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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 1,170 Documents
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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
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
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
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
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
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
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.
Measurement of Employee Information Security Awareness: A Case Study of National Civil Service Agency Fadhil, Ahmad; Yazid, Setiadi
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3640

Abstract

National Civil Service Agency is a State institution tasked with the role and function of overseeing and implementing national civil servant management using information technology. There are 4.2 million civil servant data distributed throughout Indonesia that must be safeguarded by BKN. As the utilization of information systems grows, it also leads to an increase in information security risks. Based on the reports from Id-SIRTII/CC and BKN's internal report, there has been an increase in cyber attacks targeting BKN. In addition, there are other types of attacks that occur, such as online defacement, phishing, DDOS, and employee data theft, as well as the presence of employees who are still indifferent to information security. Based on this, the objective of this research is to measure the level of information security awareness among BKN employees and identify the factors that influence it. The Human Aspects of Information Security Questionnaire (HAIS-Q) using the Knowledge, Attitude, and Behavior (KAB) model was selected for measurement, with an additional focus on the Management of Information Systems/Technology Assets, consisting of a total of 75 statements. The quantitative measurements conducted yielded a result of 88.80% for the level of information security awareness among BKN employees, categorized as good. Furthermore, there is a significant influence on information security awareness from the dimensions of knowledge towards attitude, attitude towards behavior, and knowledge towards behavior.
Self-Efficacy: Meningkatkan Jiwa Kewirausahaan Di Era Digital Marta, Rizkayeni; Ganefri; Yulastri, Asmar; Riyanda, Afif Rahman; Hasan, Hanapi; Yunus, Yuliawati
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3641

Abstract

In the digital era which is full of rapid changes and complex challenges, success in the world of entrepreneurship is not only determined by technical knowledge and skills, but also by psychological factors. The entrepreneurial spirit is very important economically and socially so that entrepreneurship is very important both economically and socially. One of the factors driving the entrepreneurial spirit in the digital era is self-efficacy. Self-efficacy is essential for the willingness to act entrepreneurially, to identify and seize opportunities. Self-efficacy plays an important role in building an entrepreneurial spirit. The method for writing this article adopts the literature review method, articles sourced from the Google Scholar, elsevier, tanfonline platforms. In an effort to improve the entrepreneurial spirit in the digital era, contributions from the world of education are needed, so that educational programs can influence individuals' self-efficacy and self-confidence, supporting them to try, learn, and persist in pursuing an entrepreneurial future. Thus, individuals who have high self-efficacy regarding entrepreneurship will have high self-confidence, thereby triggering enthusiasm to become someone who has an entrepreneurial spirit.
Deteksi Penyakit Tanaman Padi Berbasis Android Melalui Pemanfaatan Teachable Machine Saputra, Heru; Stephane, Ilfa; Sundara, Tri; Bahri, Aulia Hidayatul
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3643

Abstract

Padi adalah tanaman pangan utama di banyak negara, termasuk Indonesia, dan pertumbuhannya sangat dipengaruhi oleh faktor lingkungan dan kualitas tanah. Namun, petani sering menghadapi tantangan dalam mengelola Organisme Pengganggu Tanaman (OPT) yang dapat merusak tanaman dan mengurangi produktivitas. Untuk membantu petani mengatasi tantangan ini, penelitian ini memanfaatkan Teachable Machine, sebuah aplikasi berbasis web untuk mendeteksi penyakit pada daun padi. Penelitian ini menggunakan dataset dari Kaggle dan melatih model dengan gambar daun padi yang terinfeksi. Hasilnya menunjukkan bahwa aplikasi ini efektif dalam mendeteksi penyakit daun padi dan dapat membantu petani dalam mengidentifikasi dan menangani hama pada tanaman padi mereka. Namun, efektivitas aplikasi ini sangat bergantung pada kualitas dan jumlah data yang digunakan untuk melatih model
Penggunaan Teknologi Natural Language Processing dalam Sistem Chatbot untuk Peningkatan Layanan Informasi Administrasi Publik Nadzif, Mukhamad Abid; Saefurrohman; Soelistijadi, R.
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3645

Abstract

Penelitian membahas pengembangan chatbot dengan platform DialogFlow yang terintegrasi pada aplikasi Telegram untuk menyediakan informasi layanan administrasi di Pemerintahan Desa Tosari. Tujuannya adalah untuk meningkatkan kualitas layanan publik khususnya informasi layanan administrasi melalui sistem terpadu di tingkat desa guna mempercepat aliran informasi yang diperlukan, berupa pengembangan sistem kecerdasan buatan berupa Chatbot. Chatbot adalah program yang mampu berkomunikasi dengan manusia melalui pesan teks atau suara. Dengan menggunakan pemrosesan Natural Language Processing (NLP) yang merupakan bagian dari kecerdasan buatan, memungkinkan pengguna untuk berinteraksi dengan komputer menggunakan bahasa sehari-hari, seolah-olah sedang berbicara dengan manusia. Pengujian Usability dengan System Usability Scale (SUS) dan pengujian pengalaman pengguna pada chatbot dengan User Experience Questionnaire (UEQ) menunjukkan hasil yang positif, pengujian SUS memperoleh nilai akhir sebesar 86 dan UEQ memperoleh rata – rata nilai skala diatas 0,8, yaitu berada pada level Excellent. Hal ini menunjukkan bahwa implementasi chatbot efektif dalam memberikan informasi layanan administrasi di Pemerintahan Desa Tosari

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