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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 59 Documents
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Search results for , issue "Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS)" : 59 Documents clear
Microsoft Excel Learning Application Design with Android Based using Gamification Method Permana, Angga; Rizal, Mochamad; gunawan, Dennis
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3374

Abstract

Microsoft excel is software can support performance in data processing, microsoft excel provides formulas and function that can be used to facilitate perfomance in data processing. Utilization of microsoft excel can be used in every day life in business and educational activities. Microsoft excel can perform arithmetic calculation, so can simplifying the assessment results and as an alternative that can provide maximum results. The purpose of this research is design and build a microsoft excel learning application with the gamification method to increase behavioral intention to use and immersion in the learning process to provide an alternative learning process in learning formulas and functions in microsoft excel. The method used in this study was designed and built with the gamification method using the six steps to gamification framework developed by Kevin Werbach in 2016. The results of this learning application have been evaluated by 32 respondents by filling out a survey based on the Hedonic Motivation System Adoption Model. From the survey, 77.5% were obtained for the behavioral intention to use aspect and 64.53% were obtained for the immersion aspect. The conclusion of this study in implementing gamification using the six steps to gamification framework states that they agree with evidence of 77.5% for the behavioral intention to use aspect and 64.53% for the immersion aspect.
Komparasi Metode Naive Bayes dan SVM pada Sentimen Twitter Mengenai Persoalan Perpu Cipta Kerja : Comparison of Naive Bayes and SVM Methods on Twitter Sentiment Regarding the Government Regulations on Job Creation Issue Farhan, Nur Muhammad; Setiaji, Bayu
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3375

Abstract

Salah satu yang baru ini ramai diperbincangkan adalah persoalan UU Cipta Kerja yang banyak ragam orang berbincangkan mengenai dampak postif dan negatif mengenai hal tersebut. Oleh karena itu analisa sentimen pada persoalan UU Cipta Kerja untuk bisa mengetahui berapaa banyak orang yang menolak atau mendukung hal tersebut. Penelitian ini menggunakan data tweet sebanyak 622 data tweet yang berbahasa Indonesia. Kemudian ulasan tersebut di katagorikan ke beberapa sentimen dan algoritma, sentimen positif mendapatkan sebanyak 224 tweet, sebanyak 332 tweet yang bersentimen negative, dan sebanyak 66 bersentimen netral. Kemudian data tersebut dimasukkan kedalam algoritma Naïve Bayes dan SVM untuk menentukan tingkat akurasi yang didapatkan. Algoritma Naïve Bayes mendapatkan akurasi 73% dengan data akurasi training 87% dan SVM mendapatkan 78% untuk data testing dengan akurasi 99% dengan data training. Dari hasil tersebut menunjukka bahwa tingkat akurasi algoritma SVM lebih tinggi daripada akurasi algoritma Naïve Bayes.
Penerapan Metode User Centered Design Pada Perancangan Website Evidence File Kegiatan Dinas Kesehatan Provinsi Sumatera Selatan Perdani, Tharisa Antya; Ruskan, Endang Lestari; Meiriza, Allsela
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3377

Abstract

Saat ini hampir di semua kegiatan pemerintah maupun non pemerintah telah memanfaatkan teknologi informasi, salah satu contohnya adalah sistem penyimpanan data kegiatan. Tidak hanya memerhatikan fungsionalitas dari sebuah sistem, akan tetapi tampilan juga termasuk ke dalam aspek penting yang sering kali terjadi masalah di bagian tersebut. Pada pengelolaan data evidence file aktivitas di Dinas Kesehatan Provinsi Sumatera Selatan saat ini menggunakan Google Drive yang memiliki masalah terkait tampilan. Pada Google Drive tidak bisa memberikan input keterangan atau caption tentang file kegiatan yang dilaksanakan, karena Google Drive hanya menyimpan gambar, pdf, doc, dan lainnya. Selain itu, Google Drive dapat diakses oleh banyak orang yang mengakibatkan layout tampilan bisa berubah-ubah. Maka, membutuhkan suatu strategi terkhusus dalam membuat sistem terkomputerisasi secara otomatis dalam mengelola evidence file, dengan merancang tampilan yang sesuai keinginan pengguna dari sisi layout menu file menerapkan metode User Centered Design (UCD). Hasilnya berupa prototype website evidence file kegiatan. Evaluasinya menggunakan metode System Usability Scale guna mengetahui nilai kegunaan rancangan yang dibuat. Hasil yang diperoleh adalah 82. Skor ini dikatergorikan “Excellent”, grade scale B, dan tingkat penerimaannya “Accaptable” yang artinya dapat diterima sesuai dengan keinginan user dan layak untuk dikembangkan.
Implementasi Deep Classifier untuk Diagnosis Penyakit Glaukoma pada Citra Retina Mata Dharmawan, Dhimas Arief; Leuveano, Raden Achmad Chairdino; Suryotomo, Andiko Putro; Tahya, Michel Pierce; Sani, Sayang
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3378

Abstract

Penerapan deep learning untuk diagnosis glaukoma dari gambar retina merupakan bidang yang berkembang pesat dalam pencitraan medis. Penelitian ini menyelidiki keampuhan model pembelajaran mendalam dengan menggunakan dua set data uji yang berbeda: DRISHTI-GS dan ORIGA, yang menjelaskan potensi dan tantangan dalam tugas medis yang kritis ini. Dalam kasus dataset DRISHTI-GS, model deep learning menunjukkan kinerja yang bervariasi di seluruh zaman. Epoch awal menunjukkan akurasi yang rendah dan kehilangan yang tinggi, tetapi peningkatan yang signifikan terjadi antara epoch 40 dan 70, mencapai akurasi sekitar 96% pada epoch 100. Hal ini menunjukkan potensi deep learning dalam mendiagnosis glaukoma dari gambar retina DRISHTI-GS. Sebaliknya, dataset ORIGA menunjukkan kemajuan yang lebih konsisten. Model ini terus meningkatkan akurasi, mencapai 97,54% pada epoch 80, dengan penurunan kerugian yang terjadi secara bersamaan, yang mengindikasikan konvergensi yang kuat. Hal ini menggarisbawahi kemahiran model dalam diagnosis dataset ORIGA, menyoroti janji klinisnya. Singkatnya, penelitian ini menunjukkan kelayakan deep learning untuk diagnosis glaukoma dari gambar retina, dengan hasil yang menjanjikan pada dataset DRISHTI-GS dan ORIGA.
Machine Learning and Fuzzy C-Means Clustering for the Identification of Tomato Diseases Saleh, Amir; Ridwan, Achmad; Gibran, M Khalil
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3379

Abstract

Diseases in tomato plants can cause economic losses in the agricultural industry. Identification of tomato plant diseases is important to choosing the right action to control their spread. In this research, we propose an approach to identify tomato plant diseases using a machine learning algorithm and lab colour space-based image segmentation using the fuzzy c-means (FCM) clustering algorithm. The segmentation method aims to separate the infected area, leaf image, and background in the tomato plant image. In the first step, the tomato image is represented in the Lab colour space, which allows for combining information on brightness (L), red-green colour components (a), and yellow-blue colour components (b). Then, the FCM algorithm is applied to segment the image. The segmentation results are then evaluated through an identification process using machine learning techniques such as k-Nearest Neighbors (kNN), Random Forest (RF), Support Vector Machine (SVM), and Naïve Bayes (NB) to measure the level of accuracy. The dataset used in this research is tomato images, which include various plant diseases obtained from the Kaggle dataset. The performance results of the proposed method show that the segmentation approach based on Lab colour space with the FCM clustering algorithm is able to identify infected areas well. The accuracy value of each machine learning method used is kNN of 85.40%, RF of 88.87%, SVM of 80.73%, and NB of 74.60%. The proposed method shows success in accurately identifying types of tomato plant diseases and obtains improvements compared to without using segmentation.
Pengaruh Knowledge Sharing Factor Terhadap Keberlanjutan Penggunaan E-Learning Pasca Covid-19: The Influence of Knowledge Sharing Factors on the Continuity of Using E-Learning Post-Covid-19 Ariyanti, Putri; Ditha Tania, Ken; Wedhasmara, Ari; Meiriza, Allsela
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3382

Abstract

E-learning includes learning methods that use information technology and can be accessed via the internet, making it possible to learn remotely without face-to-face meetings. E-learning functions to implement knowledge management practices, especially in sharing knowledge. Studies on various knowledge-sharing factors influencing the adoption of e-learning in the post-pandemic context are still limited in the existing literature. Therefore, this study has the objective of developing an Expectation Confirmation Model by taking into account the factors of knowledge sharing (communication openness, personal trust, sharing motivation, use of technology, and perceptions of ease of use of technology) to test the viability of using e-learning, especially at Srivijaya University. This study uses the Partial Least Squares Structural Equation Modeling (PLS-SEM) method to test the validity of the developed model. Study data was collected from active students at Sriwijaya University who used or are currently using e-learning in lectures. The results of this study show that knowledge sharing factors, including openness of communication, personal trust, motivation to share, usefulness of technology, and perceived ease of use of technology, are important factors in determining the continued use of e-learning services at Sriwijaya University.
Sentiment Analysis Performance Value Optimization Using Hyperparamater Tunning With Grid Search On Shopee App Reviews Muhammad Luthfi Al-Ghifari; Ken Ditha Tania
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3384

Abstract

The rapid development of technology today has provided convenience for us in today's civilization. One of these developments is the invention of the internet due to high internet penetration and rapid growth in mobile usage, online shopping has increased tremendously. This online shopping is now often referred to as e-commerce. E-commerce is one of the trade models that has been widened under the effect of extensive use of technology. Specifically, e-commerce refers to the usage of the Internet or other networks. Shopee is one of the popular marketplaces in Indonesia that has the highest number of visitors of 129 million per month and can be downloaded on the Google Play Store. Play Store itself has several features such as Reviews that can allow users to give opinions. All complaints and opinions from shopee users can be channeled into this feature. With this a research aims to optimize the performance value of sentiment analysis with the Term Frequency-Inverse Document Frequency (TF-IDF) method and Hyperparameter Tuning with Gridsearch for the Shopee application on the Google Play Store. Based on research the reviews resulting in 3000 data where 2015 user data is positive and 985 data is negative. Testing data was split by a ratio of 90:10 for 300 data test in each classification model to find the accuracy score. With hyperparameter tuning using gridsearch we can see the result of each accuracy score of KNN, DCT, RF, and LR is increasing from 0.73 to 0.77, 0.823 to 0.826, 0.856 to 0.87, and 0.856 to 0.866. This indicated that among the machine learning model that had been tuning using gridsearch, KNN is the one that highly increased.
Faktor Adopsi Microsoft Teams Sebagai Teknologi Kolaborasi Pada Perusahaan Dengan Modifikasi UTAUT2 Tanizar, Ade Lido; Gui, Anderes
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3386

Abstract

Beberapa perusahaan di Indonesia telah melakukan adopsi Microsoft Teams untuk mendukung kegiatan berkolaborasi di perusahaan. Adopsi ini dilakukan sebagai langkah adaptasi selama masa pandemi Covid-19, serta selanjutnya mendukung skema hybrid-working arrangement yang diadopsi beberapa perusahaan pasca berakhirnya masa pandemi. Studi ini melakukan identifikasi atas faktor yang mempengaruhi adopsi teknologi kolaborasi yang digunakan di perusahaan, dengan pendekatan UTAUT2 yang diadopsi dengan melakukan modifikasi dengan menambahkan konstruk perceived value. Hasil yang didapatkan pada penelitian ini menunjukkan sebagian besar konstruk UTAUT2 dapat menjelaskan penerimaan adopsi teknologi kolaborasi, termasuk perceived value. Pada penelitian ini, Effort Expectancy ditemukan tidak berpengaruh signifikan pada adopsi Microsoft Teams di perusahaan.
Automatic Generation of Unit Test Data for Dynamically Typed Languages Hayatou Oumarou; El Mansour, Faouzi
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3396

Abstract

Testing is the major means of verifying and validating software. It is a repetitive and time-consuming activity. Testing is neglected because of its high cost and the fact that it does not add functionality to the system. As a result, many programmers don't write tests. To remedy this, some researcher proposed automatic test generation. Test generation is a solution that reduces workload and increases productivity. In this paper, we propose a test data generation approach for unit tests in dynamically typed languages. Our approach is based on the analysis and decomposition of the AST (Abstract Syntax Tree) obtained when compiling the source code of the method under test. We validate this approach in Pharo a real system. The results on three systems show the effectiveness of the approach.
IT Project Management Control and The Control Objectives for IT and Related Technology COBIT 2019 Framework Jaya, Ruddy Kusuma; Melissa Indah Fianty
The Indonesian Journal of Computer Science Vol. 12 No. 5 (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.v12i5.3397

Abstract

The development of information technology has been leveraged by state-owned enterprises (BUMN) operating in the fields of Maintenance, Repair, and Overhaul, as well as industrial services in Indonesia. Among the company's 21 priority projects, three projects have been identified as experiencing delays in the planning phase related to the delivery of business requirements. The measurement of IT governance capability was conducted using the process rating of COBIT 2019. The selected process objectives were APO02, APO03, and APO05. The results of the capability level measurement indicate that APO02, APO03, and APO05 have reached level 2. Based on the measurement results, findings have been identified that require improvement, especially in APO03, such as providing understanding to key stakeholders about enterprise architecture and enterprise architecture design. As a recommendation for improvement, it is expected that the company can engage in Enterprise Architecture design to align strategic program priorities with architectural objectives.

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