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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal F. Teknik : RESULTAN Paradigma : Journal of Science, Religion and Culture Studies TELKOMNIKA (Telecommunication Computing Electronics and Control) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic JREC (Journal of Electrical and Electronics) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Cakrawala : Jurnal Humaniora Bina Sarana Informatika Bina Insani ICT Journal Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) BENTANG : Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil Jurnal Komtika (Komputasi dan Informatika) Jurnal Kajian Ilmiah Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat DEVOSI Journal of Students‘ Research in Computer Science (JSRCS) Journal of Computer Science Contributions (Jucosco) Jurnal Komtika (Komputasi dan Informatika)
Rahmadya Trias Handayanto
Program Studi Teknik Komputer Fakultas Teknik, Universitas Islam 45
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Transportation Other

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Analisis Sentimen Pada Situs Google Review dengan Naïve Bayes dan Support Vector Machine Handayanto, Rahmadya Trias; Herlawati, Herlawati; Atika, Prima Dina; Khasanah, Fata Nidaul; Yusuf, Ajif Yunizar Pratama; Septia, Dwi Yoga
Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 2 (2021)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v5i2.6280

Abstract

Tourism is the sources of income which is influenced by customer satisfaction. One way to know customer satisfaction is feedback, one of which is a review using an application. One of the feedback applications is Google Review. Such applications are have been widely used, for example in this study in this case study, Summarecon Mal Bekasi, can reach 60,000 comments. To find out the sentiment of the large number of comments, it is necessary to use computational tools. The current research applies sentiment analysis using the Naïve Bayes method and the Support Vector Machine. Data retrieval is done by web scrapping technique. Furthermore, the comment data is processed by pre-processing and labelling using the Lexicon dictionary. The process of applying sentiment analysis is carried out to determine whether the comments are positive or negative. In this study, the accuracy of the Naïve Bayes and Support Vector Machine methods in conducting sentiment analysis on the Summarecon Mal Bekasi review with a data of 2,143 comments with an accuracy for Naïve Bayes and Support Vector Machine 80.95% and 100% respectively. A Jason-style application is built to show the implementation in Flask framework. Keywords:
VISUAL HISTORICAL DATA-BASED TRAFFIC MOVEMENT AND DENSITY PATTERN EXTRACTION FOR ADAPTIVE PATTERN DETECTION BASE ON VEHICLE TYPE Angellia, Filda; Merlina, Nita; Subekti, Agus; Handayanto, Rahmadya Trias
International Journal of Artificial Intelligence Research Vol 9, No 1.1 (2025)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i1.1.1570

Abstract

Traffic congestion in urban areas has become a crucial issue, impacting time efficiency, energy consumption, and quality of life. One of the main causes of difficulties in traffic management is the lack of optimal predictive systems capable of detecting and adaptively responding to vehicle movement patterns. This study proposes a historical digital image-based approach to extract traffic movement patterns and density based on vehicle type and dimensions. The developed model utilizes historical traffic video footage from CCTV systems as a visual data source, which is then processed using the YOLOv5 algorithm to detect the number, size, and type of vehicles. After the detection process, vehicle information is converted into a sequential format that reflects vehicle movement in the temporal dimension. This data is then analyzed using a Long Short-Term Memory (LSTM) model to generate traffic density prediction patterns. This study also compares the performance of LSTM with other algorithms such as Random Forest and XGBoost in terms of prediction accuracy. Model evaluation is conducted using MSE and RMSE metrics to measure accuracy against actual data.The research results show that the integration of dimension-based vehicle detection with a visual historical data-driven prediction approach can improve the accuracy and flexibility of modeling future traffic conditions. This approach significantly contributes to the development of intelligent transportation systems that can adapt to dynamic environmental conditions and traffic patterns
OPTIMIZING GAS STATION LOCATION USING GENETIC ALGORITHMS Rahmadya Trias Handayanto; Soedarmin Soenyoto; Yopi Handoyo
Bentang : Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil Vol 1 No 1 (2013): BENTANG Jurnal Teoritis dan Terapan Bidang Rekayasa Sipil (Januari 2013)
Publisher : Universitas Islam 45

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/bentang.v1i1.398

Abstract

Gas station location is not only based on financial but also environment aspects because it will give negative impact if there are some accidents such as fire, tank leakage, etc. Helping customer in supplying fuels should not sacrifice other needs such as health, food, education, living circumstance, and so on. Therefore we propose the system that can help someone deciding and analyzing the location of gas station, especially when doing proper analysis. By using genetic algorithms our system can find optimum location of gas station after considering other important location that must be far away from it. The distance from important place was counted by normal euclidean after converting road and the river at map into nonlinear equation using interpolation. Population was generated from converting road on the map into equation. The important places that must be far away from gas station are collected and with that equation then give an objective function. Testing result showed the system could find optimum gas stations location at Bekasi regency. Keywords : GAS STATION, GENETIC, ALGORITHMS
Analyzing Land Suitability for Housing in Bekasi Regency: Managing Farmland Conversion During Urban Growth Herlawati Herlawati; Rahmadya Trias Handayanto
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9968

Abstract

Bekasi Regency is a buffer area for Jakarta and is part of the Jakarta Metropolitan Region (JMR). Along with Karawang, this region is a major rice producer, but it is currently experiencing significant land conversion from agriculture to residential and industrial uses. Preventing this conversion is very challenging due to the high population growth in the area. To address this issue, this study aims to conduct a suitability analysis to identify areas that are unsuitable for agricultural land but still suitable for residential purposes. The factors considered in the suitability analysis include slope, distance to roads, distance to residential areas, distance to facilities and infrastructure, and distance to rivers and irrigation systems. The results of the study identify areas that are unsuitable for agriculture, allowing local governments to focus on these areas as potential sites for new residential developments. The location is situated in the southern part of Bekasi Regency, specifically in the Cikarang area and its surroundings.
Comparative Study of PCA, t-SNE, and UMAP for CNN Feature Representation of Image Classification Herlawati Herlawati; Rahmadya Trias Handayanto
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.v13i2.11634

Abstract

Currently, the use of Deep Learning is widespread across various domains, with Convolutional Neural Networks (CNNs) as one of its main pioneers due to the principle of convolution. Recent methods continue to emerge with steadily increasing accuracy, in some cases approaching perfection. However, their implementation is often limited by the lack of sufficient computational resources in many environments. Moreover, the growing demand for explainable AI compels researchers to explore approaches that reveal the inner workings of deep learning models rather than treating them as mere black boxes. In this study, a simple CNN model is employed as a testbed for examining the feature extraction process through convolution, which is subsequently transformed into a user-friendly two-dimensional representation. The dataset used in this study is the Cats and Dogs dataset from Kaggle, which contains 25,000 labeled images equally distributed between the two classes. The dimensionality reduction methods utilized include Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP). The results demonstrate that UMAP achieves superior performance compared to PCA and t-SNE, with the highest silhouette score and a lower Davies–Bouldin index, indicating more compact and well-separated feature clusters.
Deteksi Lokasi Perubahan Penutup Lahan Untuk Meminimalkan Risiko Keamanan Wilayah Rahmadya Trias Handayanto; Haryono; Ramdhani Setiawan
Journal of Students‘ Research in Computer Science Vol. 5 No. 1 (2024): Mei 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/dnk1hq28

Abstract

Changes in land use and cover of an area significantly affect the quality of the area, especially from a socio-economic perspective. If city and regional governments are unable to anticipate these changes, it can greatly impact the security of the area, such as a lack of availability of public facilities, increased crime, and other social aspects. Research on changes in land use and cover has mostly focused on agriculture and rarely addresses regional security. Therefore, this study focuses on changes in land use, particularly in the type of urban residential land use in Bekasi city. The data used are Landsat satellite images from two different years for the Bekasi city area, utilizing trend change analysis with the Idrisi Selva application. Initially, a land cover classification process was carried out using the Iterative Self-Organizing Clustering (ISOCLUST) method, followed by reclassification with the same application into five classes: agriculture, vacant land, buildings, vegetation, and water bodies. The results show the direction of land change development where residential areas increase in the direction according to the degree of trend change, namely to the lower middle for the third degree and to the northwest and lower middle for the fifth degree. The research results can be used by regional planners in creating Spatial and Regional Plans (RTRW) as well as Detailed Spatial Plans (RDTR).
Konversi ke Microservices Untuk Peningkatan Layanan Perpustakaan Malikus Sumadyo; Rahmadya Trias Handayanto; Ramdhani Setiawan
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/vr275f23

Abstract

Most web-based applications are applications that provide services to users. The services themselves often change according to policies that are usually based on user satisfaction information. Unfortunately, existing applications are mostly based on open-source which is mostly monolithic. If there is an addition of a new service, it requires development from the beginning again. Especially when there is an imbalance between one service and another where one service requires large resources while other services do not require too many resources such as processors, network speed, or database size. This study tries to propose a system change in the library based on PHP-MySQL to be based on microservices.
Implementasi Sistem Monitoring Jaringan Mikrotik Dengan The Dude M Jaelani; Retno Nugroho Whidhiasih; Rahmadya Trias Handayanto
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: 10.31599/15w1se86

Abstract

The internet service provider, CV. Sekarjaya Computindo, is currently still using a manual monitoring system. This manual monitoring system relies on the Windows command prompt. As a result, detecting network issues takes longer because the administrator must manually search for and ping IP addresses within the network or wait for user reports when network problems occur. In this study, a Mikrotik network monitoring system using The Dude was developed for CV. Sekarjaya Computindo to assist the administrator in monitoring network devices more efficiently, enabling faster identification and resolution of network disruptions. The results of the study show that The Dude monitoring system can quickly monitor the status of network devices when they are up or down due to damage or network disturbances. These statuses are displayed on The Dude’s network maps and real-time notifications are sent via Telegram.
Co-Authors A.A. Ketut Agung Cahyawan W Aeri Sujatmiko Agus Subekti Ahmad Liyas Sani Ahmad Wafiq Amrillah Aji Trisnantoro Andi Hasad Angga Fahreja Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anussara Hirunpongchai, Anussara Atika , Prima Dina Bagus Suryasa Majanasastra Ben Rahman Benrahman Boravin Teng, Boravin Dadan Irwan Dadan Irwan Dadan Irwan Dadan Irwan Dede Rosadi Ekawati, Inna Endang Retnoningsih Faisal Adi Saputra Fata Nidaul Khasanah Fikri, Muhammad Ramadan Filda Angellia Galih Apriansha Pradana Haryono Haryono Haryono Haryono . Haryono . Haryono Haryono Haryono Haryono Hendharsetiawan, Andy Achmad Heri Setiawan Herlawati Herlawati Intan Juwita Irwan Raharja Khanittha Saengmanee, Khanittha M Jaelani Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah Malikus Sumadyo Malikus Sumadyo Malikus Sumadyo Malikus Sumadyo Muhammad Aqil Emeraldi Muhammad Arifin Muhammad Ilham Muhammad Irvan Muhammad Ramadan Fikri Muhammad Ramadhan Fikri Nita Merlina, Nita Nitin Kumar Tripathi Nove Anggara Syah Sejati Nutthapong Khangkhun, Nutthapong Pradana , Galih Apriansha Priatna , Wowon Prima Dina Atika Rafika Sari RAFIKA SARI Ramdhani Setiawan Randika Purwadhana Rejeki , Sri Retno Nugroho Whidhiasih Retno Nugroho Whidhiasih Retno Nugroho Whidhiasih Retno Whidhiasih Reyvan Karani Rika Sylviana Samsiana , Seta Sani, Ahmad Liyas Saputra , Faisal Adi Sella Alaida Syifa1 Sella Alayda Syifa Septia, Dwi Yoga Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Setiaji Setiaji Setyo Supratno Setyowati Srie Gunarti, Anita Soedarmin Soenyoto Soedarmin Soenyoto Sohee Minsun Kim Sri Marini Sri Rejeki Sugeng Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sumarlin Syahbaniar Rofiah Taufiqur Rakhman Tyastuti Sri Lestari Yopi Handoyo Yopi Handoyo Yusuf, Ajif Yunizar Pratama