cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Tri A. Sundara
Contact Email
tri.sundara@stmikindonesia.ac.id
Phone
+628116606456
Journal Mail Official
ijcs@stmikindonesia.ac.id
Editorial Address
Jalan Khatib Sulaiman Dalam 1, Padang, Indonesia
Location
Kota padang,
Sumatera barat
INDONESIA
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
 34   35   36   37   38 
Identifikasi Nilai Acak Melalui Pemosisian Ulang Fungsi XOR di Blok Pertama LFSR A5/1 Susilo Wibowo, Ayub; Wowor, Alz Danny
The Indonesian Journal of Computer Science Vol. 12 No. 6 (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.v12i6.3601

Abstract

Skema A5/1 menggunakan linear feedback shift register (LFSR) untuk menghasilkan keacakan. Reposisi awal dari fungsi linier pertama didasarkan pada pemilihan 4 dari 19-bit menurut hukum komutatif, dengan paling banyak 60 peristiwa reposisi.  Bit-bit yang dipilih ini menjalani proses iterasi fungsi XOR yang menghasilkan output bit acak maksimum. Hasil akhir dihasilkan oleh XOR yang memproses output dari setiap fungsi linier. Pengujian ekstensif dilakukan pada kemampuan algoritma untuk menghasilkan bit keluaran acak menggunakan metode perhitungan statistik seperti Runs Test, Block Bit, dan Mono Bit untuk mengukur keacakan. Hasilnya secara konsisten menunjukkan bahwa algoritma ini menghasilkan output acak untuk berbagai jenis input. Untuk mengevaluasi kemampuan enkripsi, sepuluh keluaran dipilih dan diuji tingkat korelasinya. Sembilan dari keluaran tersebut menghasilkan tingkat korelasi yang 'sangat rendah', sementara satu keluaran memiliki tingkat korelasi 'rendah'. Hasil ini mendukung keandalan desain sebagai generator kunci untuk melindungi informasi.
Penentuan Keabsahan Dokumen KHS Dengan Menggunakan QR Code dan Digital Signature di Politeknik Negeri Manado Lordan Kimbal, Heaven; Sudarsono, Amang; Winarmo, Idris
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.v13i1.3603

Abstract

The change in the KHS process from manual to computerized has positive impacts such as integration with the judicial system, ease of inputting and printing data, and in recapitulating data. However, there are risks in this concept, namely loss and damage to data which can cause doubts about the validity of KHS data. Departing from this problem, an idea emerged to create a system that can prove the validity of KHS printed documents by applying QR Code technology and Digital Signature. With Digital Signature, information about the contents of KHS when it is first printed is encrypted first so that it cannot be changed by unauthorized parties, then the encryption results will be stored on the QR Code. So that the determination of document validity is done by comparing the contents of the current document with the contents of the document in the QR Code, if the information from both is the same then the printed document is declared an original document and vice versa. The verification process will use hash logic which is one of the functions of providing verification and authentication because it produces a unique value for each input. This result is expected to help Politeknik Negeri Manado to check the validity of KHS printed by students.
Pemanfaatan Analisis Sentimen Terhadap Kasus Bunuh Diri Mahasiswa Menggunakan Naïve Bayes Classifier Ainnur Rafli; Kusnawi, Kusnawi
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.v13i1.3605

Abstract

Suicide is currently a serious problem in higher education, especially among university students, and special approaches and attention are required to prevent it. With today's advances in technology, emotion analysis techniques can be an effective way to understand students' feelings and thoughts that may lead to suicidal behavior or indicate a risk of suicide. For this study, we scraped the data for his 1,151 tweets on Twitter and cleaned it up to 817. Of these, there are 745 negative tweets and 72 positive tweets. Additionally, the data is implemented in an algorithm that performs a data split of 80:20 with an accuracy of 90,24%. That's the "depression" that often appears when visualizing Lata data. Especially in Indonesia, there are many suicides due to depression. The purpose of this study is to understand the factors associated with student suicide and to determine the effectiveness and accuracy of this algorithm. Additionally, this study is expected to provide insights into educational and mental health settings to improve prevention strategies and more effective approaches
Perancangan Sistem E-Commerce Dan Layanan Konsultasi Terintegrasi Pada Industri Landscape And Gardening Consultant Berbasis Website Acnan Dini Niken Putri Darmasari, Niken; Supriyono, Heru
The Indonesian Journal of Computer Science Vol. 12 No. 6 (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.v12i6.3606

Abstract

CV Karya Taman Alam merupakan sebuah perusahaan penyedia jasa yang berfokus pada berbagai aspek landscape dan kebun. Namun, proses transaksi yang masih mengandalkan metode tradisional dan manual yang memakan waktu lama. Penelitian ini bertujuan mengintegrasikan layanan konsultasi dengan sistem e-commerce pada platform berbasis website, untuk meningkatkan pengalaman pelanggan, memudahkan proses pembelian, dan meningkatkan efisiensi operasional. pengembangan sistem dilakukan menggunakan metode model waterfall dengan menggunakan bahasa pemrograman PHP dan basis data MySQL. Hasil pengujian, termasuk pengujian menggunakan black box dan System Usability Scale (SUS), menunjukkan skor rata-rata sistem sebesar 84,2, masuk dalam kategori grade scale B menurut SUS, menunjukkan penerimaan yang baik. Integrasi ini diharapkan dapat membawa perubahan positif dalam mengoptimalkan layanan perusahaan dan memenuhi kebutuhan yang semakin dinamis di industri landscape.
Sistem Rekomendasi Produk dengan Metode ABC-Cycle Counting untuk Pelayanan dan Pengelolaan Inventory Toko : Store Service and Inventory Management Application Using Product Recommendation System with ABC-Cycle Counting Method Nurrido, Dodi; Triase
The Indonesian Journal of Computer Science Vol. 12 No. 6 (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.v12i6.3608

Abstract

Toko ashion adalah usaha yang biasanya menyediakan segala jenis fashion seperti baju, celana, sendal, dan aksesoris. Masih banyak terdapat toko fashion yang melakukan penanganan manajemen keuangan dan inventaris secara manual sehingga perkembangan usaha terhambat oleh perputaran kas yang kurang ideal karena disebabkan tidak adanya rencana perputaran pendapatan maupun pendataan produk yang dapat menimbulkan perputaran uang yang tidak maksimal dan menyebabkan usaha susah untuk berkembang. Oleh sebab itu, dibutuhkan sebuah sistem yang mampu membantu mengelola pendapatan maupun kegiatan usaha dengan membangunan Aplikasi Pelayanan dan Pengelolaan Inventory toko (Appfashion) berbasis website yang mampu merekomendasikan produk yang harus segera dibeli dengan menggunakan Metode ABC-Cycle Counting.
Lean and Agile Software Development for Managing Technical Debt on A Large-scale Software: A Systematic Literature Review Simangunsong, Surya Seven Y; Raharjo, Teguh; Anita Nur Fitriani
The Indonesian Journal of Computer Science Vol. 12 No. 6 (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.v12i6.3612

Abstract

Agile methodologies are employed by software development teams for collaboration and adapting to changing requirements. However, this flexibility may lead to technical debt (TD), causing potential bugs in the long term. Lean principles, focusing on waste elimination and continuous process improvement, can be applied to manage TD in agile software development. This research conducts a systematic literature review on using lean and agile methodologies for TD management. The review identifies 34 papers, categorizing TD types, pinpointing lean and agile principles, and aligning technical debt categories with suitable lean and agile principles. Additionally, three existing technical debt management frameworks are identified: the TAP framework, the LTD framework, and the CoDVA framework. The study concludes that integrating lean principles into agile software development assists organizations in effectively managing technical debt. Furthermore, the research offers insights into selecting the most suitable TD management framework based on an organization's needs and available resources.
Analisis Sentimen Putusan Mahkamah Konstitusi terhadap Batas Usia Capres dan Cawapres Menggunakan IndoBERT Septian, Luffi; Aljauza, Teguh; Juliane, Christina
The Indonesian Journal of Computer Science Vol. 12 No. 6 (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.v12i6.3614

Abstract

Putusan Mahkamah Konstitusi nomor 90/PUU-XXI/2023 tentang batas usia calon presiden dan wakil presiden telah memicu perbincangan masyarakat. Hal ini ditandai dengan kata kunci ‘Putusan MK” pada media sosial Twitter/X menduduki peringkat tiga trending topik Nasional selama pertengahan bulan Oktober. Putusan tersebut dinilai kontroversial karena berkaitan dengan momentum Pemilihan Presiden 2024. Peneliti tertarik untuk memanfaatkan data dari media sosial twitter/X dalam menganalisis respon masyarakat terhadap Putusan Mahkamah Konstitusi dengan cara mengklasifikasikan respon tersebut ke dalam sentimen. Model yang digunakan dalam penelitian ini adalah IndoBERT, sebuah arsitektur transformer BERT yang dikembangkan oleh tim IndoNLU. Metode ini dipilih berdasarkan efektivitasnya dalam memproses teks berbahasa Indonesia untuk mengidentifikasi dan mengategorikan opini publik menjadi positif, negatif, atau netral terkait dengan keputusan Mahkamah Konstitusi. Hasil awal menunjukkan model IndoBERT tanpa augmentasi data mencapai akurasi 0.81 dan F1 skor 0.58. Selanjutnya, penggunaan teknik Synthetic Minority Over-sampling Technique (SMOTE) meningkatkan F1 skor namun tidak berdampak signifikan pada akurasi. Eksperimen selanjutnya dengan augmentasi random swap, menghasilkan peningkatan performa yang substansial, dimana model IndoBERT mencapai akurasi dan F1 skor sama-sama pada angka 0.90.
Tren Riset Sistem Informasi Dalam Publikasi Internasional: Analisis Bibliometrik Menggunakan VosVIEWER Lizar, Yaslinda; Siregar, Elfi Ramadani; Rosmita, Ummi; Silvia Ariati; Masyaratul Hayati
The Indonesian Journal of Computer Science Vol. 13 No. 5 (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.v13i5.3615

Abstract

Sistem informasi pada era ini sedang sangat hangat diperbincangkan dalam dunia IT. Tentunya hal ini akan berdampak pada peningkatan minat para peneliti untuk mempelajari serta mendalami pemahaman terkait sistem informasi dalam kurun waktu 5 tahun terakhir. Jurnal ini dibuat dengan maksud untuk memetakan tren penelitian sistem informasi melalui kajian bibliometrik terhadap 20.000 artikel jurnal internasional terindeks Scopus dalam jangka tahun 2019-2023. Analisis kejadian bersama kata kunci dengan VOSviewer mengidentifikasikan 4 kelompok utama dalam penelitian sistem informasi ini. Cluster dengan kepadatan tertinggi pada topik gis, patient, theory, dan outcome. Dan topik seperti magnesium, annual percent change, lightgbm, postoperative length tidak terlalu banyak diteliti. Pemetaan ini diharapkan dapat memberikan pengetahuan tentang arah penelitian sistem informasi di masa depan, terutama pada topik-topik yang masih sedikit dieksplorasi.
Machine Learning on Opinion Mining of Netizen's Hate Speech Pratiwi, Mutiana; Liana Gema, Rima
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.v13i1.3617

Abstract

Netizen comments written in an online news portal through social media platforms, one of which is Instagram, can be used as material in the sentiment analysis process, which can be classified into positive, negative, or neutral sentiments. Sentiment analysis is part of the study of text mining, the science of discovering unknown knowledge by automatically extracting information from large volumes of unstructured text into useful information. The resulting information is in the form of sentiment towards a topic, whether it tends to be positive, negative, or neutral. The classification method used in this research is Support Vector Machine (SVM) and TF-IDF data weighting to classify text. Stages to perform data analysis are pre-processing to clean data, word weighting, labeling data into positive, negative, or neutral classes, and classifying and visualizing data with graphs. Accuracy tests using 70:30 split data showed that the accuracy reached 98%. Tests with 80:20 and 90:10 split data also showed high accuracy of 98% and 99%.
Algorithm Decision Tree in Analysis Social Media Sentiment to Understand Consumer Views of Brands Pramana Gusman, Aggy; Andrianof, Harkamsyah
The Indonesian Journal of Computer Science Vol. 12 No. 6 (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.v12i6.3619

Abstract

Online marketplaces in Indonesia are growing rapidly and have become one of the main destinations for internet and social media users. Various marketplace services are available and accessed by the majority of Indonesians. However, with this development, consumer satisfaction with marketplace services varies, from positive, to negative, to neutral. Many consumers express their reactions on social media, including Twitter. In this study, an analysis of opinions was conducted on posts by online business customers in Indonesia on Twitter from various consumers. However, due to the large number of comments, it is difficult to conclude the customer's opinion about online shopping sites that offer the best services. Even trending topics on Twitter only display hot topics that are widely discussed without clear conclusions. To classify general opinion data on Twitter from e-commerce sites, the first step is to process tweet data using Rapidminer tools to recognize the tweet data. Then, the decision tree algorithm is used to categorize opinion data. The results showed that using cross-validation, the decision tree algorithm achieved an accuracy of 70.27 percent while using split validation, it achieved an accuracy of 66.95 percent. In this case, better accuracy was achieved using cross-validation. The results of this study can provide useful information for online businesses in Indonesia to improve the quality of their services and increase customer satisfaction. In addition, this study also provides an overview of the importance of utilizing the decision tree algorithm in categorizing opinion data on social media, especially on Twitter, as a tool for analyzing consumer sentiment towards a service or product.

Page 36 of 113 | Total Record : 1127

 34   35   36   37   38 

Filter by Year

2022 2026


Reset
Filter By Issues
All Issue Vol. 15 No. 1 (2026): The Indonesian Journal of Computer Science Vol. 14 No. 6 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 5 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 4 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science Vol. 14 No. 1 (2025): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science (IJCS) Vol. 12 No. 3 (2023): The Indonesian Journal of Computer Science Vol. 12 No. 2 (2023): The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science Vol. 11 No. 3 (2022): The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science More Issue