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All Journal Infotech Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Electrical Technology IT JOURNAL RESEARCH AND DEVELOPMENT INTECOMS: Journal of Information Technology and Computer Science KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknik dan Informatika Building of Informatics, Technology and Science Jurnal Mantik Jurnal Sains dan Teknologi Community Engagement and Emergence Journal (CEEJ) Jurnal Tekinkom (Teknik Informasi dan Komputer) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Darma Agung Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) International Journal Of Science, Technology & Management (IJSTM) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer Jurnal Info Sains : Informatika dan Sains Bulletin of Information Technology (BIT) International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) Jurnal Fokus Manajemen Jurnal Minfo Polgan (JMP) Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Nasional Teknologi Komputer Jurnal Pengabdian Masyarakat Gemilang (JPMG) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Data Sciences Indonesia (DSI) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Best Journal of Administration and Management Bulletin of Engineering Science, Technology and Industry Jurnal Pengabdian Masyarakat Variasi The Journal of Information Technology, Computer Science, and Electrical Engineering
Sitorus, Zulham
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OPTIMASI CNN DENGAN ADAM OPTIMIZER UNTUK KLASIFIKASI DATA JAMUR Dika; Zulham Sitorus; Muhammad Syahputra Novelan
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

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Abstract

Mushrooms are one of the most nutritious food sources; however, several species contain toxic compounds that can cause serious poisoning or even death if incorrectly identified. The high visual similarity between edible and poisonous mushrooms makes manual identification difficult, especially for non-experts. Therefore, an automatic image classification system is needed to improve the accuracy and consistency of mushroom identification. This study aims to develop a mushroom image classification model using a Convolutional Neural Network (CNN) optimized with the Adam Optimizer. The dataset was obtained from Kaggle and consisted of 2,820 images, divided into 2,256 training images, 282 validation images, and 282 testing images. The model was further validated using an external dataset of 83 real mushroom images to evaluate its generalization capability. All images were preprocessed through image resizing to 224 × 224 pixels and pixel normalization before model training. Model performance was evaluated using accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). Experimental results on the Kaggle test dataset achieved an accuracy of 62.77%, precision of 58.28%, recall of 71.97%, F1-score of 64.41%, and an AUC of 0.6482. Evaluation on the external dataset demonstrated improved performance, achieving an accuracy of 85.54%, precision of 94.59%, recall of 77.78%, and F1-score of 85.37%. These findings indicate that the CNN model optimized with the Adam Optimizer is capable of performing mushroom image classification effectively and demonstrates good generalization performance on real-world data, making it a promising approach for automatic mushroom identification.
Klasterisasi Pola Curah Hujan Berdasarkan Data Alat Pengamatan Menggunakan Hierarchical Cluster Analysis (Studi Kasus: BMKG Wilayah Sumatera Utara) Edy Sarwono Ponco; Zulham Sitorus; Khairul
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

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Abstract

The planning of hydrometeorological disaster mitigation, water resource management, agriculture, and regional spatial planning is highly dependent on the weather. The diverse geographical conditions of North Sumatra can cause significant variations in rainfall patterns between regions. The objective of this research is to cluster rainfall patterns based on BMKG observation data in the North Sumatra region. This is done using the hierarchical cluster analysis method. The stages of data preprocessing, standardisation, distance measurement between objects, dendrogram formation, and determination of the number of clusters are used to analyse rainfall data to systematically identify the similarities in rainfall characteristics between observation stations. The clustering results show that areas are grouped based on similar rainfall patterns, with each cluster representing different levels of rainfall. These results can help us understand the distribution of rainfall in North Sumatra and assist in making decisions about climatology, disaster mitigation, and regional planning. This study shows that hierarchical cluster analysis can be used as an analytical method to accurately group rainfall patterns based on meteorological observation data.
Optimasi Klasifikasi Kerawanan Gempa Bumi di Wilayah Sumatra Utara Berbasis Spatio-Temporal AutoML dengan Bayesian Optimization Menggunakan Data Historis Seismik Albertus Tua Simanullang; Khairul; Zulham Sitorus
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

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Abstract

Earthquakes are one of the most uncertain geological disasters and have the potential to cause significant damage in North Sumatra. The pattern of earthquake occurrences is influenced by complex tectonic conditions, which are affected by changes in seismic activity over time and the characteristics of the location. The aim of this research is to develop a spatiotemporal-based AutoML earthquake vulnerability classification model optimised with Bayesian optimisation methods. The seismic data used includes epicentre coordinates, depth, magnitude, time, frequency, and distance from active earthquake sources. Data preprocessing, spatial and temporal pattern analysis, feature engineering, vulnerability class determination, training several classification algorithms through an automated machine training framework, and hyperparameter optimisation using Bayesian optimisation. To assess the model's performance, accuracy, precision, recall, F1-score, area under the curve, and confusion matrix metrics are used. To reduce the possibility of bias and ensure that the model can be generalised to various locations and periods of occurrence, spatial and temporal validation are used. It is expected that the research results will produce a classification model with higher accuracy and stability than conventional classification methods. Next, the best model is used to divide the area into low, medium, and high vulnerability categories. It is hoped that this research will help develop a more adaptive, objective, and efficient data-based earthquake vulnerability mapping system that will assist in the decision-making process and disaster mitigation planning in the North Sumatra region.
Klasifikasi Potensi Bencana Ekstrem Hidrometeorologi di Kota Medan Menggunakan Algoritma Random Forest Dengan Teknik Purposive Sampling Indra Wadiasto; Khairul; Zulham Sitorus
Jurnal Nasional Teknologi Komputer Vol 6 No 4 (2026): Oktober 2026
Publisher : CV. Hawari

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Abstract

One of the threats that can endanger society is extreme hydrometeorological disasters, especially in cities with high construction activity and population density. Due to weather changes and local environmental characteristics, Medan City, one of the major cities in Indonesia, is vulnerable to hydrometeorological events such as floods, extreme rainfall, strong winds, and puddles. This study uses the Random Forest algorithm and purposive sampling technique to classify the likelihood of extreme hydrometeorological disasters in the city of Medan. The data used is based on specific criteria relevant to disaster potential indicators, such as topographic conditions, land use, population density, and rainfall. The Random Forest method is used because it can process data with many variables and make accurate classifications through the combination of several decision trees. The research results are expected to classify the areas of Medan City based on their disaster potential: low, medium, or high. This category can be used as a basis for spatial planning, mitigation strategies, and decisions made by the government and relevant parties to reduce the risk of hydrometeorological disasters in the City of Medan.
APLIKASI METODE QUALITY FUNCTION DEPLOYMENT UNTUK SISTEM PENINGKATAN PELAYANAN KONSUMEN Fahmi Kurniawan; Zulham Sitorus; Said Oktaviandi
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 4 No. 3 (2021): October 2021
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v4i3.713

Abstract

Pelayanan merupakan hal terpenting dalam memberikan kenyamanan terhadap pelanggan. Loyalitas kepada konsumen ditandai dengan konsumen yang terus menerus mau menggunakan jasa dari suatu perusahaan. Selain mengetahui tingkat layanan yang sudah ada, dan mengetahui adanya perbedaan antara kondisi yang ada dengan harapan konsumen maka perlu dilakukan usaha untuk meningkatkan kualitas layanan sesuai dengan harapan konsumen. Sektor jasa adalah sektor yang banyak bekontribusi pada sektor pertumbuhan ekonomi. Peningkatan layanan konsumen adalah salah satu faktor dari keberhasilan industri jasa. Pada sistem manajemen perusahaan merasa perlu melakukan peningkatan kualitas layanan untuk mempertahankan konsumen yang ada di PT. Telkom Ases tersebut. Aplikasi metode QFD (Quality Function Deployment) adalah sebuah metode yang membawa sebuah system pelayanan menjadi terbesar di Asia dan dunia. Metode QFD telah luas digunakan diberbagai bidang penelitian dan sistem pengambilan keputusan. QFD merupakan penelitian yang didasarkan bagaimana suara konsumen diterjemahkan kepada aspek-aspek teknis yang menunjang pelaksanaannya di lapangan. Dalam penelitian ini metode QFD digunakan dalam sistem peningkatan layanan konsumen.
Co-Authors , Arpan , Fery Anugerah A.A. Ketut Agung Cahyawan W Abda Abda Abdul Razaq Ade Alma Yuni Ade Guna Suteja Ade Surya Bakti Pane Aditya Ramadhani Afrizal, Henri Afrizal, Sandi Albertus Tua Simanullang Aldi Kesuma Alvian Alvian Alviona Marsya Ami Abdul Jabar Ami Abdul Jabar Amnisuhaila Abarahan Ananda Aulia Ananda Aulia Andi Ernawati Andi Ernawati Andi Ernawati Andysah Putera Utama Siahaan Angkat, Chairul Indra Anshari, Ari Antoni, Robin Anzas Ibezato Zalukhu Ardya, Dwika Arief, Muhammad Arif Rahman Astri Mutia Rahma Aulia, Ananda Ayu Ofta Ayu Ofta Sari Ayumi Kartika Sari azwan, m Baehaqi Bambang Sugito Bambang Sugito Batubara, Supina Boy Rizki Akbar Boy Rizki Akbar Br Tarigan, Sella Monika Chelfina Utami Chelfina Utami Daniel Happy Putra Danu Wardhana Azhari Darmeli Nasution Desy Ramatika DEWI SARTIKA Dhimas Prayogi diansyah, Suhar Didi Riswan`` Dika Diva, Krisna Dwina Pri Indini Edy Sarwono Ponco Eko Hariyanto Eko Hariyanto Eko Hariyanto Eko Wahyudi Elsya Sabrina Asmita Simorangkir Erbin Sitorus Fachri, Barany Fahmi Izhari Fahmi Kurniawan Fajar Aulia Lubis Feby Wulandari Sembirinng Fery Anugerah Fikri Zuhaili Simbolon Gilang Ramadhan Gultom, Ananda Christianto Hafiz Rodhiy Haliza, Siti Nur Hamzah, Iswadi Harmiati Bungsu Bangun Hartono Sinambela, Sugi Helmy, Ahmad Hendra Harnanda Hendra Utama Heni Wulandari Heri Eko Rahmadi Putra Heri Kurniawan Hilal Prayogi Hindra Syahputra Hrp, Abdul Chaidir Ibezato Zalukhu, Anzas Ibrahim Ika Devi Perwitasari Indra Angkat, Chairul Indra Wadiasto IQBAL , MUHAMMAD Irwan Syahputra Irwan Syahputra, Irwan Josua M.H Simaremare Khairul Khairul Khairul Khairul, Khairul Kiki Artika Kurniawan, Fahmi Laila Maghfirah Laila Maghfirah Larius Ambasador Parlindungan Leni Marlina Leni Marlina Lia Nazliana Nasution Limbong, Yohannes France M Imam Santoso M. Azhari Rizko M. Rasyid M.Rizki Khadafi Maida Indrayani Mardiah, Nia Marzuki Sianturi, Ismail Maulian Saputra Meiarni Situkkir Melva Sari Panjaitan Meri Sri Wahyuni Mhd Arfan Sitorus Mhd Arie Akbar Mhd Ihsan Abidi Mohammad Yusuf Mohammad Yusuf, Mohammad Muhammad Fahriza Muhammad Fahriza Muhammad Hafizh Al-Ghifari Rangkuti Muhammad Iqbal Muhammad Iqbal Muhammad Irfan Sarif Muhammad Raihan Harahap Muhammad Syahputra Novelan Muhammad Wahyudi Nahampun, Natalia Nainggolan, Andreas Ghanneson Nainggolan, Irfan Nazar Saputra, Risfan Nelviony Parhusip Nurwijayanti Oktavia Tumangger Parhusip, Nelviony Pasaribu, Ryan Fahreza Pebri Ramadani Pranoto, Sugeng Putra, Khairil Ragil Satya Adi W Rahima Br Purba Rahmat Hidayat Rahmat Hidayat Raihan Risky Ramadani, Pebri Ramadhan, Aditya Ramadhani, Aditya Ramli S Siburian Rangga Rafandi Razaq, Abdul Retno Mutiara Rezkinah Rambe Rian Farta Wijaya Rian Farta Wijaya Rian Putra, Randi Rika Uli Samosir, Siska Risky, Raihan Robin Antoni Rowiyah Asengbaramae Rusydi Tanjung , Miftah Ryan Fahreza Pasaribu Sahputra, Fajar Said Oktaviandi Sarifuddin Septia Harliansyah Septiani, Nadya Sianturi, Ismail Sibarani, Dina Marsauli Simamora, Siska Sinambela, Sugi Hartono Sinyo Andika Nasution, Ahmad Sipra Barutu Sipra Barutu Siregar, Andree Risky Yuliansyah Sitepu, Fernando Siti Nurhaliza Sofyan Siti Nurhaliza Sofyan Sitinur, Siti Nurhaliza Sofyan Sitompul, Jelly Rolley Sofyan, Siti Nurhaliza Solahuddin Asri Ritonga Solly Aryza Sri Wahyuni, Meri Sugeng Pranoto Suhardiansyah Suhardiansyah Suhardiansyah Suherman Suherman Sukrianto, Sukrianto Sulis Sutiono Susilawati Yahya Sutiono, Sulis Syahputri, Maulisa Syamsiar, Syamsiar T, Siti Isna Syahri Tanjung, Miftah Rusydi Tiara Aninditha Utama, Hendra Vina Arnita Vivin Yulfia Sarah Wahyu Agung Pratama Wahyuni, Meri Sri Wijaya, Rian Farta Wirda Fitriani Yasri, Afif Yulianus Zai Zulfahmi Syahputera Zulfahmi Syahputra Zulfahmi Zulfahmi Zulfahmi Zulfahmi