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<![CDATA[Implementasi Metode CNN Dan K-Nearest Neighbor Untuk Klasifikasi Tingkat Kematangan Tanaman Cabai Rawit ]]>
<![CDATA[Muhammad Rifki Bahrul Ulum]]>;
<![CDATA[Basuki Rahmat]]>;
<![CDATA[Made Hanindia Prami Swari]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 3 (2024): Juli : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i3.131
<![CDATA[The process of identifying the ripeness level of cayenne peppers is an important step in cultivation and post-harvest handling. Dependence on the quality factors of farmers, such as visual diversity and differences in ripeness perception, results in subjective harvest outcomes. This manual process is also prone to inconsistent results, as humans have time limitations, fatigue, and sometimes lack concentration when sorting for long periods. To minimize these issues, technological intervention is needed to mechanically classify the ripeness level of cayenne peppers. This research aims to develop a classification model for the maturity level of cayenne pepper plants. This research proposes the use of the CNN method for feature extraction and KNN for data classification based on the features extracted by CNN. From the test scenarios carried out, the classification carried out by KNN based on CNN feature extraction got the best accuracy of 99.33%, while the CNN classification model got the best accuracy of 87.33%.]]>
<![CDATA[Sistem Pakar Diagnosis Penyakit Gizi Pada Balita Dengan Menggunakan Metode Dempster Shafer ]]>
<![CDATA[Debi Unsilatur Utami]]>;
<![CDATA[Budi Nugroho]]>;
<![CDATA[Agung Mustika Rizki]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 3 (2024): Juli : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i3.132
<![CDATA[Children under five are more at risk of experiencing nutritional disorders because during this period children will experience very rapid growth and development. Nutritional disorders can result in children's performance in activities not being optimal, hampering the growth and development process, and can even cause disease. Malnutrition sufferers in Indonesia are increasing every year, and the percentage of malnutrition in Indonesia is around 3.4%. An expert system is a computer-based system built based on facts, knowledge and reasoning that can help solve a problem. However, to measure the uncertainty and level of expert confidence in identifying and detecting malnutrition, an expert system can use the Dempster-Shafer method. The results of testing the system model using the Dempster-Shafer method on toddler nutritional diseases obtained quite good results with system accuracy of 84% with a precision value of 81.83% and also a recall value of 80%.]]>
<![CDATA[Analisis Pola Pembelian Pelanggan Menggunakan Algoritma Squeezer, Apriori dan FP-Growth Pada Toko Bangunan ]]>
<![CDATA[Faris Syaifulloh]]>;
<![CDATA[Eva Yulia Puspaningrum]]>;
<![CDATA[M. Muharram Al Haromainy]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 3 (2024): Juli : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i3.153
<![CDATA[To compete with other stores, store owners need to design various strategies, one of which is understanding customer purchase patterns. This article examines the Squeezer algorithm and compares the performance of the Apriori and FP-Growth algorithms in forming customer purchase association patterns that can be used as a reference for store owners in planning sales strategies. The data mining process was carried out using Association Rules and Clustering methods. A total of 1256 sales transaction data samples were analyzed to understand the association patterns produced by each method. Based on the test results with a minimum support of 0.2 and a confidence of 0.6, the Apriori algorithm produced 194 association rules with a total rule strength of 1.16. Meanwhile, the FP-Growth algorithm produced 52 association rules with the same total rule strength of 1.16. The Clustering Method resulted in 7 clusters with a similarity value of 0.06322. After comparison, the FP-Growth algorithm proved to have better performance in generating association rules compared to the Apriori algorithm.]]>
<![CDATA[Perancangan Sistem Penggajian Web yang Terintegrasi di PT Hong Xin Printing Equipment ]]>
<![CDATA[Kevin Kevin]]>;
<![CDATA[Prya Artha Widjaja]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 3 (2024): Juli : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i3.155
<![CDATA[PT Hong Xin Printing Equipment is encountering obstacles in improving operational efficiency and managing human resources in the digital age. Despite the use of a fingerprint attendance system, there are concerns about errors and reduced efficiency due to manual data processing. Additional challenges arise when recording attendance for employees on business trips and manually calculating leave. To tackle these issues, the company is planning to create a web-based payroll system that will automate payroll, attendance, and leave management. The implementation of this system is anticipated to enhance efficiency and accuracy, thereby allowing the company to maintain its competitiveness in the market.]]>
<![CDATA[Media Pembelajaran Kimia Berbasis AR ]]>
<![CDATA[Marco Suteja]]>;
<![CDATA[Ary Budi Warsito]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 3 (2024): Juli : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i3.157
<![CDATA[The integration of augmented reality (AR) technology in education is advancing, as seen in a project at Atisa Dipamkara School. This project developed a chemistry learning application using Unity, Android XR Plugin, and ARCore to address laboratory limitations. The app uses interactive 3D visualizations to help students grasp complex chemistry concepts. Blackbox testing showed that all main modules work well, except for a bug in the compound reset module. The app effectively improves students' understanding, interest, and motivation in chemistry, making abstract concepts more tangible. This application is both a learning aid and an educational innovation, promoting a more interactive and enjoyable learning experience.]]>
<![CDATA[Implementasi Teknologi LoRa untuk Monitoring Real-Time Lampu PJU Berbasis Solar Panel ]]>
<![CDATA[Sujono Sujono]]>;
<![CDATA[Moh. Anshori Aris Widya]]>;
<![CDATA[Zakiah Nur Cahya Putri]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 3 (2024): Juli : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i3.166
<![CDATA[In the digital age, public road lighting (PJU) monitoring efficiency is becoming essential for effective infrastructure management. The research developed a PJU monitoring system based on LoRa technology and an Arduino microcontroller to monitor the operating conditions of PJU solar panels in real time. The system uses the LoRa 433 MHz module for remote data communication and is equipped with a voltage sensor to monitor batteries and solar panels as well as an ACS712 current sensor to measure current consumption on LED lights. The data is displayed on an I2C 16x2 LCD screen, making monitoring easy. LoRa technology offers the advantages of broad communication range and low power consumption. The development method used is prototyping, including needs analysis, system design, implementation, testing, and maintenance. Test results show that the system works well, with sensors providing adequate accuracy and LoRa communication enabling remote data access. The system improves the efficiency and accuracy of PJU monitoring, as well as reduces time and effort in the monitoring process. Overall, the system is an effective solution for PJU management in the digital age.]]>
<![CDATA[Diagnosa Penyakit Malaria Menggunakan Metode Case Base Reasoning (CBR) (Studi Kasus: RSUD Djoelham Kota Binjai) ]]>
<![CDATA[Abdullah Husein]]>;
<![CDATA[Rusmin Saragih]]>;
<![CDATA[Husnul Khair]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 4 (2024): Oktober : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i4.211
<![CDATA[The application of information technology has been widely used in medicine. This application provides convenience and smoothness in the medical world to detect symptoms of various diseases, especially malaria. Malaria is still included in the endemic diseases suffered by the community in Binjai City, the more malaria patients, of course the more doctors are needed/work to diagnose patients. Artificial intelligence is one solution and helps doctors in supporting decision making for certain diseases. Building a system to diagnose malaria using the Case-Based Reasoning (CBR) method offers various significant advantages. CBR utilizes experience and knowledge from previous cases, allowing the system to provide a more accurate diagnosis based on patterns and symptoms that have occurred in the past.]]>
<![CDATA[Diagnosa Penyakit Tuber Culosis (TBC) menggunakan Metode Case Based Reasoning (CBR) : (Studi Kasus : RSUD Dr.R.M. Djoelham) ]]>
<![CDATA[Muhammad Reza Habibi]]>;
<![CDATA[Rusmin Saragih]]>;
<![CDATA[Marto Sihombing]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 4 (2024): Oktober : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i4.212
<![CDATA[Tuberculosis (TB) is one of the infectious diseases caused by Mycobacterium tuberculosis bacteria infection in the human lungs. Tuberculosis is a disease that can be transmitted from people with TB through coughing, sneezing, talking, laughing or singing. Lack of public knowledge about TB and lack of funds for health checks make many people late to be treated. Expert systems are technologies developed based on programs, in accordance with human methods and mindsets. This aims to help people who want to check their health, but are hampered by costs, besides saving time if the examination place is far from the residential environment of the community concerned. Expert systems require a method that can help solve existing problems. In this study, the method used is the Case-Based Reasoning (CBR) method, because the main function of this method is to diagnose the disease. The calculation process of the Case-Based Reasoning (CBR) method which looks for the similarity value or proximity of old cases to new cases of a patient.]]>
<![CDATA[Rancang Bangun Kontrol Bel Otomatis Berdasarkan Jadwal Perkuliahan Menggunakan Internet of Things (IoT) ]]>
<![CDATA[Muhammad Ali Imran]]>;
<![CDATA[Achmad Fauzi]]>;
<![CDATA[Husnul Khair]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 4 (2024): Oktober : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i4.225
<![CDATA[The Internet of Things (IoT)-based automatic bell system is designed to enhance the efficiency of bell operations in educational institutions by utilizing modern technology. This research aims to develop a system that can control the bell automatically according to the class schedule, while also enabling remote control via a mobile application using the Blynk platform. The system is built using an ESP8266 as the main microcontroller, a DFPlayer Mini module for audio playback, and an RTC DS1307 for time management. The results show that the system functions as expected, both in automatic mode based on the schedule and in manual mode through the mobile application. Testing and debugging demonstrated that integration with WiFi networks allows for flexible and effective bell control. For further development, it is recommended to add a power backup feature, web interface, and push notifications to improve system reliability and flexibility. This system provides an efficient and practical IoT solution for automating bell operations in educational environments.]]>
<![CDATA[Diagnosa Penyakit Obsessive-Compulsive Disorder Menggunakan Metode Certainty Factor ]]>
<![CDATA[Artika Dini Anggriani]]>;
<![CDATA[Akim M.H. Pardede]]>;
<![CDATA[I Gusti Prahmana]]>
<![CDATA[ Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 4 (2024): Oktober : Modem : Jurnal Informatika dan Sains Teknologi ]]>
Publisher : <![CDATA[Asosiasi Riset Teknik Elektro dan Informatika Indonesia ]]>
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DOI: 10.62951/modem.v2i4.227
<![CDATA[Obsessive-Compulsive Disorder (OCD) is a psychiatric disorder characterized by uncontrollable obsessive thoughts and compulsive behaviors. The disorder triggers anxiety in sufferers that often drives them to avoid situations or places that can trigger obsessions, such as shaking hands or using public restrooms. Proper treatment is necessary to prevent further impact on the quality of life of OCD sufferers. However, early diagnosis is often constrained by limited time and access to medical experts. To overcome this, an expert system based on the Certainty Factor method was developed. This system mimics the thought process of a medical expert in diagnosing OCD using symptoms selected by the user. Certainty Factor is used to calculate the certainty level of each diagnosis based on the inputted symptoms. From the analysis, the system is able to provide diagnoses with high accuracy, even reaching 100% for some OCD cases. These results show that expert systems can be an effective tool in detecting OCD early, thus accelerating the process of proper handling and treatment]]>
