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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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Analysis Of Licensing Data Using Naive Bayes And Decision Tree Algorithms To Evaluate The Performance Of Digital Public Services (Case Study: Invesment and One-Stop Integrated Services Office Of Medan City) Parhusip, Nelviony; Muhammad Iqbal; Zulham Sitorus
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 02 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i02.1290

Abstract

Digital public services have become increasingly essential with the rapid development of technology and information. Over the past six years, the digital transformation of public services at the Investment and One-Stop Integrated Services Office (DPMPTSP) of Medan City has been highly significant. This can be observed from the national implementation of Online Single Submission (OSS) and the “Si Cantik” online application by the Ministry of Communication and Information in 2018, the launch of the “Sipandu” digital service application in Medan City in 2022, and the inauguration of the Public Service Mall and “Si Medan Pantas” application in 2024. In this digital era, innovation in public service is a necessity that cannot be overlooked, especially in efforts to improve the efficiency and effectiveness of licensing processes. This study aims to evaluate digital public service performance by analyzing licensing data in Medan City. The methods applied in this research are Naive Bayes and Decision Tree algorithms, utilizing the Orange data mining tool to optimize the assessment of digital public service performance.The main findings of this study highlight the evaluation of public service performance and identify potential areas for innovation, ideas, or new insights to enhance future public service delivery..
Implementasi Data Mining Untuk Clustering Produktivitas Bawang Merah Menggunakan Metode K-Means Sitinur, Siti Nurhaliza Sofyan; Sitorus, Zulham
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 02 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i02.1442

Abstract

Bawang merah merupakan tanaman holtikultura dan hampir di seluruh Indonesia dapat di tanami oleh tumbuhan ini. Bawang merah merupakan pelengkap dalam masakan nusantara. Penambangan data yang dilakukan dalam produktivitas bawang merah melalui Badan Pusat Statistik di Indonesia dari tahun 2019 - 2024 bertujuan untuk pengoptimalan dalam produksi bawang merah yang akan menunjang produktivitas di setiap provinsi. Teknik K-Means Clustering mengelompokkan menjadi 3 cluster, yaitu : C1 bermakna sangat rendah di dominasi 32 provinsi seperti Sumatera Utara dengan Siluet 0.635069 dan Banten dengan Siluet 0.68097. Kemudian C2 bermakna bagus yaitu produksi bawang merah tertinggi di Indonesia seperti Jawa Tengah – siluet 0.690777 dan Jawa Timur – siluet 0.670607 dan cluster terakhir yaitu C3 dengan produksi sedang termasuk provinsi Jawa Barat – siluet 0.667291, Sumatera Barat – siluet 0.672978, Sulawesi Selatan – siluet 0.658588 dan terakhir Nusa Tenggara Barat – siluet 0.669592. Hasil penelitian ini sangat berguna untuk pemerintah dalam pengembangan produksi bawang merah disetiap provinsi untuk kemajuan tanaman holtikultura.
Designing an Alumni Information System Based on UML (Unified Modeling Language) Sitorus, Zulham; Pranoto, Sugeng; Sutiono, Sulis; Arief, Muhammad
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.162

Abstract

This research designed a UML-based Alumni Information System for SD IT Jabal Nur Tebing Tinggi. The stages involve collecting data through observation and interviews, followed by designing UML using use case, activity, sequence, and class diagrams. The aim is to facilitate collaboration between schools and system developers, providing a visual depiction of admin and system interactions in managing alumni data. Although still at the design stage, the results provide a strong basis for further implementation, with the potential to increase efficiency and support future school development. The suggestion involves a system implementation phase to test the effectiveness of the design, accompanied by clear documentation for system maintenance and new user training.
Pengembangan Dan Implementasi Aplikasi Pelayanan Jasa Berbasis Web Pada CV Altrama Energi Gultom, Ananda Christianto; Batubara, Supina; Sitorus, Zulham
Data Sciences Indonesia (DSI) Vol. 4 No. 2 (2024): Article Research Volume 4 Issue 2, December 2024
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/dsi.v4i2.5401

Abstract

Kualitas jasa layanan yang prima mampu menciptakan loyalitas konsumen sehingga dapat tercipta hubungan kerja yang saling menguntungkan antara kedua belah pihak. CV Altrama Energi adalah salah satu perusahaan layanan jasa penyewaan alat berat maupun perawatan atau perbaikannya untuk berbagai kebutuhan pekerjaan berat seperti konstruksi maupun pertanian. Dengan kondisi pengelolaan data yang tidak efektif mengakibatkan pimpinan CV Altrama Energi kesulitan melakukan pencarian data, pemantauan jadwal pekerjaan maupun penagihan. Hal ini dapat mempengaruhi reputasi CV Altrama Energi dimata konsumen yang dapat mengakibatkan terputusnya hubungan kerjasama dengan konsumen. Tujuan penelitian ini adalah mengembangkan dan mengimplementasikan aplikasi layanan jasa berbasis web untuk mengolah data jasa penyewaan dan jasa perbaikan alat berat pada CV Altrama Energi menggunakan metode prototipe, perancangan aplikasi menggunakan unified modelling language, dan pengujian menggunakan metode Black Box. Hasil penelitian ini menunjukkan bahwa metode prototipe cocok digunakan dalam pengembangan aplikasi di CV Altrama Energi karena seringnya terjadi perubahan kebutuhan serta aplikasi yang dihasilkan user friendly digunakan oleh pegawai administrasi maupun pimpinan CV Altrama Energi.
Perancangan Sistem Administrasi Pada Kantor Lurah Kuala Langkat Berbasi Web Sitepu, Fernando; Sitorus, Zulham; Perwitasari, Ika Devi
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 1: JUNI 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i1.7320

Abstract

Studi ini bertujuan untuk merancang sistem manajemen berbasis web yang dapat meningkatkan efisiensi dan efektivitas pelayanan di Kantor Lurah Kuala Langkat. Sistem ini diciptakan untuk menyederhanakan proses pengelolaan data administrasi, seperti pendaftaran, pengelolaan surat, dan pengarsipan dokumen secara digital. Metodologi yang diterapkan dalam penelitian ini adalah metode pengembangan perangkat lunak dengan pendekatan terstruktur, yang mencakup analisis kebutuhan, desain, pembangunan, dan pengujian sistem. Dalam perancangan sistem, digunakan bahasa pemrograman PHP dan MySQL sebagai basis data, dengan tujuan untuk mempermudah pengelolaan data secara daring dan memastikan aksesibilitas yang lebih baik bagi pegawai dan masyarakat. Hasil dari studi ini diharapkan dapat memberikan solusi praktis untuk mengurangi pemakaian kertas, mempercepat proses administrasi, serta meningkatkan akurasi dan keamanan data di Kantor Lurah Kuala Langkat. Dengan adanya sistem manajemen berbasis web ini, diharapkan pelayanan publik di tingkat kelurahan dapat menjadi lebih transparan, efisien, dan terorganisir
Analisis Sentimen Google Review terhadap Mutu Kualitas Pendidikan pada Perguruan Tinggi STIE Al-Washliyah Sibolga dengan Metode Lexicon dan Algoritma Naive Bayes Tanjung, Miftah Rusydi; Iqbal, Muhammad; Sitorus, Zulham
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 02 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i02.1549

Abstract

Perkembangan teknologi informasi telah mendorong masyarakat untuk menyampaikan opini terhadap institusi pendidikan melalui platform digital seperti Google Review. Penelitian ini bertujuan untuk menganalisis sentimen masyarakat terhadap mutu layanan pendidikan di STIE Al-Washliyah Sibolga berdasarkan komentar Google Review dengan membandingkan dua pendekatan analisis sentimen, yaitu Lexicon-Based dan Naïve Bayes. Sebanyak 51 komentar dianalisis melalui tahapan praproses teks yang meliputi case folding, tokenisasi, stopwords removal, dan stemming. Hasil klasifikasi menunjukkan bahwa sebagian besar komentar bersentimen positif, dengan fokus pada kenyamanan lingkungan kampus, keramahan layanan, serta aksesibilitas lokasi. Model dievaluasi menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil evaluasi menunjukkan bahwa metode Naïve Bayes memiliki performa lebih unggul dengan akurasi sebesar 98%, recall 97,8%, dan F1-score 98,8%, dibandingkan Lexicon-Based yang hanya mencapai akurasi 94,1% dan F1-score 96,6%. Temuan ini menunjukkan bahwa citra STIE Al-Washliyah Sibolga di ruang digital sangat positif, serta algoritma Naïve Bayes layak digunakan sebagai pendekatan efektif dalam pemantauan opini publik terhadap perguruan tinggi berbasis data digital.
Artificial Intelligence Analysis of Recommendations for Granting Business Licenses to Determine the Priority of Business Supervision and Control Using the DBSCAN Method (Case Study: DPMPTSP Langkat Regency) diansyah, Suhar; Sitorus, Zulham; Iqbal, Muhammad
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 2 (2025): July
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i2.8900

Abstract

In facing the challenges of limited resources and business complexity, the Investment and One-Stop Integrated Services Office (DPMPTSP) of Langkat Regency requires a data-driven approach to determine priorities for business supervision and enforcement. This study applies the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to cluster business entities based on three main parameters: risk level, business scale, and licensing status. Secondary data from 3,748 companies were collected, processed through label encoding and normalization, and analyzed in a three-dimensional space (X1_Risk, X2_Scale, X3_License). The clustering results revealed the formation of clusters and a Silhouette Score value, indicating optimal cluster structure and separation between groups. Each cluster was interpreted as a representation of recommendation categories such as Routine Monitoring and Evaluation, Intensive Monitoring and Evaluation, Administrative Warning, Temporary Operational Suspension, and Permanent Operational Termination. The resulting visualizations enhanced the understanding of spatial mapping and clustering patterns comprehensively. This demonstrates that DBSCAN is effective as a decision-support tool for automated and objective priority mapping in business supervision, and capable of detecting business entities that deviate from general norms (outliers). This approach significantly contributes to improving the efficiency and accuracy of decision-making in business license supervision and enforcement at the regional level.
ROI and SNA Analysis in Testing the Effectiveness of New Student Admission Promotion: A Case Study at MAS Al Washliyah Gedung Johor Angkat, Chairul Indra; Sitorus, Zulham; Iqbal, Muhammad
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 2 (2025): July
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i2.8901

Abstract

Globalization and intense competition in the education sector, especially among private high schools, require institutions such as MAS Al Washliyah Gedung Johor to continue optimizing their new student admission promotion strategies. Although the school has implemented multi-channel promotions that include social media (Instagram, TikTok), conventional methods (brochures), and financial incentives (alumni tuition fee discounts), there has been no in-depth analysis of the effectiveness of each variable. The problem of less than optimal promotion results due to inappropriate media selection often results in inefficient allocation of promotion costs with minimal student recruitment results. This study aims to analyze the effectiveness of various promotion variables used by MAS Al Washliyah Gedung Johor, in order to support a more appropriate and efficient allocation of funding sources. Data were collected through a questionnaire given to new students regarding their sources of promotional information. To achieve this goal, this study uses a two-method approach: Return on Investment (ROI) to measure financial efficiency and return on funds, and Social Network Analysis (SNA) to visualize interaction patterns, reach, and identify the most influential communities or promotions in the student exposure network. By combining ROI and SNA analysis, it is hoped that this study can provide clear information regarding promotion costs and the most efficient and effective types of promotion, as a basis for improving the school promotion system in the future.
Performance Analysis of CNN (Convolutional Neural Network) in Nominal Classification of Rupiah Emissions 2022 Sahputra, Fajar; Sitorus, Zulham; Iqbal, Muhammad; Marlina, Leni; Nasution, Darmeli
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 2 (2025): July
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i2.8903

Abstract

This study aims to analyze the performance of Convolutional Neural Network (CNN) algorithm in classifying the nominal of Rupiah banknotes issued in 2022. Three test models are developed, namely two CNN architectures with different optimizers (Adam and RMSprop), and one transfer learning model using VGG16. The dataset used consists of 1,848 banknote images of seven denominations: Rp1,000, Rp2,000, Rp5,000, Rp10,000, Rp20,000, Rp50,000, and Rp100,000. The data was collected using a smartphone camera and processed through augmentation, normalization, and classification stages. The model was evaluated using accuracy, precision, recall, and F1-score metrics. The results show that CNN with Adam's optimizer achieves a validation accuracy of 98.97%, while CNN with RMSprop reaches 99.59%. Meanwhile, the VGG16 model achieved perfect validation accuracy of 100%, with precision, recall, and F1-score values of 1.00 each. These results show that the transfer learning approach provides the best performance compared to conventional CNN models. This research supports the development of an accurate and efficient banknote recognition automation system for digital finance applications.
Comparative Analysis of Sequencing Methods and Markov Models for Predicting High-Achieving Students at Budi Darma University Sinambela, Sugi Hartono; Iqbal, Muhammad; Khairul, Khairul; Darmeli Nasution; Zulham Sitorus
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 2 (2025): July
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i2.8964

Abstract

The prediction of high-achieving students is a strategic step in supporting the development of academic quality within higher education institutions. This study aims to compare two data mining approaches, namely the Sequencing method and the Markov Model, in predicting high-achieving students at Universitas Budi Darma Medan. The Sequencing method is used to identify patterns in the sequence of academic grades and non-academic activities of students from semester to semester, while the Markov Model is used to calculate the probability of transitions in students' academic status based on historical data. The research adopts a quantitative approach involving 100 active students with complete academic and non-academic data. The data analyzed include semester GPA, participation in organizations, seminars, and achievements in competitions. Both methods were evaluated using metrics such as accuracy, precision, recall, and F1-score. The evaluation results show that the Sequencing method achieved an accuracy of 87%, precision of 85%, recall of 88%, and an F1-score of 86%, while the Markov Model recorded an accuracy of 81%, precision of 79%, recall of 83%, and an F1-score of 81%. Based on these results, the Sequencing method is considered superior in detecting patterns and providing more accurate predictions of students’ achievement potential. The comparison of these two methods provides a foundation for institutions to develop more accurate, objective, and comprehensive student achievement prediction systems. Thus, universities can implement early and well-targeted interventions and guidance.
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 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`` Diva, Krisna Dwina Pri Indini Eko Hariyanto Eko Hariyanto Eko Hariyanto Eko Wahyudi 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 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 Simorangkir, Elsya Sabrina Asmita 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 Ariza Solly Ariza Lubis 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