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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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An Integrated Gesture Framework of Smart Entry Based on Arduino and Random Forest Classifier Almufti, Saman M.; Abdulazeez, Adnan Mohsin
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.v13i1.3735

Abstract

Gesture-based systems have emerged as a prominent breakthrough in the field of smart access control, effectively integrating security measures with user comfort. This study presents a novel gesture detection framework for smart entry systems that combines the computational capabilities of a Random Forest Classifier with the practicality of Arduino-based hardware. Central to methodology is the utilization of MediaPipe, an advanced computer vision library, to extract hand motion landmarks from live video streams. The selected landmarks function as a comprehensive dataset for training a Random Forest Classifier, which has been specifically chosen due to its high level of accuracy and efficiency in managing intricate classification jobs. The model exhibits outstanding competence in the categorization of gestures in real-time, attaining high levels of accuracy that are crucial for ensuring dependable entrance control. The Arduino microcontroller plays a vital role in the execution of the entry mechanism as it serves as the intermediary between the gesture detection software and the tangible entry control hardware. The incorporation of gesture recognition technology facilitates a cohesive and prompt user experience, wherein identified motions are directly converted into input commands. The system's practical use is demonstrated through a series of detailed tests, which highlight its dependability and efficiency across diverse climatic circumstances. The findings underscore the system's capacity as a flexible and safe solution for contactless access in many environments, including both private homes and highly protected establishments. Furthermore, the study makes a substantial contribution to the larger domain of human-computer interaction by showcasing the practicality of advanced gesture detection systems in many everyday contexts. The suggested framework presents a novel approach to smart entry systems and also paves the way for further investigation in the domains of smart home automation and interactive systems. In these areas, gesture-based interfaces have the potential to deliver user experiences that are both intuitive and efficient.
Analisis Keamanan Web Menggunakan Open Web Application Security Web (OWASP) Victor Ilyas Sugara; I Wayan Sriyasa
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.v13i2.3736

Abstract

Aplikasi web telah menjadi bagian integral dari kehidupan sehari-hari, memberikan layanan yang diperlukan untuk berkomunikasi, berbelanja, bertransaksi, dan berbagai aktivitas lainnya. Permasalahan yang muncul terkait keamanan web adalah ketidakmampuan sistem aplikasi untuk melindungi informasi sensitif dari ancaman siber. Top 10 OWASP adalah daftar yang diperbarui secara berkala yang memuat sepuluh kerentanan keamanan aplikasi web yang paling umum terjadi Level risiko yang bersifat medium memiliki confidence level yang sama, yakni 11.1%, dengan total level risiko Medium adalah 33.3%. Seluruh celah kemanan yang ditemukan hampir semuanya berkaitan dengan A05 Kesalahan Konfigurasi Keamanan & A06 Komponen yang Rentan dan Kedaluwarsa pada OWASP Top 10:2021.Rekomendasi perbaikan terhadap temuan sudah diberikan, dan diantaranya bersifat perbaikan didalam source code dan konfigurasi pada application server/web server yang diprioritaskan kepada temuan yang bersifat High, Medium dan Low.
Perancangan Antarmuka Aplikasi Edukasi Bisnis dengan Pendekatan Design Thinking Humaira Fauziah, Myeisha; Andrian, Rian; Venica, Liptia
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.v13i1.3737

Abstract

Di era digital sekarang teknologi sangat berperan aktif dalam hampir semua kegiatan manusia. Termasuk kegiatan bisnis, sekarang seorang pengusaha dituntut untuk bisa memanfaatkan teknologi untuk mempertahankan bisnisnya. Salah satu tipe usaha yang paling membutuhkan perubahan digitalisasi adalah UMKM (Usaha Mikro Kecil dan Menengah). Karena masih banyak UMKM tidak bisa beralih ke digitalisasi, salah satu cara untuk membantu meningkatkan perubahan UMKM ke dunia digital adalah dengan mendorong pelaku UMKM untuk mengikuti pelatihan bisnis atau kelas bisnis agar mereka mendapatkan pengetahuan untuk mengembangkan bisnisnya ke arah dunia digital. Maka dari itu dirancanglah antarmuka aplikasi edukasi bisnis Entrevo untuk memahami lebih baik permasalahan dan kebutuhan pengguna. Penelitian ini menggunakan metode design thinking dan Single Ease Question (SEQ) didapatkan hasil akhir yaitu 9 (dari 10 poin) yang menunjukkan bahwa desain aplikasi sudah baik dan user-friendly.
Predictions of Early Hospitalization of Diabetes Patients Based on Deep Learning: A Review: Machine Learning Al-Atroshi, Chiai; Adnan Mohsin Abdulazeez
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.v13i1.3738

Abstract

Unmanaged diabetes can result in a number of complications that need to be hospitalised. Diabetes is a chronic disorder. With preventive treatment, outcomes may be improved through early prediction of diabetes-related hospitalisation using data-driven algorithms. Here, we examine recent advances in deep learning methods for anticipating readmissions and unexpected hospital stays in adult patients with diabetes. Firstly, we present an overview of the main factors that indicate the need for hospitalisation due to diabetic complications. The research on hospitalisation risk prediction using structured health data, such as demographics, prescriptions, test results, etc., using conventional machine learning techniques is then summarised. Using data from insurance claims and electronic health records, we then examine current research that has used deep learning models. It is emphasised that longitudinal data can be included using recurrent neural networks. Model architectures, training methods, and important data modalities are covered. The assessment also addresses deployment difficulty and the model's performance assessment on real-world datasets. Ultimately, potential paths forward include hybrid models that integrate data diversity, explainable predictions, and clinical knowledge. In order to provide evidence-based predictions of the risk of hospitalisation and readmission for diabetes patients, we examine the potential and constraints of recently developed deep learning algorithms in this review.
Systematic Literature Review dengan Mengidentifikasi Software serta Metode Pengembangan Augmented Reality Caraka Aji Pranata; M Fairul Filza; Akbar
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.v13i1.3742

Abstract

Perkembangan teknologi di dunia setiap harinya mengalami peningkata yang sangat pesat. Salah satu wujud pesatnya perkembangan teknologi di Indonesia belakangan ini yang juga menjanjikan adalah Augmented Reality (AR). AR merupakan teknologi yang dapat menggabungkan aspek yang ada pada dunia nyata dengan dunia virtual. Seiring berkembangnya teknologi, pastinya kita dihadapkan dengan berbagai elemen pendamping yang juga turut berkembang dan beragam. Maka dari itu, penelitian ini bertujuan untuk mengidentifikasi perangkat lunak dan metode pengembangan AR yang umum atau sering digunakan di Indonesia. Metode Systematic Literature Review (SLR) dipilih sebagai metode yang akan digunakan dalam proses review terhadap literatur yang relevan dengan perkembangan AR. Hasil akhir penelitian ini berupa jenis perangkat lunak dan metode pengembangan AR yang umum atau sering digunakan dalam pengembangannya dalam kurun waktu satu tahun selama tahun 2023. Hasil penelitian diharapkan dapat membantu sebagai rekomendasi para pengembang AR dalam kontribusinya mengembangkan AR dengan perangkat lunak dan metode yang terbarukan.
Facial Beauty Prediction Based on Deep Learning: A Review Arabo, Wahab; Abdulazeez , Adnan Mohsin
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.v13i1.3743

Abstract

This review delves into Facial Beauty Prediction (FBP) using deep learning, specifically focusing on convolutional neural networks (CNNs). It synthesizes recent advancements in the field, examining diverse methodologies and key datasets like SCUT-FBP and SCUT-FBP5500. The review identifies trends in FBP research, including the evolution of deep learning models and the challenges of dataset biases and cultural specificity. The paper concludes by emphasizing the need for more inclusive and balanced datasets and suggests future research directions to enhance model fairness and address ethical implications.
High-Level Defence Model against Routing Attacks on the Internet-of-Things Sejaphala, Lanka Chris; Malele, Vusi; Lugayizi, Francis
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.v13i1.3744

Abstract

This paper is part of the doctoral work that aims to answer the following research question: “To what extent can an intelligent security model effectively defend against routing attacks in RPL-based Internet of Things (IoT) with a demonstration of less network resource consumption, high detection rate, and minimal false negatives?” To answer this question, this paper proposes a high-level conceptual framework to defend the IoT against routing attacks. In recent works, mitigation techniques have been proposed to act against routing attacks, however conceptual defence or mitigation framework is not presented as a set of steps to follow to develop an effective and robust intelligent security model. This paper aims to present a high-level conceptual defence framework against routing attacks; specifically, sinkhole, rank, DIS-Flooding, and worst parent. The four mentioned routing attacks are capable of disturbing IoT network functions and operations, and consuming network resources such as memory and power.
Klasifikasi Citra Penyakit Tanaman pada Daun Paprika dengan Metode Transfer Learning Menggunakan DenseNet-201 Salim, Vilvilia; Abdullah, Asrul; Utami, Putri Yuli
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.v13i2.3746

Abstract

Penyakit bercak daun yang disebabkan oleh bakteri Xanthomonas campestris pv. vesicatoria merupakan salah satu penyakit penting pada tanaman paprika di Indonesia. Penyakit ini dapat menurunkan kualitas dan kuantitas hasil panen paprika. Metode yang digunakan yaitu transfer learning dengan menggunakan model DenseNet-201. Penelitian ini menggunakan data gambar daun paprika yang terinfeksi dan tidak terinfeksi sebanyak 4.876 gambar. Data tersebut dibagi menjadi data latih, data validasi, dan data uji. Hasil penelitian menunjukkan bahwa model transfer learning mampu mendeteksi penyakit bercak daun pada paprika dengan akurasi keseluruhan sekitar 99.5%. Evaluasi model terhadap kelas “Bacterial Spot” dan “Healthy” menghasilkan precision, recall, dan F1-score rata-rata sekitar 99.5%. Penelitian ini menunjukkan bahwa metode transfer learning dapat digunakan sebagai sistem deteksi penyakit tanaman yang efektif dan efisien.
Analisis Tweet Politik-Keagamaan pada Hasil Pemilihan Presiden Indonesia tahun 2014 dan 2019: Sebuah Studi Eksploratif Zain, Poppy Dalama; Sutanto, Taufik Edy; Liebenlito, Muhaza
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.v13i1.3751

Abstract

Agama dan politik saling terkait dalam konteks pemilihan umum di Indonesia. Penggunaan isu agama dalam kegiatan politik merambah luas di pemilu Indonesia tahun 2014 dan 2019 di media sosial. Paper ini mengisi kekosongan di literatur untuk mengkaji fenomena penggunaan isu agama dalam politik secara kuantitatif. Data diambil menggunakan dari media sosial twitter menggunakan API secara legal dan menjaga privasi pengguna. Pengambilan data dilakukan dengan menggunakan kata kunci terkait agama seperti Islam, Al-Qur’an, Hadits, Halal, Shalat, dan sebagainya lalu di filter dengan berbagai kata kunci terkait politik. Melalui berbagai teknik eksplorasi data seperti analisis korelasi Spearman dan visualisasi geospasial, penelitian ini menemukan adanya hubungan signifikan antara banyaknya isu agama terkait politik dan perolehan suara calon presiden. Pada tahun 2014 korelasi untuk Prabowo dibandingkan korelasi untuk Jokowi lebih tinggi yaitu sebesar 0.72, lalu menurun pada tahun 2019 menjadi 0.56. Penelitian ini dapat dijadikan inspirasi untuk penurunan dan pencegahan terjadinya polarisasi di masyarakat akibat penggunaan isu agama dalam kegiatan politik.
Modeling of Wind Power Generation in Tegal Region using Matlab Simulink Saputri, Fahmy; Delana Wijaya, Sarah
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.v13i1.3752

Abstract

The increasing energy demands require larger energy production. However, fossil energy sources are depleting, necessitating the use of renewable energy to replace fossil fuels and meet energy needs in Indonesia. Indonesia has a significant wind energy potential. Wind power generation modeling is carried out in one of the cities in Indonesia, namely Tegal. By using Matlab Simulink, it is expected to assist in predicting renewable energy production. Tegal is one of the regions with high wind speeds in Indonesia, specifically at 3 m/s. From the modeling, the optimal blade radius and rotor angular velocity that can generate maximum power at a wind speed of 3 m/s can be determined. Wind power generation in Tegal with a wind speed of 3 m/s has the potential to produce electrical power of 768.55 W.

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