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Muhammad Wali
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International Journal Software Engineering and Computer Science (IJSECS)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : 27764869     EISSN : 27763242     DOI : https://doi.org/10.35870/ijsecs
Core Subject : Science,
Computer Science & IT
IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer science. IJSECS is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of information technology and computer science applications..
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 387 Documents
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Optimizing E-commerce Inventory to prevent Stock Outs using the Random Forest Algorithm Approach Ridwan, Achmad; Muzakir, Ully; Nurhidayati, Safitri
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2326

Abstract

This research investigates the effectiveness of the Random Forest algorithm in optimizing e-commerce inventory management. In a digital business that continues to grow, inventory management is crucial for smooth operations and customer satisfaction. The Random Forest algorithm, a development of the CART method by applying bagging techniques and random feature selection, was tested to predict inventory. An experimental design is used to test the algorithm's performance algorithms performance, using data relevant to the observed inventory variables. The analysis involves evaluating the performance of algorithms in predicting and preventing stockouts. The results show that the Random Forest algorithm provides more accurate inventory predictions than traditional methods. Comparison with linear and rule-based regression reveals higher accuracy, making this algorithm a promising choice for e-commerce inventory management. These findings imply that the Random Forest Algorithm can be an effective solution in overcoming the complexity and fluctuations of digital markets. Practical recommendations include a deep understanding of the data, engagement of trained human resources, and training strategies for optimal use of these algorithms. This research also contributes to the literature by expanding understanding of the application of the Random Forest algorithm in various contexts, including forest basal area prediction, supply chain management, and backorder prediction. In conclusion, the Random Forest algorithm has great potential to improve e-commerce inventory management, opening up opportunities for broader application in the digital business world. Proactive adoption of these algorithms can have a positive impact on operational efficiency, customer satisfaction, and a company's competitiveness in an ever-evolving market.
Optimization of Product Placement on E-commerce Platforms with K-Means Clustering to Improve User Experience Ridwan, Achmad; Setiadi, Sandi; Maulana, Rizky
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2328

Abstract

This study delves into product placement strategies on E-commerce platforms using K-Means Clustering analysis. Employing an experimental methodology, data about products and user preferences were gathered to delineate product and user clusters. The K-Means Clustering analysis yielded three primary product clusters and four user preference clusters. These findings hold significant practical implications, empowering E-commerce platforms to refine user experience personalization, streamline sales efficiency, and bolster overall business performance. Platforms can positively influence sales conversion rates and user satisfaction by implementing targeted and adaptable product placement strategies. This research contributes not only to the theoretical comprehension of product placement in E-commerce but also furnishes actionable insights for stakeholders to optimize platform operations and deliver an enriched online shopping experience.
Design of an Android-Based Motorcycle Service Booking Application Farizqi, Muhammad Ridwan; Kalifia, Anna Dina; Sejati, Rr.Hajar Puji
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2334

Abstract

A motorbike is a two-wheeled vehicle powered by an engine. Motorbike users are required to service their cars because the components on the motorbike will experience a decrease in performance along with the length of time they use the motorbike. However, this can be overcome by servicing your motorbike regularly. However, sometimes motorbike users have to face queues at workshops that are long and quite time-consuming. Then, an Android-based online motorbike service booking system was created, which did not require customers to come to the seminar directly to make a booking. With this application, customers must book via Android by selecting the desired schedule. The application was created using Android Studio with the Kotlin programming language. The database section uses the Firebase Real-time Database to update the data in real-time. The service provider will also easily confirm orders via the website connected to Firebase. In short, it is hoped that this application can help motorbike users book services online so they don't have to spend time queuing.
Development of a Web-Based Trading Term Application Using Flask Framework at PT. XYZ Larasati, Sarah; Susetyo, Yeremia A.
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2339

Abstract

The use of information technology in data management and collaboration with suppliers has increased efficiency for retail companies such as PT. XYZ. However, some companies still still need help managing data and cooperation agreement documents, which hinders the preparation of reports and has the potential for conflict. This research aims to build a web-based Trading Term application using the Flask framework at PT. XYZ. This application was developed in Python because of its simplicity and diversity of libraries. The waterfall method used in this research includes several stages, including data analysis, software design, system implementation, testing, and application maintenance. The application of the MVC architectural pattern supports fast website development. This research produces a Trading Term Application, to help record and store trade agreement data, thereby increasing efficiency and order in business cooperation. The results of black box testing show that the Trading Term Application developed has passed a series of tests well and has achieved 100% success in the functional tests carried out.
Design Principles for Enhancing AI-Assisted Moderation in Hate Speech Detection on Social Media Platforms Graf, Alex; Coolsaet, Danny
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2345

Abstract

Hate speech on social media poses a growing threat to individuals and society, necessitating technological support for moderators in detecting and addressing problematic content. This article explores the design principles essential for creating effective user interfaces (UIs) in decision support systems that employ artificial intelligence (AI) to aid human moderators. Through a comprehensive study involving 641 participants across three design cycles, we qualitatively and quantitatively evaluate various design options. Our assessment encompasses perceived ease of use, usefulness, and intention to use, while also delving into the impact of AI explainability on users' cognitive efforts, informativeness perception, mental models, and trustworthiness. Notably, software developers affirm the high reusability of the proposed design principles. The findings reveal that well-designed UIs can significantly enhance the effectiveness of AI-based moderation tools, providing clear and understandable explanations that improve user trust and engagement. By addressing both technical and user-centered aspects, this research contributes to the development of more robust and user-friendly AI systems for hate speech detection. Future work should focus on further refining these principles and exploring their applicability in diverse social media contexts to ensure comprehensive and adaptable solutions for content moderation.
Implementation of Web-Based Loan Application Information System Using Simple Additive Weighting (SAW) at CV. Taruna Jaya Nusantara Tambunan, William Jeans; Darusalam, Ucuk; Nugroho, Catur
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2348

Abstract

Financial institutions offer cash loans with lighter terms and collateral compared to banks, including motor vehicle ownership as collateral. This study focuses on implementing a web-based Loan Application Information System using the Simple Additive Weighting (SAW) method at CV. Taruna Jaya Nusantara. The research aims to enhance the efficiency of the loan application process and evaluate loan feasibility. The system development method is integrated with web technology, with SAW used to measure relevant criteria. Implementing the Loan Application Information System with SAW significantly simplifies decision-making, reduces potential errors, and improves loan feasibility evaluation. Based on the ranking results, V1 = 1.9; V2 = 1.779; V3 = 2.0625. The selection process uses a tolerance limit for acceptance, where the accepted value threshold is set at > 2. Thus, it can be concluded that A3 with a value of 2.0625 meets the criteria for recommendation.
Development of an Android-based Application as a Solution for Maternal Health Tarsono; Fachrie, Muhammad
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2355

Abstract

This research highlights the problem of lack of accessibility of health services for pregnant women, especially in consultations with doctors and access to pregnancy information. To overcome these challenges, the research aims to develop an application that allows pregnant women to access pregnancy information easily, consult with doctors, and monitor pregnancy progress efficiently. This research proposes the development of an Android-based application as a solution for health care for pregnant women, which uses an approach known as Rapid Application Development (RAD). RAD was chosen because of its reputation as a software development approach with rapid development capabilities and readiness to respond to change. Adopting the RAD method aims to create flexible and responsive applications that can adapt to changes that may occur over time. This learning and consultation application for pregnant women is very helpful for them to always know about their pregnancy. This application is also very useful for health workers. Health workers can quickly help patients at any time. Health workers can also provide advice regarding pregnancy by entering it into the application, which will be very helpful for mothers in maintaining their pregnancy. The research addresses the accessibility of health services for pregnant women. It is hoped that with this application, pregnant women will become more educated and guided about pregnancy so that cases of maternal and infant mortality in Indonesia will decrease.
Analysis of Networking Tools Using Cisco Packet Tracer (CPT) Thoyyibah. T; Hidayat, Asep Ridwan; Hanggara, Imam Satria; Sudarsono, Rizki Satriawan
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2359

Abstract

This study aims to evaluate the performance and effectiveness of network devices using Cisco Packet Tracer (CPT) as a simulation tool. CPT is a widely utilized network simulation software, commonly employed for designing and testing network configurations prior to real-world implementation. This research investigates various network topologies to assess the performance of devices such as routers, switches, and end devices. The research methodology encompasses the design of network scenarios, device configuration, and testing of various network protocols. The analysis reveals that CPT is capable of accurately replicating most functions and behaviors of network devices, providing a clear depiction of network performance under different conditions. The findings suggest that CPT serves as an effective and efficient tool for both educational purposes and network planning, despite certain limitations in features and realism when compared to actual hardware. This study is expected to offer valuable insights for professionals and academics in understanding and optimizing network design before deployment in real-world environments.
Classification of Drug Data Usage Using the K-Means Deep Algorithm to Minimize Drug Stock Shortages (Case Study: South Cikarang Community Health Center) Mantona, Muhamad Risvan; Turmudi Zy, Ahmad; Suwarno, Agus
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2366

Abstract

Efficient utilization of medicines is essential for effective health service delivery, especially in community health centers. This research explores the application of the K-Means clustering algorithm to categorize drug usage data and minimize stock shortages. This research, conducted at the South Cikarang Community Health Center, analyzed drug use patterns to identify drugs with high and low demand. Through data collection, cleaning, and pre-processing, medication use data is converted into a format suitable for clustering analysis. The clustering method approach can be applied to analyze the level of drug use produced by utilizing data sets to record the process of drug data results. The K-Means algorithm model applied has results that show new insights, namely grouping usage levels based on 2 clusters; cluster 1 (C0) is a high potential category consisting of 3.4 data from the tested dataset, and cluster 2 (C1) is Low Potential. Consists of 7.2 tested data, right? Collaborative testing can also produce collaborative testing results that show an average figure of 0.545.
Purchasing Patterns Analysis in E-commerce: A Big Data-driven Approach and Methodological Riwayat, Andik Adi Putra; Susilawati, Agnes Dwita; Naqiah, Zakiyyatun
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i1.2384

Abstract

This research aims to analyze purchasing patterns in e-commerce using a Big Data-based approach and data analysis methods. Leveraging advanced technology and analytical methodology, this research explores consumer behavior, market trends, and factors influencing purchasing decisions in e-commerce. Through collecting transaction data from leading e-commerce platforms and applying rigorous data analysis techniques, this research identifies significant patterns and provides valuable insights for e-commerce companies. This research shows that big data has great potential in understanding consumer behavior and market trends in e-commerce. In contrast, sophisticated data analysis methods are essential in interpreting the large and complex data generated by e-commerce. The findings of this research significantly contribute to the development of the e-commerce industry by helping companies improve their marketing strategies and business decision-making. However, this research also needs help, as it requires data analysis skills and privacy issues. To overcome these challenges, collaboration between researchers, e-commerce companies, and governments is needed to develop the necessary data analysis expertise and ensure that consumer data is managed securely and ethically. Thus, this research provides a more holistic view of consumer behavior and market dynamics in e-commerce, assisting companies and policymakers in addressing challenges and opportunities in an ever-evolving landscape.

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