IJISTECH
IJISTECH (International Journal of Information System & Technology) has changed the number of publications to six times a year from volume 5, number 1, 2021 (June, August, October, December, February, and April) and has made modifications to administrative data on the URL LIPI Page: http://u.lipi.go.id/1492681220 IJISTECH (International Journal Of Information System & Technology) is a peer-reviewed open-access journal published two times a year in English-language, provides scientists and engineers throughout the world for the exchange and dissemination of theoretical and practice-oriented papers dealing with advances in intelligent informatics. All the papers are refereed by two international reviewers, accepted papers will be available online (free access), and no publication fee for authors. The articles of IJISTECH will be available online in the GOOGLE Scholar. IJISTECH (International Journal Of Information System & Technology) is published with both online and print versions. The journal covers the frontier issues in computer science and their applications in business, industry, and other subjects. Computer science is a branch of engineering science that studies computable processes and structures. It contains theories for understanding computing systems and methods; computational algorithms and tools; methodologies for testing of concepts. The subjects covered by the journal include artificial intelligence, bioinformatics, computational statistics, database, data mining, financial engineering, hardware systems, imaging engineering, internet computing, networking, scientific computing, software engineering, and their applications, etc. • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Autonomous Agents and Multi-Agent Systems • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Cognitive systems • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, fault analysis, and diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High-Performance Computing • Information storage, security, integrity, privacy, and trust • Image and Speech Signal Processing • Knowledge-Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Memetic Computing • Multimedia and Applications • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition, and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Stochastic systems • Support Vector Machines • Ubiquitous, grid and high-performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data
Articles
394 Documents
<![CDATA[Evaluation of the New Student Admission Website of STMIK Widya Cipta Dharma Using the End-User Computing Satisfaction Method ]]>
<![CDATA[Damaya, Filio Angga]]>;
<![CDATA[Pratiwi, Heny]]>;
<![CDATA[Yunita, Y]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.381
<![CDATA[The New Student Admission (PMB) website is one of the platforms used in the admission and registration process for prospective students at STMIK Widya Cipta Dharma. An evaluation of the PMB website is necessary to ensure user convenience and satisfaction during the registration process. This study aims to evaluate the new student admission website of STMIK Widya Cipta Dharma using the End-User Computing Satisfaction (EUCS) method. The EUCS method consists of five main dimensions: content, accuracy, format, ease of use, and timeliness. Data was collected through questionnaires distributed to registered students, prospective students of STMIK Widya Cipta Dharma, and users of the PMB website. The analysis results indicate user satisfaction in using the PMB website.]]>
<![CDATA[The Development of a Web Profile System for SMK N 1 Singingi Hilir Using the Prototyping Method ]]>
<![CDATA[Sucinta, Hanny Handayani]]>;
<![CDATA[Mahmuda, Muhimmatul]]>;
<![CDATA[Mujahidah, Latifatul]]>;
<![CDATA[Sugiantoro, Bambang]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.395
<![CDATA[The development of a web-based information system for the school profile is a strategic step in improving the accessibility of information and interaction between the school and the community, particularly prospective students and parents. This study aims to develop a web profile system for SMK N 1 Singingi Hilir by applying the Prototyping method, so that the system can be developed based on user feedback during the design process. This system presents comprehensive information about the school profile, expertise programs, facilities, student activities, and other important information. With the Prototyping approach, system development is carried out iteratively by building an initial prototype, which is then improved based on user evaluations. The result of this development is expected to enhance school promotion as well as transparency and efficiency in delivering information.]]>
<![CDATA[Analysis of Fertilizer Requirements in Red Chili Cultivation Using an Artificial Neural Network Approach ]]>
<![CDATA[Marpaung, Mairani]]>;
<![CDATA[Apdillah, Dicky]]>;
<![CDATA[Ayyub, Muhammad Azwar Al]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.387
<![CDATA[Red chili farmers on the East Coast of North Sumatra still rely on manual calculations to determine the use of NPK Biru 16 Mutiara fertilizer, often leading to inaccurate and inefficient fertilizer application. This study proposes the Backpropagation method within Artificial Neural Networks (ANN) as a solution to analyze fertilizer needs more precisely. The method enables the system to learn from historical data and plant growth patterns, providing accurate recommendations for the type and amount of fertilizer required. The implementation of ANN in this context not only enhances agricultural efficiency but also supports environmental sustainability by minimizing excessive fertilizer usage.]]>
<![CDATA[Comparison of Naive Bayes and C4.5 Methods with Particle Swarm Optimization on Customer Loyalty Classification ]]>
<![CDATA[Wati, Embun Fajar]]>;
<![CDATA[Perangin-Angin, Elvi Sunita]]>;
<![CDATA[Indriyani, Luthfi]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.382
<![CDATA[The Company attaches great importance to customer loyalty for the sustainability of the Company. Loyal customers will buy many times and provide great profits. In this study, the decision tree method or C4.5 and naïve bayes were used with PSO optimization for customer classification which aims to design a strategy in decision-making towards disloyal customers. Some of the stages carried out are data load into MS. Excel, data cleaning from noise, data selection as many as 238 obtained from previous research with several attributes, including, namely age, annual income, purchase amount, region, purchase frequency, and loyalty score, as well as data transformation, namely each attribute is grouped into 2 with their own criteria, data testing by modeling data through Rapidminer, Data evaluation by examining the values of accuracy, precision, recall, and AUC. Both methods have the same accuracy value of 96.67% and the same recall value of 100%. For the precision value, there is a difference of 0.6% and the precision decision tree value is higher than the naïve Bayes which is 96.16%. As for the AUC value, it is higher naïve bayes, which is 0.922 with the difference from the decision tree of 0.059. It can be concluded that the two methods in processing customer loyalty data in this study have the same accuracy, so both methods are equally good.]]>
<![CDATA[Analysis of The Influence of Lack of Cellular Network on The Quality of Education in Schools in Long Gelawang Village ]]>
<![CDATA[Jemeq, Margareta]]>;
<![CDATA[Rangan, Andi Yusika]]>;
<![CDATA[Khair, Ahmad Abul]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.389
<![CDATA[Cellular networks are one of the supporting factors in implementing learning activities, especially in the digital era which requires connectivity to access information and online learning technology. However, not all areas in Indonesia have adequate network infrastructure, including Long Gelawang Village. This study aims to analyze the impact of limited cellular networks on the quality of education in the area. The quantitative approach was used with descriptive statistical methods and Spearman correlation tests. Data were obtained from 55 respondents consisting of students and teachers through questionnaires and interviews. The results of the normality test showed that the data were not normally distributed, so non-parametric analysis was used. The results showed that the relationship between network limitations and education quality was very weak (ρ = 0.143) and not significant (p = 0.299). This means that network limitations do not directly impact the quality of education. Local efforts such as the use of printed teaching materials, hands-on learning, and parental and community involvement help maintain the continuity of education. These findings emphasize that improving the quality of education in remote areas depends not only on technology, but also on a collaborative and locally based approach.]]>
<![CDATA[Image Feature Extraction for Determining the Ripeness Level OF Oil Palm Fruits Using the K-Nearest Neighbor Algorithm Based on Color Features (Case PTPN IV Aceh Utara) ]]>
<![CDATA[Sudarti, Atrida]]>;
<![CDATA[Ula, Munirul]]>;
<![CDATA[Fajriana, F]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.391
<![CDATA[The availability of oil palm fruits at the appropriate ripeness level is crucial to achieving optimal oil production. Farmers often struggle to accurately determine fruit ripeness, resulting in inconsistent quality and reduced efficiency. This study aims to develop a classification system to determine the ripeness level oil palm fruits using the K-Nerest Neighbor (K-NN) algorithm based on color features extracted from fruits image. Color is a key indicator of maturity and directly influences oil yield. The data was collected through image acquisition and direct observation at the Cot Girek Palm Oil Mill (PKS) of PTPN IV, Aceh Utara. Image preprocessing was carried out to enhance and nomalize the data before feature extraction. The extracted color features were then used to classify the fruits into ripe and unripe categories using the K-NN algorithm. The results show that K-NN successfully classifies the ripeness level of oil palm fruits with an accuracy of 72.80%. This system provides a recommendation for fruit feasibility before processing, helping reduce production losses caused by immature or overripe fruits. Overall, this research contributes to improving decision-making in the palm oil industry through the application of image processing of machine learning techniques.]]>
<![CDATA[Expert System for Detecting Diseases in Cattle Using Backward Chaining Method ]]>
<![CDATA[Ramadani, Putri]]>;
<![CDATA[Wahyuni, Alvi Dwi]]>;
<![CDATA[Putra, Eka Ramadhani]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.383
<![CDATA[Cow is one of the livestock animals with commercial or economic value due to the sale of beef and bull semen. Livestock diseases can reduce the quality of livestock and cause a decline in sales. This research aims to help farmers recognize or identify types of diseases in cows based on visible symptoms or to prevent the risk of disease to avoid outbreaks. All data used comes from experts and a collection of documents from magazines and books related to livestock diseases. This analysis applies backward chaining in expert systems, particularly systems that process existing facts to reach conclusions. Facts are derived from physical conditions, also called symptoms. Backward chaining is a goal-based analysis that starts with an assumption of what might happen, then searches for facts (evidence) or symptoms that support (or refute) the hypothesis. The development of a web-based expert system makes it easier for farmers to access the system online. The accuracy of the expert system has been tested by stakeholders or experts, resulting in fast, accurate, and effective information. This research can assist farmers in diagnosing symptoms in livestock, and the test results can accurately detect the type of disease in livestock so that treatment can be carried out quickly.]]>
<![CDATA[Optimization of Mobile Attendance System with Haversine Formula Method for Field Work Practice Students ]]>
<![CDATA[Alkodri, Ari Amir]]>;
<![CDATA[Fitriyani, F]]>;
<![CDATA[Isnanto, Burham]]>;
<![CDATA[Sari, Melati Suci Maya]]>;
<![CDATA[Andrika, Yuyi]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.378
<![CDATA[Conventional attendance of Field Work Practice (PKL) students still has various obstacles, such as manipulation of attendance, late recording, and difficulties in validating accurate attendance. In today's digital era, the use of location-based technology is a solution to overcome these problems. Therefore, this study aims to develop and optimize a location-based mobile attendance system by implementing the Haversine Formula Method. This method is used to calculate the distance between the student's GPS coordinates and the predetermined PKL location, so that the system only allows attendance if the student is within a certain radius.With implementation on the Android platform. The main features of this system include real-time location recording, automatic validation based on GPS coordinates, and encrypted data security. Accuracy measurement uses a comparison of the Haversine distance calculation results with a mapping application. The results of the study show that the Haversine Formula method is able to calculate distances with high accuracy, and the system developed can prevent cheating in attendance. Thus, the application of this method can improve transparency, efficiency, and accuracy of recording the attendance of PKL students in real-time, provide convenience for institutions in monitoring the presence of coordinates laboratory location accurately with a distance of ≤ 50 meters, so that the system can determine whether students are within the radius permitted to take attendance at Latitude: -2.123900 and Longitude: 106.788800. at the location of the PKL institution, namely in the ISB Atma Luhur computer laboratory.]]>
<![CDATA[The Influence of Ease of Use and Utilization of the E-Stock Application on the Effectiveness of the Learning Process Using the EUCS Method (Case SMKN 10 Samarinda) ]]>
<![CDATA[Mumek, Trifena Oliviana]]>;
<![CDATA[Yunita, Y]]>;
<![CDATA[Yulindawati, Y]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.388
<![CDATA[The management of inventory items in vocational school environments often faces administrative challenges, such as manual record-keeping that is prone to errors and process delays. SMKN 10 Samarinda implemented the E-Stock application as an information system solution to address these issues. This study aims to evaluate user perceptions of the ease of use and utilization of the E-Stock application, as well as its impact on the effectiveness of use in school operational activities and in supporting the efficiency of the learning process, which depends on the availability of facilities and infrastructure. This research employs a descriptive quantitative approach, with data collected through a closed-ended questionnaire distributed to nine active respondents. The instrument consists of 18 statements representing three main variables: ease of use, utilization, and effectiveness. Each item was rated using a Likert scale ranging from 1 to 5. Data were analyzed descriptively using SPSS to obtain the average score for each variable studied. The analysis results show that ease of use received an average score of 4.37, utilization scored 4.40, and effectiveness scored 4.28. All three scores fall into the high category, indicating that users have a very positive perception of the application. Based on these results, it can be concluded that the E-Stock application has met user expectations in supporting work efficiency and school administration, as well as contributing to the smooth running of the learning process through improved inventory management. This study also affirms that evaluation models such as EUCS are relevant to be used in the context of educational information systems.]]>
<![CDATA[Evaluating Urban Green Space Dynamics in Makassar City Through NDVI-Based Analysis of Sentinel-2 Imagery ]]>
<![CDATA[Edra, Anggun Purnama]]>;
<![CDATA[Azzahra, Cantika]]>;
<![CDATA[Nurhayati, Shifa]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.392
<![CDATA[Urban expansion in rapidly growing cities like Makassar has considerable implications for vegetation loss and ecosystem degradation. This study investigates vegetation cover changes in Makassar City by analyzing the Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 imagery for the years 2020 and 2024. A threshold of NDVI > 0.5 was applied to identify areas classified as dense vegetation. Image pre-processing, NDVI computation, and binary classification were performed to quantify and map vegetation extent. The analysis reveals a noticeable reduction in densely vegetated areas. This study analyzes the changes in vegetation health in Makassar City using the Normalized Difference Vegetation Index (NDVI) for the years 2020 and 2024. The NDVI threshold of >0.5 was used to identify areas of healthy vegetation. The spatial analysis and classification maps reveal a significant decline in vegetated areas, with a decrease from 4,792.93 hectares in 2020 to 1,157.23 hectares in 2024. This trend highlights a substantial reduction in healthy vegetation cover, potentially caused by urban development, land-use changes, and environmental pressures. The findings underscore the need for sustainable land management and green infrastructure policies to mitigate the adverse effects of vegetation loss and promote ecological balance in urban areas.]]>
