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Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Banjarbaru
ISSN : 20893787     EISSN : 26850893     DOI : -
Core Subject : Science,
Computer Science & IT
Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi adalah Jurnal Ilmiah bidang Teknik Informatika dan Sistem Informasi yang diterbitkan secara periodik tiga nomor dalam satu tahun, yaitu pada bulan April, Agustus dan Desember. Redaksi Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi menerima sumbangan tulisan hasil penelitian atau atau artikel konseptual bidang Teknik Informatika dan Sistem Informasi.
Arjuna Subject : -
Articles 951 Documents
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Perancangan Sistem Informasi Biro Perjalanan Wisata Di CV Oppa Tour And Travel Berbasis Web Al Fajri, Muhammad Khoirul Wafa; Jazuli, Ahmad; Fiati, Rina
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2712

Abstract

CV Oppa Tour And Travel is experiencing problems with service efficiency because it does not yet have a web-based information system, which has an impact on delays in data access and customer service. This research aims to develop a web-based travel agency application to increase speed, accuracy and service satisfaction. The development method uses the Waterfall model, including requirements analysis, design, implementation, testing and documentation. The system is designed with main features such as authentication, data management, search, reports, and backup, and implemented using Laravel and MySQL. Testing is carried out using the Black Box method to ensure functionality runs as required. Test results show that the system is able to increase operational efficiency and provide easy access to information, ordering and printing tickets independently, thereby supporting faster and more professional service in the digital era.Keywords: Travel Agency; Booking; Study; Design; Waterfalls. AbstrakCV Oppa Tour And Travel mengalami kendala efisiensi layanan karena belum memiliki sistem informasi berbasis web, yang berdampak pada keterlambatan akses data dan pelayanan pelanggan. Penelitian ini bertujuan mengembangkan aplikasi biro perjalanan berbasis web untuk meningkatkan kecepatan, akurasi, dan kepuasan layanan. Metode pengembangan menggunakan model Waterfall, mencakup analisis kebutuhan, perancangan, implementasi, pengujian, dan dokumentasi. Sistem dirancang dengan fitur utama seperti autentikasi, manajemen data, pencarian, laporan, dan backup, serta diimplementasikan menggunakan Laravel dan MySQL. Pengujian dilakukan dengan metode Black Box untuk memastikan fungsionalitas berjalan sesuai kebutuhan. Hasil pengujian menunjukkan sistem mampu meningkatkan efisiensi operasional dan memberikan kemudahan akses informasi, pemesanan, serta pencetakan tiket secara mandiri, sehingga mendukung pelayanan yang lebih cepat dan profesional di era digital. 
Analisis Beban Kendaraan Terhadap Karakteristik Jalan Menggunakan Metode YOLOv5 Dan Perhitungan ESAL Wanda, Melifan; Himamunanto, Agustinus Rudatyo; Budiati, Haeni
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2713

Abstract

Roads are essential infrastructure supporting various types of vehicles; however, excessive loads are a primary cause of surface damage. The increasing volume of vehicles and imbalanced infrastructure development contribute significantly to road deterioration, leading to a reduction in road service life and increased maintenance costs. This study aims to address these issues by developing a system for vehicle detection, classification, and load estimation using the YOLO (You Only Look Once) algorithm a deep learning method capable of detecting and classifying vehicle objects in real time with high speed and accuracy. The data were obtained from CCTV surveillance video recordings. The results indicate that a total of 4,395 vehicles were successfully detected. These detections were then used to estimate the vehicle load using the Equivalent Single Axle Load (ESAL) method. The estimated total daily traffic reached 632,880 vehicles, with a corresponding daily load estimation of 284,214.74 ESAL. The findings highlight the significant impact of vehicle loads on road characteristics and demonstrate the effectiveness of YOLOv5 as a real time tool for monitoring and detecting vehicular load.Keywords: Computer Vision; YOLOv5; Vehicle detection; Vehicle load; Equivalent Single Axle LoadAbstrakJalan merupakan infrastruktur yang penting dalam  menopang berbagai jenis  kendaraan, namun beban berlebih menjadi penyebab utama kerusakan permukaan  pada jalan. Volume kendaraan yang meningkat dan pembangunan infrastruktur yang tidak seimbang  menyebabkan kerusakan pada jalan   yang menyebabkan  pengurangan umur jalan dan meningkatkan biaya perbaikan. Penelitian ini bertujuan untuk mengatasi permasalahan tersebut yaitu dengan membangun Pendeteksi, Klasifikasi dan menghitung  beban kendaraan berbasis Algoritma YOLO (You Only Look Once), sebuah algoritma deep learning yang mampu mendeteksi dan mengklasifikasikan objek kendaraan secara  real-time dengan kecepatan dan akurasi  yang sangat baik. Data yang digunakan diambil dari  rekaman video pengawas CCTV.  Hasil penelitian menunjukan  kendaraan  yang terdeteksi sebanyak 4.395 unit, kendaraan yang  berhasil terdeteksi kemudian dilakukan untuk  perhitungan estimasi beban kendaraan menggunakan perhitungan  Equivalent Single Axle Load (ESAL). Hasil  terhitung dengan total lalu lintas harian mencapai 632.880 unit kendaraan dengan estimasi beban harian sebesar 284.214,74 ESAL. Hasil penelitian menegaskan adanya  pengaruh signifikan beban kendaraan terhadap karakteristik jalan serta menunjukkan efektivitas YOLOv5 sebagai alat dalam memantau  dan mendeteksi beban kendaraan secara  real time 
Perbandingan Algoritma Boosting Untuk Klasifikasi Gaya Belajar Siswa Sekolah Menengah Kejuruan Ihsan, M Khaerul; Saputri, Dian Syafitri Chani; Sulistianingsih, Neny
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2701

Abstract

Education is a planned activity to improve human resources. However, based on interviews at SMKN 2 Mataram, the learning process has not been running optimally because the teaching method is not in accordance with the student learning styles. This study aims to identify students learning styles (Visual, Auditory, and Kinesthetic) using the Boosting method, namely AdaBoost, Gradient Boosting, and XGBoost. Data were obtained from questionnaires that had been tested for validity and reliability, and distributed to 203 students in grades X and XI from the TKJ, RPL, and ULW department. The dataset was divided into tree schemes: 70:30, 80:20, and 90:10. The best result were obtainet from XGBoost in the 70:30 scheme with an accuracy of 0.93, precision of 1.00, recall of 0.97, anf f1-score of 0.97. GradentBoost followed with an accuracy of 0.92, while ADaBoost had the lowest accuracy of 0.80. thus, XGBoost is superior and can be used as a refence in determining learning methods according to student charateristics.Keywords: Boosting Algorithm; Classification; Learning Style; Algorithm Comparison AbstrakPendidikan merupakan aktivitas terencana untuk meningkatkan mutu sumber daya manusia. Namun, berdasarkan wawancara di SMKN 2 Mataram, proses pembelajaran belum berjalan optimal karena metode pengajaran tidak sesuai dengan gaya belajar siswa. Penelitian ini bertujuan untuk mengidentifikasi gaya belajar siswa (Visual, Auditori, dan Kinestetik) menggunakan metode Boosting, yaitu AdaBoost, Gradient Boosting, dan XGBoost. Data diperoleh dari kuesioner yang telah diuji validitas dan reliabilitasnya, dan disebarkan kepada 203 siswa kelas X dan XI dari jurusan TKJ, RPL, dan ULW. Dataset dibagi dalam tiga skema: 70:30, 80:20, dan 90:10. Hasil terbaik diperoleh dari XGBoost pada skema 70:30 dengan akurasi 0.93, precision 1.00, recall 0.97, dan f1-score 0.97. Gradient Boosting menyusul dengan akurasi 0.92, sedangkan ADaBoost memiliki akurasi terendah sebesar 0.80. Dengan demikian, XGBoost lebih unggul dan dapat dijadikan referensi dalam menentukan metode pembelajaran sesuai karakteristik siswa. 
Model Game Survival Legenda Lokal Menggunakan RPG Maker MV Muslihuddin, Muslihuddin; Rosmawanti, Nidia; Ruslan, M.
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2792

Abstract

Game technology can expand opportunities for people to learn about the world, to develop communication and thinking skills. In Indonesia, there are countless legends and mythologies. Games can be an educational tool to preserve local culture. The legend of Dayuhan and Intingan from Tapin Regency, South Kalimantan, is not yet widely known by the younger generation. As a solution, a desktop-based Role-Playing Game (RPG) Survival game was developed using RPG Maker MV to introduce the legend interactively. The results of the test on 50 respondents showed that 79% strongly agreed and 21% agreed with the game's usefulness, and 62% strongly agreed and 18% agreed with its quality. This indicates that this game has an interface that matches the game theme, has clear sound, no stuck in the game, appropriate controls and character designs that match the story theme. Thus, this game is considered effective as a medium for preserving the legend of Dayuhan and Intingan so that it remains known and not forgotten.Keywords: Game; Role-Playing Game; Dayuhan and Intingan; Desktop AbstrakTeknologi  game  dapat  memperluas  berbagai  peluang  bagi  seseorang untuk belajar tentang dunia, untuk mengembangkan kemampuan komunikatif dan berfikir. Di Indonesia, terdapat banyak cerita legenda dan mitologi. Game dapat menjadi sarana edukatif untuk melestarikan budaya lokal. Legenda Dayuhan dan Intingan dari Kabupaten Tapin, Kalimantan Selatan, belum dikenal luas oleh generasi muda. Sebagai solusi, dikembangkan game RPG (Role-Playing Game) Survival berbasis desktop menggunakan RPG Maker MV untuk memperkenalkan legenda tersebut secara interaktif. Hasil uji terhadap 50 responden menunjukkan 79% sangat setuju dan 21% setuju terhadap kemanfaatan game, serta 62% sangat setuju dan 18% setuju terhadap kualitasnya, yang menunjukkan bahwa game ini memiliki antarmuka yang sesuai dengan tema game, memiliki suara yang jelas, tidak memiliki stuck dalam game, kontrol yang sesuai dan desain karakter yang sesuai dengan tema cerita. Dengan demikian, game ini dinilai efektif sebagai media pelestarian legenda Dayuhan dan Intingan agar tetap dikenal dan tidak terlupakan. 
Comparison of Naive Bayes and Support Vector Machine Algorithms in Sentiment Analysis Sela, Tiara; Sonita, Anisya
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2727

Abstract

Twitter is a social media platform that quickly spreads public opinion. The Ronald Tannur case, widely discussed on this platform, triggered various public reactions. This study aims to compare the Naive Bayes and Support Vector Machine (SVM) algorithms in analyzing netizens’ sentiment toward the case. The process includes data collection and text preprocessing, such as removing duplicates, cleaning, case folding, word normalization, stopword removal, tokenization, and stemming. The text is then transformed using TF-IDF. Sentiment classification is performed using both algorithms and evaluated through metrics like accuracy, precision, recall, F1-score, and AUC. The models are tested on three data split schemes: 90:10, 80:20, and 70:30. The results show that SVM with 90% training data provides the best performance, achieving 88.78% accuracy and 0.84 AUC, outperforming Naive Bayes, which only reached 71.29% accuracy and 0.77 AUC. This shows that SVM is more accurate in detecting sentiment on social media.Keywords : Sentiment Classification; Naive Bayes Algorithm; Support Vector Machine Algorithm; Twitter; Python AbstrakTwitter merupakan media sosial yang cepat menyebarkan opini publik. Kasus Ronald Tannur, yang banyak dibicarakan di platform ini, memicu beragam reaksi dari masyarakat. Penelitian ini bertujuan untuk membandingkan algoritma Naive Bayes dan Support Vector Machine (SVM) dalam menganalisis sentimen warganet terhadap kasus tersebut. Proses analisis mencakup pengumpulan data, praproses teks seperti penghapusan duplikat, pembersihan, case folding, normalisasi kata, penghapusan stopword, tokenisasi, dan stemming, lalu data ditransformasi menggunakan TF-IDF. Klasifikasi sentimen dilakukan menggunakan kedua algoritma dan dievaluasi dengan metrik seperti akurasi, presisi, recall, F1-score, dan AUC. Pengujian dilakukan pada tiga skema pembagian data latih dan uji, yaitu 90:10, 80:20, dan 70:30. Hasil menunjukkan bahwa SVM dengan rasio data latih 90% memberikan hasil terbaik dengan akurasi 88,78% dan AUC 0,84, melampaui Naive Bayes yang hanya mencapai akurasi 71,29% dan AUC 0,77. Ini menunjukkan bahwa SVM lebih akurat dalam mengenali sentimen di media sosial. 
Perancangan Sistem Informasi Penjualan Boneka Pada Store Adede Menggunakan Metode Waterfall Nurfajria, Dera; Tukino, Tukino; Hananto, Agustia; Hananto, April Lia
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2718

Abstract

Digitalization of sales systems is an important need to improve transaction efficiency and accuracy. This study aims to build a web-based doll sales system at Toko Adede Cikampek using the Waterfall method which includes needs analysis, design, implementation, testing, and maintenance. The system was developed using PHP and MySQL, and tested using the black box method and System Usability Scale (SUS). The test results showed that all features ran as expected, with a SUS score of 83.3 which is classified as "excellent". The main features include product catalogs, stock management, shopping carts, checkouts, and order management. This system has been proven to improve transaction efficiency, recording accuracy, and online marketing reach.Keywords: Waterfall method; Sales system; Website; Dolls; UsabilityAbstrakDigitalisasi sistem penjualan menjadi kebutuhan penting untuk meningkatkan efisiensi dan akurasi transaksi. Penelitian ini bertujuan membangun sistem penjualan boneka berbasis web pada Toko Adede Cikampek menggunakan metode Waterfall yang mencakup analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Sistem dikembangkan menggunakan PHP dan MySQL, serta diuji menggunakan metode Black box dan System Usability Scale (SUS). Hasil pengujian menunjukkan seluruh fitur berjalan sesuai harapan, dengan skor SUS 73,48 yang tergolong “baik”. Fitur utama meliputi katalog produk, manajemen stok, keranjang belanja, checkout, dan pengelolaan pesanan. Sistem ini terbukti dapat meningkatkan efisiensi transaksi, keakuratan pencatatan, dan jangkauan pemasaran secara online. 
Evaluasi Pengukuran Tingkat Kepuasan Pengguna Aplikasi Disney+ Menggunakan Metode End User Computing Satisfaction Dellia, Prita; Mardania, Saskia Dwi; Ummah, Rovikotul; Putra, Hengky Ulman Armanda; Amin, Mohammad
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2818

Abstract

This research aims to assess user satisfaction with the Disney+ streaming application through the application of the End User Computing Satisfaction (EUCS) method. It focuses on user perceptions related to several dimensions, including content, accuracy, format, ease of use, and system reliability. A quantitative approach was adopted by distributing online questionnaires to active users. The gathered data were processed using descriptive statistical techniques, along with validity and reliability testing. The results reveal that all EUCS dimensions have a positive impact on overall user satisfaction, with ease of use being the most influential. These insights are expected to help developers enhance the service quality of the Disney+ application to meet user expectations more effectively.Keywords: User satisfaction; Disney+ application; End User Computing Satisfaction; Digital servicesAbstrakStudi ini dimaksudkan untuk menilai sejauh mana tingkat kepuasan pengguna dalam menggunakan aplikasi Disney+ dengan menggunakan pendekatan End User Computing Satisfaction (EUCS). Penilaian dilakukan terhadap persepsi pengguna mengenai lima aspek utama: konten, akurasi, format tampilan, kemudahan penggunaan, dan keandalan sistem. Metode yang digunakan dalam penelitian ini adalah kuantitatif, dengan menyebarkan kuesioner kepada pengguna aktif. Data yang terkumpul dianalisis menggunakan teknik statistik deskriptif serta uji validitas dan reliabilitas. Hasil menunjukkan bahwa seluruh dimensi EUCS memberikan pengaruh positif terhadap kepuasan pengguna, dengan kemudahan penggunaan menjadi faktor yang paling dominan. Temuan ini diharapkan dapat memberikan masukan bagi pengembang aplikasi untuk meningkatkan kualitas layanan Disney+ ke depannya. 
Evaluasi K-Means dan Hierarchical Clustering dalam Segmentasi Wilayah Penerimaan Bantuan Sosial Pangan di Provinsi X Fathoni, Fathoni; Khairani, Annisa; Nur'Aini, Risma; Gultom, Gina Destia; Alfitrah, Intan Aidita; Ibrahim, Ali
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.2672

Abstract

The allocation of food social assistance in Indonesia faces challenges in targeting accuracy and distribution effectiveness. To improve distribution efficiency, this study explores regional segmentation using two clustering methods K-Means and Hierarchical Clustering based on social and economic characteristics. The analysis uses 324 secondary records from the Satu Data Indonesia portal, categorized by regency and city in Province X. Clustering performance was evaluated using the Silhouette Coefficient and Davies-Bouldin Index. Results show that K-Means Clustering outperforms Hierarchical Clustering, achieving a Silhouette Coefficient of 0.5371 and a Davies-Bouldin Index of 0.7173 with five clusters. In contrast, Hierarchical Clustering produced a Silhouette Coefficient of 0.4976 and a Davies-Bouldin Index of 0.7607. Based on these findings, K-Means is recommended for more effective regional segmentation in the distribution of food social assistanceKeywords: Regional Segmentation; Food Social Assistance; K-Means; Hierarchical Clustering AbstrakAlokasi bantuan sosial pangan di Indonesia masih menghadapi kendala ketepatan sasaran dan efektivitas penyaluran. Salah satu pendekatan untuk meningkatkan efisiensi penyaluran adalah dengan melakukan segmentasi wilayah penerima bantuan sosial pangan berdasarkan atribut sosial dan ekonomi. Penelitian ini bertujuan untuk mengkaji dua teknik klasterisasi, yaitu K-Means dan Hierarchical Clustering, untuk melakukan segmentasi wilayah penerima bantuan sosial pangan di Provinsi X. Data yang digunakan adalah data sekunder yang bersumber dari portal Satu Data Indonesia sebanyak 324 record yang dikelompokkan berdasarkan kabupaten dan kota. Evaluasi kinerja klasterisasi dilakukan dengan menggunakan dua metrik, yaitu Silhouette Coefficient dan Davies-Bouldin Index. Hasil penelitian menunjukkan bahwa pendekatan K-Means Clustering menghasilkan segmentasi wilayah yang unggul, ditunjukkan dengan nilai Silhouette Coefficient sebesar 0,5371 dan Davies-Bouldin Index sebesar 0,7173 untuk lima klaster. Pendekatan Hierarchical Clustering menghasilkan nilai Silhouette Coefficient sebesar 0,4976 dan Davies-Bouldin Index sebesar 0,7607. Dengan demikian, metode K-Means direkomendasikan untuk menggambarkan wilayah dalam distribusi bantuan sosial pangan. 
Noise and Gradient-Aware Sampling for Efficient Diffusion Generation Andra, Muhammad Bagus
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.3116

Abstract

Diffusion models have achieved remarkable success in generative tasks but remain computationally expensive due to their iterative sampling process. The Denoising Diffusion Implicit Model (DDIM) is one of the popular choices for sampling methods, yet it is still riddled with some drawbacks. DDIM employs a fixed-step schedule that allocates equal computational effort across all noise levels, overlooking the varying difficulty of the denoising process. In this work, we propose Adaptive Timestep Allocation for DDIM, a simple yet effective sampling scheme that dynamically adjusts step sizes based on both noise variance and gradient sensitivity of the denoising network. Our approach allocates larger steps during high-noise sampling stages, where coarse updates are sufficient, and smaller steps during low-noise sampling stages, where detail and intricate parts of the image are critical. This dual adaptation is inspired by insights from signal-to-noise ratio (SNR) analysis and adaptive ODE solvers, requiring no retraining or architectural modifications. We evaluate our method on Stable Diffusion v1.5 and SDXL using MS-COCO captions and DrawBench prompts. Our evaluation shows improvements in Fréchet Inception Distance (FID) and CLIP score, while reducing sampling steps. Our results highlight that principled, adaptive step allocation offers a practical and plug-and-play solution for accelerating diffusion sampling without compromising image quality. 
Implementation of Zabbix-Based Network Monitoring with Telegram and Web Reporting Isnandar, Ahmad Yazid; Ridwandono, Doddy; Sembilu, Nambi
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.3040

Abstract

Effective network monitoring is essential in ensuring the stability and performance of campus IT infrastructure. This study aims to implement an open-source network monitoring system using Zabbix, integrated with Telegram alerts and a web-based visualization dashboard built with Laravel Filament. The development process follows the PPDIOO methodology, encompassing stages such as planning, installation, configuration, alert integration, and dashboard development. The system was implemented for the network infrastructure of two buildings at Universitas Pembangunan Nasional "Veteran" Jawa Timur: the Faculty of Computer Science Building (FIK2) and the Shared Lecture Building (GKB). The results show that the system effectively monitors the status of network devices, CPU and memory usage, DHCP leases, and network traffic. Additionally, it features real-time alerts via Telegram and web-based reports for visualizing network data. This solution enhances operational efficiency and offers a flexible and adaptive monitoring tool tailored to the needs of campus network management. 

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