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All Journal JTERA (Jurnal Teknologi Rekayasa) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Vocatech : Vocational Education and Technology Journal Jurnal Pengabdian Masyarakat: Darma Bakti Teuku Umar JATI (Jurnal Mahasiswa Teknik Informatika) JTIK (Jurnal Teknik Informatika Kaputama) Brilliance: Research of Artificial Intelligence Jurnal Minfo Polgan (JMP) TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Informasi Heca Journal of Applied Sciences Infolitika Journal of Data Science Jurnal Pengabdian Mitra Indonesia
Suryadi Suryadi
Universitas Teuku Umar Fakultas Teknik Program Studi Teknologi Informasi
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Sistem Pendukung Keputusan Rating Mitra Pada Badan Pusat Statistik Kabupaten Aceh Barat Menggunakan Metode Simple Additive Weighting (SAW) Astrianda, Nica; Away, Asmaul Husna; Suryadi, Suryadi
VOCATECH: Vocational Education and Technology Journal Vol 6, No 1 (2024): October
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v6i1.188

Abstract

AbstractStatistics Indonesia (BPS) is a non-ministerial government responsible for ensuring the availability of data for use by the government and the public. The data collection process at BPS is conducted through various methods, including surveys, which require substantial manpower. Therefore, BPS employs partners for the data collection process. Partners are recruited through the Sobat BPS application; however, there is often no assessment of these partners within the application, making it difficult for BPS to select high-performing partners. This issue allows for the potential re-selection of irresponsible partners. This study successfully designed and implemented an effective decision support system for evaluating BPS partners using the Simple Additive Weighting (SAW) method. The evaluation results show that this system not only provides accurate and objective assessments but also improves the efficiency of the partner selection process. With 100% accuracy in testing, this system can be adopted as a new standard to ensure that selected partners perform well, thereby supporting BPS in carrying out its duties more effectively and responsibly in the future.AbstrakBadan Pusat Statistik (BPS) merupakan lembaga pemerintah nonkementerian yang bertugas menjamin ketersediaan data untuk digunakan oleh pemerintah dan masyarakat. Proses pengumpulan data di BPS dilakukan melalui berbagai metode, termasuk survei, yang membutuhkan tenaga lebih besar. Oleh karena itu, BPS menggunakan jasa mitra untuk proses pendataan. Mitra direkrut melalui aplikasi Sobat BPS, namun seringkali tidak ada penilaian terhadap mitra pada aplikasi tersebut, menyulitkan BPS dalam menyeleksi mitra berkinerja baik. Masalah ini menyebabkan mitra yang tidak bertanggung jawab dapat terpilih Kembali. Penelitian ini merancang "Sistem Pendukung Keputusan Rating Mitra Pada Badan Pusat Statistik Kabupaten Aceh Barat Menggunakan Metode Simple Additive Weighting (SAW)" untuk menyeleksi mitra berkinerja baik atau buruk agar tidak terulang pada pekerjaan selanjutnya. Hasil penelitian menunjukkan bahwa sistem ini menghasilkan keputusan yang akurat, cepat, objektif, dan dapat menjadi standar baru bagi BPS dalam menyeleksi mitra berkinerja baik. Pengujian perhitungan pada sistem sesuai dengan perhitungan manual menggunakan metode SAW menunjukkan akurasi sebesar 100%.
Leveraging Machine Learning for Sentiment Analysis in Hotel Applications: A Comparative Study of Support Vector Machine and Random Forest Algorithms Suryadi, Suryadi; Syahputra , Dedek; Astrianda, Nica; Syahputra, Rizki Agam; Suhendra, Rivansyah
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4877

Abstract

This research aims to conduct sentiment analysis on user reviews of hotel booking applications such as Trivago, Tiket, Booking, Traveloka, and Agoda, collected from the Google Play Store. The dataset used consists of 5,000 user reviews, with 80% of the data allocated for training and 20% for testing. Two algorithms applied in this study are Support Vector Machine (SVM) and Random Forest, with performance evaluation based on accuracy, precision, recall, and F1-score metrics. The test results show that the Random Forest algorithm delivers the best performance on the Trivago application with 94% accuracy, 94% precision, 100% recall, and a 97% F1-score. Random Forest proves to be more effective in handling diverse review data, while the Support Vector Machine (SVM) algorithm also produces good results in sentiment classification. This research contributes to the development of sentiment analysis based on user reviews, which can be utilized by app developers and hotel management to improve service quality and user experience.
Sentiment Analysis on Tabungan Perumahan Rakyat (TAPERA) Program by using Support Vector Machine (SVM) Syahputra, Rizki Agam; Arifin, Riski; ., Suryadi; Iqbal, Muhammad
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8694

Abstract

This study aims to analyze public sentiment towards the Housing Savings Program (TAPERA) using the Support Vector Machine (SVM) algorithm. The dataset comprises 16,061 reviews about TAPERA which was gathered from web scrapping and YouTube API. The sentiment analysis results indicate that 99.8% of the reviews are negative, while only 0.2% are positive. The SVM model applied in this study achieved a very high accuracy rate of 99.81%. This indicates that the model is highly effective in classifying sentiments, particularly in identifying negative sentiments. The resulting confusion matrix shows the model's excellent performance in detecting negative sentiments, with no False Positives (FP) and a very high number of True Negatives (TN). However, the model exhibits weaknesses in detecting positive sentiments, as indicated by the presence of several False Negatives (FN) and the absence of True Positives (TP). The findings of this study suggest that the public generally holds a very negative view of the TAPERA program. This insight is crucial for program administrators to consider as they evaluate and improve the program based on negative feedback received from the public. Overall, this research provides important insights into public perceptions of TAPERA and underscores the need for better modeling for more representative sentiment analysis. These findings can serve as a basis for policymakers in designing more effective communication strategies and program improvements to increase public acceptance of TAPERA.
Pemanfaatan Potensi Lokal Jengkol Menjadi Keripik Bernilai Jual Dalam Kegiatan KKN Di Gampong Tuwi Kareung Kecamatan Panga Rizki Aldiansyah; Yudi Nurcahyanto; Andra Alfian; Febri Ariyanti; Heri Firnanda; Vela Haswita; Nurul Sa'ada; Puput Arisna; Ilham Juliwardi; Sanusi; Muhammad Ardiansyah; Suryadi; Rivansyah Suhendra
Jurnal Pengabdian Mitra Indonesia Vol 2 No 1: Februari 2026
Publisher : Mitra Akademia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67380/jpmina.v2i1.23

Abstract

Kuliah Kerja Nyata (KKN) merupakan wujud pengabdian masyarakat untuk mengintegrasikan ilmu akademik dengan kebutuhan riil di lapangan. Desa Tuwi Kareung, Kabupaten Aceh Jaya, memiliki potensi komoditas jengkol yang melimpah, namun nilai ekonominya masih rendah karena umumnya dijual dalam bentuk mentah. Kegiatan pengabdian ini bertujuan untuk meningkatkan nilai tambah jengkol melalui inovasi produk keripik, meningkatkan keterampilan teknis masyarakat dalam produksi dan pengemasan, serta memperkuat kapasitas kewirausahaan warga desa. Metode yang digunakan adalah pendekatan deskriptif-partisipatif dengan model learning by doing yang meliputi tahap pra-pelaksanaan (observasi dan koordinasi), pelaksanaan (sosialisasi, praktik produksi, dan pendampingan pengemasan), serta evaluasi. Hasil kegiatan menunjukkan adanya peningkatan signifikan pada keterampilan teknis masyarakat, mulai dari teknik perebusan untuk mengurangi aroma hingga teknik penggorengan yang menghasilkan tekstur renyah. Selain itu, masyarakat berhasil memproduksi keripik jengkol dengan kemasan dan label sederhana yang siap pasarkan. Secara kualitatif, terjadi perubahan persepsi masyarakat terhadap potensi jengkol sebagai produk olahan bernilai ekonomi tinggi. Meskipun durasi kegiatan terbatas untuk mengukur dampak ekonomi jangka panjang, program ini berhasil meletakkan dasar unit usaha produktif bagi ibu rumah tangga. Kesimpulannya, inovasi pengolahan jengkol merupakan strategi yang aplikatif dan relevan dalam memperkuat ketahanan ekonomi perdesaan berbasis potensi lokal di Desa Tuwi Kareung.
VoIP Jitter Buffers in Practice: A Performance Comparison Across Commercial Networks Murhaban Murhaban; Siti Aisah; Teuku Farizal; Suryadi Suryadi; Mukhlizar Mukhlizar; Muzakir Muzakir
JTERA (Jurnal Teknologi Rekayasa) Vol 10 No 2: December 2025
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The proliferation of Voice over Internet Protocol (VoIP) has revolutionized modern communication, offering cost-effective, feature-rich alternatives to traditional telephony. However, the inherent packet-switched nature of VoIP introduces challenges in maintaining real-time voice quality, primarily due to jitter—variations in packet arrival timing—and subsequent packet loss. This study empirically investigates the effectiveness of Jitter Buffer (JB) algorithms in mitigating these issues across diverse commercial network environments. Using a rigorous pre-test/post-test design, we evaluated VoIP call quality by deactivating and then reactivating JB mechanisms on the FreePBX platform. Utilizing standardized metrics, including Mean Absolute Deviation (MAD) for jitter quantification and packet loss rate, and employing the G.711 codec with Linphone clients across three distinct commercial ISPs, we captured and analyzed performance under controlled conditions. Baseline measurements revealed significant jitter and packet loss variations across ISPs, with one ISP exhibiting particularly precarious transmission stability. Post-implementation, our findings demonstrate substantial improvements across all ISPs. Notably, packet loss was reduced to 0% across all packets, and MAD values decreased dramatically, indicating significantly enhanced temporal stability. These results, further translated through the Mean Opinion Score (MOS) framework, confirm JB's critical role in stabilizing VoIP transmissions, validating its efficacy as a generalizable solution for improving voice quality and user experience in practical, real-world network conditions, irrespective of underlying ISP infrastructure disparities.
Dari Risiko Terbuka ke Risiko Terkendali:Mengevaluasi Aturan Firewall MikroTik dalam Keamanan Jaringan Murhaban Murhaban; Muzakir Muzakir; Ulfa Merlinda; Teuku Farizal; Suryadi Suryadi; Mukhlizar Mukhlizar
JTERA (Jurnal Teknologi Rekayasa) Vol 11 No 1: Vol. 11 No. 1: Juni 2026
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31544/jtera.v11.i1.2026.199-208

Abstract

The increasing dependence of government institutions on internet-based services has made network security a strategic requirement for preserving data confidentiality, service availability, and public trust. This study evaluates the reliability and mitigation effectiveness of MikroTik firewall rules in securing the internet network of a local government institution against three attack scenarios: packet sniffing, port scanning, and Distributed Denial of Service (DDoS). An experimental design was employed to compare network conditions before and after the activation of firewall rules. ARP spoofing-based packet sniffing was simulated using Ettercap, port scanning was performed using Zenmap, and DDoS traffic was generated using Hping3. In contrast, Wireshark and Winbox were used to monitor network traffic and firewall responses. The initial results show that before firewall activation, the network was exposed to multidimensional risks: packet sniffing revealed DHCP packets and IP-MAC metadata, port scanning identified 8 open ports, and the DDoS attack increased CPU utilization to 100% and elevated memory usage. After the firewall rules were activated, all three attacks were successfully mitigated. Sniffing activity was limited to normal DHCP Discover traffic, port scanning no longer revealed open ports, and DDoS packets were dropped before establishing effective connections. Overall, the MikroTik firewall achieved 100% reliability within the tested scenarios, demonstrating its effectiveness in reducing traffic exposure, controlling service visibility, and maintaining system availability in a government network environment.
Pelatihan Jurnalisme Investigasi Bagi Mahasiswa Jurnalistik UTU dan UIN Ar-Raniry di Banda Aceh dan Aceh Besar Muzakkir Muzakkir; Murhaban Murhaban; Teuku Farizal; Ismu Ridha; Iwan Doa Sempena; Futri Syam; Suryadi Suryadi; Mukhlizar Mukhlizar
Jurnal Pengabdian Masyarakat: Darma Bakti Teuku Umar Vol 6, No 2 (2024): Juli-Desember
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/baktiku.v6i2.11356

Abstract

In today's digital era, the continuous advancement of information has become meaningful in societal life. The development of investigative journalism exposes various irregularities or hidden issues covered up by state officials or authorities entrusted with the responsibility to manage and control various resources for the public's benefit. Additionally, investigative journalism is a methodological discipline, requiring opportunities to be understood and mastered. Thus, aspiring journalists need intelligence and agility to examine, research, and deconstruct journalistic knowledge to reveal hidden cases, prepared to face resistance, challenges, and threats. The purpose of this investigative journalism training for prospective journalists is to enable students to fully understand investigative reporting, which demands mental resilience and courage to disclose cases deliberately concealed. The benefit of this activity is to inspire students, as future journalists, to engage critically and insightfully with information evolving across various channels. As aspiring journalists, critical thinking is essential in addressing rumors, emerging public issues, and a skeptical stance toward information disseminated by certain parties, emphasizing the need for thorough verification. The direction and objective of this training for prospective journalists are to foster understanding and the ability to think critically in investigating and researching events or cases suspected of irregularities. This training employs lecture and discussion methods. The outcomes for aspiring journalists are to inspire, motivate, and express their investigative journalism work, serving as a medium to report events or cases suspected of anomalies to the public. Consequently, media users can better understand news or rumors constructed by aspiring journalists, which is then widely disseminated to the public.
IMPLEMENTASI SISTEM INFORMASI PRESENSI ONLINE BERBASIS WEBSITE DENGAN GEOLOCATION DAN FOTO SELFIE meutia rahayu herfala; suryadi suryadi; muhammad ardiansyah; Alisman Alisman
Jurnal Teknologi Informasi Vol 5, No 1 (2026): Mei
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jti.v5i1.12958

Abstract

Presensi karyawan merupakan aspek penting dalam menunjang kedisiplinan dan efektivitas administrasi di suatu instansi. Pada praktik sebelumnya, sistem absensi masih dilakukan secara manual, yang dinilai kurang efisien, rentan terhadap manipulasi data, serta menyulitkan proses rekapitulasi kehadiran. Oleh karena itu, penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem informasi presensi online berbasis website yang dilengkapi dengan fitur geolocation dan foto selfie sebagai bentuk validasi kehadiran. Sistem dikembangkan menggunakan metode prototype yang bersifat iteratif agar dapat menyesuaikan dengan kebutuhan pengguna secara bertahap, serta diuji menggunakan metode Blackbox Testing dengan teknik Equivalence Partitioning. Hasil implementasi menunjukkan bahwa sistem ini mampu mencatat presensi secara realtime, merekam lokasi pengguna, menyimpan foto selfie, dan menghasilkan laporan kehadiran secara otomatis serta akurat. Penerapan sistem ini dapat meningkatkan efisiensi operasional, transparansi pencatatan kehadiran, dan mengurangi potensi terjadinya kecurangan. Dengan demikian, instansi dapat mengelola data kehadiran karyawan secara lebih modern, efektif, dan profesional, sekaligus mendukung pengambilan keputusan manajerial berbasis data yang valid dan dapat di andalkan.
Assessing LightGBM Performance in Automated Leukemia Cell Classification Rara Syifa Qaisa; Hayatun Maghfirah; Suryadi Suryadi; Noviana Husdayanti; Rivansyah Suhendra
Infolitika Journal of Data Science Vol. 4 No. 1 (2026): May 2026
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v4i1.351

Abstract

Leukemia is a type of blood cancer that requires fast and accurate diagnosis for effective treatment. Manual identification of leukemia blood cell subtypes is often challenging, time-consuming, and prone to observer variability, making automated image-based classification essential. This study evaluates the performance of the Light Gradient-Boosting Machine (LightGBM) as a computationally efficient and interpretable alternative to deep learning models for classifying leukemia subtypes. The dataset includes 3,000 microscopic images representing five classes: acute lymphocytic, acute myelogenous, chronic lymphocytic, chronic myelogenous, and healthy blood cells. Images were preprocessed using bilinear interpolation to balance quality and efficiency, and 90 statistical features were extracted across 13 distinct color spaces. The model was trained on an 80% subset and validated on a 20% hold-out set after hyperparameter optimization. LightGBM achieved robust performance with an accuracy of 93.3%, precision of 99.1%, recall of 94.9%, and an F-measure of 96.8%. Feature importance analysis revealed that texture variance in the YIQ color space (STD_YIQ_I) was the most critical predictor, highlighting the biological relevance of chromatin texture in classification. These results indicate that LightGBM is an effective, lightweight, and reliable approach for leukemia subtype classification, holding strong potential for implementation in resource-constrained automated diagnostic systems.
Co-Authors Abdurrahman Ridho Alisman Alisman Andini, Mirna Ria Andra Alfian Arie Budiansyah Arifin, Riski Away, Asmaul Husna Baehaqi Candra, Rudi Arif Chandra, Radja Aditya Earlia, Nanda Farizal, Teuku Febri Ariyanti Futri Syam Hayatun Maghfirah Heri Firnanda Husdayanti, Noviana Ikhsan Ikhsan Ilham Juliwardi Ilham, Dirja Nur Ismu Ridha Iwan Doa Sempena Juliawardi, Ilham Kasmawati Kasmawati Maulana, Aga meutia rahayu herfala Muhammad Ardiansyah Muhammad Ardiansyah muhammad ardiansyah Muhammad Subianto Mukhlizar Mukhlizar Mukhlizar Mukhlizar Mukhlizar, Mukhlizar Murhaban Murhaban Murhaban Murhaban Murhaban Muzakir Muzakir Muzakkir Muzakkir Nica Astrianda Noviana Husdayanti Nurdjannah J. Niode Nurul Helda Nurul Sa'ada Puput Arisna Rara Syifa Qaisa Rinaldi Idroes Rivansyah Suhendra Rivansyah Suhendra Rizki Agam Syahputra Rizki Aldiansyah Saifullah Saifullah Sanusi Sanusi Sanusi Saputra Lubis, Doni Sasmita, Novi Reandy Shahrul Siti Aisah Suhendra, Rivansyah Syahputra , Dedek Teuku Farizal Teuku Rizky Noviandy Ulfa Merlinda Vela Haswita Yudi Nurcahyanto