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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
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AnoaTIK: Jurnal Teknologi Informasi dan Komputer
Published by Universitas Halu Oleo
ISSN : -     EISSN : 29877652     DOI : https://doi.org/10.33772/anoatik
Core Subject : Science,
Computer Science & IT
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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol 2 No 2 (2024): Desember 2024" : 8 Documents clear
KAMUS BAHASA DAERAH TORAJA – INDONESIA BERBASIS WEB Eko Pasinggi; Gidion Aryo Nugraha Pongdatu
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.60

Abstract

Indonesia is a country rich in linguistic diversity, with thousands of regional languages spread across the archipelago. However, this diversity also brings serious problems, as many of these languages face the risk of extinction or even near extinction. To maintain the survival of a language, the availability of a reference in the form of a dictionary is of key importance. One of the local languages facing such challenges is Toraja. Toraja is one of the local languages in Indonesia that has a rich history and culture. Although there is already a Toraja language dictionary available, the number is limited, which makes it difficult for some people to utilize it. However, with the development of information and communication technology, there is new hope to overcome this challenge. This research aims to develop a prototype of a web-based Toraja language dictionary. The system is designed to provide easier and wider access to the Toraja language dictionary, thus helping to preserve and enrich the language. The test results show that the system has features that function properly and are able to provide accurate translation results. With this web-based Toraja language dictionary prototype, it is hoped that Toraja people and language researchers can easily access information on their language and promote the sustainability of Toraja language.
ANALISIS KLASIFIKASI KEPUASAN MAHASISWA TERHADAP PENYELENGGARAAN PELAYANAN AKADEMIK FMIPA UNIVERSITAS HALU OLEO MENGGUNAKAN ALGORITMA RANDOM FOREST Auni Tiftazani; Andi Tenriawaru; Gusti Arviana Rahman
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.64

Abstract

Student satisfaction with academic services is an important indicator for assessing the performance of higher education institutions. This research aims to measure the level of satisfaction of Halu Oleo University FMIPA students with the academic services provided. It is hoped that the results of this research can help universities improve inadequate services and maintain or improve the quality of services that are already good. This research uses quantitative methods with a survey approach. Data was obtained through a questionnaire filled out by 91 FMIPA students at Halu Oleo University. Data analysis was carried out with the Random Forest algorithm using R Studio software. The analysis process includes data cleaning, dividing data into training data and test data, as well as classification using Random Forest. Model evaluation was carried out with a confusion matrix and k-fold cross-validation to ensure the accuracy and reliability of the classification results. The research results show that the Random Forest algorithm can classify student satisfaction levels with 94% accuracy. The factors that most influence student satisfaction are assurance (guarantee), tangibles (physical evidence), reliability (reliability), responsiveness (responsiveness), and empathy (empathy).
OPTIMALISASI PENGGUNAAN WHATSAPP SEBAGAI ALAT MANAJEMEN KEARSIPAN DI KALANGAN MAHASISWA Mohammad Ricky Ramadhan Rasyid
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.65

Abstract

This study aims to analyze students' perceptions of using WhatsApp as a tool for archival management by applying the Technology Acceptance Model (TAM). The research measures four variables: Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, and Behavioral Intention to Use. A quantitative approach using a survey method was employed, involving 88 students from the Library and Information Science program at Universitas Halu Oleo, class of 2024. The research instrument consisted of a questionnaire utilizing a Likert scale to evaluate students' perceptions of the ease and benefits of using WhatsApp. The findings indicate that the Perceived Usefulness and Perceived Ease of Use variables have an average score of 3.7, categorized as optimal. Meanwhile, the Attitude Toward Using variable achieved a mean of 3.5, also classified as optimal. However, the Behavioral Intention to Use variable showed an average score of 3.4, which has not yet reached the optimal category. Overall, WhatsApp is perceived as a beneficial and easy-to-use tool, though there is room for improvement in fostering a stronger intention to use it consistently.
SISTEM CERDAS IRIGASI MENGGUNAKAN METODE FUZZY LOGIC PADA TANAMAN TOMAT Juliarni Pogasang; Gunawan Gunawan; La Surimi
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.69

Abstract

This study designs an IoT-based intelligent irrigation system using Fuzzy Logic to manage tomato plant watering. The system monitors soil moisture and temperature in real-time, automating irrigation to optimize water usage based on plant needs. Using the Fuzzy Sugeno method, it combines moisture and temperature data to determine watering duration. Key components include sensors, a microcontroller, an IoT module integrated with the Blynk app, and an automatic water pump. Testing shows the system functions effectively, detecting environmental changes with a 0.47% deviation from manual methods and achieving a 99.50% automation success rate.
ANALISIS SENTIMEN APLIKASI PEMINJAMAN ONLINE BERDASARKAN ULASAN PADA PLAY STORE MENGGUNAKAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE (STUDI KASUS : ADAKAMI DAN EASYCASH) La Ode Muhammad Hafidz Abdillah Sam Mongkito; Natalis Ransi; La Surimi; Andi Tenriawaru; Gunawan Gunawan; Budi Wijaya Rauf
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.71

Abstract

This research aims to analyze the sentiment of online lending applications based on reviews on the Google Play Store using the Naïve Bayes and Support Vector Machine methods and determine which online lending applications are more trustworthy. AdaKami is an online lending application under the auspices of PT Pemfinaan Digital Indonesia. EasyCash is an online lending application which is a financial technology company owned by PT. Indonesia Fintopia Technology which provides a digital financial service portal, especially online lending. However, to determine whether this online lending application is reliable or trustworthy, it requires a collection of information that comes from previous user experience. The Naïve Bayes and Support Vector Machine methods are used to analyze loan application sentiment based on relevant review data which is processed using the Python programming language with Google Colabs as a tool for carrying out the research stage. The research results show that the Naïve Bayes and Support Vector Machine methods can be applied in analyzing the sentiment of online lending applications and based on the results of application analysis using the Naïve Bayes Adakami method, it is more trusted by previous users because it produces 95% positive review data and the Easycash application produces positive review data of 95%. 93% and the results using the Adakami Support Vector Machine method produced positive review data of 91% and the Easycash application produced positive review data of 83%.review data while the Easycash application produces 93% positive review data.
ANALISIS PENGGUNAAN APLIKASI E-VOTING PEMIRA UNIVERSITAS HALU OLEO: PERLUASAN TECNOLOGY ACCEPTANCE MODEL DENGAN TRUST IN INTERNET SEBAGAI VARIABEL MODERATOR Fazlul Rachmat Mubbaraq; Natalis Ransi; Ferdinand Murni Hamundu
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.72

Abstract

This study aims to conduct an in-depth analysis of the level of acceptance of the e-voting application in the Halu Oleo University PEMIRA using TAM. This research is a quantitative research, using the SPSS application.The Technology Acceptance Model (TAM) is a framework that can be used to understand user behavior towards technology. TAM is a model that explains how technology users accept and use it. According to this theory, a person's behavior model is influenced by behavioral goals. The attitude towards the behavior determines the purpose of the behavior. In this context, the variables used are perceived usefulness and perceived ease of use, Attitude Toward Using, Behavioural Intension to Use Actual Use and Trust In Internet.  Of the 6 variables, there are 8 hypotheses and of  these 8 hypotheses 7 hypotheses are accepted and the rest are rejected. Based on the results of the analysis, trust in the internet is able to moderate the relationship between perceived usefulness and behavior to use, the contribution of the influence of the PU variable on the BITU variable after the moderation variable is 97.3%.
KLASIFIKASI TINGKAT KEMATANGAN BUAH NAGA KRISTAL BERDASARKAN WARNA KULIT MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS Erick Hernando; Ade Chandra Saputra; Jadiaman Parhusip
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.77

Abstract

This research aims to develop an effective method for determining the maturity level of dragon fruit in the harvestable, ripe, raw classes automatically by utilizing the K-Nearest Neighbors (K-NN) algorithm through the Knowledge Discovery in Databases (KDD) process. The KDD process, which involves a series of steps starting from data selection, data preprocessing, data transformation, to applying algorithms to produce useful knowledge, is used in this research to process and analyze dragon fruit image data. In this research the classification is processed through the KDD stages, including a preprocessing process to clean and prepare the data, the use of Min-Max Normalization to standardize the data so that all features are on the same scale, very important for the performance of the K-NN model, transformation to extract class data, and application of the K-NN algorithm for fruit maturity classification. The selection of the K-NN algorithm in the KDD stage is based on its simplicity and ability to classify data with a high level of accuracy. The research results show that the KDD method applied with the K-NN algorithm is able to classify the ripeness of dragon fruit with the best accuracy obtained at a value of K = 3 with an accuracy percentage of 91% without requiring physical cutting of the fruit. Thus, this research not only contributes to the field of precision agriculture but also shows how the KDD method can be applied effectively to solve real problems in the field.
IDENTIFIKASI TITIK KEPUTUSAN DALAM PROSES BISNIS OTOBUS Ela Ilmatul Hidayah; Aaziza Mun; Muhammad Ainul Yaqin
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.83

Abstract

This study aims to analyze and optimize business processes in bus companies using the ERP (Enterprise Resource Planning) system approach. By employing Business Process Modeling and Notation (BPMN) to map workflows and data-driven analysis to evaluate operational efficiency and customer satisfaction, the study identifies seven key decision points: ticket order validity, seat availability, bus departure scheduling, route planning, invoice creation, maintenance scheduling, and spare parts fulfillment. The implementation of an ERP system with BPMN provides valuable insights and supports process improvements. The study further recommends the development of a more comprehensive ERP system by integrating advanced data analytics and artificial intelligence (AI) to predict operational needs, such as ticket demand, fleet allocation, and route optimization, enhancing both efficiency and responsiveness in customer service. Ultimately, the study concludes that ERP is a strategic solution to sustain and improve the competitiveness of bus companies in the digital era.

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