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INDONESIA
Indonesian Journal on Computing (Indo-JC)
Published by Universitas Telkom
ISSN : 24609056     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Indonesian Journal on Computing (Indo-JC) is an open access scientific journal intended to bring together researchers and practitioners dealing with the general field of computing. Indo-JC is published by School of Computing, Telkom University (Indonesia).
Arjuna Subject : -
Articles 251 Documents
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Development of Android-Based Classroom Presentation System by using Android Set?Top-Box Dita Oktaria; Herman Tolle; Aryo Pinandito
Indonesia Journal on Computing (Indo-JC) Vol. 8 No. 3 (2023): December 2023
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2023.8.3.855

Abstract

The integration of multimedia technology in classroom presentations offers significant benefits in delivering material effectively to students and enhancing the presenter's credibility. Traditionally, teachers faced issues like weak laptop battery life and unavailability of chargers. An innovative solution to this problem is the use of set-top-boxes, compact internet-enabled mini-PCs designed for specific purposes. With new-generation set-top boxes based on Android, users can develop their applications, opening new possibilities in presentation delivery. One effective solution involves creating a centralized system to manage presentation files stored on a server accessible through the set-top box. Through functional and non-functional testing, the system proves to meet desired needs. Users reported high satisfaction rates of 93%, and the application's response time was less than one second, confirming the efficiency of the Android Set-top-box. This technology not only enhances lesson delivery but also efficiently addresses classroom presentation challenges in a user-friendly manner.
Convergence Sublayer Analysis and Implementation on Medium Access Control Layer using The Embedded Configurable Operating System Febri Dawani; Tri Brotoharsono; Setyorini
Indonesia Journal on Computing (Indo-JC) Vol. 8 No. 3 (2023): December 2023
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2023.8.3.856

Abstract

This study explores the implementation of the Convergence Sublayer (CS) defined in IEEE Std 802.16TM-2004. The CS, situated atop the Medium Access Control Layer, plays a crucial role in classifying and mapping MAC Service Data Units (MSDU) to specific connections identified by Connection Identifiers (CID). Using the Embedded Configurable Operating System (eCos), an Open Source Real-Time Operating System, this research successfully demonstrates the implementation of MAC CS on a specific hardware platform. The findings indicate that eCos facilitates the efficient execution of MAC CS's classification and mapping functions.
QUIDS: A Novel Edge-Based Botnet Detection with Quantization for IoT Device Pairing Aji Gautama Putrada; Nur Alamsyah; Mohamad Nurkamal Fauzan; Sidik Prabowo; Ikke Dian Oktaviani
Indonesia Journal on Computing (Indo-JC) Vol. 8 No. 3 (2023): December 2023
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2023.8.3.878

Abstract

Advanced machine learning has managed to detect IoT botnets. However, conflicts arise due to complex models and limited device resources. Our research aim is on a quantized intrusion detection system (QUIDS), an edge-based botnet detection for IoT device pairing. Using knearest neighbor (KNN) within QUIDS, we incorporate quantization, random sampling (RS), and feature selection (FS). Initially, we simulated a botnet attack, devised countermeasures via a sequence diagram, and then utilized a Kaggle botnet attack dataset. Our novel approach includes RS, FS, and 16-bit quantization, optimizing each step empirically. The test results show that employing a mean decrease in impurity (MDI) by FS reduces features from 115 to 30. Despite a slight accuracy drop in KNN due to RS, FS, and quantization sustain performance. Testing our model revealed 1200 RS samples as optimal, maintaining performance while reducing features. Quantization to 16-bit doesn’t alter feature value distribution. Implementing QUIDS increased the compression ratio (CR) to 175×, surpassing RS+FS threefold and RS by 13 times. This novel method emerges as the most efficient in CR.
Business Process for debit card transactions using Electronic Data Capture (EDC) Case study: Bank CIMB Niaga Tbk Samuel Andi Kristyan; Suhardi
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 1 (2024): April, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.1.880

Abstract

EDC (Electronic Data Capture) in banking is a means of expediting transactions at trade outlets. Sometimes not all buyers bring cash to buy the goods they want, usually the shop owner/keeper directs the buyer to withdraw money at an ATM or transfer using mobile banking or something similar. The problem that occurs is that sometimes there are queues at the ATM and not all buyers activate mobile banking. In fact, sometimes you don't end up buying an item that you have bargained for/liked, it's just a matter of a difficult transaction process. The presence of EDC banking machines can reduce the above problems. EDC is a transaction tool that is widely used today. Apart from ease of transactions, it also leaves several problems that need to be fixed. In this paper the author wants to analyze business processes and improvements so that they can minimize the risk of crime and lost property.
Estimasi Biaya Proyek Pengembangan Aplikasi E-Government Di Indonesia Anung Asmoro; Lukito Edi Nugroho; Sujoko Sumaryono
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 2 (2024): August, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.2.881

Abstract

Proyek yang berhasil adalah yang menyelesaikan semua fitur yang dipersyaratkan sesuai jadwal dan biaya. Under-estimate dalam estimasi proyek dapat mengakibatkan understaffing, under-scoping, dan jadwal yang terlalu pendek. Over-estimate dalam estimasi proyek cenderung mengakibatkan biaya lebih besar dan memperpanjang waktu proyek, menghambat penggunaan sumber daya untuk proyek berikutnya. Pemanfaatan teknologi digital telah menciptakan e-government, sebuah bentuk baru birokrasi pemerintahan di negara maju. Dalam penerapan e-government, diperlukan penyesuaian birokrasi, regulasi, visi pimpinan daerah, alokasi anggaran, dan peningkatan kemampuan SDM. Tantangan utama dalam implementasi e-government termasuk birokrasi yang rumit, regulasi yang belum memadai, serta kurangnya pemahaman teknologi informasi oleh DPRD. Pengelolaan anggaran dan proyek e-government menjadi kunci keberhasilan implementasi e-government, namun masih sering terjadi pemotongan anggaran dan pengalokasian yang kurang tepat. Penelitian ini bertujuan menganalisis metode estimasi untuk proyek software e-government di Indonesia dan merekomendasikan model estimasi yang sesuai.
Utilizing GP 2 for Restaurant Recommendation Nitamayega; Gia Septiana Wulandari; Kemas Rahmat Saleh Wiharja
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 1 (2024): April, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.1.907

Abstract

The increasing diversity of food and beverage providers poses a challenge for people to find a restaurant that aligns with their preferences. Restaurant recommendation systems can address this problem by providing accurate and relevant suggestions. Although there are many previous studies have explored various recommendation methodologies, the utilization of knowledge graph implemented with GP 2 is still limited. Knowledge graphs can represent complex information in a structured way, while GP 2 is a graph-specific programming language that has a simple syntax. This research focuses on the implementation of a knowledge graph-based restaurant recommendation system with GP 2. The recommendation scheme built can provide the best accuracy, reaching 84.97%. This shows that the knowledge graph-based restaurant recommendation system with GP 2 can demonstrate the effectiveness of the system in providing accurate and relevant recommendations, showing the potential of knowledge graph and GP 2 for the development of recommendation systems in the future and being an effective solution to overcome recommendation problems.
Music Recommendation System Using Alternating Least Squares Method Muhammad Rafi Irfansyah; Dade Nurjanah; Hani Nurrahmi
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 1 (2024): April, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.1.908

Abstract

Music is not just entertainment, but it also has a positive impact on psychological well-being. The music landscape is generally dominated by millennials, especially in Indonesia. Music recommendation systems are becoming an important factor in offering songs that match users' preferences. Collaborative Filtering (CF), particularly the Alternating Least Squares (ALS) method, has become a popular solution for data sparsity problems in user-item interactions. Using the Precision@K metric, ALS provides the best results at a 50:50 data split ratio, 0.30225 for the Last FM dataset and 0.19742 for the Taste Profile dataset. Further analysis shows that ALS is more effective on datasets with balanced data distributions, such as Last FM, than on datasets with noisier characteristics, such as Taste Profile. The main conclusion is that ALS is suitable for use on datasets with balanced data distributions and can provide more optimal recommendations. For further development, handling sparsity data on Taste Profile needs to be improved to improve the performance of the recommendation model. This illustrates the importance of adapting the model to the unique characteristics of each dataset to achieve more accurate music recommendations.
Securing KTP Data Using QR Code Modification and Elliptic Curve Cryptography Rakha Aditya Nugraha; Ari Moesriami Barmawi
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 1 (2024): April, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.1.909

Abstract

Identity Cards (KTP) are essential for Indonesian people. KTP contains personal information, such as National Identity Number (NIK), Name, Address, Gender, etc. Since KTP has essential data and is still printed conventionally, there is a vulnerability if the KTP is lost, and the owner's data is disclosed so that if an irresponsible person finds it, the data can be used for impersonating the owner. In the previous method proposed by Haque et al., [1], the data was stored in a QR Code. However, there was no verification method to legitimize the original owner, and the system did not have a login feature. To overcome the weakness of Haque et al., method [1], the owner's NIK is encrypted using the Elliptic Curve El-Gamal (ECEG) and further signed using ECDSA by the owners before storing it in the QR Code. For obtaining the owner's data in the database, the verification process should be done after the QR Code is scanned. Using the proposed method, the probability of success for a guessing attack is 1 / (n-1). Meanwhile, the probability of success for an impersonation attack is 1 / (q1 * q2 * l).
SIMULASI PEMBANGUNAN JARINGAN MOBILE DENGAN SRSLTE DAN OAI Moch. Fahru Moch. Fahru Rizal; Prajna Deshanta Ibnugraha; Sandy Krisna Mukti; Malik Abdul Aziz
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 1 (2024): April, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.1.923

Abstract

Open Air Interface is a telecommunications infrastructure development platform that aims to create an open source 4G/5G telecommunications network. This technology can replace commercial 4G/5G network infrastructure and or interconnect with existing 4G/5G cellular networks. This study aims to create test-beds of 4G OAI and srsLTE in a limited non-commercial scope, using USRP B205-mini and B210 which runs 4G standard cellular services using a single-site scheme. The results of srsLTE and OAI integration have adequate performance in power of -32.6 dBm and a Power to Signal Ratio of 19.54 dB.
Implementation of IndoBERT for Sentiment Analysis of Indonesian Presidential Candidates Primanda Sayarizki; Hasmawati; Hani Nurrahmi
Indonesia Journal on Computing (Indo-JC) Vol. 9 No. 2 (2024): August, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.2.934

Abstract

In this modern era, Indonesian society widely utilizes social media, particularly Twitter, as a means to express their opinions. Every day, various opinions of Indonesian citizens are disseminated on this platform, including their views on prospective presidential candidates for the year 2024. Analyzing public opinions regarding prospective presidential candidates in 2024 is crucial to understanding the sentiment of the people toward these candidates. Such sentiment analysis can be conducted using deep learning techniques such as IndoBERT to acquire knowledge regarding the classification of sentiments as positive, neutral, or negative. IndoBERT is employed to generate vector representations that encapsulate the meaning of tokens, words, phrases, or texts. These representation vectors can then be input into a classification model to perform sentiment analysis. The sentiment classification model undergoes testing with a diverse set of tweets in the test dataset, which represent a wide range of public opinions. The evaluation results indicate an overall accuracy rate of 80%, with precision rates of 62% for negative sentiment, 81% for neutral sentiment, and 85% for positive sentiment. Additionally, the recall rates for each sentiment are 64% for negative, 81% for neutral, and 84% for positive, with corresponding F1-scores of 63%, 81%, and 85%, respectively.

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