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Journal of Data Mining and Information Systems
Published by Yayasan Pendidikan Penelitian Pengabdian Algero
ISSN : 29865271     EISSN : 29863473     DOI : https://doi.org/10.54259/jdmis
Core Subject : Science,
Computer Science & IT
Journal of Data Mining and Information Systems (JDMIS) is intended as a medium for scientific studies of research results, thoughts, and critical-analytic studies regarding research in the field of computer science and technology, including Information Technology, Informatics Management, Data Mining, and Information Systems. It is part of the spirit of disseminating knowledge resulting from research and thoughts for the service of the wider community. In addition, it serves as a reference source for academics in Computer Science and Information Technology. JDMIS publishes papers regularly two times a year, namely in February and August. All publications in JDMIS are open, allowing articles to be freely available online without a subscription.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 38 Documents
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Sentimen Komentar Universitas Pelita Harapan Pada TikTok Menggunakan Metode K-Nearest Neighbor Wijaya, Robert; Suwandhi, Albert
JDMIS: Journal of Data Mining and Information Systems Vol. 2 No. 1 (2024): February 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v2i1.2418

Abstract

In the evolving digital era, social media, particularly TikTok, has become a pivotal platform for information sharing and communication, including by educational institutions such as Universitas Pelita Harapan (UPH). The use of TikTok at UPH has generated diverse comments that require effective management, prompting this research to develop sentiment by using the K-Nearest Neighbor (KNN) algorithm. This study aims to address two main issues: analyzing the accuracy of the K-Nearest Neighbor algorithm in sentiment of comment sentences and measuring the performance of the K-Nearest Neighbor algorithm in calculating analysis results on comment sentences. This research employs the KNN method with a dataset of 1213 entries from 2021 to 2023 containing keywords related to UPH from TikTok platform content. The study is managed and conducted on Google Colab using the Python programming language. Based on the results of training and testing data, an accuracy of 91% is obtained, with precision at 93%, recall at 91%, and an f-1 score of 92%. From the performance of the KNN algorithm, it can be concluded that the KNN method can classify sentiment in comments
Perancangan Sistem Informasi Kedai Kopi Menggunakan Metode Rapid Application Development (RAD) Ardhana, Valian Yoga Pudya
JDMIS: Journal of Data Mining and Information Systems Vol. 2 No. 1 (2024): February 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v2i1.2422

Abstract

The development and speed of information technology in the industrial revolution 4.0 requires companies or business people to switch to using systems that are able to work together and collaborate between technology and human resources. Current technological developments also have an impact on MSME business actors, especially culinary. For example, coffee shop, usually in the ordering process, coffee shops still use a manual ordering process. In this process, customers who come in must enter, order and immediately pay manually. This is of course risky for the company because the data could be lost or damaged. This problem occurs because there is no system that can support the ordering process, manage incoming data, market and introduce the product to reach the wider community. Customers sometimes find it difficult to get the latest updated information regarding available menus and the ordering and payment process. For this reason, an information system is needed so that problems can be resolved. With the Rapid Application Development (RAD) approach, the coffee shop information system can be developed relatively quickly and produce a system that suits your needs. This web-based coffee shop information system has the features that coffee shop entrepreneurs need to run their business effectively and efficiently and makes ordering and payment easier for customers. Apart from that, the test results using black-box testing produced a score of 100%, this means that the features contained in the system are in accordance with requirements.
Penerapan Data Mining Untuk Klasifikasi Kualitas Udara di Daerah Istimewa Yogyakarta Menggunakan Algoritma C4.5 Nur Adiya, Az Zahra Dwi; Desvita, Amanda Fitria; Fidela, Anindya; Amelia, Dwi; Astuti, Tri
JDMIS: Journal of Data Mining and Information Systems Vol. 2 No. 2 (2024): August 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v2i2.2800

Abstract

Air pollution is a global environmental problem that is of serious concern in various regions around the world, including in Indonesia. Poor air quality has negative impacts on human health, ecosystems and economic growth. The purpose of this research is to classify the air quality in the Special Region of Yogyakarta. Classification is done using data mining techniques with the C4.5 algorithm or decision tree. The results of the analysis that has been studied using the C4.5 algorithm used 5822 data and 20 replacement samples with 100 repetitions, so the results of this study obtained 7 decisions or leaves with a success rate of 99.9485% and a failure rate of 0.0515%.
Tinjauan Literatur terhadap Persiapan dan Tantangan Implementasi Enterprise Architecture di Pemerintahan Stephanie; Darianty, Rosita; Ayumi; Fayola, Angela
JDMIS: Journal of Data Mining and Information Systems Vol. 2 No. 2 (2024): August 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v2i2.2958

Abstract

Enterprise Architecture merupakan kegiatan pengorganisasian data untuk mencapai tujuan proses bisnis organisasi dan berfungsi sebagai cetak biru untuk mengintegrasikan elemen TI dengan manajemen informasi. Namun, dalam praktiknya, banyak organisasi gagal dalam mencapai ekspektasi mereka terkait implementasi EA sehingga menciptakan hasil yang ambigu. Meski demikian, pemerintah Indonesia percaya bahwa implementasi enterprise architecture adalah langkah yang krusial guna mewujudkan tata kelola pemerintahan yang efektif dan efisien. Tujuan dari penelitian ini adalah untuk mengidentifikasi kebutuhan yang perlu disiapkan dalam konteks sektor pemerintahan, serta mengidentifikasi tantangan-tantangan yang mungkin dihadapi pemerintahan Indonesia dan negara lain dalam proses implementasi EA. Hasil tinjauan menunjukkan bahwa Indonesia masih memiliki peluang besar untuk memajukan diri dan mengejar ketertinggalannya dari standar yang dianggap baik di berbagai negara. Tahapan dan tantangan implementasi EA pada pemerintahan di Indonesia dan negara lain memiliki kesamaan dalam berbagai aspek, dengan perbedaan utama terletak pada jenis kasus dan kebutuhan unik dari setiap pemerintahan. Penelitian ini juga mengemukakan prospek pengembangan penelitian ini, terutama rekomendasi strategis untuk memperbaiki implementasi arsitektur ini di masa mendatang, terutama bagi pemerintahan.
Kajian Literatur terhadap Penerapan Enterprise Architecture dalam Institusi Pendidikan Halim, Daniel Lexandrosth; Cuaca, Davidsen; Chenardy, John Michael; Felix, Owen; Maulana, Ade
JDMIS: Journal of Data Mining and Information Systems Vol. 2 No. 2 (2024): August 2024
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v2i2.2983

Abstract

Enterprise Architecture (EA) merupakan sebuah kerangka kerja yang membantu pengembangan tata Kelola sebuah bisnis. Namun dalam beberapa institusi Pendidikan, sering menghadapi kendala seperti kompleksitas tinggi dan kurangnya integrasi dalam sebuah sistem informasi yang dibangun. Sehingga, penelitian ini bertujuan untuk menunjukkan dampak positif penerapan Enterprise Architecture (EA) dan memberikan wawasan mengenai berbagai metode dalam penerapan EA.Penelitian ini menggunakan metode kualitatif. Teknik pengumpulan data dalam penelitian ini menggunakan metode literature review melalui berbagai database akademik. Berdasarkan hasil penelitian menunjukkan bahwa institusi pendidikan menghadapi tantangan dalam mengelola data kompleks dan koordinasi antar sistem, yang dapat diatasi dengan implementasi Enterprise Architecture (EA) menggunakan kerangka kerja seperti TOGAF ADM,dll. Penelitian ini menitikberatkan pada lima jenis arsitektur: visi, bisnis, data/informasi, teknologi, dan aplikasi, dengan metode analisis seperti Value Chain, Use Case, ERD, Class Diagram, dan McFarlan’s Strategic Grid. Kesimpulannya, penerapan EA dengan kerangka kerja dan metode analisis yang efektif dapat meningkatkan integrasi sistem informasi, meningkatkan akurasi data, efisiensi operasional, optimalisasi sumber daya, dan dan mendukung pencapaian visi serta misi institusi pendidikan.
Studi Literatur Perancangan Arsitektur Data dan Aplikasi pada Perusahaan Telekomunikasi Jason, Jason; Sutanto, Jefferson; Angkasa, Verrel; Darmana, Vicky; Maulana, Ade
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 1 (2025): February 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i1.3004

Abstract

Enterprise Architecture (EA) serves as a blueprint for aligning business processes and IT systems to achieve organizational objectives. It provides a structured framework for integrating and optimizing various business units, enhancing overall effectiveness and maximizing outcomes. A well-defined EA is crucial for achieving business success. This research delves into the analysis of data and application modeling approaches in EA frameworks. Telecommunication companies, like other organizations, rely on EA to integrate and align their business processes and data with their corporate mission. Employing a qualitative literature review methodology, this study aims to identify the most prevalent data and application modeling approaches in EA frameworks, providing valuable insights for telecommunication companies seeking to refine their EA models in the future.
Klasifikasi Kualitas Udara di Jakarta Pada Bulan Agustus 2024 Menggunakan Algoritma C4.5 Ayu, Ika Juni Nur; Putri, Nayla Rahmania; Nugraha, Ridho Putra; Febriansyah, Ryan
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 1 (2025): February 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i1.3745

Abstract

Air is one of the important factors in human survival besides land and water. Poor air quality will have a negative impact on human health, ecosystem balance and climate change. This study aims to classify air quality in Jakarta in August 2024 using data mining techniques with the C4.5 algorithm. The data analyzed was obtained from the Satu Data Jakarta website published on February 19, 2024, including several measurement parameters, namely pm_sepuluh, pm_duakomalima, sulfur_dioxide, carbon_monoxide, ozone and nitrogen_dioxide. In its implementation, this research uses RapidMiner tools to process and analyze data. The classification results show that air quality in Jakarta during the period can be categorized into two groups, namely unhealthy and moderate, with the majority of measurements falling into the moderate category. The resulting classification model achieved an accuracy rate of 99.35%, indicating that the C4.5 algorithm is very effective in identifying and predicting air quality in Jakarta. This result shows that most of the air quality measurement data in Jakarta is still in a category that meets good air quality standards
Analisis Persepsi Publik Terhadap Pilkada Jakarta 2024 dengan Clustering dan Sentimen pada Artikel Berita Zavira, Anggi Nur; Fathiyarahmani, Ilma; Nadhifa, Khansa; Putri, Kinanti Anindia; Mulyadi, Widya Amanda; Syawaliana, Zalfa
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 1 (2025): February 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i1.3812

Abstract

This study analyzes the pattern of mass media coverage related to the 2024 Jakarta Gubernatorial Election using a text mining approach with the K-Means Clustering algorithm and Lexicon-based sentiment analysis. Data were obtained through web scraping from Google News RSS Feeds, resulting in 100 articles that were analyzed after undergoing preprocessing processes such as tokenizing, filtering, and stemming. The K-Means algorithm was used to cluster the articles into eight clusters based on dominant themes, such as political support, candidacy failures, and strategic issues related to the election. This algorithm works by calculating the distance between data points and centroids, which are continuously updated until an optimal cluster is achieved based on the Silhouette Score method. Sentiment analysis revealed that most articles had a neutral sentiment, reflecting media objectivity, although some clusters showed positive and negative sentiments, indicating potential bias in the coverage. These findings provide insights into the role of media in shaping public opinion and the influence of news coverage on public perceptions in the democratic process. This study is expected to enhance political literacy among the public and encourage more critical participation, while also opening opportunities for further development of analysis methods to better understand media bias
Color Space Influence on Photosynthetic Pigment Measurement Accuracy Using CNN in Color Constancy Harefa, Ade May Luky; Insandi, Arief Muhazir
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 1 (2025): February 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i1.4064

Abstract

This study aims to design a plant pigment measurement system using digital images and deep learning, incorporating various color spaces including RGB, HSV, LAB, and YCbCr. The proposed method serves as a faster, more cost-effective, and accurate alternative to traditional methods such as spectrophotometric analysis and HPLC. Experimental results indicate that the choice of color space and inpaint preprocessing settings significantly impacts the accuracy of the CNN P3Net model. The combination of RGB+YCbCr with inpaint and RGB+LAB without inpaint yielded the lowest validation MAE values. The study also demonstrates that color constancy phenomena influence model accuracy, with color spaces that account for this phenomenon, such as RGB+YCbCr with inpaint, providing better accuracy than those that do not.
Pengembangan Aplikasi Insentif dan Komisi Salesman sebagai Strategi Peningkatan Kinerja SDM Marketing Suwandi, Suwandi; Hatta, Muhammad; Turini, Turini; Akbari, Safitri; Yanti, Limbong Aprilina
JDMIS: Journal of Data Mining and Information Systems Vol. 3 No. 1 (2025): February 2025
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/jdmis.v3i1.4066

Abstract

The performance of salespeople is greatly influenced by the incentive and commission system implemented by the company. A system that is not transparent and structured can reduce salesman motivation and productivity. This research aims to develop an application for salesman incentives and commissions as a strategy to improve marketing HR performance. The methods used in this research include requirements analysis, system design, implementation and application testing. This application is designed to be web-based to make it easier to access and increase transparency in calculating incentives and commissions. The test results show that the implementation of this application is able to increase sales force satisfaction and motivation through a fairer and real-time commission calculation system. Apart from that, the sales target tracking feature and automatic rewards contribute to improving marketing HR performance. The conclusion of this research is that the use of digital-based applications can be an effective solution in increasing transparency, trust and salesman motivation, which ultimately has a positive impact on sales productivity.

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