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FIRMAN TEMPOLA
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Jiko (Jurnal Informatika dan komputer)
Published by Universitas Khairun
ISSN : 26148897     EISSN : 26561948     DOI : -
Core Subject : Science,
Computer Science & IT
Jiko (Jurnal Informatika dan Komputer) Ternate adalah jurnal ilmiah diterbitkan oleh Program Studi Teknik Informatika Universitas Khairun sebagai wadah untuk publikasi atau menyebarluaskan hasil - hasil penelitian dan kajian analisis yang berkaitan dengan bidang Informatika, Ilmu Komputer, Teknologi Informasi, Sistem Informasi dan Sistem Komputer. Jurnal Informatika dan Komputer (JIKO) Ternate terbit 2 (dua) kali dalam setahun pada bulan April dan Oktober
Arjuna Subject : -
Articles 16 Documents
 1   2 
Search results for , issue "Vol 8, No 1 (2025)" : 16 Documents clear
CLASSIFICATION OF BONE FRACTURES IN THE WRIST AND HAND USING DENSENET AND XCEPTION Nusantara, Michelle Swastika Bianglala; Wonohadidjojo, Daniel Martomanggolo
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.9201

Abstract

This study aims to apply Convolutional Neural Network (CNN) using DenseNet and Xception to classify fracture in the wrist and hand bones, while utilizing transfer learning to enhance model's performance. Accurate diagnosis and successful treatment of bone fractures depend on early identification, which lowers the likelihood of long-term issues such avascular necrosis or non-union. The research utilized data from two publicly available musculoskeletal radiography datasets and employed deep learning techniques with the Keras framework. DenseNet was selected for wrist image analysis due to its dense connectivity, which preserves information from previous layers, while Xception was chosen for hand bone image analysis because of its ability to identify complex patterns using depthwise separable convolutions. Transfer learning was implemented to accelerate training and improve accuracy. The DenseNet model achieved a test accuracy of 97.5% for wrist classification, while the Xception model reached 92% accuracy for hand bone classification. By tailoring CNN architectures to specific radiographic images and employing transfer learning, this study demonstrates significant potential for improving diagnostic precision in clinical situations. Furthermore, the findings can support medical personnel in detecting bone fractures more efficiently and accurately, ultimately expediting clinical decision-making and improving patient care.
DESIGN OF VERTICULTURE PLANT MONITORING AND IRRIGATION SYSTEM USING FUZZY LOGIC AND WIRELESS SENSOR NETWORK Ramdana, Ramdana; Irma, Ade; Muhammad, Figur
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.8895

Abstract

Verticulture is a gardening method that addresses land limitations by using a multi-layered vertical planting system. However, there are several issues in verticulture, one of which is providing water based on plant needs. The irrigation of verticulture plants is routinely done every day, either in the morning or during the day. This certainly consumes time and effort for the farmers. Therefore, the objective of this research is to design a monitoring and irrigation system for verticulture plants based on soil moisture sensor data that will be processed using fuzzy logic algorithms and Wireless Sensor Network technology. The result of this research is a system implemented at 16 verticulture planting points. Sixteen sensor nodes successfully read soil moisture data in real time and sent this data to a sink node. The sink node then received and collected the moisture data sent by the sensor nodes. The algorithm used in this system is fuzzy logic, which successfully categorizes the readings from the soil moisture sensors into dry, moist, or wet categories, allowing the system to decide whether to irrigate the plants or not. The monitoring application created successfully displays the soil moisture sensor data as a percentage (%).
DEVELOPMENT OF A BUGIS LANGUAGE DICTIONARY APPLICATION WITH SM-KMP ALGORITHM FOR STUDENTS IN SOUTH SULAWESI M, Effendi; Juhardi, Juhardi; Ahmad, Muhammad Sabri; Zainuddin, Zainuddin
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.8822

Abstract

The decline in the use of the Bugis language among younger generations in South Sulawesi poses a significant challenge in preserving local languages and cultures. One solution to this issue is developing a Bugis language dictionary application based on technology, which can interactively facilitate language learning. This study aims to develop a Bugis language dictionary application using the Knuth-Morris-Pratt (SM-KMP) algorithm to improve the efficiency of word searches within the dictionary. The research method involves application development with a prototype tested in South Sulawesi schools. This application is designed with features for fast and accurate word searches and interactive elements such as quizzes and educational games to enhance student motivation in learning the Bugis language. The results show that the application improved students' vocabulary comprehension by 85%, and 90% reported increased motivation to learn Bugis due to the interactive features. The application also supports preserving local culture by integrating character education that teaches ethical values and local wisdom in Bugis. In conclusion, this Bugis language dictionary application based on the SM-KMP algorithm is practical as an interactive learning tool. It holds significant potential in preserving the Bugis language and culture
EVALUATING POST-DIVORCE WOMEN'S AND CHILDREN'S RIGHTS FUNDING APPLICATION USING OWASP TOP TEN AND ISO 25010:2023 Oktariani, Deta; Utami, Ema
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.9490

Abstract

Evaluating an information system from both performance and security aspects is crucial for anticipating and improving the quality of the information system. A High Religious Court in collaboration with the Provincial Government developed a web-based application to support one of its services, to monitor court decisions regarding alimony payments from former husbands to former wives and children in divorce cases involving civil servants. This is certainly very important because before the existence of this application, there were many complaints filed due to the non-payment of alimony. To ensure that the application runs in accordance with its purpose and that the data is secure, a comprehensive system evaluation is required. The main objective of this evaluation is to identify vulnerabilities and their mitigations, as well as to ensure that the functions in the application work as expected, so that the application's goals are achieved. To achieve this goal, this study uses the ISO 25010:2023 information system standard integrated with OWASP Top Ten to evaluate its security This study uses five ISO 25010:2023 characteristics selected according to the system's goals. The results show that the combination of ISO 25010:2023 and OWASP Top Ten effectively identifies vulnerabilities in the application's functions and security comprehensively. Overall, the functions in the application have run as expected, although there are still several things that need to be improved to enhance the quality and secure its data.
SMART WATER PUMP DESIGN USING DECISION TREE FOR IOT-BASED AUTOMATIC FRUIT PLANT IRRIGATION Muhammad, Figur; Ramdana, Ramdana
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.8893

Abstract

The continuous growth of the population each year increases the demand for adequate food supplies, while land for cultivation is becoming more limited. One solution to this issue is the technique of growing fruit in pots (tabulampot). Irrigating potted plants is a crucial maintenance stage, where deficit irrigation can help manage fruit quality. However, manual watering by farmers is time-consuming and labor-intensive, necessitating an automation system. This research aims to design and build a smart water pump system based on the Internet of Things (IoT) using a Decision Tree algorithm to monitor and irrigate potted fruit plants. The designed system can irrigate plants based on predetermined times and soil moisture conditions. Utilizing IoT technology, this system can be accessed and controlled via smartphone. The research results indicate that the system operates automatically, with the ability to monitor soil moisture and irrigate based on real-time sensor data. The implementation of this system is expected to enhance the efficiency of potted plant care and reduce farmers' workload.
QUALITY MANAGEMENT OF INFORMATION TECHNOLOGY GOVERNANCE COBIT 2019 FRAMEWORK EDUCATION FACTORS IN INDONESIA: A REVIEW Prasetya, Bismar Rifki wahyu; Muhammad, Alva Hendi
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.9498

Abstract

This study examines information technology (IT) governance in Indonesia's education sector using the COBIT 2019 framework through a systematic literature review (SLR) approach. COBIT 2019 is a globally recognized framework designed to help organizations manage IT effectively by integrating quality management principles to achieve strategic objectives. In the education sector, implementing robust IT governance is crucial to supporting ongoing digital transformation efforts. The SLR process involved identifying, selecting, and analyzing relevant literature to assess the implementation of COBIT 2019 in the Indonesian education sector. The findings indicate that this framework can enhance IT governance quality, particularly in risk management, resource efficiency, and operational sustainability. However, challenges persist, including limited managerial understanding, shortages of skilled human resources, and inadequate infrastructure support. To address these challenges, collaboration among the government, educational institutions, and the private sector is essential. Additionally, continuous training programs are necessary to enhance the competencies of management and IT personnel in effectively implementing COBIT 2019. The study underscores the importance of integrating technological and educational aspects to improve service quality in the education sector. Furthermore, the COBIT 2019 framework is recognized as a valuable tool for fostering collaboration among stakeholders to achieve sustainable education development in Indonesia.
INTERACTIVE MOBILE-BASED EDUCATIONAL GAME TO INTRODUCE WASTE SORTING USING MULTIMEDIA DEVELOPMENT LIFE CYCLE (MDLC) METHOD Pradhana, Faisal Reza; Musthafa, Aziz; Permadani, Agustin Amalia
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.9151

Abstract

Increasing public awareness of waste management is an important focus in order to maintain environmental sustainability. However, the level of understanding about waste sorting is still minimal, especially among children. To overcome this lack of literacy, a technology-based educational game was developed which aims to introduce the concept of waste sorting to children. This research aims to design and develop an interactive and fun educational game application to improve children's understanding of the importance of waste management. Using iterative development techniques, this app is designed to provide an effective learning experience and support the formation of positive habits from an early age. The application is designed following the stages of the Media Development Life Cycle (MDLC) method. The game media has gone through several tests, namely software functionality tests with 100% results, learning material tests by distributing questionnaires to material experts with an average rating of 90%, tests to learning media experts with an average rating of 93.33%, and tests to potential users with an average rating of 78.57%. The results of the research are expected to contribute significantly to educating the younger generation, especially children, about the importance of maintaining environmental cleanliness through wise waste management. This application is expected to be an innovative learning tool that supports environmental sustainability.
CLASSIFICATION OF BEEF FRESHNESS LEVELS BASED ON IMAGE USING CONVOLUTIONAL NEURAL NETWORK Anshori, M Subhan; Putra, Fatra Nonggala; Lestariningsih, Lestariningsih
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.9519

Abstract

Beef is an essential food commodity with high economic value and a primary source of protein for society. The quality of beef affects consumer preferences, pricing, and market competitiveness. Quality assessment is generally conducted manually through visual inspection and smell, but this method is subjective and time-consuming and requires trained experts. This study aims to design and develop a beef quality classification system using a Convolutional Neural Network (CNN) model based on digital imagery. The dataset used consists of three beef quality categories: Grade 1 (fresh beef), Grade 2 (beef stored at room temperature for 7-14 hours), and Grade 3 (beef stored at room temperature for more than 14 hours). The dataset includes 180 images processed using cropping, resizing, and data augmentation techniques to enhance model variation and accuracy. The CNN architecture employs four convolutional layers with max pooling, followed by dropout and fully connected layers. The model was trained using the Adam optimizer, with a training-to-test data ratio of 80:20. Evaluation results demonstrated the model achieved an accuracy of 97.22%, with precision, recall, and f1-score values of 97.44%, 97.22%, and 97.22%, respectively. These findings suggest that the developed system has the potential to be used as an automatic tool for objective, fast, and accurate beef quality assessment.
CLASSIFICATION OF BEEF FRESHNESS LEVELS BASED ON IMAGE USING CONVOLUTIONAL NEURAL NETWORK Anshori, M Subhan; Putra, Fatra Nonggala; Lestariningsih, Lestariningsih
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.9519

Abstract

Beef is an essential food commodity with high economic value and a primary source of protein for society. The quality of beef affects consumer preferences, pricing, and market competitiveness. Quality assessment is generally conducted manually through visual inspection and smell, but this method is subjective and time-consuming and requires trained experts. This study aims to design and develop a beef quality classification system using a Convolutional Neural Network (CNN) model based on digital imagery. The dataset used consists of three beef quality categories: Grade 1 (fresh beef), Grade 2 (beef stored at room temperature for 7-14 hours), and Grade 3 (beef stored at room temperature for more than 14 hours). The dataset includes 180 images processed using cropping, resizing, and data augmentation techniques to enhance model variation and accuracy. The CNN architecture employs four convolutional layers with max pooling, followed by dropout and fully connected layers. The model was trained using the Adam optimizer, with a training-to-test data ratio of 80:20. Evaluation results demonstrated the model achieved an accuracy of 97.22%, with precision, recall, and f1-score values of 97.44%, 97.22%, and 97.22%, respectively. These findings suggest that the developed system has the potential to be used as an automatic tool for objective, fast, and accurate beef quality assessment.
SMART WATER PUMP DESIGN USING DECISION TREE FOR IOT-BASED AUTOMATIC FRUIT PLANT IRRIGATION Muhammad, Figur; Ramdana, Ramdana
JIKO (Jurnal Informatika dan Komputer) Vol 8, No 1 (2025)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v8i1.8893

Abstract

The continuous growth of the population each year increases the demand for adequate food supplies, while land for cultivation is becoming more limited. One solution to this issue is the technique of growing fruit in pots (tabulampot). Irrigating potted plants is a crucial maintenance stage, where deficit irrigation can help manage fruit quality. However, manual watering by farmers is time-consuming and labor-intensive, necessitating an automation system. This research aims to design and build a smart water pump system based on the Internet of Things (IoT) using a Decision Tree algorithm to monitor and irrigate potted fruit plants. The designed system can irrigate plants based on predetermined times and soil moisture conditions. Utilizing IoT technology, this system can be accessed and controlled via smartphone. The research results indicate that the system operates automatically, with the ability to monitor soil moisture and irrigate based on real-time sensor data. The implementation of this system is expected to enhance the efficiency of potted plant care and reduce farmers' workload.

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