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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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Terrestrial Laser Scanning for 3D Assets Registry Suhari, Ketut Tomy; Purwanto, Hery; Sai, Silvester Sari
The Indonesian Journal of Computer Science Vol. 12 No. 2 (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.v12i2.3195

Abstract

This study aimed to assess the feasibility of using terrestrial laser scanning (TLS) technology for creating 3D asset registries in facilities management. The research utilized a case study approach to scanning an industrial facility, and the resulting data was processed to create a 3D model of the assets. The study found that TLS technology can produce highly accurate and detailed 3D models of assets, which can aid in asset management and maintenance. However, the technology has some limitations, such as cost and the need for skilled operators. The study suggests that TLS technology can be a valuable tool for asset management and recommends further research in this area.
T-S Fuzzy Tracking Control Based on H∞ Performance with Output Feedback for Pendulum-Cart System Rosalinda, Hanny Megawati; Agustinah, Trihastuti; Alfathdyanto, Khairurizal
The Indonesian Journal of Computer Science Vol. 12 No. 2 (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.v12i2.3196

Abstract

In some practices, not all state variables are available because of limited or noisy measurements. Thus, via output feedback, an observer is used to estimate the unmeasured states. To apply linear controllers to the pendulum-cart system, the Takagi-Sugeno fuzzy model is utilized by linearizing the system in more than one operating point. The effect of disturbances on tracking performance is reduced to the prescribed attenuation level by H∞ performance. The stability of the whole closed-loop system is investigated using the Lyapunov function. Sufficient conditions are derived in terms of a set of Linear Matrix Inequality (LMI) to obtain the controller and observer gain. Simulation results show that the proposed control method can make the system track the sinusoidal reference signal, maintain stability, and attenuate the effect of disturbances to less than the prescribed attenuation level measured by L2 gain. In the implementation process, an adjustment is needed to move the observer’s pole and speed up the observer’s responses.
Incremental News Mining Using Evolving Clustering with Functional Operators Hidayah, Amalia Wirdatul; Barakbah, Ali Ridho; Syarif, Iwan
The Indonesian Journal of Computer Science Vol. 12 No. 2 (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.v12i2.3197

Abstract

Online media publish journalistic products, one of which is news online (online news). This is in line with the findings of the Ministry of Communication and Informatics (Kemkominfo), that in 2018 there were 43,000 online media in Indonesia. On generally in getting actual news, humans tend to read the news on online media one by one. The activity is not effective because of the news that produced by online media have the same information with each other news. In this study, we propose an innovative solution to this issue by developing a news mining system that employs clustering based on an evolving system. This system has the potential to improve the effectiveness of news retrieval by grouping similar news together and identifying key information trends, ultimately enhancing the ability of individuals to obtain actual news. Based on research observations, the performance of news clustering using an evolving clustering system with functional operators is quite good, as evidenced by an accuracy of 83%.
Anti-spoofing methods in face recognition Bezas, Konstantinos; Foteini Filippidou
The Indonesian Journal of Computer Science Vol. 12 No. 3 (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.v12i3.3198

Abstract

Biometric data are personal data that result from specialized processing techniques and are associated with physical, biological, or behavioral characteristics of a natural person that allow for or confirm their unquestionable identification. These characteristics or identifiers are permanent and unique. This paper refers to the biometric characteristics used by systems, their mode of operation, and the categories they are distinguished in. The types of attacks that they may be subjected to are then analyzed, along with the anti-spoofing methods proposed in some studies specifically for systems that use the face as a biometric feature. Finally, numerical data is presented regarding the scientific interest that the topic of anti-spoofing methods in biometric systems has shown in the last decade.
Analisis Sentimen Terhadap Topik Kenaikan Harga Bahan Bakar Minyak (BBM) pada Media Sosial Twitter Tiara Danirmala; Nugroho, Yusuf Sulistyo
The Indonesian Journal of Computer Science Vol. 12 No. 3 (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.v12i3.3199

Abstract

Media sosial Twitter menjadi salah satu media yang banyak digunakan masyarakat Indonesia untuk membagikan informasi, pendapat, ataupun sekedar berdiskusi tentang topik yang sedang tren dan beredar luas, misalnya tentang kenaikan harga bahan bakar minyak (BBM). Penelitian ini bertujuan untuk menganalisis sentimen masyarakat tentang kenaikan harga BBM di media sosial Twitter . Penelitian ini dilakukan dengan cara menganalisis sentimen tweet yang diunggah di Twitter untuk mengetahui polaritasnya dengan menerapkan klasifikasi Naïve Bayes. Selain analisis sentimen, data tweet juga dicari diskusi topik yang paling banyak dibahas terkait dengan kenaikan harga BBM dengan menggunakan metodeAlokasi Dirichlet Laten (LDA ). Hasil penelitian menunjukkan bahwa sebanyak 53.3% tweet memiliki polaritas positif, 31.2% tweet berpolaritas negatif, dan 15.5% tweet dinyatakan netral. Hasil evaluasi klasifikasi dengan Naive Bayes diperoleh nilai akurasi 60% . Sedangkan topik yang banyak dibicarakan masyarakat di Twitter secara umum menyatakan penolakannya terhadap kenaikan harga BBM. Hal ini menunjukkan bahwa masyarakat menolak kebijakan tersebut namun dinyatakan dengan komentar secara positif.
Pengaruh Sistem Informasi Terhadap Proses Penciptaan Ilmu Pengetahuan Pada Mahasiswa Fakultas Ilmu Komputer Universitas Sriwijaya Aritonang, Cindy Nadira Elfarisa; Jambak, Muhammad Ihsan
The Indonesian Journal of Computer Science Vol. 12 No. 3 (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.v12i3.3200

Abstract

Penciptaan pengetahuan merupakan suatu proses yang dilakukan oleh individu untuk menciptakan dan mendapatkan ide-ide kreatif oleh organisasi. Namun, terjadinya proses penciptaan pengetahuan dalam diri masing-masing individu tentunya berbeda berdasarkan faktor-faktor yang mempengaruhi proses penciptaan pengetahuan tersebut. Teknologi merupakan faktor pendukung paling penting dari produktivitas proses penciptaan pengetahuan di berbagai kalangan dan sistem informasi diperlukan sebagai media dalam proses penciptaan pengetahuan. Theory of Planned Behavior dan teori Budaya Organisasi merupakan teori yang mendasari konstruk penelitian ini. Penelitian ini menggunakan metode kuantitatif. Populasi dalam penelitian ini berjumlah 2.666 dan jumlah sampel sebanyak 348 yang diperoleh melalui metode stratified random sampling. Dalam menganalisis data dalam penelitian ini menggunakan teknik Structural Equation Model (SEM-PLS) dan menggunakan software SmartPLS. Hasil yang diperolah adalah proses penciptaan pengetahuan dipengaruh oleh Sikap Individu, Budaya Organisasi dan Sistem Informasi. Sedangkan Sistem Informasi tidak dapat mempengaruhi hubungan antara Sikap Individu dan Budaya Organisasi dengan Proses Penciptaan Pengetahuan.
Perspektif Penerima Pengetahuan untuk Penciptaan Pengetahuan Mahasiswa Fakultas Ilmu Komputer Universitas Sriwijaya Chantika, Trievanni; Ihsan Jambak, Muhammad
The Indonesian Journal of Computer Science Vol. 12 No. 3 (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.v12i3.3201

Abstract

Dalam proses pembelajaran, penciptaan pengetahuan terjadi ketika seorang individu dapat menerima pengetahuan dari individu lain dan dapat menciptakan pengetahuan yang baru. Namun, proses tersebut terkadang tidak berjalan dengan baik, maka dibutuhkan suatu sistem informasi yang sesuai dengan kebutuhan pengguna dengan mengetahui perspektif penerima pengetahuan dalam proses pembelajaran untuk penciptaan pengetahuan. Teori yang mendasari konstruk penelitian ini adalah Model SECI (Sosialisasi, Eksternalisasi, Kombinasi, Internalisasi). Penelitian ini menggunakan metode kuantitatif. Populasi dalam penelitian ini berjumlah 2.666 dan jumlah sampel 348 yang diperoleh menggunakan metode Stratified Random Sampling. Dalam menganalisis data, menggunakan teknik Rasch Model dan software Winstep. Hasil yang diperoleh adalah proses sosialisasi dan kombinasi merupakan faktor yang mempengaruhi penerima pengetahuan karena cenderung lebih mudah dilakukan dan banyak disetujui untuk diterapkan dalam proses pembelajaran.
Faktor-Faktor yang Mempengaruhi Pemilik Pengetahuan dalam Proses Pembelajaran pada Mahasiswa Fakultas Ilmu Komputer Universitas Sriwijaya Dian Apriani, Dian Apriani; Ihsan Jambak, Muhammad
The Indonesian Journal of Computer Science Vol. 12 No. 4 (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.v12i4.3203

Abstract

Dalam proses pembelajaran, penciptaan pengetahuan terjadi ketika seorang individu yang berperan sebagai pemilik pengetahuan dapat menyampaikan pengetahuan yang dimilikinya ke individu lain. Namun, proses tersebut terkadang tidak berjalan dengan baik, sehingga dibutuhkan suatu sistem informasi yang sesuai dengan kebutuhan pengguna sebagai pemilik pengetahuan dengan mengetahui faktor-faktor yang mempengaruhi pemilik pengetahuan dalam menyampaikan pengetahuan pada saat proses pembelajaran. Teori yang mendasari konstruk penelitian ini adalah Model SECI (Sosialisasi, Eksternalisasi, Kombinasi, Internalisasi). Penelitian ini menggunakan metode kuantitatif. Populasi dalam penelitian ini berjumlah 2.666 dan jumlah sampel 348 yang diperoleh menggunakan metode Stratified Random Sampling. Dalam menganalisis data, menggunakan teknik Rasch Model dan software Winstep. Hasil yang diperoleh adalah proses sosialisasi dan internalisasi merupakan faktor yang dapat mempengaruhi mahasiswa sebagai pemilik pengetahuan karena cenderung lebih mudah dilakukan dan banyak disetujui untuk diterapkan.
The Multi-Layer Perceptron Neural Network Implementation as Train Type Classification Cahyo, Anton Cahyo Saputro; sudarsono, amang sudarsono; Yuliana, Mike Yuliana
The Indonesian Journal of Computer Science Vol. 12 No. 3 (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.v12i3.3204

Abstract

The purpose of train detection systems is to check that related track section is clear of vehicles before a train may be authorized to pass through a railroad. The detection of the train is important task for ensuring the safety of train traffic. Multi-layer Perceptron classifier, which consists of feedforward neural networks constructed of multiple layers of interconnected artificial neurons, proved to be effective for trainset class classification in this study. Using Raspberry Pi and IMU sensor BNO055, dynamic response of any train type interaction can be handled by windowing and Real Fast Fourier Transform (RFFT). Dense layer with 5 neurons, using the ReLu activation function, and specifying the input shape as (6= 3-axis accelerometer in X, Y, and Z directions, and 3 axis directions from gyroscope). The classification process in this implementation, which consist of three classes of train types, has been completed with accuracy above 92,7%.
Semantic Information Search with Automatic Ontology Creation in Regulations National Standards for Higher Education in Indonesia Hidayah, Nadila Wirdatul; Ali Ridho Barakbah; Iwan Syarif
The Indonesian Journal of Computer Science Vol. 12 No. 3 (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.v12i3.3207

Abstract

In Indonesia, there are around ten types of legal products that contain higher education regulations. With a large number of articles, more effort is needed when users search for links between one article and another. Based on these problems, it is necessary to have an automatic article representation search system using an automatic ontology. Ontology refers to the hierarchical structure of entities and their relationships. In this paper, the results of the development of an information retrieval system with an automated ontology will be explained. This system describes a process begins with receiving input of higher education regulatory files which are used as data samples Permendikbud No 3 of 2020. Then split the data into articles, paragraphs and contents which are then formed ontologies by building 3 detection functions (Definitive Creation, Compound Creation, and Reference Detection). System output has an accuracy of search results reaching an accuracy of 92.5%.

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