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All Journal Information Technology and Telematics Dinamik Jupiter Publikasi Eksternal Jurnal Buana Informatika Pixel : Jurnal Ilmiah Komputer Grafis JUITA : Jurnal Informatika Proceeding SENDI_U Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL ILMIAH INFORMATIKA JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknik Informatika UNIKA Santo Thomas INTECOMS: Journal of Information Technology and Computer Science Building of Informatics, Technology and Science Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Manajemen Informatika dan Sistem Informasi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Teknik Elektro dan Komputasi (ELKOM) JATI (Jurnal Mahasiswa Teknik Informatika) Aiti: Jurnal Teknologi Informasi Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) International Journal of Social Learning (IJSL) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Informatika Teknologi dan Sains (Jinteks) Maritime Park: Journal Of Maritime Technology and Socienty Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Eduvest - Journal of Universal Studies Seminar Nasional Teknologi dan Multidisiplin Ilmu Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) INOVTEK Polbeng - Seri Informatika
Eri Zuliarso
Universitas Stikubank
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Neuroscience Public Health Social Sciences Other

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IMPLEMENTASI CHATBOT YANG TERINTEGRASI LAYANAN KEPOLISIAN DALAM PEMBUATAN SIM Allaam, Ekananda Naufal; Zuliarso, Eri
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.77-83

Abstract

This research explores the deployment of a chatbot integrated with police services, focusing on the driver's license (SIM) application process. The urgency of this research arises from the need to enhance the accessibility and efficiency of public services. By leveraging Natural Language Processing (NLP), the chatbot is designed to provide rapid and accurate information regarding the SIM application procedures, renewal guidelines, and necessary documents. The study employs a mixed-methods approach, combining quantitative methods such as surveys and statistical analysis with qualitative methods including observations and interviews. This comprehensive approach allows for the development and assessment of the chatbot system within the context of SIM applications. The findings reveal that the chatbot significantly reduces processing time, improves user satisfaction, and streamlines the overall application experience. This integration demonstrates substantial potential for advancing public service delivery by making it more accessible and efficient. The research underscores that chatbot technology can play a crucial role in modernizing and optimizing public services, offering scalable solutions for future improvements in service delivery.
Mapping the Potential of Prospective New Students Utilizing K-Means and Fuzzy C-Means Clustering Fathoni, Ahmad; Zuliarso, Eri; Toman, Sarah Husain
International Journal of Social Learning (IJSL) Vol. 6 No. 1 (2025): December
Publisher : Indonesian Journal Publisher in cooperation with Indonesian Social Studies Association (APRIPSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijsl.v6i1.481

Abstract

UIN Walisongo Semarang has implemented outreach initiatives to engage prospective students, but these endeavors often lack data-inforamed approaches. This research intends to analyze the potential of incoming students through K-Means and Fuzzy C-Means (FCM) clustering techniques. The dataset comprises admission information ranging from 2022 to 2024, concentrating on five essential factors: gender, admission pathway, study program, school type, and geographic origin. Data preprocessing was carried out before performing clustering analysis. The Elbow Method and Silhouette Score were utilized to identify the optimal K for K-Means, whereas the Fuzzy Partition Coefficient and Xie-Beni Index were applied for FCM. Findings indicate that K-Means generated more distinct cluster boundaries, while FCM provided adaptability with overlapping clusters. Principal Component Analysis and the Davies-Bouldin Index aided in the assessment. The mapping results are displayed by faculty, showcasing regional patterns and student demographics. This research establishes a data-driven basis for UIN Walisongo's strategic recruitment and admissions strategies.
Perbandingan Metode Recurrent Neural Network (RNN) dan Long Short-Term Memory (LSTM) untuk Prediksi Curah Hujan Hermawan, Taufan; Zuliarso, Eri
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.8099

Abstract

The increase in extreme rainfall intensity due to climate change has caused Batang Regency to become a hydrometeorological disaster-prone area. This research aims to build an day rainfall prediction model using Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) based on BMKG historical data. The model is evaluated using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) metrics. The results show that LSTM has higher accuracy than RNN, with an RMSE: 0.1036 | MAE: 0.0730. Meanwhile, RNN obtained an RMSE: 0.1035 | MAE: 0.0763. LSTM is also more stable in predicting temperature, direction, and wind speed variables. These findings show that LSTM is more effective for weather time series data and can be used as a basis for developing data-based disaster early warning systems in local areas.
Co-Authors . Sulastri . Suwarsito Aditya Bobby Rizki Ahmad Fathoni Allaam, Ekananda Naufal Amalina, Hana Anefia Mutiara Atha ariadi, hastomo Arief Jananto Ariyani, Dewi Ayu Arya Sena Setyanegara Astuti, Vivi Rizki Indri Bambang Wiranto, Joko budi hartono Cahyono Purbomartono Dewi Handayani Untari Ningsih Dian Kristiawan Nugroho Dwi Agus Diartono Dwi Budi Santoso Edy Winarno Fathoni, Aliffatul Majid Februarianti, Herny Fidiniari, Fathia Gunadi, Ilham Hastomo Ariadi Hermawan, Taufan Herny Februariyanti Herny Februariyanti Hersatoto Listiyono Hindayati Mustafidah Indah Widhi Prastika Indriani, Cheryllista Isworo Nugroho Khabib Mustofa Kogoya, Erminus Kusuma Satria, Hafiyan Nafan Mardi Siswo Utomo Munna, Aliyatul Nur Rohim Nurmakhlufi, Alfin Hilmy Priambodo, Wisnu Putra Alva, Ilyasa Garuda Putri, Indah Lissiana R. Soelistijadi Radyanto, Mohammad Riza Rara Sri Artati Redjeki Ratmoko, Hari Rezal Arminto, Edo Rina Candra NS Rizky Abdul Malik Rosyida, Elviana Rudi setyo P Ruslana, Zauyik Nana S Sunardi Safra, Icha Adellia Safra, Kyla Kaneshia Sariyun Naja Anwar Sri Eniyati Sri Hartati Sudiantoro, Adhi Viky Sugiyamto Sugiyamto, Sugiyamto Sulastri Sulastri Sulastri Sulastri Sulatri sulis, Sulistiyowati Sunardi Sunardi Toman, Sarah Husain Velamentosa, Desvio Wahyu Prasetyo Wibowo, Sayogo Wismarini T.D. Wismarini, Th Dwiati Yassin Achmad Nur Aziz Yohanes Suhari Yunus Anis Yunus Anis, Yunus Yuwan, Ridho Pangestu Zulfa Febriana Dewi Mellinia