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INDONESIA
IKRA-ITH Informatika : Jurnal Komputer dan Informatika
Published by Universitas Persada Indonesia YAI
ISSN : 25804316     EISSN : 26548054     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 504 Documents
 43   44   45   46   47 
Implementasi Sistem Monitoring Zabbix Dan Discord Webhook Untuk Nontifikasi Real-time Server Maria Afri Yani; Dia alemisa br Sembiring; Lotar Mateus Sinaga
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6906

Abstract

Server monitoring is an important aspect of maintaining the availability, reliability, and performance of information technology services. Delays in detecting server disruptions can lead to decreased service quality, increased downtime, and hindered operational processes. Therefore, a monitoring system capable of providing fast and accurate information about server conditions to administrators is required. This study aims to implement a monitoring system using Zabbix integrated with Discord Webhook as a real-time notification medium. The research method includes problem identification, literature review, system requirements analysis, implementation, and system testing. The implementation was carried out through network topology design, installation and configuration of the Zabbix Server on the Debian 12 operating system, creation of monitoring hosts using the ICMP Ping method, and integration of Discord Webhook for automatic notification delivery. Testing was conducted by simulating disruptions on the Debian 12 server to trigger problem and recovery conditions in Zabbix. The results show that the system successfully detected the conditions of Unavailable by ICMP Ping and High ICMP Ping Loss automatically. In addition, both disruption and recovery notifications were successfully sent to a Discord channel in real time according to changes in server status. The implementation of this system can assist network administrators in monitoring server conditions more effectively, accelerate the process of identifying disruptions, and improve responses to network problems without having to continuously access the Zabbix dashboard.
Integrasi MEREC dan MOORA untuk Pemilihan Ketua OSIS Oktoverano Lengkong; Edson Yahuda Putra; Ibrena Reghuella Chrisanti
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6922

Abstract

The selection of a student council president requires an objective assessment process because the decision affects student leadership and the continuity of student programs. At SMK Yadika Manado, the assessment of student council president candidates may still be influenced by subjectivity and requires relatively long processing time when performed manually. This study develops a web-based decision support system for selecting the student council president using a combination of MEREC and MOORA. MEREC is used to determine objective criteria weights based on the removal effect of each criterion, while MOORA is used to rank alternatives using normalized values and criteria weights. The test data consist of three candidates evaluated using four criteria: leadership, responsibility, discipline, and achievement. The results show that responsibility has the highest weight of 0.262295, followed by discipline at 0.252831, achievement at 0.248925, and leadership at 0.235948. The final ranking identifies Keanu Mangundap as the best alternative with a score of 0.672946. The developed system supports candidate data management, criteria management, weight calculation, and transparent ranking presentation.
Sistem Pendukung Keputusan Pemilihan Guru Terbaik Menggunakan Metode MOORA (Studi Kasus: TK Persiwa II) Tahlia Jelita Putri; Nasrul Hidayah
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6926

Abstract

TK Persiwa II has not conducted a routine best teacher selection due to the absence of standard procedures and clear measurement tools, leading to subjective evaluations. This study aims to build a web-based Decision Support System (DSS) to automate the recommendations for the best teacher. The method applied is Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), which processes six evaluation criteria categorized into benefit and cost attributes. The system was developed using the Waterfall model with PHP programming language and MySQL database. The final result of this research is a DSS application capable of generating automatic teacher ranking reports. The implementation of this system successfully assists the principal in making the best teacher selection decisions more transparently, objectively, and accountably.
Analisis Sentimen Ulasan Pengguna Aplikasi KitaLulus Berdasarkan Skala Rating Menggunakan Algoritma Support Vector Machine (SVM) Gheryyan Syagara; Setyono Setyono; Hilmy Aliy Andra Putra
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6929

Abstract

The KitaLulus job-search application has been downloaded more than 10 million times and holds an average rating of 4.7 on the Google Play Store, yet the large volume of user reviews makes manual interpretation of user perception difficult. This study applies the Support Vector Machine (SVM) algorithm to classify the sentiment of KitaLulus user reviews into five classes based on the 1-5 rating scale. Data were collected through web scraping using the google-play-scraper library, yielding 15,000 reviews that were reduced to 10,536 after data cleaning. The research followed the Sample, Explore, Modify, Model, Assess (SEMMA) framework, comprising text preprocessing (cleaning, case folding, tokenization, slang normalization, stopword removal, and stemming), TF-IDF feature weighting, SVM modeling with 10-fold cross validation, and hyperparameter tuning using GridSearchCV across three kernel types (Linear, Radial Basis Function, and Polynomial). The initial LinearSVC evaluation achieved a mean accuracy of 74.17%. Hyperparameter tuning selected the RBF kernel with C=1 and gamma=scale as the best configuration, which, when evaluated on the full dataset using cross_val_predict, produced an accuracy of 70.10%, with the highest F1-Score on the rating-5 class (0.86) and considerably lower performance on the minority rating-2 class (0.04) due to class imbalance. The study demonstrates that SVM is reasonably effective for multiclass sentiment classification of application reviews, although handling imbalanced data remains an important consideration for future research.
Estimasi Dimensi Kepribadian Melalui Analisis Citra Ekspresi Wajah Menggunakan Convolutional Neural Network Annas Prasetio; Sri Handayani
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6936

Abstract

Personality is a crucial aspect that influences a person's behavior, way of thinking, and interaction patterns in various situations. Advances in digital image processing and artificial intelligence technology offer opportunities for developing systems capable of automatically estimating personality dimensions through facial expression analysis. This study aims to build a personality dimension estimation model based on facial expression images using the Convolutional Neural Network (CNN) method. The research steps include collecting a dataset of facial images representing various expressions, image preprocessing, including face detection, image size normalization, and data augmentation, followed by training a CNN model to learn visual characteristics related to facial expressions. The resulting model is then tested using data not involved in the training process to measure the model's generalization ability. System performance is evaluated using metrics such as accuracy, precision, recall, F1-score, and confusion matrix. The results are expected to demonstrate that the Convolutional Neural Network approach is capable of effectively extracting visual features from facial expressions and can therefore be used as a basis for estimating personality dimensions. This research is expected to contribute to the development of computer vision and artificial intelligence technology, particularly in the fields of human behavior analysis, decision support systems, and more adaptive human-computer interaction applications. Keywords: Personality Estimation, Facial Expression Images, Digital Image Processing, Convolutional Neural Network, Computer Vision, Artificial Intelligence.
RANCANG BANGUN APLIKASI PENJUALAN TOKO BUNGA “FRESH FLOWERS INDONESIA (FFI FLORA)’’ BERBASIS WEB UNTUK MENDUKUNG PEMASARAN DAN PEMESANAN SECARA ONLINE Nisda Ramadanti; Kartini Kartini
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6938

Abstract

Perkembangan teknologi informasi mendorong pelaku usaha memanfaatkan media digital untuk meningkatkan efektivitas pemasaran dan pelayanan pelanggan. Fresh Flowers Indonesia (FFI Flora) masih melakukan pemasaran dan pemesanan melalui media sosial dan komunikasi langsung sehingga penyampaian informasi produk, pengelolaan pesanan, serta pencatatan transaksi belum berjalan secara efektif. Penelitian ini bertujuan merancang dan membangun aplikasi penjualan berbasis web untuk memudahkan pelanggan memperoleh informasi produk dan melakukan pemesanan secara online serta membantu admin mengelola data penjualan. Penelitian menggunakan metode pengumpulan data berupa observasi, wawancara, studi pustaka, dan kuesioner. Analisis sistem dilakukan menggunakan metode PIECES, sedangkan pengembangan perangkat lunak menggunakan metode Waterfall. Sistem dibangun menggunakan MERN Stack yang terdiri atas MongoDB, Express.js, React.js, dan Node.js dengan konsep Responsive Web Design sehingga dapat diakses melalui berbagai perangkat. Hasil penelitian menunjukkan bahwa sistem mampu meningkatkan efektivitas pengelolaan produk, transaksi, pembayaran, dan laporan penjualan. Berdasarkan hasil User Acceptance Testing (UAT) terhadap 53 responden, aplikasi memperoleh tingkat penerimaan yang baik sehingga dinilai mampu memenuhi kebutuhan pengguna. Dengan demikian, aplikasi penjualan berbasis web dapat menjadi solusi dalam meningkatkan efektivitas pemasaran, kualitas pelayanan, dan efisiensi operasional pada Fresh Flowers Indonesia (FFI Flora).
Implementasi Sistem Informasi Rapor Digital (SIDORAL) Berbasis Web pada SMA Kapuas Pontianak Anggi Basifatul Rahma; Erica Gracila Muntu; Eri Bayu Pratama; Lady Agustin Fitriana
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6940

Abstract

Report card management is a crucial part of the academic process in schools. However, at SMA Swasta Kapuas, the grade recapitulation process is still largely conducted semi-manually using separate spreadsheet applications. This mechanism triggers human error risks, slows down report card compilation, and complicates data retrieval. This study aims to build a web-based Digital Report Card Information System (SIDORAL) to integrate academic data management effectively. The system was developed using the CodeIgniter 4 Framework with Model-View-Controller (MVC) architecture and MySQL database. The software development methodology applied was Extreme Programming (XP), which includes planning, design, coding, and testing stages. The system functionality test was conducted using a structured testing method. The results show that SIDORAL successfully simplifies the integrated management of teacher, student, subject, and grade component data. Based on the testing phase results, all main features of the system were declared 100% valid and functioned properly without program logic errors. The implementation of SIDORAL is able to transform conventional grade data processing at SMA Swasta Kapuas into a secure digital system, thereby increasing distribution time efficiency and facilitating transparent delivery of learning outcomes information to students and parents.
Perbandingan Kinerja Multinomial Naïve Bayes pada Variasi Rasio Data Training dan Testing dalam Analisis Sentimen Ulasan Taman Rakyat Slawi Ayu Moh. Syaogi; Nur Ariesanto Ramdhan; Otong Saeful Bachri
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6941

Abstract

Sentiment analysis is one of the text mining techniques used to identify public opinions toward a particular object or service. Taman Rakyat Slawi Ayu, as one of the public green spaces in Tegal Regency, receives numerous visitor reviews through Google Maps, which can be utilized as a source of information to evaluate the quality of its services and facilities. This study aims to compare the performance of the Multinomial Naïve Bayes algorithm using different training and testing data split ratios for sentiment analysis of Taman Rakyat Slawi Ayu reviews. The data were collected through a web crawling technique on Google Maps, resulting in 4,153 reviews. After the data selection process, 1,794 reviews met the analysis criteria. The preprocessing stage consisted of cleaning, case folding, tokenizing, stopword removal, and stemming, resulting in 1,789 reviews ready for classification. Sentiment labeling was performed based on user ratings, where ratings of 1–3 were categorized as negative sentiment and ratings of 4–5 as positive sentiment. The experiments were conducted using three data split ratios: 70:30, 80:20, and 90:10. The results showed that the 90:10 ratio achieved the highest accuracy of 87.71%, with a precision of 0.88, recall of 0.99, and F1-score of 0.93. However, this ratio used a smaller testing dataset, making the evaluation results less representative than those obtained using the other data split ratios. Overall, the study demonstrates that variations in the training and testing data split ratio affect the classification performance of the Multinomial Naïve Bayes algorithm in sentiment analysis of Taman Rakyat Slawi Ayu reviews.
Sistem Pemantauan dan Pengontrol Lampu Otomatis Berbasis Internet of Things dengan Integrasi Kamera CCTV Zahra Khoirothun Nissak Ferdian; Muhammad Mahmud; Wincoko Wincoko
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6944

Abstract

Perkembangan teknologi Internet of Things (IoT) memberikan kemudahan dalam pengembangan sistem otomatisasi rumah (smart home), khususnya pada pengontrolan lampu. Penggunaan lampu secara manual sering menyebabkan pemborosan energi listrik dan keterbatasan dalam melakukan pemantauan kondisi rumah dari jarak jauh. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pemantauan dan pengontrol lampu otomatis berbasis IoT yang terintegrasi dengan kamera CCTV. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan model pengembangan ADDIE yang meliputi tahap analisis, perancangan, pengembangan, implementasi, dan evaluasi. Sistem dibangun menggunakan timer switch sebagai pengatur waktu otomatis, relay sebagai pengendali lampu, terminal block sebagai penghubung rangkaian, adaptor 12V sebagai sumber daya CCTV, serta kamera CCTV V380 Pro sebagai media monitoring. Pengontrolan dan pemantauan dilakukan melalui aplikasi V380 Pro pada smartphone yang terhubung internet. Hasil penelitian menunjukkan bahwa sistem mampu mengontrol lampu secara otomatis sesuai jadwal yang telah ditentukan dan dapat dikendalikan secara manual melalui smartphone. Kamera CCTV juga mampu menampilkan kondisi lampu secara real-time sehingga pengguna dapat melakukan monitoring dari jarak jauh. Berdasarkan hasil uji kelayakan, sistem dinyatakan sangat layak digunakan sebagai solusi otomatisasi rumah berbasis IoT.
Perancangan dan Implementasi Sistem Pembangkitan Kunci Kriptografi Deterministik Berbasis Biometrik Sidik Jari pada Android Imam Faozi; M. Imam Sulistyo Sarjowo; M. Agus Sunandar
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.6953

Abstract

Digital data security on Android platforms relies heavily on cryptography, yet conventional authentication methods such as passwords are increasingly vulnerable to cyberattacks and prone to user forgetfulness. Fingerprint biometric authentication offers a secure alternative, but it faces inherent constraints due to the fuzzy nature of biological data, which is inconsistent with the rigid requirements of deterministic cryptographic keys. Furthermore, modern smartphone sensors have physical limitations, capturing only 10 to 15 percent of the fingerprint area partially. This research aims to design and build a mobile application using the Flutter framework to bridge these biometric reading inconsistencies. The development process utilizes the Waterfall model, including analysis, design, implementation, and testing phases. The system delegates biometric validation to the Android native Trusted Execution Environment (TEE) to ensure data privacy. Upon successful authentication, the system retrieves Helper Data from a cloud database (Supabase) and concatenates it with the user's identity. This combination is then fused using the SHA-256 one-way hash algorithm to generate a private key. Black-Box testing results demonstrate that the system successfully generates a 256-bit private cryptographic key that is 100% consistent for every scan validated by the TEE. This architectural approach effectively overcomes hardware sensor limitations without exposing raw biological data, making it highly reliable as a high-level passwordless security mechanism on mobile devices.

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