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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,127 Documents
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Komparasi Pendidikan Kewirausahaan Di Indonesia Dan China Melalui Kewirausahaan Teknologi Informasi Digital Oriza, Wike; Ganefri; Giatman; Yulastri, Asmar; Maksum, Hasan
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): 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.v12i6.3620

Abstract

Tujuan dari penelitian ini untuk mengetahui faktor yang mempengaruhi minat berwirausaha di Indonesia dan China serta perbedaan yang dimiliki dan untuk mengetahui perbandingan atau komparasi pendidikan kewirausahaan antara Indonesia dan China. Metode yang digunakan dalam penelitian ini yaitu study literatur kemudian dianalisis dan ditarik kesmpulan. Hasil kajian literatur menunjukkan bahwa Pendekatan pendidikan kewirausahaan di kedua negara dapat disesuaikan dengan mempertimbangkan perbedaan yang ditemukan untuk memenuhi minat dan motivasi kewirausahaan mahasiswa masing-masing negara. Di China, fokus dapat diberikan pada membangun keyakinan mahasiswa untuk mengatasi rintangan, sementara di Indonesia, penekanan dapat diberikan pada memperkuat kepercayaan bahwa berwirausaha memberikan manfaat. Selain itu, penggunaan profil wirausaha sukses, terutama wirausaha muda, dapat menjadi motivator yang efektif di kedua negara. Indonesia maupun China telah mengambil langkah-langkah penting dalam mengembangkan pendidikan kewirausahaan. Meskipun keduanya menghadapi tantangan yang berbeda, baik Indonesia maupun China memiliki potensi besar untuk terus memajukan pendidikan kewirausahaan dan mendukung generasi muda dalam membangun bisnis yang inovatif dan berkelanjutan. Tumbuh dan berkembang pesatnya kewirausahaan di China dan diIndonesia tidak lepas dari peran teknologi informasi digital. Dunia digital menawarkan sumber daya baru yang sangat luas bagi wirausahawan untuk memanfaatkan peluang mempromosikan bisnis yang digelutinya. Mulai dari pengumpulan data terbuka, konten, kode dan layanan yang tumbuh secara eksponensial hingga kontribusi online penggunan dan komunitas di seluruh dunia. Keywords : Minat Berwirausaha di Indonesia dan China, Pendidikan Kewirausahaan di Indonesia dan China, Teknologi digital.
Optimalisasi Metode Naive Bayes Classifier Untuk Prediksi Persetujuan Kredit Syakur, Achmad; Purwandi Putra, Rendri; Juliane, Christina
The Indonesian Journal of Computer Science Vol. 13 No. 1 (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.v13i1.3622

Abstract

Kredit adalah bentuk pembiayaan yang banyak orang ajukan ke bank atau perusahaan penyedia kredit. Dalam proses pengajuan kredit, dilakukan analisis untuk menentukan apakah kredit yang diajukan layak atau tidak. Penelitian ini bertujuan untuk membantu bank atau perusahaan penyedia kredit dalam melakukan persetujuan kredit dengan efektif dan akurat dalam menentukan status pengajuan. Penelitian ini menggunakan teknik data mining dan kumpulan dataset yang berasal dari kaggle.com. Terdapat 12 atribut dan 2 kelas yang digunakan dalam penelitian ini. Dalam penelitian ini, metode klasifikasi Naive Bayes dan optimasi kelompok partikel (PSO) digunakan. Prediksi persetujuan kredit dengan metode naïve bayes classifier menghasilkan nilai akurasi sebesar 80,00% dengan nilai AUC 0,884. Sebaliknya, prediksi persetujuan kredit dengan metode particle swarm optimization (PSO) menghasilkan nilai akurasi sebesar 96,67% dengan nilai AUC 0,69.
Cybersecurity Improvement Design in Critical Infrastructure PT XYZ Case Study Gunawan, Adi; Rizal Fathoni Aji
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): 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.v12i6.3624

Abstract

Prevention of cyber attacks is an important factor that organizations need to do to support maximum business process continuity. One of the important factors needed is the protection of data and information assets by the critical infrastructure owned. This paper discusses increasing the capacity of critical infrastructure at XYZ organization. The NIST CSF framework is a benchmark assessment tool for critical infrastructure capacity at PT XYZ. The results obtained from the assessment are used to make recommendations for controls related to critical infrastructure. The risk assessment found 107 risk scenarios that led to 11 recommendations for critical infrastructure improvement areas. Prioritization of the resulting recommendations is expected to increase the resilience and capacity of critical infrastructure at PT XYZ in the face of current and future cyber threats.
Platform Budidaya Perairan Ekosistem Tambak Berbasis Internet Of Things Arisdiawan, Rossi; Setiawardhana; Agus Indra Gunawan
The Indonesian Journal of Computer Science Vol. 13 No. 1 (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.v13i1.3627

Abstract

Indonesia has a potential pond area of 2,963,717 hectares. Ponds are a place for breeding ecosystems such as shrimp. The digitalization system in ponds is very necessary for management and development and has an impact on economic growth. Development in the field of aquaculture involves extensification and intensification. One of the intensification programs is to utilize Internet of Things (IoT) technology to identify various parameters from the Pond which are sent to the Webserver. This research is to produce a webserver-based platform to serve as a data center and monitor several IoT devices on the farm. This platform uses an internet network with HTTP and MySql protocols. Operations related to web servers and devices refer to standard quality settings from pond farmers.
Desain Sistem Keamanan terhadap Spoofing GPS pada Aplikasi Android: Integrasi Program Perlindungan dalam Source Code Zaim Irfansyah Arbi; Santoso , Banu
The Indonesian Journal of Computer Science Vol. 13 No. 1 (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.v13i1.3630

Abstract

Perkembangan aplikasi Android berbasis lokasi menghadapi ancaman serius dari serangan spoofing GPS yang semakin canggih. Penelitian ini mengusulkan sebuah sistem keamanan yang responsif dengan mengintegrasikan perlindungan langsung ke dalam source code aplikasi Android. Fokusnya adalah memblokir akses opsi pengembang, yang sering dimanfaatkan oleh aplikasi spoofing GPS di Play Store. Metode ini diharapkan dapat meningkatkan keamanan aplikasi Android berbasis lokasi. Tujuan utama adalah mencegah serangan spoofing dengan melindungi integritas data lokasi. Hasil penelitian menunjukkan efektivitas sistem dalam mengatasi celah keamanan yang spesifik ini, memberikan kontribusi penting dalam menjaga keamanan aplikasi Android di era serangan spoofing GPS yang semakin mengancam.
Data Mining Implementation in Admission of New Students Using Zone Systems Nurhidayat, Hikmat; Hariyanto; Chirstina Juliane
The Indonesian Journal of Computer Science Vol. 13 No. 1 (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.v13i1.3631

Abstract

Every aspect of education that is now in place has to be continuously improved by the government. The Admissions Process for New Students (PPDB) in schools that have a zoning system in place is examined in this study. The primary goal of the study is to use the clustering approach to calculate the distance between students and schools. Analyzing, gathering, processing, and evaluating data are all steps in the research methodology. The study's findings demonstrate how the zoning system has a big impact on school enrollment trends. These results highlight how crucial it is to keep the PPDB's zoning system under constant review in order to provide equitable access to education for all pupils without sacrificing educational quality. The investigation ultimately discovered clustering in the distance, classified as the closest and farthest radius, between the student's home and the school. as well as the significance of a more comprehensive study.
Simulasi Algoritma Apriori dan FP-Growth Dalam Menentukan Rekomendasi Kodefikasi Barang Pada Transaksi Persediaan Sari, Purwita; Kesuma, Lucky Indra; Oklilas, Ahmad Fali; Buchari, M. Ali
The Indonesian Journal of Computer Science Vol. 13 No. 1 (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.v13i1.3632

Abstract

Keberhasilan proses pembangunan memerlukan dukungan optimal dalam pertukaran data dan informasi antar instansi guna mencapai integrasi sistem yang seimbang antara pemerintah dan para pengguna. SAKTI, sebuah aplikasi keuangan tingkat instansi, telah dirancang untuk mengelola segala aspek keuangan, mulai dari perencanaan hingga pertanggungjawaban anggaran. Aplikasi SAKTI ini mengintegrasikan semua aplikasi satuan kerja yang ada, bertujuan untuk meningkatkan efektivitas, efisiensi, transparansi, dan akuntabilitas dalam pengelolaan keuangan. Meskipun telah diimplementasikan sejak awal tahun 2022, operator komitmen masih menghadapi kendala dalam penentuan kodefikasi barang, terutama karena kurangnya familiaritas dengan tugas tersebut dan jumlah barang yang banyak sebagai referensi. Kesalahan yang dilakukan oleh operator komitmen dapat berdampak pada proses pendetailan aset pada modul persediaan dan aset. Dalam penelitian ini, peneliti menggunakan metode Algoritma Apriori dan frequent pattern growth (FP-growth) sebagai alat untuk menemukan sejumlah aturan asosiasi dari data transaksi barang yang disimpan dalam basis data aplikasi SAKTI. Hasil simulasi menunjukkan bahwa aturan yang memenuhi minimum support dan minimum confidence, dengan pemilihan terbanyak adalah Ballpoint Standar Tecno, refill tisu plastik, Lak Ban Hitam 2 Inchi Merk Daimaru, dan Ballpoint Kenko K1 (0,5) sebesar 100%.
Development of Corrosion Segmentation Using Deep Learning Double Architecture Method to Assist the Analysis and Evaluation Process of Corrosion Inspection Juliarsyah, Rizanto; Alief Wikarta
The Indonesian Journal of Computer Science Vol. 13 No. 2 (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.v13i2.3633

Abstract

Corrosion of pump unit components often occurs in coal mines and can lead to frequent failures of some components. As a result, a corrosion inspection needs to be performed on each component to minimize the possibility of damage. Currently, manual inspection methods are used for corrosion testing but there are still metal defects in the form of corrosion that are uninspected. Therefore, this study aimed to develop corrosion segmentation using computer vision with deep learning double architecture method for detection and evaluation of metal corrosion in order to reduce the loss due to manual inspections. To produce a faster and more accurate analysis method, deep learning double architecture algorithm, namely VGG16-UNET, can be applied with the help of computer vision technology. Consequently, the use of VGG16-UNET method achieved an accuracy of 98.42%. This is in contrast with the single UNET architecture, which produced an accuracy of 92.6%. Based on these findings, it was concluded that the development of this recommended inspection made the analysis and evaluation of corrosion inspection to be quick and easy.
The Influence of Optimization of the k-Means Algorithm with Genetic Algorithm on the Results of High Dimension Data Clustering Ramadhana, Yulinda; Jambak, Muhammad Ihsan
The Indonesian Journal of Computer Science Vol. 13 No. 1 (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.v13i1.3634

Abstract

Clustering k-means begins with the random initial determination of the centroid. Initially generated random centroids often cause k-means to be trapped in the optimum local solution, which results in poor clustering quality. Therefore, this study examined the effect of genetic algorithms in determining initial centroids in k-means. Clustering k-means with random initial centroids and with initial centroids from genetic algorithm calculations are each tested on the data with dimension reduction and without dimension reduction. Based on the results of the initial centroid testing obtained from genetic algorithms, the quality of cluster results increased by 54.9% in the high dimensional data and 52.4% in the data that had been carried out for the dimensional reduction. This result shows that the k-means clustering with initial centroids obtained from genetic algorithm calculations has the best cluster/solution results with significant results.
Approaches in Determining User Story Quality through Requirement Elicitation : A Systematic Literature Review Angga Hendriana; Raharjo, Teguh; Nurfitriani, Anita
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): 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.v12i6.3639

Abstract

A survey of 108 agile practitioners revealed that user stories are the most widely used method for capturing requirements. However, user stories can be interpreted differently by different stakeholders, leading to potential misunderstandings within the development team. Additionally, the interconnectedness of user stories poses challenges during the requirement elicitation process. A Systematic Literature Review (SLR) of 27 articles about user story elicitation process were selected and these are examined to determine user story quality. This research will provide a comprehensive summary of user story elicitation approaches and their application in addressing user story quality issues. The study will also offer insights into selecting appropriate approaches for resolving challenges in user story requirement elicitation. Finally, most user story elicitation approach primarily focus on addressing the issue of ambiguity.

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