cover
Contact Name
Gunawan
Contact Email
gunawan@uho.ac.id
Phone
-
Journal Mail Official
anoatik@uho.ac.id
Editorial Address
Program Studi Ilmu Komputer Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Halu Oleo Kampus Hijau Bumi Tridharma Jalan H. E. A. Mokodompit, Anduonohu Kendari, Sulawesi Tenggara - Indonesia 93232
Location
Kota kendari,
Sulawesi tenggara
INDONESIA
AnoaTIK: Jurnal Teknologi Informasi dan Komputer
Published by Universitas Halu Oleo
ISSN : -     EISSN : 29877652     DOI : https://doi.org/10.33772/anoatik
Core Subject : Science,
AnoaTIK: Jurnal Teknologi Informasi dan Komputer (eISSN 2987-7652) merupakan salah satu jurnal yang dikelola oleh program studi Ilmu Komputer pada Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Halu Oleo. Terbit 2 (dua) kali dalam setahun pada bulan Juni dan Desember sebagai salah satu wadah publikasi ilmiah pada bidang teknologi informasi dan ilmu komputer berbahasa Indonesia.
Articles 45 Documents
ARSITEKTUR BISNIS PERUSAHAAN OTOBIS Intan Nurhidayah; Isma Izha Utama; Muhammad Ainul Yaqin
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 1 (2025): Juni 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i1.85

Abstract

Transportasi umum memegang peranan penting dalam mendukung mobilitas dan aktivitas ekonomi di berbagai wilayah. Perusahaan otobus, sebagai komponen utama transportasi umum, menghadapi tantangan besar di era kemajuan teknologi dan perubahan preferensi konsumen. Penelitian ini bertujuan untuk merancang arsitektur bisnis terintegrasi bagi perusahaan otobus dengan menggunakan kerangka Business Model Canvas (BMC) yang didukung modul-modul Enterprise Resource Planning (ERP). Melalui pendekatan deskriptif-kualitatif, modul ERP utama seperti Sales and Distribution, Production Planning, Materials Management, Financial Accounting, dan Human Capital Management dipetakan ke elemen-elemen BMC. Hasil penelitian menunjukkan bahwa integrasi modul ERP ke dalam kerangka BMC meningkatkan efisiensi operasional, pengendalian biaya, dan pengelolaan hubungan pelanggan. Penelitian ini menyimpulkan bahwa penerapan arsitektur bisnis berbasis ERP memungkinkan perusahaan otobus meningkatkan daya saing, adaptasi terhadap dinamika pasar, serta mendukung tujuan keberlanjutan.
IMPLEMENTASI FINITE STATE AUTOMATA UNTUK OPTIMALISASI PROSES DISTRIBUSI DAUR ULANG SAMPAH Tyas Nur Taufiq; Sulthon Syahril Oku; Ryan Ari Setyawan
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 1 (2025): Juni 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i1.100

Abstract

Effective waste management is a significant challenge in efforts to create a sustainable environment. One crucial step in waste management is the recycling process, which requires an efficient and accurate sorting system. This study aims to implement Finite State Automata (FSA) as a modeling method to optimize the waste recycling process. FSA is used to model the waste sorting flow based on categories such as organic, inorganic, and hazardous materials. This model is designed to improve the speed and accuracy of identifying waste types suitable for recycling.
ANALISIS PERBANDINGAN ANTARA FRAMEWORK FLUTTER DENGAN NATIVE UNTUK PENGEMBANGAN APLIKASI MOBILE ABSENSI FACE RECOGNITION Adhy Rizaldy; Nur Farid Mufid NR
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 1 (2025): Juni 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i1.103

Abstract

Penelitian ini membandingkan performa antara framework Flutter dan pengembangan native dalam pembuatan aplikasi absensi berbasis face recognition. Dua prototipe aplikasi dengan fitur yang sama dikembangkan menggunakan kedua pendekatan tersebut, diikuti dengan pengujian performa yang mencakup kecepatan request data, penggunaan CPU dan RAM, serta kecepatan kompilasi file .apk. Metodologi yang digunakan adalah pendekatan komparatif dengan metode Rapid Application Development (RAD). Data pengujian performa dianalisis untuk mengidentifikasi perbedaan antara kedua pendekatan tersebut. Hasil penelitian menunjukkan bahwa pengembangan aplikasi dengan pendekatan native memiliki performa yang lebih baik dalam segala aspek yang diuji, yakni kecepatan request data, penggunaan CPU dan RAM, serta kecepatan kompilasi file .apk. Implikasi penelitian ini memberikan panduan bagi pengembang aplikasi dalam memilih antara Flutter dan pengembangan native, terutama untuk aplikasi yang membutuhkan performa tinggi dan efisiensi penggunaan sumber daya. Penelitian ini juga berkontribusi pada literatur teknologi, memberikan pemahaman yang lebih mendalam tentang kelebihan dan kekurangan masing-masing framework. Selain itu, membuka peluang untuk studi lebih lanjut mengenai optimalisasi pengembangan aplikasi mobile.
IMPLEMENTASI ALGORITMA KRIPTOGRAFI BLOWFISH UNTUK PENGAMANAN FILE BERBASIS DESKTOP Winda; La Surimi; Ilham Julian Efendi
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 1 (2025): Juni 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i1.108

Abstract

This research aims to implement the Blowfish cryptographic algorithm in a desktop-based file security application, to enhance user data confidentiality and security. Blowfish, as a symmetric block cipher, was chosen for its effectiveness in encrypting 64-bit data through 16 rounds of the Feistel function. The encryption process involves the use of P-array and S-box tables, as well as XOR and modulo 2^32 addition operations. The developed application supports various file formats, including PDF, TXT, JPG, PNG, MP3, and MP4, with a maximum size limit of 50 MB. The research methodology uses Rapid Application Development (RAD) to accelerate the development cycle, with stages including user requirements planning, design, iterative development, and testing. White box testing is applied to verify the implementation of the Blowfish algorithm and application functionality. Avalanche effect analysis is performed to evaluate the algorithm's sensitivity to small changes in input, ensuring robust data security. The test results show that the Blowfish algorithm was successfully implemented, with each application function running as expected. The avalanche effect proves that small changes in input produce significant changes in the encryption output, indicating a high level of security. This application is designed to operate offline and has a user-friendly interface, making it accessible to users with various levels of technical expertise.
IMPLEMENTASI ALGORITMA LONG SHORT-TERM MEMORY PADA SISTEM KLASIFIKASI MAHASISWA BERPOTENSI DROP OUT Niken Mutiara; La Ode Saidi; Budi Wijaya Rauf
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 1 (2025): Juni 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i1.109

Abstract

This research aims to produce a classification system for students who have the potential to drop out. This classification system is expected to help identify students who have the potential to drop out early on in prevention efforts. This research uses academic data in the form of Semester Grade Point Average (IPS) 1-7, Cumulative Grade Point Average Semester 7 (IPKS7), and Cumulative SKS 7, as well as non-academic data including Study Program and Entry Path as classification parameters. The method used is the Long Short-Term Memory (LSTM) algorithm with system development using the CRISP-DM approach. System testing is done using black box testing method and performance evaluation using confusion matrix. The results showed that the classification system developed achieved an accuracy rate of 93% based on confusion matrix evaluation, and all system functionality runs as expected based on the results of black box testing.
IMPLEMENTASI MODEL TRANSFER LEARNING PADA KLASIFIKASI KESEHATAN TERUMBU KARANG BERBASIS CITRA DIGITAL Azeslim Azeslim; Andi Tenriawaru; Gunawan
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 1 (2025): Juni 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i1.110

Abstract

Coral reefs are marine ecosystems that are highly vulnerable to damage and require regular monitoring of their health conditions. However, the manual classification process of coral reef health tends to be time-consuming. Therefore, this research aims to develop an application that implements a transfer learning model for classifying coral reef health based on digital images. This study utilizes three pretrained model architectures: DenseNet121, MobileNetV2, and EfficientNet-B0. Each model is trained and evaluated to measure its performance in classifying coral reef images. The best-performing model, DenseNet121, is then integrated into a mobile application for real-time classification. The evaluation results show that DenseNet121 achieved the highest accuracy compared to MobileNetV2 and EfficientNet-B0. The training data accuracy of DenseNet121 reached 98.80%, and the testing data accuracy was 98.25%.
ANALISIS FAKTOR KUALITAS PELAYANAN UPA PERPUSTAKAAN UNIVERSITAS HALU OLEO DENGAN METODE SEM-LISREL Mohammad Ricky Ramadhan Rasyid
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 2 (2025): Desember 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i2.114

Abstract

This study aims to analyze the factors influencing service quality at the Library of Halu Oleo University by employing the Structural Equation Modeling (SEM) method supported by LISREL 8.80 software. The variables examined include service quality (X1) and library facilities (X2) as exogenous variables, as well as perceived quality (Y) as the endogenous variable. Data were collected through questionnaires distributed to 100 library users from various faculties and academic years who visited the library. Each indicator was measured using a five-point Likert scale. The data were analyzed through several stages, including tests of normality, validity, reliability, measurement model estimation, and structural model evaluation. The results of the validity and reliability tests showed that the indicators used met the required criteria for loading factor, t-value, Construct Reliability (CR), and Variance Extracted (VE). The structural model analysis revealed that service quality had a positive and significant effect on perceived quality, with a coefficient of 0.78. Meanwhile, library facilities also had a positive and significant effect, with a coefficient of 0.29. The R² value of 0.89 indicates that 89% of the variance in perceived quality can be explained by these two variables. This study demonstrates that service quality plays the most dominant role in enhancing users’ perceptions of library service quality, followed by library facilities. These findings emphasize the importance of improving service performance and managing library facilities effectively to create an optimal service experience for users
IMPLEMENTASI MODEL LONG SHORT-TERM MEMORY PADA PREDIKSI HARGA SAHAM BERBASIS WEB Fadhillah Muslimin; Andi Tenriawaru; Muhammad Riansyah Tohamba
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 2 (2025): Desember 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i2.116

Abstract

This study aims to develop a web-based stock price prediction system using the Long Short-Term Memory (LSTM) algorithm to forecast the highest and lowest prices of stocks listed in the LQ45 index. LSTM was chosen for its ability to recognize long-term patterns in time series data and its more stable performance compared to methods such as ARIMA and GRU. The system features an interactive interface and user activity logging to enhance usability and user experience. Evaluation results show that the LSTM model performs well, with MAPE below 3% and RMSE values varying according to stock volatility. The best results were achieved by ACES, with RMSE values of 28,772 (High) and 27,142 (Low), and MAPE of 2,19% and 2,2%, while AMMN had the highest error rates with RMSE values of 247,154 and 281,926, and MAPE of 2,42% and 2,79%. The system successfully delivers real-time predictions through a responsive and user-friendly web interface.
KLASIFIKASI STATUS GIZI BAYI MENGGUNAKAN METODE K-NEAREST NEIGHBOR Sri Ayu Lestari; Natalis Ransi; Muhammad Arfan
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 2 (2025): Desember 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i2.117

Abstract

The development of a baby nutritional status classification system was carried out by applying the K-Nearest Neighbor (KNN) method with the aim of supporting more accurate monitoring of infant growth and development. The system determines the nutritional status of infants based on input data including age, weight, height, and mid-upper arm circumference, which are then compared with available training data. The system development process employed the waterfall approach, encompassing requirements analysis, system design, implementation, and testing stages. Testing was conducted using black box testing to ensure that all system functions operated according to requirements, as well as a confusion matrix to measure classification accuracy. The results showed that all system features functioned properly and the achieved accuracy rate reached 97.30%, indicating that the system has very good performance in effectively supporting the monitoring of infant nutritional status.
DESAIN DAN IMPLEMENTASI APLIKASI SIMULASI TOEFL MENGGUNAKAN ALGORITA RANDOM NUMBER GENERATOR BERBASIS WEB Muh Istikmal Husain; Gunawan; Budi Wijaya Rauf
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 2 (2025): Desember 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i2.120

Abstract

This research aims to develop a web-based TOEFL simulation application system using the RNG algorithm to randomize questions. The study was conducted using three different scenarios for different test types (listening, reading, and structure). The first scenario involved 10 trials for each test type to test the consistency and randomness of the algorithm used. The second test scenario was conducted to assess the quality of randomization when there was a large amount of data in the question bank stored in the database. The third test scenario was conducted to examine the results of randomization when there were two users with the same access time but different user IDs. The randomization process was carried out through a previously designed web application and used the MCG equation, one of the methods in the RNG algorithm. The results of the research conducted indicate that the use of the RNG algorithm using the MCG method can be applied well to the TOEFL simulation system. For example, the results of the first scenario test showed that in each trial, the resulting question order was different. For example, in the structure test, a question with a certain number may appear in position 18 on the first trial, but in subsequent trials it may shift to position 27 or 32; The test results also found that even though both users had the same access time, differences in User ID values caused different initial seed values. This small difference in seed values resulted in a significantly different question order.