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Applied Information Technology and Computer Science (AICOMS)
Published by Politeknik Negeri Ketapang
ISSN : -     EISSN : 29647703     DOI : https://doi.org/10.58466/aicoms
Core Subject : Science,
Computer Science & IT
Applied Information Technology and Computer Science (AICOMS) is an online version of national journal in Bahasa Indonesia and English, published by Department of Informatics Engineering, Politeknik Negeri Ketapang. AICOMS also has a print version. AICOMS also invites academics and researchers in the field of information technology, particularly from informatics engineering and information systems research to submit their articles. The articles to be published is an original work and has never been published. Incoming articles will be reviewed by a team of reviewers from internal and external sources.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 37 Documents
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Analisis dan Evaluasi Fitur Web Aptikom Menggunakan Metode Customer Knowledge Management (Studi Kasus: Website Aptikom.org) Widjiyati, Nur; Pramono, Eko
Applied Information Technology and Computer Science (AICOMS) Vol 2 No 2 (2023)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v2i2.1328

Abstract

Aptikom merupakan badan organisasi yang didalamnya tergabung perguruan tinggi dan prodi bidang Informatika dan Komputer seluruh Indonesia, beralamat web di aptikom.org, situs ini merupakan perpanjangan tangan Aptikom dalam menyampaikan informasi dan proker-proker pada calon anggota dan anggotanya. Situs ini juga mencantumkan pendaftaran online danperpanjangan keanggotaan dengan media Google Form yang ditempelkan pada web aptikom, oleh karena itu penulis merasa tertarik untuk mengevaluasi dan mengeksplorasi web tersebut. Penulis menggunakan metode CKM untuk sebagai dasar evaluasinya, dimana fokus poin penilaian ada pada segi konten dan informasi, segi layouting dan segi fitur tambahan. Hasil penelitian menunjukkan, rata – rata web Aptikom sudah sangat baik sebagai media informasi anggotanya, namun penulis menemukan beberapa halaman yang masih blank dan tidak menampilkan uraian berita web apapun. Selain itu dari segi layouting, penulis merasa editor web sangat menghargai keindahan seni pengolahan tata layout pada web Aptikom, dengan ditemukannya contohnya pada halaman Sejarah Aptikom, dengan penegasan teks menggunakan bold dan Capitalize Each Word. Dari segi fitur tambahan, peneliti menghighligt halaman login yang penulis belum merasa cukup untuk mendapatkan datanya
Pengembangan sistem informasi pembangunan daerah berbasis website menggunakan metode waterfall Tulkhoiriyah, Inayah; Dwi Kurniawan, Safar; Darmanto, Darmanto
Applied Information Technology and Computer Science (AICOMS) Vol 3 No 1 (2024)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v3i1.1330

Abstract

Regional Development is a crucial aspect in achieving community progress and welfare. The Regional Development Information System (SIPD) serves as a vital tool in supporting the planning, management, and monitoring of development projects. This study discusses the development of a web-based SIPD using the Waterfall software development method. The Waterfall method was chosen for its structured and linear framework, with clear stages from analysis to design, implementation, testing, and maintenance. The study focuses on the design and implementation of a system capable of presenting regional development information transparently and accurately to the public. The development of SIPD involves several steps, including requirements analysis, responsive user interface design, integration of project monitoring features, and testing to ensure the system's reliability and security. Implementing the website as the primary platform enables easy access for stakeholders, including local governments, the public, and related parties. The results of this study indicate that the development of a web-based SIPD using the Waterfall method provides an efficient and structured solution. The system facilitates quick and easy access to regional development information, enhances transparency, and strengthens public involvement in the development process. Therefore, the application of the Waterfall method in the development of a web-based SIPD is expected to provide a solid foundation for improving the effectiveness of regional development planning and management.
Perancangan Sistem Informasi Manajamen Pelayanan Pasien Rawat Jalan Berbasis Web Di Puskesmas Miftakhudin, Mokh; Dwi Kurniawan , Safar
Applied Information Technology and Computer Science (AICOMS) Vol 3 No 1 (2024)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v3i1.1340

Abstract

The Web-Based Outpatient Service Management Information System at Community Health Centers is an application designed to support outpatient service processes for patients seeking medical check-ups at health centers. This application aims to assist health center staff in providing better services to patients. It also serves as a platform for storing patient data related to medical check-ups conducted at the health center. The application is developed using Hypertext Preprocessor (PHP) as the programming language, the Waterfall development method, and Unified Modeling Language (UML) for design modeling. The study resulted in a web-based application that allows health center staff to manage patient data, examiner data, queues, patient medical records, visits, prescriptions, medications, patient referral information, payment data, and generate necessary reports to support patient services.
Audit Manajeman Keamanan Informasi Untuk Kelayakan Keamanan Sistem Informasi(Studi Kasus : Politeknik Lamandau, Kalimantan Tengah) Hidayat, Rahmat; Febriani, Ariana; Nilam Sari, Kurnia Ayu; Rahayu, Riska Puji; Puji Rahayu, Riska
Applied Information Technology and Computer Science (AICOMS) Vol 2 No 1 (2023)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v2i1.1448

Abstract

It should be written in one paragraph consisting of a maximum of 200 words. For scientific articles, the abstract should provide an overview of the work. We strongly advise authors to use the following structured abstract style, but without headings: (1) Background: Place the question in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarise the main findings of the article; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and should not contain results that are not presented and substantiated in the main text and should not overstate the main conclusions.
Pemanfaatan Wireless Sensor Netwrok Untuk Monitoring Parameter Kualitas Air Kolam Budidaya Ikan Tawar di SMKN 2 Ketapang Kalimantan Barat Wahyudi, Eka; Darmanto, Darmanto; Indah Pradasari, Novi
Applied Information Technology and Computer Science (AICOMS) Vol 2 No 2 (2023)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v2i2.1510

Abstract

Tujuan dari kegiatan Penelitian ini adalah membangun sistem monitoring parameter kualitas air kolam budidaya ikan tawar di Lab APAT SMKN 2 Ketapang. Hasil penelitian ini diharapkan mampu menyumbangkan kajian ilmiah dalam bidang perancangan dan pengembangan sistem informasi. Pada sistem monitoring nantinya siswa dan guru dapat melakukan kontrol parameter kualitas air yaitu suhu dan pH tanpa harus mengecek satu per satu kolam budidaya. Sistem ini menyediakan fitur pengontrolan suhu dan pH memanfaatkan Wireless Sensor Netwrok (WSN) sehingga apabila terdapat kolam budidaya yang mengalami kenaikan maupun penurunan parameter kualitas air langsung dapat diketahui dan dapat segera diberi perlakuan khusus. Sistem monitoring memanfaatkan WSN dibuat untuk membantu proses kontrol parameter kualitas air yang pada awalnya harus dilakukan secara manual dengan membutukan waktu sekitar 30 menit sampai dengan 1 jam untuk mengecek masing-masing kolam. Diharapkan dengan adanya sistem tersebut kegiatan mengecek parameter kualitas air menjadi lebih hemat waktu maupun tenaga serta dapat meningkatkan keakuratan dalam pemeriksaan parameter kualitas air dan sistem tersebut dapat membantu para taruna/taruni maupun guru untuk monitoring dari jarak jauh tanpa harus datang ke kolam budidaya. Sistem kontrol parameter kualitas air tersebut dibuat berbasis Android agar dapat diakses dan terjangkau selama prosesmonitoring. Monitoring dilakukan agar semua data informasi yang diperoleh dari hasil pengamatan tersebut dapat menjadi landasan dalam mengambil keputusan tindakan selanjutnya yang diperlukan.
Analisis Sentimen Komentar Twitter Tentang Perfoma Manchester United Dengan Menggunakan Algoritma Support Vector Machine Dwi Cahyadi, Ambrosius; Rizvi Roshan, Muhamad; Rizky Pribadi, Muhamad
Applied Information Technology and Computer Science (AICOMS) Vol 3 No 1 (2024)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v3i1.1511

Abstract

Manchester United is one of the largest clubs in the English Premier League with an exceptional history in European and global football. In the 2023/2024 season, Manchester United experienced a very poor season, leading to various positive and negative sentiments from its fans, especially on social media. Sentiment data was gathered from Twitter, where Manchester United fans expressed their opinions regarding the team's performance in the Premier League. This study employs the Support Vector Machine (SVM) method to process and classify data collected from Twitter, aiming to analyze the sentiments of Manchester United fans based on their social media comments. The results indicate that the performance of the Support Vector Machine is relatively poor, achieving an accuracy of 58.73%. This is due to the dataset relying on a single keyword, which led to suboptimal and less complex data, resulting in the Support Vector Machine (SVM) producing relatively low accuracy.
Perbandingan Algoritma SVM dan Naïve Bayes Berbasis SMOTE dalam Analisis Sentimen Komentar Tiktok pada Produk Skincare Liem, Steven; Setiawan, Thomas; Pribadi , M. Rizky
Applied Information Technology and Computer Science (AICOMS) Vol 3 No 1 (2024)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v3i1.1523

Abstract

This research compares the performance of the Support Vector Machine (SVM) and Naïve Bayes algorithms in sentiment analysis of TikTok comments about skincare products, using the Synthetic Minority Over-sampling Technique (SMOTE) to address data imbalance. The evaluation results indicate that SVM outperforms Naïve Bayes, achieving an accuracy of 59.43% compared to 47.65%. Additionally, SVM excels in the F1 Score metric (60.37% versus 54.74%), although Naïve Bayes demonstrates slightly higher precision (67.96% compared to 62.76%). Therefore, SVM proves to be more effective in classifying sentiment comments, making it the recommended algorithm for sentiment analysis tasks in the skincare product domain on TikTok.
Analisis Sentimen Hasil Pertandingan Sepakbola Timnas Indonesia di Piala Asia U-23 pada Platform Youtube menggunakan Algoritma Suport Vector Machine (SVM) Pangestu, Danang; Malik, Maulana; Pribadi, Muhammad Risky
Applied Information Technology and Computer Science (AICOMS) Vol 3 No 1 (2024)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v3i1.1528

Abstract

This study aims to analyze YouTube users' perceptions of the Indonesian national football team's matches in the 2024 AFC U23 Asian Cup. The research seeks to identify whether user sentiments toward the team's match results are positive, negative, or neutral. By using comments from the YouTube platform, the study examines public reactions to the outcomes of the Indonesian national team's matches in the U23 Asian Cup. Sentiment analysis of the match results was conducted using the Support Vector Machine (SVM) algorithm. Two SVM-based classification models were evaluated, one utilizing 40% of the data for testing and the other using 60%. The findings reveal that the first model, with 40% test data, achieved an accuracy of 65.41%, while the second model achieved an accuracy of 63.76%. Although the first model demonstrated slightly higher accuracy, the second model performed better in terms of precision (61.65%), recall (63.76%), and F1-Score (55.68%).
Analisis Sentimen Terhadap Aplikasi Mitra Darat Menggunakan Algoritma Naive Bayes Classifier dan K-Nearest Neighbor Wijaya, Ananda; Rivaldo, Mario; Rizky Pribadi, Muhammad
Applied Information Technology and Computer Science (AICOMS) Vol 3 No 1 (2024)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v3i1.1542

Abstract

The transportation industry is now an important element as the times develop, especially for today's young generation. Mitra Darat itself is also one of these industries. An application that allows users to easily find out the bus departure schedule that they will take anywhere and anytime on their mobile device. Reviews are definitely given for every app available both positive and negative. With this, we are trying to conduct sentiment analysis research for the Mitra Darat application through reviewing comments from the Google Play Store so that we can identify sentiments related to the use of the Mitra Darat application, as well as provide valuable insights to land transportation service providers to understand user views and improve user services. from the results of our sentiment analysis. The algorithms we use are KNN and NBC. These two algorithms are commonly used by many people because of their expertise in classifying sentiment analysis data and are also popular among researchers. Based on our test results, it can be concluded that our sentiment analysis model designed using the NB algorithm displays higher accuracy performance than KNN. The accuracy of the NB model reached 99.28%, while KNN achieved an accuracy of 80%. This shows that the naïve Bayes algorithm is more suitable to obtain maximum accuracy compared to using k-nearest neighbors.
Klasifikasi Opini Masyarakat Terhadap Naturalisasi Pemain Sepak Bola Menggunakan KNN dan SMOTE Rikky, Rikky; Graciela, Michelle; Irsyad, Hafiz
Applied Information Technology and Computer Science (AICOMS) Vol 3 No 1 (2024)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v3i1.1547

Abstract

This study analyzes public sentiment toward the naturalization of football players using the K-Nearest Neighbor (KNN) method and the Synthetic Minority Oversampling Technique (SMOTE). KNN is employed for sentiment classification, while SMOTE addresses class imbalance in the dataset. The methodology includes data collection, labeling, cleaning, preprocessing, classification, and model evaluation using Google Colab and Python. The results indicate that without SMOTE, the model performs better, achieving high precision, recall, F1 score, and accuracy. In contrast, applying SMOTE reduces performance, particularly in precision and F1 score. The "Manhattan Neighbor 7" and "Manhattan Neighbor 3" models without SMOTE demonstrate near-perfect results, while SMOTE significantly decreases several evaluation metrics. Additionally, the analysis of public opinions on YouTube reveals a tendency toward negative sentiment in podcasts about player naturalization, hosted by Bung Towel and Anjas Asmara, reflecting public skepticism and critical views on the topic. This study provides valuable insights into public sentiment and the effectiveness of classification methods in the context of national sports issues.

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