (Persero) launched BRI Mobile, an e-banking service designed for its customers. Bank Rakyat Indonesia utilizes satisfaction surveys to engage with and prioritize its customers. Findings from these surveys are used to evaluate the bank's performance. The bank conducts annual customer satisfaction surveys to measure service quality and customer satisfaction index, which is based on customer expectations and the company's reputation and experience. The Technology Acceptance Model (TAM), developed by Davis in 1989, is widely used to assess the utilization and recognition of information systems and technologies by individual clients. Studies have shown that computer usage behavior is influenced by perceived usefulness and ease of use. The research findings indicate that 83% of the factors influencing user satisfaction of the BRImo application can be explained by the model, as indicated by a coefficient of determination value of 0.838.   BRI Mobile telah diperkenalkan oleh PT Bank Rakyat Indonesia (Persero) pada awal tahun 2019 pada bulan Februari. Bank Rakyat Indonesia menciptakan aplikasi BRI Mobile sebagai layanan e-Banking bagi nasabahnya. Survei kepuasan merupakan salah satu cara yang digunakan BRI untuk berkomunikasi, menjaga hubungan dan menjadikan nasabah sebagai pemangku kepentingan yang penting. Temuan dari Bank BRI dapat dijadikan alat untuk mengukur kinerja Bank BRI. Di antaranya, melakukan survei kepuasan pelanggan tahunan melalui survei kualitas layanan dan kemitraan telepon. Indeks kepuasan pelanggan yang diperoleh dari survei partisipasi pelanggan yang dilakukan pada 1-5 poin, dan indeks kepuasan pelanggan yang diperoleh dari kualitas layanan penjualan fasilitas, pelayanan yang baik diharapkan pelanggan berdasarkan reputasi dan pengalaman perusahaan. (Technology Acceptance Model) disempurnakan oleh Davis (1989) adalah salah satu bentuk penelitian paling terkenal akan menilai pemanfaatan dan pengakuan kerangka data dan inovasi bagi masing-masing klien. Sejumlah penelitian yang meneliti perilaku penerimaan teknologi individu dalam berbagai sistem informasi mendukung generalisasi TAM. Menurut model TAM, perilaku penggunaan komputer dipengaruhi oleh dua faktor: manfaat yang dirasakan dan kemudahan penggunaan. Berdasarkan hasil didapatkan nilai koefisien determinasi 0,838 bearti 83% Faktor yang berpengaruh kepuasan pengguna aplikasi BRImo.
Linear Regression Analysis to Predict the Percentage of Smoking in the Population Age 15 Years and Over Riziq Shihab, Muhammad Alfata; Napiah, Musriatun
Informatics and Software Engineering Vol. 2 No. 2 (2024): December 2024
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v2i2.328

Abstract

Smoking is a serious public health problem in many countries, including Indonesia, as it can cause diseases such as lung cancer, heart disease and respiratory disorders. According to data from the Ministry of Health of the Republic of Indonesia, the prevalence of smoking among the population aged 15 years and above is still high. This study uses secondary data from the Central Bureau of Statistics (BPS) that records the percentage of smoking in the population aged 15 years and above by age group from 2019 to 2023. With this data, a linear regression algorithm was applied using RapidMiner to predict the percentage of smoking in 2024. The analysis showed that out of 11 age groups, 6 age groups experienced an increase in smoking percentage from the previous year: 15-19, 20-24, 25-29, 30-34, 55-59, and 60-64. Meanwhile, the other 5 age groups experienced a decrease: 35-39, 40-44, 45-49, 50-54, and 65+. Evaluation of the prediction model using root mean squared error (RMSE) resulted in a value of 0.4 +/- 0.000. This RMSE value indicates that the model has a low error rate, making it reliable for predicting the percentage of smoking by age group in Indonesia.   Merokok adalah masalah kesehatan masyarakat yang serius di banyak negara, termasuk Indonesia, karena dapat menyebabkan penyakit seperti kanker paru-paru, penyakit jantung, dan gangguan pernapasan. Menurut data Kementerian Kesehatan Republik Indonesia, prevalensi merokok di kalangan penduduk usia 15 tahun ke atas masih tinggi. Penelitian ini menggunakan data sekunder dari Badan Pusat Statistik (BPS) yang mencatat persentase merokok penduduk usia 15 tahun ke atas berdasarkan kelompok umur dari tahun 2019 hingga 2023. Dengan data ini, algoritma regresi linear diterapkan menggunakan RapidMiner untuk memprediksi persentase merokok pada tahun 2024. Hasil analisis menunjukkan bahwa dari 11 kelompok umur, terdapat 6 kelompok umur yang mengalami peningkatan persentase merokok dari tahun sebelumnya: 15-19, 20-24, 25-29, 30-34, 55-59, dan 60-64. Sementara itu, 5 kelompok umur lainnya mengalami penurunan: 35-39, 40-44, 45-49, 50-54, dan 65+. Evaluasi model prediksi menggunakan root mean squared error (RMSE) menghasilkan nilai 0.884 +/- 0.000. Nilai RMSE ini menunjukkan bahwa model memiliki tingkat kesalahan yang rendah, sehingga dapat diandalkan untuk memprediksi persentase merokok berdasarkan kelompok umur di Indonesia.
An Integrated Operations Management System for Enhancing Administrative Efficiency in Ghana's District Assemblies Brown, Philip; Bankas, Edem Kwedzo
Informatics and Software Engineering Vol. 2 No. 2 (2024): December 2024
Publisher : SAN Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58777/ise.v2i2.348

Abstract

The COVID-19 pandemic, driven by the SARS-CoV-2 virus, necessitated an unprecedented shift to remote work, revealing critical gaps in digital infrastructures capable of maintaining organizational operations. This challenge was particularly pronounced in district assemblies in Ghana, where traditional, paper-based workflows impeded the transition to remote environments, heightening operational vulnerabilities. Despite the World Health Organization (WHO) downgrading COVID-19 as a Public Health Emergency of International Concern (PHEIC), the global ramifications of the virus and potential for future pandemics underscore the need for resilient, adaptable digital solutions. This paper presents an online integrated business operation management system tailored for district assemblies in Ghana. The system was developed using the Rapid Application Development (RAD) methodology, facilitating rapid, iterative deployment and user-centric design. Technologies such as HTML, CSS, and PHP were utilized for the front-end, while MySQL ensured secure and efficient back-end data management. The approach helped to digitize core administrative processes and transition from paper-based operations to streamlined electronic workflows. The implemented system successfully digitalized essential administrative workflows, improving operational continuity and efficiency. By replacing conventional procedures with robust electronic processes, the system provides a sustainable framework for enhanced functionality in public sector management. Furthermore, it strengthens organizational preparedness for future disruptions, ensuring resilience in remote and hybrid work contexts. The scope of this research is limited to district assemblies in Ghana, which may constrain the generalizability of the findings to other administrative contexts or geographical regions. Further studies could explore customization for broader governmental structures and assess long-term impacts on service delivery and user satisfaction. This paper presents a novel application of digital transformation principles within the public sector, addressing a critical gap in e-governance solutions for district assemblies in Ghana. By integrating user-focused design and scalable technology, the proposed system not only meets current administrative demands but also positions district assemblies for enhanced functionality and resilience in the face of future challenges.

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