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INDONESIA
JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Published by STMIK Global Informatika MDP
ISSN : 24074322     EISSN : 25032933     DOI : -
Core Subject : Science,
Computer Science & IT
JATISI bekerja sama dengan IndoCEISS dalam pengelolaannya. IndoCEISS merupakan wadah bagi para ilmuwan, praktisi, pendidik, dan penggemar dalam bidang komputer, elektronika, dan instrumentasi yang menaruh minat untuk memajukan bidang tersebut di Indonesia. JATISI diterbitkan 2 kali dalam setahun (September dan Maret), makalah yang diterbitkan JATISI minimal terdiri dari 60% dari luar Sumatera Selatan, dan 40% dari Sumatera Selatan. Makalah yang diterbitkan melalui tahap review oleh reviewer yang berpengalaman dan sudah memiliki makalah yang diterbitkan di jurnal internasional yang terindeks SCOPUS.
Arjuna Subject : -
Articles 1,216 Documents
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Perancangan dan Penerapan Sistem Informasi Maintenance dan Biaya Mesin di PT. XYZ Apriyanto, Joni
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11188

Abstract

Competition in the business world is getting tighter, including in the manufacturing industry. Companies that will survive are companies that can maximize machine capacity with the most efficient costs in their operations. PT. XYZ already has a maintenance information system to monitor machine performance but does not yet have a system to monitor costs incurred for machine maintenance and repairs so that it cannot find out machine performance in terms of costs. The purpose of this study is to complement the existing maintenance information system with an additional integrated cost monitoring system that helps the engineering department to find out the costs incurred in detail. The method used in this study is to conduct a survey of the existing system and plan a system that is able to find out machine costs in detail. The results of this study are a maintenance and machine cost information system that can be used well at PT. XYZ. This system is able to assess machine performance, engineering department performance and is able to find out the costs incurred in detail and the report data can be used for maintenance planning and spare part reserves in the engineering department.
PERBANDINGAN METODE KLASIFIKASI PADA JENIS PENJUALAN PT. YLO Putri, Manda Anugerah; Siagian, Bekman
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11254

Abstract

Strategi pengelolaan penjualan menjadi faktor yang cukup krusial yang perlu dipertimbangkan dengan baik oleh industri demi keberlanjutan bisnis ditengah persaingan global yang kompetitif. PT. YLO merupakan salah satu pelaku bisnis yang bergerak pada industri rokok multinasional di Indonesia. Dalam menjalankan bisnisnya banyak tantangan yang dihadapi khususnya dari pesaing sehingga kecermatan dalam menentukan jenis penjualan kepada rantai pasok secara tunai maupun kredit secara akurat diharapkan mampu membantu perusahaan dalam mencapai tujuan perusahaan dengan meningkatkan profitabilitas dengan risiko gagal bayar yang rendah. Atas dasar tersebut pendekatan data mining diperlukan untuk dapat mengklasifikasikan jenis penjualan yang lebih optimal bagi perusahaan. Dalam penelitian ini, ada beberapa metode klasifikasi yang dibandingkan yaitu Decision Tree, Gradient Boosted Tree, k-NN, Logistic Regresion dan Naïve Bayes. Berdasarkan pengujian dari beberapa metode tersebut menunjukkan bahwa walaupun tingkat akurasi Logistic Regresion sebesar 71,39% lebih rendah daripada Naïve Bayes namun metode tersebut memiliki recall tertinggi sebesar 92,45% dan F-1 Score sebesar 68, 15% hasil tersebut mengintrepretasikan bahwa Logistic Regresion menunjukkan performa terbaik dalam mendeteksi transaksi kredit yang dapat digunakan oleh PT. YLO dalam menentukan langkah strategis dalam bisnisnya.
DETEKSI PLAT NOMOR KENDARAAN MENGGUNAKAN METODE YOLOv8 Putra, Lipi Amanda; Yohannes, Yohannes
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11261

Abstract

Motorized vehicles play a crucial role in daily life, making vehicle management and monitoring increasingly necessary. One common issue arises in parking systems, where current systems only capture photos of vehicles and still require manual input of license plate numbers upon vehicle exit. These systems are not yet capable of automatically detecting and recognizing license plates. Therefore, this study aims to design an application for license plate recognition using the YOLOv8 method to automatically and accurately detect license plates. YOLOv8 is a fast and accurate object detection model. The dataset used consists of 764 images of vehicle license plates, divided into 70% training data, 20% validation data, and 10% test data. he results of the study show a detection accuracy with a precision value of 94.3%, recall of 87.3%, and mAP of 95.3%.
Rancangan Manajemen Server Log Menggunakan Rsyslog dengan Metode Design Thinking Yushini, Silmi; Azizzan, Rangga; Voutama, Apriade
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11334

Abstract

Manajemen server log merupakan aspek kritis dalam menjaga keamanan dan kinerja sistem IT. Penelitian ini bertujuan untuk mengembangkan solusi server log terpusat yang dirancang untuk memantau dan menganalisis log dari beberapa server RHEL. Selain itu, penelitian ini akan melakukan pengujian dan penilaian penetrasi untuk memastikan kemampuan akuisisi data log yang efektif. Dengan memanfaatkan teknik pemrosesan log tingkat lanjut, kami akan merumuskan aturan keamanan yang bertujuan untuk mencegah pelanggaran keamanan sistem. Hasil penelitian menunjukkan bahwa sistem berhasil mengelola log dengan baik, termasuk enkripsi file log, pengiriman ke server penyimpanan, dan pengarsipan inkremental. Struktur direktori yang terorganisir memudahkan administrator dalam melacak dan memelihara log. Penelitian ini menjadi dasar bagi pengembangan lebih lanjut, seperti penambahan fitur notifikasi dan kompabilitas dengan berbagai distribusi Linux.
Digitalisasi Monitoring Kesehatan Pondok Pesantren Berbasis Sistem Informasi Website Sumantri; sumantri, Sumantri; Rakhmawati, Puji Utami
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11339

Abstract

Digitalisasi dalam berbagai aspek kehidupan terus berkembang, termasuk dalam bidang kesehatan. Pondok pesantren, sebagai salah satu institusi pendidikan berbasis keagamaan, memerlukan sistem monitoring kesehatan yang efektif untuk mendukung kesejahteraan santri. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem informasi berbasis website yang mempermudah proses pemantauan kesehatan di lingkungan pondok pesantren. Sistem ini mencakup fitur pencatatan data kesehatan, pemantauan riwayat medis, dan notifikasi terkait kebutuhan medis santri. Dengan menggunakan metode pengembangan sistem berbasis prototype, penelitian ini menunjukkan bahwa sistem ini mampu meningkatkan efisiensi dalam pengelolaan data kesehatan, meminimalisir kesalahan pencatatan, dan mempermudah akses informasi oleh pihak terkait. Melalui pendekatan prototipe, sistem ini memungkinkan perbaikan berkelanjutan berdasarkan umpan balik pengguna selama proses pengembangan. Implementasi sistem ini diharapkan dapat memberikan kontribusi positif terhadap kesehatan santri dan mendukung digitalisasi di pondok pesantren.
OPTIMASI ALGORITMA K-NEAREST NEIGHBOR DENGAN ALGORITMA GENETIKA PADA DETEKSI PENYAKIT DIABETES MELLITUS Darmawan, Marcellinus Aditya Vitro; Haromainy, M. Muharrom Al; Junaidi, Achmad
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11353

Abstract

This study discusses the optimization of the K-Nearest Neighbor (KNN) algorithm using Genetic Algorithm (GA) in detecting diabetes mellitus. The research includes stages of collecting datasets on diabetes mellitus symptoms, data preprocessing through normalization and dataset alignment, model implementation, and testing with various scenarios to achieve the highest accuracy. The data used consists of the Pima Indians Diabetes Database as dataset 1 and the Early Stage Diabetes Risk Prediction Dataset as dataset 2. The evaluation is conducted by comparing the accuracy results between KNN without optimization and KNN optimized using Genetic Algorithm. The study's results indicate that optimization is performed by finding the optimal combination of the k-value and the features used in classification. The Genetic Algorithm produces individuals with the best fitness based on the combination of k-values and features that yield the highest accuracy. Testing was conducted on two datasets with two different fold values. The best accuracy was obtained in the 10-fold test, where the accuracy for dataset 1 increased from 74.2% to 79.1% after optimization. Meanwhile, for dataset 2, the accuracy improved from 97.5% to 98.2% after optimization. There was an increase in accuracy for dataset 1, whereas for dataset 2, the improvement was not significant. The conclusion of this study is that optimizing the KNN algorithm using Genetic Algorithm has proven to enhance the accuracy of diabetes mellitus detection, especially in numerical datasets with more complex features.
Perangkat Lunak Pendeteksi Jenis Seragam Siswa Jenjang Pendidikan Menengah Menggunakan Yolov8 Dody, Muhammad; Yohannes, Yohannes
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11356

Abstract

In a school environment, policies and regulations play a vital role in teaching students discipline, particularly in adhering to uniform rules. School uniforms help instill discipline by requiring students to dress according to the rules, without modifications, and in compliance with set standards. These regulations foster equality among students, reduce social differences, and support character and moral education. However, enforcing uniform policies can pose challenges for schools. Schools need to regularly monitor compliance to ensure every student follows the uniform rules, a process that often requires significant time and effort. To address this issue, this study developed a student uniform detection system using the You Only Look Once Version 8 (YOLOv8) method. YOLOv8 is a convolutional neural network-based object detection method capable of identifying objects in real-time with high accuracy. The aim of this study is to create a system that can automatically detect student uniforms, improve record-keeping accuracy, and reduce excessive time and energy spent monitoring detection results through cameras. The research methodology includes image data collection, YOLOv8 model training, and system testing. The testing results showed that the developed model achieved a precision of 95.%, a recall of 85%, a mean Average Precision (mAP) of 92.2%.
Analisi Komparasi Metode K-Nearest Neighbor dan Naïve Bayes Classifier Berbasis Optimasi Randomized Search Dalam Klasifikasi Berita Hoaks Christopher, Bryan
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11371

Abstract

In the digital era, the spread of hoax news has become a serious challenge that can lead to misinformation and negative societal impacts. Therefore, effective methods are needed to accurately classify hoax news. This study compares the performance of the K-Nearest Neighbor (KNN) and Naïve Bayes Classifier (NBC) algorithms in hoax news classification, utilizing the Randomized Search optimization approach to improve model accuracy. The dataset used is the Indonesia False News (Hoax) Dataset from Kaggle, with input attributes consisting of news titles and narratives. The results show that Randomized Search optimization successfully enhanced the performance of both algorithms. Naïve Bayes demonstrated superior performance compared to KNN, achieving an accuracy of 84.77%, precision of 84.77%, recall of 84.77%, and a misclassification error of 15.23%. Meanwhile, KNN achieved an accuracy of 84.30%, precision of 82.88%, recall of 84.30%, and an error rate of 15.70%. Based on these findings, Naïve Bayes is more effective in detecting hoax news than KNN. This study contributes to the development of hoax news detection systems by optimizing models using Randomized Search, which can help reduce the spread of false information in society.
CLUSTERING PENINDAKAN KASUS KORUPSI DI INDONESIA MENGGUNAKAN K-MEANS: ANALISIS DATA KPK TAHUN 2004-2024 Anjarwati, Dwi
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11375

Abstract

Abstract The enforcement of corruption cases by the Corruption Eradication Commission (CEC) from 2004 to 2024 shows variation in both the number of cases and the completion of legal processes. This study employs a quantitative approach using the K-Means Clustering method to group annual data based on five legal stages: investigation, inquiry, prosecution, final verdict (inkracht), and execution. Clustering was conducted based on the similarity of centroid values across years, with the optimal number of clusters determined using the Davies-Bouldin Index (DBI). The analysis divides the period into four main phases: initiation, expansion, transition, and intensification, illustrating shifts in enforcement patterns over time. The findings indicate that the success of corruption enforcement is determined not only by the number of cases handled but also by the ability to complete the legal process through to the final stage. This method provides an objective overview that can be used to evaluate KPK’s enforcement performance and to formulate more effective anti-corruption strategies. Keywords: Corruption, CEC, Enforcement, Clustering, K-Means, Centroid, Davies-Bouldin Index
Pengembangan Sistem Penjualan Gelang Manik Hello Eunoia Menggunakan Strategi CRM Guna Meningkatkan Loyalitas Pelanggan Wulandari, Maria Sri; Noveandini, Rahayu; Aningsih, Dewi Sifa
JATISI Vol 12 No 2 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i2.11403

Abstract

Hello Eunoia is a creative industry that has been established since 2021. This industry sells handicraft products made from beads, especially bracelets. For sales and promotion techniques, Hello Eunoia wants to apply web-based information technology. This is because so far Hello Eunoia has only relied on social media with the WhatsApp, Instagram and manual face to face platforms. Therefore, it is necessary to create a web-based sales system for bead bracelets at Hello Eunoia using CRM (Customer Relationship Management) as a sales system for the Hello Eunoia creative industry to make it easier for sellers to communicate all forms of information both about products and shops to buyers, so that buyers can receive valid information conveyed via WhatsApp and email media. The development model used is System Development Life Circle (SDLC). The software used is Sublime Tex, Xampp, and Mysql. The tests carried out are black box testing, browser performance testing and Likert scale user testing. From the test results, the function and usability of this application can run well. This application can make it easier for customers to place orders and make transactions anytime and anywhere without having to come directly to the shop.

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