cover
Contact Name
Tri A. Sundara
Contact Email
tri.sundara@stmikindonesia.ac.id
Phone
+628116606456
Journal Mail Official
ijcs@stmikindonesia.ac.id
Editorial Address
Jalan Khatib Sulaiman Dalam 1, Padang, Indonesia
Location
Kota padang,
Sumatera barat
INDONESIA
The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Articles 1,127 Documents
Data Governance Improvement Strategy for Peer-to-Peer Lending Sharia in Indonesia: Study Case PT ABC Priastomo, Ristyo Yogi; Ruldeviyani, Yova; Gunawan, Adi; Al Haq, Muhammad Hezby; Utami, Aisyah Nurlita
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4233

Abstract

Abstract—Financial Technology (fintech) is a company that supervised by the Indonesian Financial Services Authority (OJK) and fintech associations which has strict regulations. Well-defined data management can support organizations to comply with mandatory regulations. This research was conducted on a sharia peer-to-peer lending fintech in Indonesia with the aim of solving data governance problems in organizations by measure of Data Governance Maturity Level to get recommendations strategies to improve the implementation of data governance in the organization. The measurement was carried out using IBM Data Governance Maturity Model Framework. After validation and finalization of the assessment, the results showed that the average score was 2.47. It's shown that currently at the Managed level. Some domains need to be improved in the future, data value creation, data organizational structure and awareness, data policies and rules and data stewardship.
An Assessment of the Visibility of Particular Swarm Intelligence Technologies in the Resolution of the Object Classification Problem Tsedura, Nyaradzo Alice; Bhero, Ernest; Chibaya, Colin
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4275

Abstract

This article assesses the visibility of five swarm intelligence algorithms in resolving the object classification problem explicitly particle swarm optimization, artificial bee colonies, ant colony optimization, bacterial foraging optimization, and the Social Spider Optimization. 58 articles in total were reviewed and used as the ground on which this assessment was based on. Primarily articles were grouped into two categories namely the articles which directly resolve the object classification problem and those which in directly resolve the object classification problem followed by a further grouping to indicate articles that were directly linked to the object classification problem through swarm technology and finally grouped by the aim. Three aims were observable which are to modify, to improve and to investigate. More than 70% of the articles aimed at either modifying or improving already existing swarm intelligence algorithms. PSO was the most dominant algorithm of the five technologies assessed. Interesting to note was that although all these algorithms were applied there is no formal representation of knowledge in this domain.
Analisis Sentiment Publik Mengenai Neuralink dari Twitter dengan Menerapkan Naïve Bayes: Multinomial, Gaussian, dan Complement Azwan Triyadi; Purnawansyah; Darwis, Herdianti
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4278

Abstract

Elon Musk owns the business Neuralink, which attempts to build brain-machine interfaces. This study categorizes public opinion towards the use of Neuralink goods, including whether people agree (positive), disagree (negative), or feel neither way. Without accessing the Twitter API, the Twint Python Libraries were utilised to retrieve a dataset of 3000 using the keyword “neuralink”. What datasets are included in positive, neutral, or negative categories are designated using RoBERTa. Term Frequency Inverse Document Frequency (TF-IDF) is utilized for feature extraction, while Synthetic Minority Over-sampling Technique (SMOTE) is employed to handle class imbalance. Complement Naive Bayes, achieved accuracy of 81%, followed by Multinomial Naive Bayes, which achieved accuracy of 80%, and Gaussian Naive Bayes, which achieved accuracy of 75%. The model Complement Naïve Bayes was used in this study to attain the maximum accuracy, and accuracy increases when employing SMOTE compared to other Naïve bayes variants.
Rancang Bangun Aplikasi Diagnosa Sexually Transmitted Diseases Menggunakan Algoritma Certainty Factor Mandra; Nouval Trezandy Lapatta; Syaiful Hendra; Syahrullah
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4293

Abstract

This research aims to design and develop an Android application that can be used to diagnose results Sexually Transmitted Diseases using algorithms Certainty Factor. Sexually Transmitted Diseases is a sexually transmitted disease that can cause serious health impacts if not immediately identified and treated appropriately. This application is designed to help users carry out initial diagnoses independently. The method used in developing this application is the Certainty Factor algorithm, which is a rule-based decision support method. This algorithm utilizes knowledge from experts in the medical field and combines it with symptom data provided by users to produce more accurate diagnoses. The app will allow users to input suggested symptoms and generate a diagnosis based on that information. It is hoped that this application will be a useful tool in a self-directed approach to diagnosis Sexually Transmitted Diseases.
Optimasi Pengambilan Keputusan dengan Neural Network: Menuju Era Keputusan Pintar Akram Kemal Dewantara
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4300

Abstract

The ability to make quick and accurate decisions in the midst of a digital age laden with complex data is critical to success in various industries. In this research, a neural network-based reasoning system is developed to enhance the smart decision-making process. We developed a neural network architecture by utilizing the power of deep learning. This enables the processing of historical and real-time data. We also conducted case studies in healthcare, finance, and HR management to test how effective it is. The results show that, compared to conventional approaches, this method has a significant improvement in processing time efficiency and an increase in decision accuracy of up to 15%. These results show that neural networks have the ability to change the decision-making landscape and offer intelligent solutions to real-world problems.
Designing a Presence Information System for Student Mentoring Activities Using the Laravel Framework Misna Asqia
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4311

Abstract

STT NF is a private higher education institution that combines technological knowledge with Islamic values. To achieve this goal, STT NF has a program called student mentoring. Mentoring is led by a mentor and attended by several mentees. The mentoring evaluation process is conducted regularly to assess the progress of each mentee in each group. The evaluation results of each group are sent to BKPK of STT NF. The researcher intends to build an information system for student mentoring attendance using Laravel Framework. The design method used the extreme programming approach. Based on the discussions conducted, it determined that there are five mentoring activities dashboards to be created. There are two known user categories, namely admin and mentor. The program was tested using black box testing with 22 scenarios. Based on the testing, it was concluded that all categories function correctly
Penerapan Algoritma K-Means Clustering dalam Menganalisis Pola Peminjaman Buku di Perpustakaan Sigit, Rapel
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4317

Abstract

Library book borrowing reflects readers' preferences on various topics, providing insights for improving collection management. This study categorizes books into five main categories: old books with few pages, modern books with short borrowing periods, classic books with long borrowing durations, books with many pages and moderate borrowing, and new books with varying borrowing durations. The dataset is analyzed through pre-processing, including feature creation, normalization, and standard scaling. The K-Means algorithm is used to cluster data based on Euclidean distance, with results evaluated using the Davies-Bouldin Index (DBI), where a lower value indicates better clustering quality. The optimal number of clusters is determined using the Elbow Method, showing five clusters as the most effective. Applying K-Means Clustering produces five informative clusters, with a DBI of 0.50 indicating good clustering quality. Scatter plots illustrate cluster distribution based on publication year, number of pages, and borrowing duration, from a dataset of 1323 borrowing records.
Pengembangan Trainer Kendali PID pada Sistem Fisik Elektrik Terintegrasi Aplikasi Pemograman Grafis Rozani, Elvyra Jovanka; Sunarya, Adhitya Sumardi; Suryatini, Fitria
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4320

Abstract

Increased competencies in control systems are essential for the future of higher education in this field. Polytechnic Manufacturing Bandung aims to enhance the educational process by integrating theory and practice in automation and mechatronics, as reflected in their project-based learning curriculum. Previously, they created a trainer model for control systems that could only be read analogously with an oscilloscope, which was deemed insufficient for implementing control theory. Therefore, a physical trainer for electrical systems with an interface display and integrated PID controls is needed. Fifteen students evaluated this trainer using the Likert scale based on the EMPI approach, resulting in an average interface presentation score of 83.2%. This indicates that the physical trainer with PID controls and a graphical programming interface effectively represents control theory and supports the learning process.
Heart Rate and Oxygen Saturation Internet of Things System (HROS-IoT) Uses Fuzzy Logic Hermansyah, Adi; Habibi, Ismail; Afifah, Nurul; Azhar, Iman Saladin B; Prasetyo, Aditya Putra Perdana; Maulida, Mutia Nadra
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4330

Abstract

Emergencies in hospitals, including in-hospital cardiac arrest (IHCA), necessitate effective response systems for monitoring vital signs such as heart rate and oxygen saturation. This study aims to develop and evaluate a Heart Rate and Oxygen Saturation Internet of Things (HROS-IoT) system utilizing the MAX30102 sensor and ESP32 microcontroller for real-time health monitoring. The system transmits data to the Blynk application via WiFi, enabling remote monitoring. Testing involved comparing the HROS-IoT system's performance against the commercial LK87 oximeter in measuring heart rate and oxygen saturation before and after meals with five participants. Results indicated that the HROS-IoT system produced heart rate measurements with an average error of 5.2 BPM before meals and 11.3 BPM after meals. Oxygen saturation readings showed an average error of 1% before meals and after meals. Despite minor discrepancies influenced by individual physiological differences and environmental conditions, the HROS-IoT system consistently delivered reliable data. The system's real-time monitoring capability and remote data access enhance proactive health management in hospitals. This study demonstrates the potential of the HROS-IoT system to improve patient outcomes and safety, suggesting further refinements for better accuracy and integration into healthcare settings.
Sistem Informasi Perpustakaan Berbasis Website Menggunakan Repository Pattern Agung Stiven Cahyati Angely; Lapatta, Nouval Trezandy; Syahrullah; Andi Hendra; Ryfial Azhar
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4332

Abstract

Pengembangan Sistem Informasi Perpustakaan Sekolah menggunakan Metode Repository Pattern bertujuan meningkatkan efisiensi dan efektivitas pengelolaan perpustakaan yang sebelumnya dilakukan secara konvensional. Sistem informasi berbasis web ini mempermudah pencatatan peminjaman, pengembalian buku, dan pengelolaan data lainnya. Hasil penelitian menunjukkan peningkatan kualitas pengelolaan perpustakaan, dengan akses informasi yang lebih cepat dan akurat. Mayoritas pengguna menyatakan puas dengan antarmuka sistem yang intuitif dan user-friendly. Sistem ini juga memudahkan pustakawan dan admin dalam mengelola data, mencatat peminjaman dan pengembalian buku, serta mengorganisasikan kategori buku. Kesimpulannya, penerapan sistem informasi perpustakaan berbasis web dengan metode Repository Pattern di SMK Negeri 3 Palu berhasil meningkatkan efektivitas dan efisiensi pengelolaan perpustakaan, serta memberikan kemudahan akses bagi pengguna.

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