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SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan
Published by RAM PUBLISHER
ISSN : 30901626     EISSN : 30323991     DOI : -
Core Subject : Humanities, Science, Engineering,
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan or in English the publication title Information Systems, Engineering and Applied Technology is an open access journal committed to publishing high quality research articles in the fields of Information Systems, Informatics, Digital Communication Information Technology, Tourism Technology, Transportation Technology, Agricultural Technology, Plantations, Fisheries, Marine, Environmental Technology, Artificial Intelligence, Mechanical Engineering, Electrical Engineering, Industrial Engineering and Civil Engineering. Published 4 X (Times) a year in January, April, July, and October. SITEKNIK accepts and selects quality articles and focuses on providing the best service for writers. SITEKNIK is committed to being a leading platform for researchers to share their innovative findings. We also provide a fast and transparent review process to ensure the quality and originality of each published article.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 107 Documents
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Information System Requirements Analysis for MSME Digitalization Using the SDLC Waterfall Approach Alvan Dhan; Angelina Apriyani Pandiangan; Nadita; Ratih Echa Kurnia; Rafi Akmal Rizqullah
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 2 (2026): April
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.19926982

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in the economy; however, they still face various challenges in adopting digital technology. This study aims to examine the requirements of an information system to support the digitalization of MSMEs using the Software Development Life Cycle (SDLC) Waterfall model. The research focuses on the analysis and design stages, which include identifying user requirements, analyzing business processes, and designing the system using Unified Modeling Language (UML). The results indicate that the proposed system should be capable of supporting integrated product management, transactions, ordering processes, and sales reporting, involving key actors such as buyers, sellers, and administrators. This study produces a system requirements model that can serve as a foundation for developing digital applications for MSMEs, thereby improving operational efficiency and enhancing business competitiveness.
Fine-Tuning Panoptic FPN with ResNet-50 for Maritime Obstacle Detection on the LaRS Dataset Istifa Shania Putri; Sugih Ahmad Fauzan; Mega Fitri Yani; Cindy Muhdiantini
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 3 (2026): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.20768168

Abstract

Maritime obstacle detection is a critical challenge for Unmanned Surface Vehicles (USVs) operating in complex and dynamic environments. This study investigates the effectiveness of fine-tuning Panoptic FPN, a Mask R-CNN-based architecture augmented with Feature Pyramid Networks, for panoptic segmentation on the LaRS (Lake, River, Seas) dataset. Unlike prior work that explored model comparisons broadly, this research focuses specifically on the impact of hyperparameter tuning and backbone selection on maritime panoptic segmentation performance. Through systematic ablation studies, we demonstrate that adjusting the learning rate to 0.002 and the gamma decay factor to 0.2 yields significant improvements. Our fine-tuned Panoptic FPN with a ResNet-50 backbone achieves a Panoptic Quality (PQ) of 45.31%, surpassing the previous state-of-the-art Mask2Former Swin-B (41.7%) by 3.61 percentage points. Notably, ResNet-50 outperforms the deeper ResNet-101 backbone (36.47% PQ), suggesting that heavier architectures may overfit on domain-specific maritime datasets. Furthermore, Panoptic FPN requires only 8 hours of training compared to approximately 2 days for Mask2Former Swin-L, demonstrating superior computational efficiency. These findings highlight that targeted fine-tuning of lightweight architectures can outperform larger transformer-based models in maritime panoptic segmentation tasks.
Dashboard-Based Distribution Requirements Planning for Reverse Logistics Scheduling Optimization in Community Waste Collection Nia Novitasari; Gisti Ayu Pratiwi
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 3 (2026): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21533174

Abstract

This study aims to develop a dashboard-based waste collection scheduling system using the Distribution Requirements Planning (DRP) approach to improve the effectiveness of sorted gallon waste collection at Bank Sampah Bersinar (BSB), Bojongsoang. BSB manages six recycle points with a total weekly collection demand of 4,050 kg, while the available fleet consists of only one pick-up vehicle with a capacity of 1,000 kg. The absence of a structured collection schedule previously caused simultaneous collection activities and potential over-dimension and over-load problems. This study applies DRP to allocate collection activities based on demand volume, fleet capacity, operational time, and BSB’s three-day collection policy. The result shows that all weekly waste volume can be collected within three operational days by visiting two recycle points per day, with two trips conducted each day. In addition, a monitoring dashboard was developed to support daily trip tracking, collection volume monitoring, and recycle point performance evaluation. The proposed system provides a practical solution for improving reverse logistics operations, reducing fleet overload risk, and supporting data-based decision-making in community waste management.
Implementation of FSN Analysis and Periodic Review System for Inventory Management Improvement in Spare Parts Warehouse Leo Rama Kristiana; Gisti Ayu Pratiwi; Putu Giri Artha Kusuma; Grass Aditya Pringgodani; Irza Farhand; Theresia Jeremia Purba
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 3 (2026): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21533846

Abstract

Effective inventory management is essential for maintaining spare parts availability and ensuring high service levels in the automotive industry. PT IAMI, particularly the PSM Dept. and PC Dept. Bekasi, identified inventory management issues at its Medan Depot as a pilot project for inventory improvement. The depot initially achieved a fill rate of only 60%, below the company’s target of 70%, due to the absence of standardized spare parts classification, review period policies, replenishment planning, and an integrated monitoring system. To address these issues, a community service program was conducted by Telkom University through technical assistance in developing an inventory management framework. The program integrated Fast-Slow-Non Moving (FSN) Analysis, the Periodic Review System (R,s), and a dashboard-based inventory monitoring system using Microsoft Excel. The implementation stages included field observation, focus group discussion, operational data analysis, spare parts classification, inventory parameter calculation, dashboard development, and validation with the partner. The results showed that the proposed inventory policy improved the fill rate from 60% to 99%, exceeding the company target. In addition, the dashboard improved inventory visibility by displaying stock status, fill rate, safety stock, reorder warnings, and other operational indicators.
Analisis Komprehensif Teknologi Panel Surya: Prinsip, Komponen, dan Konfigurasi Sistem Pembangkit Listrik Tenaga Surya Hery Sudaryanto
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 3 (2026): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21322583

Abstract

Energi surya memainkan peran penting dalam transisi global menuju energi terbarukan, dengan teknologi fotovoltaik (PV) memimpin pasar. Artikel ini memberikan analisis komprehensif tentang teknologi panel surya, meliputi prinsip kerja fundamentalnya, komponen sistem penting, dan konfigurasi struktural di pembangkit listrik tenaga surya. Artikel ini mengevaluasi sel surya berbasis silikon tradisional bersama dengan teknologi generasi berikutnya yang sedang berkembang. Analisis kuantitatif menunjukkan bahwa panel silikon monokristalin konvensional mencapai efisiensi komersial tertinggi sebesar 15% hingga 22%, sementara teknologi polikristalin dan film tipis menawarkan efisiensi yang lebih rendah, masing-masing sebesar 13% hingga 18% dan 10% hingga 12%. Untuk mengatasi batasan efisiensi teoritis silikon, sel surya perovskit yang sedang berkembang telah menunjukkan efisiensi laboratorium melebihi 25%, dan struktur tandem/multi-junction mendorong batas kinerja melewati 30% dengan mengoptimalkan penyerapan spektral. Di luar fisika tingkat sel, studi ini meneliti komponen balance of system (BOS) yang penting, termasuk inverter, pengontrol pengisian daya, dan infrastruktur penyimpanan baterai (seperti timbal-asam dan litium-ion). Selain itu, studi ini merinci dinamika rekayasa dan operasional dari konfigurasi pembangkit listrik tenaga surya on-grid, off-grid, dan hibrida. Dengan mengintegrasikan rekayasa struktur, ilmu material, dan desain sistem, ulasan ini berfungsi sebagai referensi teknis strategis untuk mengoptimalkan penyebaran, efisiensi, dan keandalan instalasi pembangkit listrik tenaga surya modern.
Pengembangan Sistem Pakar Diagnosis Tingkat Stres Menggunakan Metode Certainty Factor Fairuz Destea Hafsha Permanasari; Adi Fajaryanto Cobantoro; Rifqi Rahmatika Az-Zahra
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 3 (2026): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21724197

Abstract

Proses penyusunan skripsi sering menimbulkan stres pada mahasiswa akibat tuntutan akademik, keterbatasan waktu, dan berbagai kendala selama penelitian. Kondisi tersebut dapat memengaruhi motivasi dan konsentrasi sehingga diperlukan sistem untuk mendeteksi kondisi psikologis mahasiswa secara dini. Penelitian ini bertujuan merancang dan membangun sistem pakar diagnosis tingkat stres mahasiswa menggunakan metode Certainty Factor (CF) di Institut Agama Islam Riyadlotul Mujahidin (IAIRM) Ngabar. Sistem dikembangkan berbasis web menggunakan framework Laravel, PHP, dan MySQL dengan basis pengetahuan yang mengacu pada instrumen Depression Anxiety Stress Scales (DASS-42) yang terdiri atas 42 gejala. Pengujian dilakukan menggunakan white box testing untuk memastikan fungsi dan alur logika sistem berjalan sesuai rancangan. Hasil penelitian menunjukkan bahwa sistem mampu menghitung nilai Certainty Factor berdasarkan nilai CF User dan CF Pakar serta menghasilkan diagnosis secara otomatis. Pada pengujian, kategori P01 (Stres Ringan) memperoleh nilai CF tertinggi sebesar 82,4%, sedangkan P02 (Kecemasan) sebesar 28% dan P03 (Depresi) sebesar 0%, sehingga sistem menetapkan diagnosis Stres Ringan dengan tingkat keyakinan 82,4%. Sistem yang dikembangkan dapat dimanfaatkan sebagai alat bantu deteksi dini tingkat stres mahasiswa selama proses penyusunan skripsi.
Implementasi Model Mobilenetv2 Untuk  Klasifikasi Ras Anjing Nurzaenab; Sul Agus Zarni; Andi Yulia Muniar; Tatik Maslihatin; Ika Yuswandari Supagi Supagi; Fitriani M. Sabir
SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan Vol. 3 No. 3 (2026): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.21579001

Abstract

Identifikasi ras anjing secara visual merupakan tantangan signifikan bagi masyarakat awam karena kemiripan fitur morfologi yang sangat tinggi antar spesies. Kesalahan identifikasi berdampak serius pada ketidaktepatan pola perawatan harian dan penanganan medis spesifik. Penelitian ini mengimplementasikan teknologi visi komputer melalui model Deep Learning berbasis arsitektur MobileNetV2 untuk klasifikasi otomatis ras Basenji, Chow, Dingo, dan Lhasa. Permasalahan utama yang diangkat adalah tingginya variasi intra-kelas dan kemiripan ekstrem antar-kelas pada citra hewan. Metodologi penelitian menggunakan 600 citra berkualitas tinggi dengan tahap preprocessing ketat dan augmentasi data intensif. Teknik transfer learning diterapkan melalui fine-tuning pada 50 lapisan terakhir MobileNetV2. Untuk meningkatkan stabilitas, model dimodifikasi dengan menambahkan lapisan Dense 32 unit, Dropout 0.6, serta Regularizer L2 sebesar 0.003 guna menekan risiko overfitting. Hasil pengujian menunjukkan performa impresif dengan akurasi pelatihan 96% dan akurasi pengujian 93%. Waktu pelatihan sangat efisien, yakni hanya 3 menit untuk 10 epoch. Analisis confusion matrix menunjukkan keunggulan model pada ras Basenji, meskipun terdapat tantangan tekstur bulu pada Lhasa dan Chow. Konfigurasi ini terbukti efektif, ringan, dan siap untuk implementasi real-time pada perangkat seluler.

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