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All Journal JSI (Jurnal sistem Informasi) Universitas Suryadarma CSRID (Computer Science Research and Its Development Journal) JISICOM (Journal of Information System, Infomatics and Computing) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Manajemen Informatika Jayakarta Indonesian Journal of Education And Computer Science Scientica: Jurnal Ilmiah Sains dan Teknologi Nusantara Journal of Multidisciplinary Science Journal of Computer Science Contributions (Jucosco) Jurnal Siber Multi Disiplin Journal of Informatics and Information Security Greenation International Journal of Engineering Science Jurnal Greenation Ilmu Teknik Jurnal Informatika dan Rekayasa Perangkat Lunak SYSTEMIC RESEARCH: Systemic and Information Technology Journal
Nurfiyah
Universitas Bhayangkara Jakarta Raya
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Perancangan Platform IoT Sebagai Sistem Peringatan Dini Banjir Menggunakan Algoritma Fuzzy Logic Di Perumahan Masnaga Bintara Jeremiah Marvin Kapoyos; Joni Warta; Nurfiyah
Indonesian Journal of Education And Computer Science Vol. 3 No. 2 (2025): INDOTECH - August 2025
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/indotech.v3i2.1418

Abstract

Banjir merupakan bencana alam yang kerap melanda wilayah urban di Indonesia, khususnya daerah yang memiliki sistem drainase yang kurang optimal. Salah satu wilayah terdampak adalah Perumahan Masnaga Bintara Jaya, yang mengalami beberapa kejadian banjir selama periode musim hujan. Untuk mengatasi hal tersebut, penelitian ini bertujuan merancang sistem peringatan dini banjir berbasis Internet of Things (IoT) yang terintegrasi dengan algoritma Fuzzy Logic tipe Mamdani guna memberikan informasi secara real-time dan adaptif terhadap perubahan ketinggian air. Perancangan sistem dilakukan menggunakan sensor ultrasonik JSN-SR04T untuk mengukur ketinggian air, mikrokontroler NodeMCU ESP8266 sebagai pengolah dan pengirim data, serta platform ThingSpeak sebagai media penyimpanan dan visualisasi data. Data yang diperoleh diklasifikasikan ke dalam tingkat risiko menggunakan logika fuzzy, dengan kategori status “Aman”, “Siaga”, dan “Bahaya”. Hasil klasifikasi tersebut ditampilkan melalui website monitoring yang dapat diakses masyarakat secara langsung untuk mendukung kesiapsiagaan. Penelitian menggunakan metode prototipe dan diuji pada lokasi nyata dengan tujuan mengevaluasi kecepatan sistem dalam merespons kenaikan muka air serta akurasi klasifikasi risiko. Hasil pengujian menunjukkan sistem mampu mendeteksi dan memberikan notifikasi secara cepat dan tepat. Dengan pendekatan ini, masyarakat dapat mengambil tindakan lebih dini, sehingga risiko kerusakan dan korban dapat diminimalisir
IDENTIFIKASI KEMATANGAN BUAH ALPUKAT (AVOCADO) MENGGUNAKAN ALGORITMA ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) Nurfiyah Nurfiyah; Hendarman Lubis; Ratna Salkiawati
Journal of Information System, Informatics and Computing Vol 10 No 1 (2026): JISICOM (June 2026)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v10i1.2473

Abstract

Avocado (Persea americana) is a horticultural commodity with high economic value but is climacteric, so the ripening process occurs quickly after harvest. Determining the ripeness level is still done conventionally (visually and manually) often results in subjective assessments and damages the fruit. This study aims to develop a non-destructive avocado ripeness identification system (unripe, ripe, and overripe) using the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm. The input parameters used are based on the Red-Green-Blue (RGB) color features and Gray Level Co-occurrence Matrix (GLCM) texture features extracted from digital images of avocados. The test results show that the combination of the ANFIS network architecture with a Gaussian membership function is able to recognize the ripeness level of avocados with an accuracy of up to 93.3% on the test data. This system is expected to be a technological solution for farmers and distributors in the process of sorting fruit objectively and quickly.
System Integration for Judicial Prediction of Case Type and Resolution Duration at Bekasi Religious Court Adi Muhajirin; Nurfiyah Nurfiyah; Arya Haifandika
SYSTEMIC RESEARCH: Systemic and Information Technology Journal Vol. 2 No. 1 (2026): July 2026
Publisher : Greenation Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/systemic.v2i1.69

Abstract

The administration of justice in Religious Courts faces inefficiencies due to manual case classification and unpredictable resolution timelines. This research addresses the gap in systemic judicial management tools by proposing a hybrid machine learning architecture. The objective is to design a systemic information model integrating Deep Learning for case type classification and Ensemble Learning for duration prediction. The method employs CRISP-DM framework combining Long Short-Term Memory (LSTM) for text analysis and XGBoost for temporal regression on 4,461 case records from Bekasi Religious Court. Results indicate a classification accuracy of 93.9% and a Mean Absolute Error (MAE) of 12.4 days for duration prediction. The novelty lies in the systemic integration of dual predictive models into judicial workflows, proposing a digital transformation model for court administration. Conclusions affirm that hybrid AI systems significantly enhance resource planning and administrative efficiency
Implementation of Priority Scheduling Algorithm in Designing Infrastructure Damage Reporting System Prio Kustanto; Wisnu Arizky Kurniawan; Achmad Noe’man; Nurfiyah Nurfiyah; Ridwan Ridwan
Greenation International Journal of Engineering Science Vol. 2 No. 3 (2024): (GIJES) Greenation International Journal of Engineering Science (September - No
Publisher : Greenation Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/gijes.v2i3.233

Abstract

The rapid growth of population and urbanization in Bekasi District has increased the demand for adequate road infrastructure, but it has also posed challenges in the maintenance and repair of existing infrastructure. The main constraint in addressing this issue is the limited available budget, although the Bekasi District Government has tried various innovative programs. In this context, it is important to have mechanisms that allow the public to report infrastructure problems quickly and accurately. Based on preliminary studies, many factors can cause road infrastructure damage. The aim of this research is to design and develop a Road Infrastructure Damage Complaint System in Bekasi District, providing easy access for the public to report road infrastructure damage and enabling authorities to prioritize infrastructure repairs more quickly and accurately, thus improving the quality of life for the community and building a complaint system that can help expedite the repair process.
Analisa dan Perancangan Aplikasi Pengelolaan Kurikulum Perkuliahan di Fakultas Psikologi Universitas Bhayangkara Jakarta Raya dengan Menggunakan Metode Antrean First In First Out Nurfiyah Nurfiyah
Jurnal Greenation Ilmu Teknik Vol. 1 No. 2 (2023): (JGIT) Jurnal Greenation Ilmu Teknik (Mei-Juli 2023)
Publisher : Greenation Publisher & Yayasan Global Resarch National

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jgit.v1i2.59

Abstract

Pada setiap satuan pendidikan mempunyai tujuan agar dapat menghasilkan lulusan yang berkualitas dan berkompeten, perguruan tinggi juga perlu menjamin agar lulusan tersebut dapat diakui didunia kerja demikian halnya dengan Fakultas Psikologi Universitas Bhayangkara Jakarta Raya. Perancangan aplikasi pengelolaan kurikulum perkuliahan merupakan salah satu cara untuk membantu dalam pengorganisiran pengelolaan kurikulum di Fakultas Psikologi Universitas Bhayangkara Jakarta Raya dan diharapkan aplikasi pengelolaan kurikulum tersebut mampu membantu meminimalisir human error. Metode First In First Out (FIFO) dipilih karena metode ini memiliki cara mengatur dan menambahkan data relative terhadap waktu dan prioritas dimana bahwa metode tersebut menggambarkan prinsip teknik pengelolaan antrean dalam perancangan kurikulum, dalam hal ini metode tersebut memiliki kinerja media penyimpanan dimana informasi yang pertama kali dikirim adalah informasi yang pertama kali diterima dengan kata lain bahwa dalam proses perencanaan kurikulum yang pertama kali dikelola maka kurikulum tersebut pula yang pertama kali selesai. Hasil perancangan aplikasi pengelolaan kurikulum perkuliahan dengan menggunakan metode FIFO adalah pengelolaan data hasil laporan distribusi matakuliah dapat kembali di review dan dijadikan arsip prodi dalam evaluasi kurikulum selanjutnya, aplikasi pengelolaan kurikulum perkuliahan yang menggunakan metode Fifo dapat menjadi lebih terorganisir dalam penggunaan atau penerapan kurikulum pada Prodi Psikologi.
Implementation of the Collaborative Filtering Algorithm in a Cultural Event Recommendation Application for Bekasi City Nurfiyah; Aida Fitriyani; Mohammad Rizqi Rias Firmansyah; Ratna Salkiawati; Hendarman Lubis
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 3 (2026): Volume 7 Number 3 September 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v7i3.2620

Abstract

The dissemination of information regarding cultural events in Bekasi City has not yet been fully optimized, resulting in uneven public participation across various cultural activities. This issue arises from the absence of a recommendation system capable of suggesting cultural events based on users' interests and preferences. This study aims to implement the User-Based Collaborative Filtering algorithm with the Pearson Correlation approach in a web-based cultural event recommendation system. The research methodology involved observation, interviews, and the collection of user rating data from 100 respondents, with the sample size determined using the Slovin formula. The recommendation process was carried out by calculating the average rating of each user, measuring the similarity between users using the Pearson Correlation coefficient, and predicting ratings for events that had not yet been evaluated by the target user. The results demonstrate that the proposed system is capable of identifying similarities in user preferences and generating personalized event recommendations that align with users' interests. In the case study, the predicted rating for User1 on the Pesta Nada event was 3.76, indicating a high likelihood that the event would be of interest to the user and therefore suitable for recommendation. The implementation of this recommendation system is expected to assist the public in discovering cultural events that match their preferences while supporting the Bekasi City Tourism and Culture Office in disseminating event information more effectively, thereby increasing public participation in cultural activities.
Co-Authors Achmad Noeman Achmad Noe’man Ade Irawan Adi Muhajirin Aida Fitriyani Al Malik MK, Abdillah Syah Alexander, Allan D Alifia Salsabila Apriliani, Lita Ardilla, Al Ihsan Fauzi Arfan Dwi Madya Arfan Dwi Madya Arif Rifai Dwiyanto Arin Novita Dewi Arizky Kurniawan, Wisnu Arya Haifandika Bagas Djoko Haryanto Darmawan , Krisna Devi Putri Ningsih Dimas Abimanyu Prasetyo El Ghozy, Ilham Nur Elvangga , Kelvin Farhan Dwi Setiawan Firdaus, Imansyah Abinda Fried Sinlae Hadi , Fairuz Irfan Hendarman Lubis Ikbal Eka Saputra Jeremiah Marvin Kapoyos Jeremiah Marvin Kapoyos Joniwarta Kustanto , Prio Linda Fitriyani Lubis, Hendarman Lubis, Hendarman Lubis Maulana , Rifqi Mochamad Reyhan Gusnaldi Mohammad Rizqi Rias Firmansyah Muhamad Akbar Putra Prasetyo Muhamad Dicky Alfaridzi Muhamad Rinjani Ramadan Muhammad Ali Mustaqim Muhammad Yasir Mujiono Sadikin Nanda Eka Rindiati Noe’man, Achmad Nurfan Ramadhandi Pratama Yusuf, Ajif Yunizar Prio Kustanto Purnomo, Rakhmat Purwanto S. Katidjan, Purwanto S. Ratna Salkiawati Ridwan Ridwan Ridwan, Ridwan Rifqi Hafidz Riyan Fauzi Hakim Trisnojuwono, Adi Ubaidillah , Muhammad Rofiq Wildan Hamzah Nur Fadholi Wisnu Arizky Kurniawan Yolanda Zahrah Khairunnisa Zahwa Erikamaretha