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All Journal JSiI (Jurnal Sistem Informasi) Jurnal Sains Indonesia Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Abdi Jurnal Publikasi Data : Journal of Information Systems and Management Digitus : Journal of Computer Science Applications Jurnal Ilmu Komputer
Tukiyat
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Mathematics Social Sciences Other

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Analisis Sentimen Opini Masyarakat Terhadap Pemilu 2024 Melalui Media Sosial X Dengan Menggunakan Naive Bayes, K-Nearest Neighbor Dan Decision Tree Cut Shifa Khoirunnisa; Tukiyat; Sajarwo Anggai
Jurnal Ilmu Komputer Vol 2 No 2 (2024): Jurnal Ilmu Komputer (Edisi Desember 2024)
Publisher : Universitas Pamulang

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This study aims to analyze public opinion sentiment towards the 2024 election using three machine learning classification algorithms: Naïve Bayes, K-Nearest Neighbors and Decision Tree. The data used in this study were taken from Social Media X, which is one of the social media platforms with a large and diverse data volume. The object of this study is public opinion expressed on Social Media X, with the subject of research in the form of tweets taken using the Twitter API, resulting in 5000 data with 2469 clean data. Data analysis involves text extraction and preprocessing processes that include data cleaning, tokenization, stopwords and stemming. The results of the study show the distribution of sentiment as follows: positive sentiment dominates with 96% of the total tweets, followed by neutral sentiment at 2% and negative sentiment at 1%. From the modeling results among the algorithms tested, K-Nearest Neighbors showed the best performance with an accuracy value reaching 97.50%, followed by Decision Tree having a performance with an accuracy value of 97.25% while Naïve Bayes had the lowest performance with an accuracy value of 96.14%. Although there is variation in performance among the algorithms used, none of them are completely consistent in classifying sentiment. This study makes a significant contribution in mapping public sentiment related to the 2024 election in Indonesia through data analysis from social media X, and provides insight into the effectiveness of various Data Mining Algorithms in sentiment analysis.
Analisis Dan Implementasi Sistem Manajemen Keamanan Informasi Menggunakan ISO/IEC 27001 (Studi Kasus Pada PT.XYZ) Wibowo, Rizki Septiyanto; Tukiyat; Sajarwo Anggai; Winarni
Jurnal Ilmu Komputer Vol 2 No 2 (2024): Jurnal Ilmu Komputer (Edisi Desember 2024)
Publisher : Universitas Pamulang

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It has become a current necessity in every company regarding the implementation of information and communication technology governance in efforts to improve service quality. The implementation of information and communication technology governance is a critical factor in enhancing service quality across various companies. Therefore, the adoption of an Information Security Management System (ISMS) based on the ISO 27001:2013 standard becomes essential, in line with the conduct of regular audits to ensure its effectiveness. This research aims to develop and design an information security governance framework in accordance with ISO/IEC 27001 and to conduct audits on the system that has been implemented in PT. XYZ, to ensure its compliance with good and efficient standards. The methodology used is Plan-Do- Check-Act (PDCA), with data collection techniques through interviews and distribution of questionnaires for internal audits. The research findings indicate that the average ISO/IEC 27001 maturity level is at levels three and four. It is expected that this research can assist and provide recommendations related to security controlsused as guidelines and procedures for the implementation of information security, as well as ensuring the overall operation runs in accordance with ISO 27001 standards.
Analisis Resiko Stunting Di Kota Tangerang Menggunakan Metode Regresi Linier dan Support Vector Machine Muhamad Farid Hasan Khadafi; Achmad Hindasyah; Tukiyat
Jurnal Ilmu Komputer Vol 3 No 1 (2025): Jurnal Ilmu Komputer (Edisi Juli 2025)
Publisher : Universitas Pamulang

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Stunting remains a significant public health issue in Indonesia, particularly in Tangerang City, affecting the physical and cognitive development of children. This problem requires serious attention due to its long-term impacts on children's quality of life and their potential in the future.This study aims to analyze the risk factors contributing to the occurrence of stunting in Tangerang City using Linear Regression and Support Vector Machine (SVM) methods. The research question focuses on identifying and predicting the main risk factors influencing the prevalence of stunting. The research method employs Linear Regression Algorithm and Support Vector Machine Algorithm. The study population consists of children under five years old registered at community health centers in Tangerang City. Data samples were collected from 5,376 children, with 80% (4,300 children) used for training and 20% (1,076 children) for model testing. Several socio-economic and health variables were considered as potential risk factors, including household income, maternal education level, access to clean water and sanitation, dietary diversity, and the presence of antenatal care. Data analysis revealed performance differences between the two models used. The SVM model achieved a significantly higher accuracy of 89% with a standard error of 0.4, demonstrating strong predictive capability. In contrast, the Linear Regression model yielded a lower accuracy of 74% with a standard error of 1.5. This difference highlights the potential advantages of SVM in capturing complex and non-linear relationships within the dataset. These findings can inform targeted interventions and policy recommendations to address the causes of stunting in Tangerang City. Further research could explore a broader range of risk factors.
OPTIMALISASI EDUKASI DIGITAL DAN PARTISIPASI MASYARAKAT DALAM MITIGASI BENCANA MELALUI SOSIALISASI APLIKASI LENCANA BMKG Tri Suwito Abdhy; Dian Herdianingsih; Tri Nurmayati; Famiyana Dewi; Citra Kusmardani; Dwi Rachmadi; Hanapi; Dwi Yuwono; Tukiyat
Abdi Jurnal Publikasi Vol. 4 No. 2 (2025): November
Publisher : Abdi Jurnal Publikasi

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This Community Service Program (PKM), organized by Master of Informatics Engineering (S-2) students of Pamulang University (UNPAM), focuses on the Optimization of Digital Education and Public Participation in Disaster Mitigation. The core objective of this activity was to enhance the preparedness and capacity of staff and employees at the Bekasi City Transportation Agency Office through intensive socialization of the BMKG 'Lencana' Application. The threat of natural and non-natural disasters requires a rapid and accurate digital response. The Lencana BMKG Application offers a near-real-time solution for reporting and accessing weather and disaster information. The methods employed included comprehensive outreach, demonstration of application features such as Weather Report, Earthquake Report, and Flood Report, alongside interactive practice to train participants as 'Citizen Reporters' ('Reporter Netizen'). The results indicated a significant increase in digital disaster mitigation literacy among participants, who now possess a better understanding of using the application as both an information source and a means of contributing data. This successful PKM reflects UNPAM's commitment to the Tridharma of Higher Education in building a more resilient community through information technology utilization. The main outcome is the creation of digital-based disaster mitigation agents within the Bekasi City Transportation Agency environment.
SOSIALISASI APLIKASI INFO BMKG DI KANTOR DINAS PERHUBUNGAN KOTA BEKASI Eko Widyantoro HS; Ade Sekarningsih; Andriana Dwi Hastanto; Andrie Febriansyah; Puji Lestari; Sarnubih Hasan; Warno Mulud; Tukiyat
Abdi Jurnal Publikasi Vol. 4 No. 2 (2025): November
Publisher : Abdi Jurnal Publikasi

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Global climate change, which has triggered an increase in extreme weather events, has had a significant impact on transportation activities in urban areas, including Bekasi City. Low digital literacy and minimal use of the BMKG Info application mean that local government officials are not optimally utilizing meteorological data to support transportation safety. This Community Service (PKM) activity was carried out by Master of Informatics Engineering students from Pamulang University in collaboration with the BMKG and the Bekasi City Transportation Agency. The goal was to increase participants' understanding of the functions and benefits of the BMKG Info application through outreach activities, live demonstrations, and interactive discussions. The results of the activity showed a significant increase in participants' knowledge of weather, climate, and earthquake information, as well as increased awareness of the importance of extreme weather preparedness. This activity also strengthened collaboration between academics and government agencies in developing digital disaster literacy.
PEMANFAATAN SISTEM INFORMASI NOWCASTING DALAM MITIGASI BENCANA HIDROMETEOROLOGI Erian Tasa; Shendyko Wicaksono; Nurdin Wibowo; Fahmi Khoirul Ichsan; Ceppy Multi Anggara; Any Widyawati; Farid Faisal; Tukiyat
Abdi Jurnal Publikasi Vol. 4 No. 2 (2025): November
Publisher : Abdi Jurnal Publikasi

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Bekasi City, West Java Province, possesses a high vulnerability to hydrometeorological disasters, particularly floods, resulting from factors such as high rainfall, land-use change, and topographical conditions involving large rivers. Currently, the monitoring system used by the Bekasi City BPBD (Regional Disaster Management Agency) still relies on CCTV and manual observation, which have limitations in automation, data integration, and response speed. To address this, the utilization of information technology, such as the Internet of Things (IoT) and Nowcasting systems, offers a solution for more responsive and real-time disaster mitigation. Nowcasting, as a precise short-term weather forecasting method, combines radar data, satellite imagery, and field observations to enhance the accuracy of extreme weather predictions. This research aims to introduce the application of IoT and radar technology within the disaster mitigation system in Bekasi City to improve the effectiveness of the early warning system and support rapid decision-making. Through community service activities, Master's students in Informatics Engineering from Pamulang University presented material on the implementation of Nowcasting and a water level monitoring system based on radar sensors and IoT. This activity also demonstrated the potential for developing predictive flood models using machine learning, such as Long Short-Term Memory (LSTM). The results indicate that integrating these systems can significantly enhance early flood detection capabilities. The collaboration between Pamulang University and the Bekasi City BPBD serves as a model of strategic synergy for disaster mitigation innovation.
Co-Authors Abu Khalid Rivai Achmad Hindasyah Ade Sekarningsih Agnia Bilqisti Agung Budi Susanto Andriana Dwi Hastanto Andrie Febriansyah Anggai, Sajarwo Any Widyawati Arya Adhyaksa Waskita Ceppy Multi Anggara Citra Kusmardani Cut Shifa Khoirunnisa Dian Herdianingsih Dwi Rachmadi Dwi Yuwono Edlianto, Dionisius Riyan Eko Widyantoro HS Erian Tasa Fahmi Khoirul Ichsan Famiyana Dewi Farid Faisal Firman Hanapi Hartanto Hesti Rahayuningsih Kanim Makhsun Misbah Muhamad Farid Hasan Khadafi Muhamad, Faruk Muhammad Rafif Misbahuddin Murni Handayani Nurdin Wibowo Nurmutia, Syahreen PUJI LESTARI Rafi Mahmud Zain Ruspendi Sarnubih Hasan Shendyko Wicaksono Supriatna, Dahlan Tri Nurmayati Tri Suwito Abdhy Warno Mulud Wibowo, Rizki Septiyanto Wiharjo, Sudarno Winarni Zain, Rafi Mahmud