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All Journal Techno.Com: Jurnal Teknologi Informasi PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic IJoICT (International Journal on Information and Communication Technology) Jurnal Pilar Nusa Mandiri Information System for Educators and Professionals : Journal of Information System Faktor Exacta Jurnal Komtika (Komputasi dan Informatika) Jurnal Cendikia JSI (Jurnal sistem Informasi) Universitas Suryadarma Jurnal Teknologi Terpadu Jurnal ICT : Information Communication & Technology Competitive JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Journal of Students‘ Research in Computer Science (JSRCS) INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Jitu: Jurnal Informatika Utama Competitive Journal of Computer Science Contributions (Jucosco) Journal of Informatics and Information Security Jurnal Riset Informatika dan Teknologi Informasi (JRITI) Jurnal Komtika (Komputasi dan Informatika)
Prima Dina Atika
Fakultas Ilmu Komputer; Universitas Bhayangkara Jakarta Raya
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Transportation Other

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Analisis Clustering K-Means untuk Pemetaan Tingkat Pengangguran Terbuka di Provinsi-Provinsi Indonesia Tahun 2013-2023 Ramadhan, Alif Izzuddin; Ramdhania, Khairunnisa Fadhilla; atika, prima dina
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/wbpydb62

Abstract

This study analyzes unemployment rates in Indonesian provinces using data from the Central Statistics Agency (BPS) for the period 2013-2023 and the K-Means clustering algorithm. The aim is to group regions based on the Open Unemployment Rate (TPT). Two main clusters were produced: one with a high unemployment rate (cluster 0) and one with a low unemployment rate (cluster 1). Cluster 0 consists of 12 provinces, while cluster 1 consists of 22 provinces. The model evaluation shows a Davies-Bouldin Index score of 0.7041, indicating good clustering quality. The clustering results are visualized in the form of a map for easy interpretation. This research is expected to help policymakers design more effective policies in reducing unemployment in Indonesia, provide deep insights into regional differences in terms of unemployment, and support targeted decision-making.
Sistem Informasi Pencegahan Dan Penanggulangan Stunting Berbasis WEB Dani Yusuf; Prima Dina Atika; Rejeki, Sri
Journal of Informatic and Information Security Vol. 4 No. 1 (2023): Juni 2023
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/mv3qjx76

Abstract

This paper discusses the design of a stunting information system starting from creating a posyandu schedule to following up on stunted children. This system is built on a web basis so that it can be accessed by agencies related to stunting management and the public who want to see stunting activities in the city area. Bekasi. The system development method used is a prototype with the aim of accelerating the system development process so that this application can be used quickly and precisely according to the needs of its users. The result of the design and manufacture of this application is software that is expected to facilitate the implementation of activities for handling and overcoming stunting children through fast and accurate data collection.
Prediksi Penjualan Menggunakan Algoritma Regresi Linear pada Koperasi Karyawan Usaha Bersama Muhamad Galih; Prima Dina Atika; Mukhlis
Journal of Informatic and Information Security Vol. 3 No. 2 (2022): Desember 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/bg5qg413

Abstract

Koperasi Karyawan Usaha Bersama is one of the cooperative that has minimarket as one of their business strategy that sales a lot of goods people need. The amount of item sold every day is sometimes uncertain. There is a day when a lot of things are sold on that day, and there is also a day when there are only a few stuff are sold. The purpose of this study is to do prediction the sales of goods sold every day. With this prediction result, the minimarket can determine and choose what strategies are the best to maximize their profit. We use Linear Regression to do this study with CRISP-DM as the model process. The result of the analysis that uses data from March to April 2022 shows that MAPE has the better result with 10.7% compared to RMSE with 42.091.
Analisis Sentimen Masyarakat Terhadap PHK di Indonesia Pada Twitter Menggunakan Naïve Bayes dan Support Vector Machine (SVM) AlHakim, Abdu Malik; Atika, Prima Dina; Herlawati, Herlawati
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/96sfw544

Abstract

The phenomenon of layoffs in Indonesia has led to various public opinions, especially on social media. This research aims to analyze public sentiment on the layoff issue using data from Twitter, and compare the performance of two text classification algorithms, namely Naïve Bayes and Support Vector Machine. The Knowledge Discovery in Databases approach is used as the research framework, which includes the stages of data selection, text cleaning, transformation, classification, and evaluation. A total of 3,458 tweets were collected and processed through the pre-processing stage, then classified into positive and negative sentiments. Performance assessment was conducted with three scenarios of training and test data sharing: 80:20, 70:30, and 90:10. The results showed that Support Vector Machine gave the highest accuracy of 84.93% in the 90:10 scenario, compared to Naïve Bayes with 82.61% accuracy in the same scenario. Visualization through wordcloud was also used to strengthen the interpretation of dominant words in public opinion. The findings show that classification algorithms can be utilized to understand public perceptions of employment issues and support social data-based decision-making. This research can be further developed by expanding data coverage and evaluating more complex methods to improve classification accuracy.
Comparative Study of Logistic Regression, Neural Network, and Deep Learning in Predicting Hypertension Risk Atika, Prima Dina
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11646

Abstract

Hypertension is a major risk factor for cardiovascular diseases, and early detection is crucial for effective management. This study compares the predictive performance of three modeling techniques—Logistic Regression (LR), Neural Network (NN), and Deep Learning (DL)—in estimating the risk of hypertension. The dataset, obtained from Kaggle, consists of demographic and clinical variables with binary labels indicating the presence or absence of hypertension. Each model was trained and evaluated using RapidMiner, with performance assessed through accuracy and Root Mean Squared Error (RMSE). The results indicate that the Neural Network outperformed both Deep Learning and Logistic Regression, achieving the highest accuracy (99.88%) and the lowest RMSE (0.124). These findings suggest that shallow neural networks can provide reliable and efficient predictions for hypertension risk, sometimes even surpassing more complex deep learning architectures.  
Regional Mapping Based on Tourism Destinations in West Java: K-Medoid Clustering Analysis Almajid, Nafis; Dina Atika, Prima; Fadhilla Ramdhania, Khairunnisa
International Journal on Information and Communication Technology (IJoICT) Vol. 10 No. 2 (2024): Vol.10 No. 2 Dec 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v10i2.1011

Abstract

The growth of the tourism sector in West Java demands an optimal development strategy. This study aims to cluster regions in West Java based on the characteristics of their tourist destinations using the K-Medoid algorithm. This algorithm was chosen because of its superiority in producing optimal clusters and robustness to outliers. Data on tourist destination characteristics were analyzed using the K-Medoid algorithm and the Elbow method to determine the optimal number of clusters. As a result, three clusters with different characteristics were formed. The first cluster, "Medium potential and achievement", consists of 1 region with unoptimized potential for campsite tourism. The second cluster, "High potential and moderate achievement", consists of 25 regions with a diversity of attractions and a high number of visits. The third cluster, "Medium potential and high achievement", consists of 1 region with popular historical and cultural attractions and high visitation. The model evaluation showed a DBI score of 0.08, indicating good clustering quality. This research is expected to provide insights for the government and related stakeholders to formulate targeted tourism development policies in West Java. The K-Medoid algorithm helps identify certain patterns, providing deeper insights into regional differences in terms of tourism.
Implementasi Sistem Informasi Sekolah Berbasis WEB pada Muhammadiyah Boarding Lab School (MBLS) Kecamatan Setu Kabupaten Tambun Atika, Prima Dina; Kusmara, Hadi; Sugiyatno; Mukhlis
Journal Of Computer Science Contributions (JUCOSCO) Vol. 1 No. 1 (2021): Januari 2021
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jucosco.v1i1.457

Abstract

Teknologi Informasi membantu penyampaian informasi dalam bentuk visual baik secara elektonik maupun non elektronik (media cetak) yang di dalamnya mempunyai arti penyempurnaan pesan untuk dipublikasikan. media penyampaian sebuah pesan kepada peserta didik. Muhammadiyah Boarding Lab School adalah lembaga pendidikan sekaligus sebagai pesantren Ma’had Tahfizul Qur’an yang dibawah naungan Pempinan Daerah Kabupaten Bekasi sehingga untuk mempermudah penyampain informasi kepada wali santri yang saat ini mukim di pesantren Muhammadiyah pada tahap awal perlu dibuatkan WEB untuk keperluan diatas, selain itu untuk mempercepat. Adapun pembuatan media informasi selama ini untuk menyampaikan kepada wali santri sering terkendala karena sumber daya manusia (SDM), sehingga wali santri kurang dapat mengikuti perkembangan santri. Menjawab permasalahan tersebut maka dibuat Sistem Informasi WEB Sekolah. Kata kunci—Web; Pelatihan
Penerapan Sistem Aplikasi Pengelolaan Materi Pembelajaran Pada Yayasan Al-Mabrur Kabupaten Bekasi Fitriyani, Aida; Hendharsetiawan, Andy Achmad; Atika, Prima Dina; Sari, Rafika
Journal Of Computer Science Contributions (JUCOSCO) Vol. 2 No. 2 (2022): Juli 2022
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/cxp0v475

Abstract

Information technology that continues to grow rapidly, especially in the field of education, requires the parties involved to be able to adapt to technology. Especially in the last two years, Indonesia has experienced the Covid-19 Pandemic, which requires the teaching and learning process to be transformed into an online form, giving rise to many e-Learning platforms. Using e-Learning can help teachers and students monitor the activity of students in doing assignments, discussion forums or other activities. This online learning process was also carried out at the Foundation for Orphans and Dhuafa Al-Mabrur Kebalen, Bekasi Regency. To assist the Foundation in implementing e-Learning, this Community Service (PKM) program was carried out which aims to develop Learning Management System (LMS) software. This training is expected to meet several targets, namely being able to manage learning materials and being able to manage e-Learning participant accounts. From the results of the training on the use of Web-based applications, it shows that teachers find it helpful to monitor student activities in accessing online learning materials. The students have also been able to use this eLearning application well.
Pelatihan Pemanfaatan Software Pendukung Statistik Dalam Pengolahan Data Kuantitatif Bagi Guru-Guru SMA Herlawati, Herlawati; Atika, Prima Dina; Handayanto, Rahmadya Trias; Sumadyo, Malikus; Samsiana, Seta; Gunarti, Anita Setyowati Srie; Maimunah, Maimunah
Journal Of Computer Science Contributions (JUCOSCO) Vol. 2 No. 2 (2022): Juli 2022
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/79gqt343

Abstract

Teachers need additional knowledge of quantitative data processing using statistical support software because of the diverse educational backgrounds of teachers such as education science, management science, although there are also those whose educational background is mathematics and natural sciences (MIPA). In addition, the level of awareness of teachers to study statistics for processing quantitative data is still low and is considered less important. Solutions that can be given to this community service activity include organizing training on the use of statistical support software to provide understanding and skills in the use of such software, including Microsoft Ms.Excel and Matlab Mobile in an effective and efficient manner. This can be done through the mentoring process in this activity and will be followed by other advanced trainings. The results of this training, based on a survey using an online mentimeter, showed that it was very useful and the participants wanted to continue this training with the theme of using the Statistical Package for the Social Sciences (SPSS).
Pelatihan Penggunaan Sistem Aplikasi Manajemen Prospek Donatur Pada Panti Yatim Indonesia (PYI) Bekasi Hendharsetiawan, Andy Achmad; Fitriyani, Aida; Atika, Prima Dina
Journal Of Computer Science Contributions (JUCOSCO) Vol. 3 No. 1 (2023): Januari 2023
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/v1544x72

Abstract

Information technology is a series of computer-based systems that can assist business processes in making decisions that affect an organization so that the organization is able to face challenges in the current era. It is time for all activities and activities to also take advantage of the latest technology-based information systems. As part of the community in an effort to carry out one of the Tri Dharma of Higher Education in the form of community service. This community service activity aims to collect data on prospects for orphanage donors, namely in the form of Donor Prospect Management Application System Training at the Duta Harapan Indonesian Orphanage (PYI) Bekasi City Branch. Donor prospects are usually obtained from donor search activities or donor prospects who contact the orphanage. By using this application system, the management or management of donor prospect data will be much more efficient and effective, namely from recording and reporting as well as data analysis. This application system simultaneously records donor data, namely data on prospects for donors who have the status of being donors or paying infaq which is urgently needed by the orphanage. The results of this training activity are felt to be useful for the orphanage to increase insight and knowledge as well as ease in carrying out daily controls or supervision as well as being beneficial to the running of daily operations.
Co-Authors .S.T., M.Kom., Suhadi Afzil Ramadian Ahmad Fathurrozi Ahmad Fathurrozi Aida Fitriyani, Aida Ajif Yunizar Pratama Yusuf AlHakim, Abdu Malik Almajid, Nafis Alviansyah, Mohammad Anita Setyowati Srie Gunarti Beno Aditya Sanusi Dadan Irwan Dani Yusuf Ekawati, Inna Endang Retnoningsih Endang Retnoningsih Faisal Adi Saputra Fata Nidaul Khasanah Fitria Nurapriani Galih Apriansha Pradana Gedhe Hilman Wakhid Gilby Lionska Wenas Haryono Haryono Hendharsetiawan, Andy Achmad Herlawati Herlawati Idaul Hasanah Indah Dwijayanthi Nirmala Ira Wardani Ismaniah Ismaniah Joni Warta Julianto Khairunnisa Fadhilla Ramdhania Kusmara, Hadi Lestari, Panca Indah Maimunah, Maimunah Malikus Sumadyo Mamang Jhulianawati Mugiarso Mugiarso Muhamad Galih Muhammad Riky Sudrajat Mukhlis Nur Amanda Pratiwi Priatna , Wowon Prihatin, Sandy Satyo RAFIKA SARI Rafika Sari Rahmadya Trias Handayanto Ramadhan, Alif Izzuddin Ramdhania, Khairunnisa Fadhilla Rasim Rasim Rasim, Rasim Resty Nandya Retna Ayu Puspitasari Retno Nugroho Whidhiasih Rizky Alfiansyah Robertoi . Samuel, Federick Dedi Sandy Satyo Prihatin Sari , Rafika Septia, Dwi Yoga Seta Samsiana Seta Samsiana Shofa Shofia SITI SETIAWATI Sri Rejeki Sri Rejeki Sugeng Murdowo Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sugiyatno Syahbaniar Rofiah Tambun, Jerisman Jhon Wesli Tyastuti Sri Lestari Tyastuti Sri Lestari Wijati, Damar Yusuf, Ajif Yunizar Pratama