Jurnal Mandiri IT 2024-07-01T08:33:59+00:00 Fristi Riandari Open Journal Systems <p>Jurnal Mandiri IT adalah jurnal peer-review yang diterbitkan dua kali setahun (Januari dan Juli) oleh Institute of Computer Science (IOCScience). Jurnal Mandiri IT dimaksudkan sebagai media publikasi untuk menerbitkan artikel-artikel yang melaporkan hasil penelitian Ilmu Komputer. Jurnal Mandiri IT terbit sejak tahun 2010 dengan ISSN <a href="" target="_blank" rel="noopener">2301-8984</a> (media cetak), dan pada tahun 2021 telah menggunakan ISSN Online.</p> Development of mobile applications for IoT-based room temperature monitoring and control 2024-06-07T15:53:09+00:00 Aang Alim Murtopo Mukhamad Zulfa Bakhtiar Amalani Syefudin Syefudin Gunawan Gunawan <p>The Internet of Things (IoT) has become one of the most significant technologies, offering a wide range of innovative solutions to improve efficiency and convenience in various aspects of life. One important application of IoT is in environmental management and control, especially room temperature. This research aims to develop a mobile application capable of monitoring and controlling room temperature with an easy-to-understand user interface and the ability to forecast future temperature needs. Research methods used include experimental approaches, data analysis, and model validation to ensure applications function optimally in real-world conditions. The results showed that the application developed was effective in monitoring room temperature conditions in real-time and was able to adjust the temperature quickly and accurately. The implication of this research is the improvement of user convenience and energy efficiency through the use of IoT technology in everyday life.</p> 2024-06-18T00:00:00+00:00 Copyright (c) 2024 Aang Alim Murtopo, Mukhamad Zulfa Bakhtiar Amalani, Syefudin Syefudin, Gunawan Gunawan Comparison of dijkstra and genetic algorithms for shortest path guci 2024-06-02T12:39:10+00:00 Sarif Surorejo Muhammad Raikhan Al Fattah Wresti Andriani Gunawan Gunawan <p>This study aims to compare the performance of the Dijkstra algorithm and the Genetics algorithm in determining the shortest path to the Guci tourist destination. The research design combines experimental methods, quantitative analysis, and model validation. The data used is the distance between points on two alternative routes to Guci. Data pre-processing is done to ensure quality and consistency. The relevant variables are selected, and model optimization is performed to obtain the best parameter configuration for both algorithms. Dijkstra and Genetics algorithms are implemented using Python, taking into account computational efficiency and ease of integration. Model evaluation is done through a series of tests with time execution and convergence metrics. The results showed that Dijkstra's algorithm was superior in finding the shortest path with a distance of 43.0 km and an execution time of 0.0017 seconds, compared to the Genetics algorithm which found a path with a distance of 44.7 km and an execution time of 0.0048 seconds. It can be concluded that Dijkstra's algorithm is more effective and efficient in this case, but Genetics algorithms have the potential for more complex optimization problems.</p> 2024-06-13T00:00:00+00:00 Copyright (c) 2024 Sarif Surorejo, Muhammad Raikhan Al Fattah, Wresti Andriani, Gunawan Gunawan Application of the latent dirichlet allocation method to determine news text topics 2024-06-07T15:47:39+00:00 Sarif Surorejo M Taufik Fajar Maulana Wresti Andriani Gunawan Gunawan <p>This research discusses the application of the Latent Dirichlet Allocation (LDA) method to determine news text topics, providing new insights into media content analysis. This research aims to develop a model that can increase the accuracy and efficiency of topic identification in Indonesian news texts. The research uses a quantitative approach with experimental methods, quantitative analysis, and model validation, where news text data is processed and analyzed using LDA. The results show that the developed model can accurately identify news topics, showing significant improvements compared to existing methods. The implications are substantial for practitioners and researchers in journalism and media analysis, offering more efficient and effective strategies for managing and understanding large flows of information and opening new directions for advanced research in news text analysis.</p> 2024-06-19T00:00:00+00:00 Copyright (c) 2024 Sarif Surorejo, M Taufik Fajar Maulana, Wresti Andriani, Gunawan Gunawan Application of weighted aggregated sum product assessment method in determining the best flour to produce vermicelli 2024-06-01T09:25:48+00:00 Sarif Surorejo Rafik Rivaldiansyah Rifki Dwi Kurniawan Gunawan Gunawan <p>This study explores the application of the Weighted Aggregated Sum Product Assessment (WASPAS) method's selection of the best wheat flour for vermicelli production, which aims to improve product quality and production efficiency. The study aimed to integrate experimental data with sophisticated decision-making models to identify the most suitable type of flour based on a comprehensive set of criteria. Using a quantitative approach, this study combines experimental methods, quantitative analysis, and model validation, using the WASPAS method to evaluate and rank various flours. The results showed significant differences among flour types, with selected flours showing superior performance across multiple parameters, including chemical composition and functional properties. The study's findings underscore the potential of advanced decision-making tools such as WASPAS in improving food production processes, demonstrating broader applicability across the food industry to optimise raw material selection.</p> 2024-06-12T00:00:00+00:00 Copyright (c) 2024 Sarif Surorejo, Rafik Rivaldiansyah, Rifki Dwi Kurniawan, Gunawan Gunawan Expert system for diagnosing pests and diseases of shallot plants with naïve bayes method 2024-06-15T09:24:44+00:00 Sarif Surorejo Muhammad Syifa Albana Nugroho Adhi Santoso Gunawan Gunawan <p>The development of an expert system for diagnosing pests and diseases of onion plants is of great importance given the significant role of these crops in the agricultural industry. This research aims to design and develop an expert system that can diagnose various pests and diseases that attack onion plants using the Naive Bayes method. This method was chosen for its ability to classify data based on probability assuming independence between features. This system is designed to assist farmers in identifying pests and diseases more accurately and quickly so that appropriate control measures can be taken immediately. The training data used in this study included symptoms that often occur in onion plants due to pest or disease attacks. Each symptom is associated with the probability of the appearance of a particular pest or disease. This expert system is designed with an easy-to-use interface for farmers, where they can enter the symptoms observed in plants. Based on these inputs, the system will analyze and provide a diagnosis along with recommendations for control actions that can be taken. The system testing results show that this expert system has good accuracy in diagnosing pests and diseases in onion plants. Thus, this system can be an effective tool for farmers in managing the health of their onion plants. Further research is recommended to improve disease and pest databases and expand the application of these systems to other plant types.</p> 2024-06-24T00:00:00+00:00 Copyright (c) 2024 Sarif Surorejo, Muhammad Syifa Albana, Nugroho Adhi Santoso, Gunawan Gunawan Application of the haversine formula method to determine the closest distance to a minimarket 2024-06-01T09:22:32+00:00 Anik Muttaqin Aang Alim Murtopo Syefudin Syefudin Gunawan Gunawan <p>In a digital era that demands speed and efficiency, determining the closest distance to minimarkets is crucial for consumers and the logistics industry. This study proposes the use of the haversine method to improve the accuracy of distance calculations. Through quantitative and quasiexperimental approaches, this study describes the steps of data collection, pre-processing, and application of haversine formulas. The results demonstrate the reliability of the haversine method in estimating distances accurately, allowing users to make more informed decisions in planning trips or logistics strategies. These findings contribute to the academic literature and field practice by providing a more robust and applicable methodology for determining the closest distance. Keywords: haversine, closest distance, minimarket.</p> 2024-06-14T00:00:00+00:00 Copyright (c) 2024 Anik Muttaqin, Aang Alim Murtopo, Syefudin Syefudin, Gunawan Gunawan Implementation of blockchain technology in digital financial management systems 2024-06-16T03:53:06+00:00 Aang Alim Murtopo Abu Hasan Al Anshori Nugroho Adi Santoso Gunawan Gunawan <p>This research aims to develop and test a digital financial management system model that is integrated with blockchain technology to address security, transparency, and efficiency issues in the traditional digital financial system. Blockchain technology is used to ensure the integrity and security of data by recording each transaction in the form of interlinked and immutable blocks. The methods used include experimental approaches, quantitative analysis, and model validation. The results of the study show that blockchain integration improves the transparency, security, and operational efficiency of digital financial management systems. Although the designed asset recording application still has weaknesses in UX and UI, such as the lack of drop-down features and manual data entry, blockchain technology has successfully strengthened data security with the use of unique record IDs (hashes) that cannot be changed and public transparency through Etherscan. This research makes a practical contribution to the application of blockchain technology in the financial industry and suggests further development to improve the user experience and add features that improve the efficiency and flexibility of the asset recording system. These findings support the potential of blockchain in advancing the integrity and performance of the digital financial system.</p> 2024-06-24T00:00:00+00:00 Copyright (c) 2024 Aang Alim Murtopo, Abu Hasan Al Anshori, Nugroho Adi Santoso, Gunawan Gunawan Implementation of the Fuzzy Tsukamoto method to determine the amount of beverage production 2024-06-02T12:41:51+00:00 Sarif Surorejo Muchamad Aries Firmansyah Zaenul Arif Gunawan Gunawan <p>Optimization of the amount of beverage production by applying the Fuzzy Tsukamoto Method at PT. Sariguna Primatirta Tbk. This study aims to develop a predictive model that can assist companies in determining the optimal amount of beverage production, minimizing production costs, and maximizing customer satisfaction. The research method uses a quantitative approach with a combination design of experimental methods, quantitative analysis, and model validation, including the collection of historical data on production, market demand, and raw material availability, data pre-processing, selection of input and output variables, implementation of the Fuzzy Tsukamoto algorithm, and model evaluation with Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) metrics. The results showed that the Fuzzy Tsukamoto Method succeeded in determining the amount of beverage production with good accuracy, with an MAE of 0.25 and RMSE of 0.274 after the data was understated, proved effective in handling the uncertainty of market demand and providing optimal production recommendations based on fuzzy rules from expert knowledge. The implications of this research contribute to the scientific literature in the field of computer science and industrial management, as well as practical benefits for PT. Sariguna Primatirta Tbk in improving its production effectiveness, with the potential to be adopted by similar industries to improve operational efficiency.</p> 2024-06-12T00:00:00+00:00 Copyright (c) 2024 Sarif Surorejo, Muchamad Aries Firmansyah, Zaenul Arif, Gunawan Gunawan Application of dijkstra algorithm to optimize waste transportation distribution routes in Tegal Regency 2024-06-06T11:53:34+00:00 Bayu Aji Santoso Misbahu Surur Syefudin Syefudin Gunawan Gunawan <p>Efficient waste management is essential for sustainable urban development, especially in densely populated areas such as Tegal Regency. The study addresses inefficiencies in current waste hauling routes that contribute to increased operational costs and environmental impacts due to long transit times and increased emissions. By applying the Dijkstra Algorithm, this study aims to optimize waste transportation routes to reduce these inefficiencies. This approach involves collecting primary and secondary data on the waste management system in Tegal, which is then analyzed using the <em>dijkstra</em> algorithm to determine the most efficient transport route. The findings show that route optimization can significantly reduce operational costs and carbon emissions, contributing to more sustainable waste management practices in the Tegal District. This study not only improves theoretical understanding of route optimization but also provides practical solutions to real problems in waste management systems.</p> 2024-06-15T00:00:00+00:00 Copyright (c) 2024 Bayu Aji Santoso, Misbahu Surur, Syefudin Syefudin, Gunawan Gunawan Applying certainty factor method to identify diseases in rice plants 2024-06-12T09:35:34+00:00 Bangkit Indarmawan Nugroho Ahmad Miftakhuddin Syefudin Syefudin Gunawan Gunawan <p>Rice (Oryza Sativa L) is the most important food crop in the world after wheat and corn, as well as the main source of protein for most of the world's population, especially in Asia. The Save Swamps for Prosperous Farmers (Serasi) program in Central Java Territory cannot run well considering the tall capacity of existing rice agriculturists to bargain with bugs and maladies of the rice they plant, so it is essential to make a device within the frame of an master framework for diagnosing rice plant infections. For this reason, it is very important to be aware of the factors that influence production levels. Disease is one of the most detrimental factors in rice production, where many losses are caused by disease. Each of these diseases generally shows symptoms of the disease suffered before it reaches a more severe and widespread stage, these symptoms can be recognized by carrying out a diagnosis first. This can be done using an expert system. In this research, an expert system was utilized which was made utilizing the certainty figure strategy, with a test of 25 ranchers within the West Tegal Area, Tegal City. From the comes about of the inquire about carried out, it was concluded that with this framework the level of exactness obtained using the posttest contains a esteem of 100%, in other words the framework encompasses a decently tall level of accuracy.</p> 2024-06-24T00:00:00+00:00 Copyright (c) 2024 Bangkit Indarmawan Nugroho, Ahmad Miftakhuddin, Syefudin Syefudin, Gunawan Gunawan Application of fuzzy genetic system to predict the number of outpatient visits 2024-05-30T11:12:26+00:00 Sarif Surorejo Septian Dwi Cahyo Nurul Fadilah Gunawan Gunawan <p>Improving the management and use of resources in outpatient care is a challenge faced by health facilities in today's digital era. The inability to accurately predict patient flow can result in inadequacies in staff scheduling and effective space management. Therefore, this study aims to develop a predictive model of outpatient visits using the fuzzy system genetic method. The research methods used include the design of a combination of experimental methods, quantitative analysis, and model validation. Outpatient visit data is taken from a hospital and processed using the Fuzzy Genetics System which optimizes fuzzy rules with genetic algorithms. The results of the model implementation show accurate and adaptive predictions to variations and uncertainties in patient visiting patterns. Based on the results of the study, it can be concluded that the use of fuzzy system genetic methods in predicting outpatient visits can improve the operational efficiency of health facilities. The developed prediction model is able to provide predictions that are more accurate, adaptive, and responsive to the real needs of health facilities. With the adoption of this method, health facilities can optimize management and resources in outpatient health services. This research contributes significantly to the development of predictive models that are more efficient and applicable in the dynamic context of healthcare.</p> 2024-06-13T00:00:00+00:00 Copyright (c) 2024 Sarif Surorejo, Septian Dwi Cahyo, Nurul Fadilah, Gunawan Gunawan Application of genetic algorithm and backpropagation neural networks to predict Tegal City population 2024-06-09T07:02:07+00:00 Aang Alim Murtopo Wahyu Nursahid Nurul Fadilah Gunawan Gunawan <p>Use of Genetic Algorithms and Backpropagation Neural Networks for Population Prediction in Tegal City, which aims to create precise prediction models using advanced computational techniques. This research uses a quantitative approach that combines experimental methods, data analysis, and model validation to implement and test predictive models. By using genetic algorithms for parameter optimization and neural network backpropagation for training, the findings show that the model can accurately predict population numbers with minimal error and high determination coefficients. The implications of this study are significant for urban planning and public policy development due to the accuracy and effectiveness of the model in forecasting population growth based on historical data.</p> 2024-06-18T00:00:00+00:00 Copyright (c) 2024 Aang Alim Murtopo, Wahyu Nursahid, Nurul Fadilah, Gunawan Gunawan Comparison of naïve bayes and KNN for herbal leaf classification 2024-05-31T07:16:31+00:00 Bangkit Indarmawan Nugroho Muhammad Wazid Khusni Pingky Septiana Ananda Gunawan Gunawan <p>This study aims to compare the effectiveness of two classification algorithms, namely Naïve Bayes Classifier and K-Nearest Neighbor (KNN), in classifying herbal leaves. This research design uses a quantitative approach with experimental analysis and model validation. The dataset consisted of images of papaya leaves, pandanus, cat's whiskers, and betel nut taken in different lighting conditions. The methodology includes pre-processing of data by converting images into grayscale, feature extraction using Gray Level Co-occurrence Matrix (GLCM), and application of Naïve Bayes and KNN algorithms. The main results showed that KNN achieved 90.00% accuracy with precision, recall, and F1-score of 88.33% respectively, higher than Naïve Bayes which had 82.50% accuracy, 81.46% precision, 85.83% recall, and 82.27% F1-score. In conclusion, KNN is superior in the classification of herbal leaves to Naïve Bayes, although it requires a longer computational time. Further research is recommended to optimize algorithm parameters and explore the integration of deep learning techniques to improve classification accuracy and efficiency.</p> 2024-06-12T00:00:00+00:00 Copyright (c) 2024 Bangkit Indarmawan Nugroho, Muhammad Wazid Khusni, Pingky Septiana Ananda, Gunawan Gunawan Application of fuzzy tsukamoto method in forecasting weather 2024-06-07T15:44:00+00:00 Aang Alim Murtopo Muhammad Nur Aslam Wresti Andriani Gunawan Gunawan <p>In today's information age, accurate weather prediction is essential given its far-reaching impact on various aspects of life and economic activity. This study aimed to test the effectiveness of Fuzzy Tsukamoto's method in predicting important weather variables such as temperature, humidity, and precipitation. This research method uses a combination design that includes experimental methods for model development, quantitative analysis of historical weather data, and model validation using separate data. The results showed that the Fuzzy Tsukamoto method was able to increase the accuracy of weather predictions compared to conventional methods, with a significant decrease in the value of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In conclusion, this study successfully demonstrates that Fuzzy Tsukamoto's method can be a more accurate alternative in weather prediction, making a significant contribution to the field of meteorology and its practical application in decision-making in various sectors that depend on weather prediction.</p> 2024-06-19T00:00:00+00:00 Copyright (c) 2024 Aang Alim Murtopo, Muhammad Nur Aslam, Wresti Andriani, Gunawan Gunawan Prediction of Bank Central Asia stock prices after dividend distribution using ARIMA method 2024-05-30T10:58:32+00:00 Sarif Surorejo Muhammad Sulthon Sawaviyya Anandianskha Gunawan Gunawan <p>This study explores the prediction of Bank Central Asia (BBCA) stock prices following the annual dividend distribution using the Autoregressive Integrated Moving Average (ARIMA) method. The primary goal is to provide a robust forecasting tool to aid investors and financial analysts in making informed decisions. The research employs a quantitative approach with a quasi-experimental design, analyzing weekly BBCA stock price data from January 2019 to February 2024. The findings demonstrate that the ARIMA (2, 1, 2) model provides stable and reliable predictions of BBCA stock prices, showing slight weekly variations but overall stability. Practically, these predictive models can be integrated into a web-based platform, allowing real-time stock price forecasting and broader accessibility for users. This study contributes to the financial literature by validating the ARIMA model's applicability in the Indonesian stock market and suggesting the exploration of hybrid models and external economic factors for future research.</p> 2024-06-12T00:00:00+00:00 Copyright (c) 2024 Sarif Surorejo, Muhammad Sulthon, Sawaviyya Anandianskha, Gunawan Gunawan Design of an Internet of Things-Based automatic cat feeding control device (IoT) 2024-07-01T08:33:59+00:00 Nofri Wandi Al-Hafiz Harianja Harianja <p>The automation era has been a big step in human civilization. The use of automation technology combined with an internet connection, or IoT, has helped a lot in everyday life. In one example, feeding cats is a problem when the owner is busy working or traveling for more than two days. However, having a cat feeding device is automatically a solution to this problem. This research created an automatic cat feeding device using the NodeMCU ESP8266 microcontroller base, which has a WiFi module installed. When it is paired with an HCR04 ultrasonic sensor to measure the feed height, it will send a message to the MQTT application on the smartphone if the remaining feed in the cat food container is at a certain height or is almost finished. The Blynk application manages this tool, which provides a widget to help monitor, change feeding times, view feeding statistics, and view the last feeding time and date. The black box testing method is used to test this tool so that it functions properly.</p> 2024-07-09T00:00:00+00:00 Copyright (c) 2024 Nofri Wandi Al-Hafiz, Harianja Harianja Application of WASPAS method in determining the best flour for nastar making 2024-06-02T13:09:20+00:00 Bangkit Indarmawan Nugroho Errika Mutiara Dewi Rifki Dwi Kurniawan Gunawan Gunawan <p>This study explores the use of the Weighted Aggregated Sum Product Assessment (WASPAS) Method in selecting the best wheat flour for pineapple cake production. The aim of this study is to develop a more systematic and quantitative approach in assessing flour quality, provide useful guidance for pineapple cake producers and enrich the academic literature in the field of food science and food technology. This study used quantitative methodology data analysis and model validation with WASPAS, aimed at overcoming the challenge of selecting the best wheat flour for pineapple cake making. Results showed that the WASPAS method was effective in identifying the best flour, with Bungasari Hana Emas flour obtaining the highest WASPAS score of 0.952863, followed by the Falcon Hijau with a score of 0.931373. This score indicates the optimal balance between cost and quality. The study emphasizes the importance of objective decision-making tools in the food industry, suggesting that such an approach can significantly improve product quality and production efficiency.</p> 2024-06-13T00:00:00+00:00 Copyright (c) 2024 Bangkit Indarmawan Nugroho, Errika Mutiara Dewi, Rifki Dwi Kurniawan, Gunawan Gunawan The Control of skincare and bodycare inventory decisions using the Multi Attribute UtilityTheory (MAUT) Method 2024-06-10T09:45:56+00:00 Ismi Novitasari Sinaga <p>Skincare is a series of facial skin care activities to maintain the health and appearance of the skin, as well as overcome various problems with skin. This activity consists of using several types of products, each of which has a different function according to its contents. In companies operating in the supply and trading sector, it is one of the core variables of business operations. Inventory management is also very important in company operations. Inventory that is not managed properly will cause many operational problems, such as running out of products or raw materials when needed, losing customers, losing goods, and other aspects of loss that can have a significant impact on the company. For this reason, this research aims to make decisions on controlling skincare supplies so that they can be guaranteed in sufficient quantities with decision support using the MAUT method. The data used in this research is the number of supplies that run out per day, per week, per month. It is hoped that the results of this research with the Multi Attribute Utility Theory (MAUT) method can help companies in making decisions on controlling skincare supplies very well.</p> 2024-06-20T00:00:00+00:00 Copyright (c) 2024 Ismi Novitasari Sinaga Implementation of cisco packet tracer as network simulation in educational environment at SMK Tarbiyatul Banin-Banat Montong School 2024-06-16T03:33:17+00:00 Ali Amran Happy Syaharani <p>This journal aims to describe the implementation of using Cisco Packet Tracer as a network simulation tool in an educational environment al Tarbiyatul Banin-Banat Montong Vocational High School (SMK) Network simulation is an important method in information technology education, especially in the context of computer network learning This research covers the steps taken in implementing Cisco Packet Tracel at SMK Tarbiyatul Banın-Banat Montong, as well as the benefits that result from using this simulation tool. The research methods include student surveys, as well as classroom observations. The journal is ahead in the use of network simulation technology such as Cisco Packe Tracer in education. As technology continues to evolve, this approach has the potential to continuously improve network leaming and prepare students for the job demands of the digital age. The results showed that the use of Cisco Packet Tracer in network learning at SMK Tarbiyatul Banin-Banat Montong has improved students understanding networking concepts, allowed them to test theories in a safe simulation environment, arid stimulated their interest in pursuing a career in information technology. In addition, the use of this tool also assists teachers in teaching more effectively and efficiently. This article details the practical implementation of Cisco Packet Tracer in an educational environment, illustrates its benefits to students and educators, and provides recommendations for further development in network education at SMK Tarbiyatul Banin-Banat Montong as well as educational institutions in conclusion, the use of Cisco Packet Tracel as a network simulation tool in an educational environment can improve similar the quality of leaming and prepare students for careers in the world of information technology.</p> 2024-07-30T00:00:00+00:00 Copyright (c) 2024 Application of centroid and geometric mean methods for face recognition 2024-06-01T09:26:34+00:00 Bangkit Indarmawan Nugroho Apriliani Maulidya Khasanah Zaenul Arif Gunawan Gunawan <p>Face recognition is one of the most important areas in artificial intelligence and image processing, with wide applications from attendance system security to human-computer interaction. This study aims to overcome the difficulties in classifying student faces in an academic environment by applying and comparing centroid and geometric mean methods. Student face data was collected and processed through conversion to grayscale, pixel intensity normalization, and statistical analysis using both methods. The results showed that both methods had the same performance with 70% accuracy, 75% precision, 60% recall, and 66.67% F1-score. The application of this method can improve the efficiency and accuracy of attendance management and security in the campus environment, especially for institutions with limited resources.</p> 2024-06-12T00:00:00+00:00 Copyright (c) 2024 Bangkit Indarmawan Nugroho, Apriliani Maulidya Khasanah, Zaenul Arif, Gunawan Gunawan