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semanTIK
Published by Universitas Halu Oleo
ISSN : 24601446     EISSN : 25028928     DOI : http://dx.doi.org/10.55679/semantik.v8i1
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Jurnal semanTIK is a is one of the media publication of research results in the field of information technology. semanTIK is published Biannually, January-June and July-December and provide scientific publication medium for researchers, engineers, practitioners, academicians, and observers in the field related to semanTIK Focus & Scope. This journal accepts original papers, review articles, case studies, and short communications. The articles published are peer-reviewed by one or two reviewers and cover various Informatics subjects related to the field journal include Software Engineering, Computer Networking, Intelligent Systems, Information Systems, Robotics, Computational Science, Geographic Information Systems, and all topics which related to informatics. The targets in publishing this journal are Lecturers, Students, and Researchers in IT. The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except as part of a lecture, review.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 64 Documents
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Perbandingan Clustering Berbasis RFM dan Implementasi K-Means untuk Segementasi Pelanggan Bisnis Laundry Nibertin Zai; Audy Aldrin Kenap; Alfiansyah Hasibuan
SemanTIK : Teknik Informasi Vol. 12 No. 1 (2026): Volume 12 Number 1 (January-june 2026)
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v12i1.275

Abstract

Bisnis laundry seperti Anty Laundry masih mengelola program loyalitas secara manual hanya mengandalkan frekuensi transaksi untuk menentukan pelanggan prioritas tanpa mempertimbangkan kebaruan dan nilai transaksi sehingga strategi pemasaran menjadi tidak tepat sasaran dan potensi retensi pelanggan bernilai tinggi tidak optimal. Penelitian ini membandingkan tiga metode clustering (K-Means, K-Medoids, dan Hierarchical Clustering) untuk segmentasi pelanggan prioritas berbasis analisis Recency, Frequency, dan Monetary (RFM), sekaligus mengimplementasikan metode terbaik dalam sistem informasi berbasis web. Data penelitian terdiri dari 2.549 transaksi valid dari 203 pelanggan unik periode Oktober 2024–Oktober 2025. StandardScaler digunakan untuk normalisasi data dan metode elbow menentukan jumlah cluster optimal (k=5). Evaluasi menggunakan Silhouette Score, Davies-Bouldin Index, dan Calinski-Harabasz Index menunjukkan K-Means mencapai hasil terbaik dengan nilai 0.5440, 0.5005, dan 282.18, mengungguli K-Medoids (0.4790, 0.7034, 145.52) dan Hierarchical Clustering (0.5141, 0.5239, 251.73). Lima segmen pelanggan teridentifikasi: Inactive Customer (36.95%), Regular Customer (49.75%), High Value Customer (11.82%), VIP Customer (0.99%), dan Top Spender (0.49%). K-Means diimplementasikan menggunakan Streamlit dengan segmentasi otomatis dan kemampuan ekspor untuk mendukung strategi pemasaran tepat sasaran per segmen. Laundry businesses such as Anty Laundry still manage loyalty programs manually — relying solely on transaction frequency to determine priority customers without considering recency and monetary value — resulting in poorly targeted marketing strategies and suboptimal retention of high-value customers. This study compares three clustering methods (K-Means, K-Medoids, and Hierarchical Clustering) for priority customer segmentation based on Recency, Frequency, and Monetary (RFM) analysis, while implementing the best-performing method in a web-based information system. The dataset consisted of 2,549 valid transactions from 203 unique customers covering October 2024 to October 2025. StandardScaler was applied for data normalization and the elbow method determined the optimal cluster number (k=5). Evaluation using Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index showed K-Means achieved the best results with values of 0.5440, 0.5005, and 282.18, outperforming K-Medoids (0.4790, 0.7034, 145.52) and Hierarchical Clustering (0.5141, 0.5239, 251.73). Five customer segments were identified: Inactive Customers (36.95%), Regular Customers (49.75%), High Value Customers (11.82%), VIP Customers (0.99%), and Top Spenders (0.49%). K-Means was implemented using Streamlit with automatic segmentation and export capabilities to support targeted marketing strategies for each segment.
Implementasi Algoritma FSM pada Digitalisasi Pengajuan Kenaikan Pangkat dan Jabatan: Studi Kasus : Universitas Negeri Manado (UNIMA) Syalomita Cinta; Kristofel Santa; Glenn Maramis
SemanTIK : Teknik Informasi Vol. 12 No. 1 (2026): Volume 12 Number 1 (January-june 2026)
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v12i1.278

Abstract

Pengajuan kenaikan pangkat dan jabatan bagi karyawan dan dosen di Universitas Negeri Manado masih dilakukan secara manual, sehingga menyebabkan proses administrasi berjalan lambat, kurang transparan, dan berpotensi menimbulkan kesalahan. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pengajuan digital dengan pendekatan algoritma Finite State Machine (FSM) sebagai pengendali alur proses. FSM digunakan untuk memodelkan tahapan pengajuan ke dalam sejumlah state yang terdefinisi secara formal, yaitu diajukan, disetujui unit kerja, disetujui kepegawaian dan ditolak, beserta event dan fungsi transisi yang merepresentasikan perpindahan status secara terstruktur dan terkontrol. Metode penelitian meliputi analisis kebutuhan, perancangan model FSM, implementasi sistem berbasis web, serta pengujian yang mencakup Black Box Testing dan validitas transisi FSM. Hasil penelitian menunjukkan bahwa pemodelan FSM mampu mengontrol alur pengajuan secara konsisten, mengurangi potensi kesalahan proses, serta meningkatkan transparansi dan keterlacakan status pengajuan secara real-time. Selain itu, sistem yang dikembangkan menunjukkan kemampuan dalam menyederhanakan alur administrasi melalui pengelolaan status yang terstruktur. Dengan demikian, penerapan FSM memberikan kontribusi dalam mendukung keteraturan alur proses serta menunjukkan potensi peningkatan efisiensi dalam pengelolaan kepegawaian di lingkungan universitas.  The promotion and position advancement process for employees and lecturers at Universitas Negeri Manado is still conducted manually, resulting in slow administrative processes, lack of transparency, and a higher potential for errors. This study aims to design and implement a digital submission system using the Finite State Machine (FSM) algorithm as the core mechanism for controlling the process flow. FSM is employed to model the submission stages into formally defined states, namely submitted, approved by the work unit, approved by the UNIMA personnel office, and rejected, along with events and transition functions that represent structured and controlled status changes. The research method includes requirement analysis, FSM model design, web-based system implementation, and system testing through Black Box Testing and FSM transition validity testing. The results indicate that the FSM model is capable of controlling the submission process consistently, reducing potential process errors, and improving transparency as well as real-time tracking of submission status. Furthermore, the developed system demonstrates the capability to simplify administrative workflows through structured state management. Thus, the implementation of the FSM contributes to improving the structure of process workflows and demonstrates the potential to enhance efficiency in personnel management within the university environment.
Perbandingan Performa Enkripsi Hybrid AES-RSA Berdasarkan Ukuran File pada WSL dan VirtualBox Almon Lanang Prasojo Prasojo; Danur Wijayanto
SemanTIK : Teknik Informasi Vol. 12 No. 1 (2026): Volume 12 Number 1 (January-june 2026)
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v12i1.280

Abstract

Keamanan data digital merupakan aspek fundamental di tengah meningkatnya intensitas pertukaran informasi melalui jaringan internet. Pendekatan enkripsi hybrid yang mengombinasikan algoritma simetris dan asimetris digunakan untuk menjaga kerahasiaan serta integritas data. Penelitian ini menganalisis performa implementasi enkripsi hybrid Advanced Encryption Standard (AES) mode Cipher Block Chaining (CBC) dan Rivest Shamir Adleman (RSA) 2048 bit pada lingkungan sistem operasi Linux. Evaluasi dilakukan dengan membandingkan kinerja Windows Subsystem for Linux (WSL) dan VirtualBox melalui pengujian proses enkripsi dan dekripsi file berukuran 10 MB hingga 1000 MB. Parameter yang diukur meliputi waktu enkripsi, waktu dekripsi, penggunaan CPU, serta validasi integritas data menggunakan algoritma hash SHA-256. Hasil pengujian menunjukkan bahwa WSL cenderung memberikan performa yang lebih stabil dan optimal dibandingkan VirtualBox, terutama pada beban data kecil hingga menengah, yang dipengaruhi oleh overhead virtualisasi yang lebih rendah. Pada proses enkripsi file berukuran 750 MB, WSL mencatat waktu 5,74 detik, lebih cepat dibandingkan VirtualBox sebesar 6,99 detik. Sebaliknya, pada proses dekripsi file berukuran 1000 MB, VirtualBox menunjukkan waktu yang lebih cepat, yaitu 4,82 detik dibandingkan WSL sebesar 6,31 detik, yang mengindikasikan adanya bottleneck sistem pada skenario tertentu. Validasi hash SHA-256 membuktikan bahwa integritas data tetap terjaga pada seluruh skenario pengujian. Berdasarkan hasil pengujian, semakin besar ukuran file, semakin lama waktu yang diperlukan untuk proses enkripsi pada platform WSL dan VirtualBox. Digital data security is a fundamental aspect amid the increasing intensity of information exchange via the internet. A hybrid encryption approach that combines symmetric and asymmetric algorithms is used to maintain data confidentiality and integrity. This study analyzes the performance of the implementation of hybrid encryption Advanced Encryption Standard (AES) Cipher Block Chaining (CBC) mode and Rivest Shamir Adleman (RSA) 2048 bits in a Linux operating system environment. The evaluation was conducted by comparing the performance of Windows Subsystem for Linux (WSL) and VirtualBox through testing the encryption and decryption processes of files ranging in size from 10 MB to 1000 MB. The parameters measured included encryption time, decryption time, CPU usage, and data integrity validation using the SHA-256 hash algorithm. The test results show that WSL tends to provide more stable and optimal performance compared to VirtualBox, especially with small to medium data loads, which is influenced by lower virtualization overhead. In the process of encrypting a 750 MB file, WSL recorded a time of 5.74 seconds, which is faster than VirtualBox at 6.99 seconds. Conversely, in the process of decrypting a 1000 MB file, VirtualBox showed a faster time of 4.82 seconds compared to WSL's 6.31 seconds, indicating a system bottleneck in certain scenarios. SHA-256 hash validation confirmed that data integrity was maintained across all test scenarios. Based on the test results, the larger the file size, the longer the encryption process takes on the WSL and VirtualBox platforms.
Analisis Sentimen dan Rating Pengguna Aplikasi Traveloka Menggunakan Vader Syarifah Ifah; Herny Februariyanti
SemanTIK : Teknik Informasi Vol. 12 No. 1 (2026): Volume 12 Number 1 (January-june 2026)
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v12i1.285

Abstract

Pesatnya perkembangan teknologi sangat berdampak besar pada platform layanan perjalanan digital, seperti aplikasi Traveloka. Hal ini terlihat dari peningkatan jumlah pengguna yang membawa tantangan tersendiri dalam mempertahankan pangsa pasar. Ulasan dan rating di Google Play Store menjadi indikator penting yang menunjukkan tingkat kepuasan dan penilaian pengguna terhadap kualitas layanan aplikasi. Tanpa analisis sistematis, Traveloka berisiko kehilangan daya saing karena rating rendah. Namun, volume data yang sangat besar menyebabkan evaluasi manual menjadi tidak efisien dan sulit dilakukan secara menyeluruh. Oleh karena itu, penelitian ini dilakukan untuk menganalisis sentimen pengguna aplikasi Traveloka menggunakan metode Valence Aware Dictionary and sEntiment Reasoner (VADER) dengan pendekatan kuantitatif deskriptif dan inferensial. Data penelitian berupa teks ulasan dan rating pengguna dikumpulkan dari Google Play Store menggunakan teknik web scraping. Tahapan penelitian meliputi pengumpulan data, text preprocessing, analisis sentimen dengan VADER, dan uji hubungan antara keduanya menggunakan uji Chi-Square. Hasil penelitian menunjukkan bahwa ulasan pengguna Traveloka didominasi oleh sentimen positif yang sesuai dengan pemberian rating tinggi pada aplikasi. Meskipun demikian, sentimen negatif juga ditemukan terkait dengan masalah teknis dan layanan pelanggan. Penelitian ini diharapkan mampu memberikan gambaran objektif tentang persepsi pengguna terhadap aplikasi Traveloka dan dapat dijadikan bahan evaluasi peningkatan kualitas layanan aplikasi bagi pengembang. The rapid development of technology has significantly affected digital travel service platforms, including the Traveloka application. This development is reflected in the growing number of users, which creates challenges in maintaining market competitiveness. User reviews and ratings on the Google Play Store serve as key indicators of user satisfaction and service quality. Without systematic analysis, Traveloka risks losing its competitive position due to unfavorable ratings. However, the large volume of review data makes manual evaluation inefficient. Therefore, this study aims to analyze user sentiment toward the Traveloka application using the Valence Aware Dictionary and sEntiment Reasoner (VADER) method with a descriptive and inferential quantitative approach. The data consist of user reviews and ratings collected from the Google Play Store through web scraping. The research process includes data collection, text preprocessing, sentiment analysis using VADER, and examination of the relationship between sentiment and ratings using the chi-square test. The results indicate that positive sentiment dominates user reviews and is associated with high application ratings, while negative sentiment mainly relates to technical issues and customer service. This study provides an objective overview of user perceptions of the Traveloka application and may serve as a reference for developers in improving application service quality.

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