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All Journal Journal on Mathematics Education (JME) Journal on Mathematics Education (JME) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Pengembangan Rekayasa dan Teknologi JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) JSAI (Journal Scientific and Applied Informatics) Progresif: Jurnal Ilmiah Komputer Jurnal Teknik Informatika (JUTIF) JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Jurnal Penyuuhan dan Pemberdayaan Masyarakat (JPPM) PELS (Procedia of Engineering and Life Science) Jurnal Teknik Indonesia Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Pengabdian Masyarakat Tekno SISFOTENIKA
Johannes Hamonangan Siregar
Universitas Pembangunan Jaya
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Nursing Public Health Social Sciences Transportation Other

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Pemberdayaan Pemuda Karang Taruna Melalui Literasi Bisnis Digital Tiktok Affiliate dan Aplikasi Keuangan SIAPIK Syihab, Faizah; Safrizal, Safrizal; Purnama, Denny Ganjar; Siregar, Johannes Hamonangan; Anwar, Chaerul
Jurnal Penyuluhan dan Pemberdayaan Masyarakat Vol. 5 No. 1 (2026): Jurnal Penyuluhan dan Pemberdayaan Masyarakat
Publisher : CV. Era Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59066/jppm.v5i1.2039

Abstract

Perkembangan ekonomi digital menghadirkan peluang bagi pemuda dalam meningkatkan kemandirian ekonomi, namun masih terkendala oleh rendahnya literasi bisnis digital dan pengelolaan keuangan. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan literasi bisnis digital dan kemampuan pencatatan keuangan pemuda Karang Taruna melalui pemanfaatan TikTok Affiliate dan aplikasi keuangan SIAPIK. Metode pelaksanaan meliputi sosialisasi, pelatihan, pendampingan praktik langsung, dan evaluasi. Pelatihan TikTok Affiliate difokuskan pada pengelolaan akun bisnis, pembuatan konten promosi, serta mekanisme perolehan komisi, sedangkan pelatihan SIAPIK diarahkan pada pencatatan transaksi pemasukan dan pengeluaran secara digital dan sistematis. Hasil kegiatan menunjukkan peningkatan pemahaman peserta terhadap konsep bisnis digital, kemampuan memanfaatkan TikTok Affiliate sebagai media promosi produk, serta keterampilan dalam melakukan pencatatan keuangan menggunakan SIAPIK. Peserta juga menunjukkan peningkatan motivasi berwirausaha dan kesadaran akan pentingnya pengelolaan keuangan yang transparan dan akuntabel. Kegiatan ini berkontribusi dalam memperkuat literasi digital dan mendukung pemberdayaan ekonomi pemuda Karang Taruna agar lebih adaptif dan kompetitif di era ekonomi digital.
AnalisisTroubleshooting Jaringan LAN Menggunakan ICMP pada Cisco Packet Tracer Michael; Johannes Hamonangan Siregar
Jurnal Pengembangan Rekayasa dan Teknologi Vol. 9 No. 2 (2025): November (2025)
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jprt.v9i2.13509

Abstract

Protokol Internet Control Message Protocol (ICMP) merupakan protokol pendukung pada lapisan jaringan yang berfungsi menyediakan informasi kendali serta pelaporan kesalahan dalam proses pengiriman paket IP. Pada jaringan Local Area Network (LAN), ICMP banyak digunakan sebagai alat troubleshooting dasar untuk menguji konektivitas, mendeteksi jalur paket, dan menganalisis kegagalan komunikasi antarperangkat. Penelitian ini bertujuan untuk menganalisis efektivitas ICMP dalam menangani permasalahan konektivitas jaringan melalui simulasi LAN menggunakan Cisco Packet Tracer. Metode penelitian dilakukan dengan merancang topologi jaringan sederhana, melakukan konfigurasi IP dan routing, serta mensimulasikan berbagai skenario gangguan seperti kesalahan konfigurasi IP, gateway tidak tersedia, dan pemutusan link jaringan. Pengujian dilakukan menggunakan perintah ping dan traceroute untuk mengamati respon pesan ICMP. Hasil penelitian menunjukkan bahwa ICMP mampu memberikan informasi diagnostik yang jelas melalui pesan echo reply, destination unreachable, dan request timed out, sehingga memudahkan identifikasi sumber permasalahan jaringan. Penelitian ini menegaskan bahwa ICMP merupakan alat fundamental dalam troubleshooting jaringan berbasis TCP/IP, khususnya untuk pembelajaran dan simulasi jaringan.
Implementation of Knowledge Management System in the Indonesian History Community Harahap, Nurul Haifa; Setiawati, Nur Fitri Rosa; Akoso, Muhammad Daffa Raihan; Siregar, Johannes Hamonangan
Jurnal Teknik Indonesia Vol. 4 No. 4 (2025): Jurnal Teknik Indonesia
Publisher : Publica Scientific Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58860/jti.v4i4.710

Abstract

Komunitas Historia Indonesia (KHI) is one of the leading historical communities in Indonesia that plays an important role in preserving and disseminating historical knowledge to the public. In the digital era, the challenges in maintaining the continuity of knowledge and collaboration between community members are increasing. Therefore, the implementation of the Knowledge Management System (KMS) is relevant to manage, store, and disseminate historical knowledge effectively. This article discusses how the implementation of KMS can improve the effectiveness of KHI community activities, as well as the obstacles and opportunities faced in the process. The method used is a literature study of KMS literature and documentation of community activities. Keywords : Knowledge Management System, Historical Community, Knowledge Preservation, Komunitas Historia Indonesia.
Penataan Administrasi GKI Maleo melalui Pendampingan Pengembangan Website Data Keanggotaan: Pengabdian Singadji, Marcello; Hulu, Dalizanolo; Siregar, Johannes Hamonangan; Sadira, Aundrel Aza; Abarua, Nathasa Rowen Frederika; Makarena, Maria Rachel Kesya; Christy, Tegar Surya
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 2 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 2 (October 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i2.4363

Abstract

Membership administration is a fundamental component of effective church governance. GKI Maleo faces challenges in managing congregational data due to the continued use of manual record-keeping systems, which leads to risks of data loss, duplicated information, and difficulties in data management. This community service activity aims to assist GKI Maleo in reorganizing its membership administration through the development of a membership data website that includes features for personal data, family information, sacramental records, membership transfers, and service history. The implementation method includes needs analysis, system design, website development, user training, as well as monitoring and evaluation. The results show a significant improvement in data accuracy, efficiency in data retrieval, and the church administrators’ ability to manage congregational information digitally. The development of this website provides a tangible contribution to the modernization of church administration and enhances the quality of services provided to the congregation.
Deep Learning-Based Detection of Potato Leaf Diseases Using ResNet-50 with Mobile Application Deployment Budy Santoso, Cahyono; Effendi, Rufman Iman Akbar; Siregar, Johannes Hamonangan
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.5186

Abstract

Plant diseases significantly reduce agricultural productivity, especially in developing regions with limited access to early detection tools. This research presents a deep learning-based approach for detecting potato leaf diseases, focusing on Early blight, Late blight, and healthy conditions. A modified ResNet-50 architecture was employed and trained using a publicly available potato leaf image dataset. Preprocessing steps included data augmentation and normalization to enhance model generalization. The model achieved a high accuracy of 99.31%, with precision, recall, and F1-score all exceeding 99%, indicating excellent classification performance. This study introduces a novel approach that improves classification performance through an optimized deep learning architecture, achieving higher accuracy compared to existing models. In addition to enhancing predictive capability, the study also addresses the practical need for accessibility by integrating the trained model into an Android-based mobile application. The application allows users to upload or capture leaf images and receive real-time predictions. The interface was designed for simplicity and usability in field conditions, making it accessible to farmers and agricultural workers. The findings demonstrate that combining deep learning with mobile technology can offer an effective and scalable solution for early disease detection in agriculture. Future work may explore cross-crop adaptability and lightweight model optimization for real-time performance on low-resource devices.
Social Network and Sentiment Analysis for Social CRM Optimalization on Indonesian Digital Recruitment Platform Seibah Humayyah; Johannes Hamonangan Siregar
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.2871

Abstract

The rapid growth of digital recruitment platforms in Indonesia has generated a large volume of user content on social media, serving as a vital data source for Social Customer Relationship Management (Social CRM) strategies. Consequently, the strategic insights that can be drawn may be limited. This study applied an integrated analytical approach combining Social Network Analysis (SNA) and lexicon-based sentiment analysis to evaluate public interactions regarding Jobstreet, Glints, and Dealls. The research methodology involved collecting data from platform X (previously known as Twitter) during the period of April 1-30, 2025, which was then analyzed using SNA with Gephi to identify influential actors through centrality metrics, alongside sentiment analysis to measure emotional polarity. The main findings revealed that Jobstreet possessed the healthiest conversational ecosystem, characterized by positive and neutral sentiment from its central actors. Glints exhibited sentiment polarization, and Dealls showed reputational vulnerability due to dominant negative sentiment from its influential users. It was concluded that the integration of these two methods provides a robust framework for designing more responsive and data-driven Social CRM strategies.Keywords: Social Network Analysis; Sentiment Analysis; Social CRM; Digital Recruitment; Lexicon-Based Features.AbstrakPerkembangan pesat platform rekrutmen digital di Indonesia telah menghasilkan volume besar konten pengguna di media sosial, yang menjadi sumber data vital untuk strategi Social Customer Relationship Management (Social CRM). Sehingga hal ini dapat menyebabkan insight strategis yang bisa diambil menjadi terbatas. Penelitian ini menerapkan pendekatan analitis terpadu yang menggabungkan Social Network Analysis (SNA) dan analisis sentimen berbasis leksikon untuk mengevaluasi interaksi publik mengenai Jobstreet, Glints, dan Dealls. Metodologi penelitian melibatkan pengumpulan data dari platform X (sebelumnya dikenal dengan Twitter) selama periode 1-30 April 2025, yang kemudian dianalisis menggunakan SNA dengan Gephi untuk mengidentifikasi aktor berpengaruh melalui metrik sentralitas, serta analisis sentimen untuk mengukur polaritas emosional. Temuan utama mengungkapkan bahwa Jobstreet memiliki ekosistem percakapan paling sehat, ditandai oleh sentimen positif dan netral dari aktor-aktor sentralnya. Sebaliknya, Glints menunjukkan polarisasi sentimen, dan Dealls menunjukkan kerentanan reputasi karena sentimen negatif yang dominan dari para pengguna berpengaruhnya. Disimpulkan bahwa integrasi kedua metode ini menyediakan kerangka kerja yang kuat untuk merancang strategi Social CRM yang lebih responsif dan berbasis data.Kata Kunci: Analisis Jaringan Sosial; Sentimen; Social CRM; Rekrutmen digital; Lexicon-Based Features.
Co-Authors Abarua, Nathasa Rowen Frederika Akoso, Muhammad Daffa Raihan Ali Godjali Ali Godjali, Ali Budy Santoso, Cahyono Chaerul Anwar Chaerul Anwar Christy, Tegar Surya Dalizanolo Hulu Effendi, Rufman Iman Akbar Harahap, Nurul Haifa Kahfi, Juan Haniful Makarena, Maria Rachel Kesya Marcello Sangaji Marcello Singadji Michael Nani Grace Berliana Nur Safitri Wakhyuningsih Nur Safitri Wakhyuningsih, Nur Safitri Nurita, Nurita Purnama, Denny Ganjar Rufman Iman Akbar E Sadira, Aundrel Aza Safrizal Safrizal Seibah Humayyah Setiawati, Nur Fitri Rosa Surya, Shabrina Naras Syihab, Faizah Wiwik Wiyanti Wiwik Wiyanti, Wiwik