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Jurnal Sistem Komputer dan Informatika (JSON)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : -     EISSN : 2685998X     DOI : https://dx.doi.org/10.30865/json.v1i3.2092
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
The Jurnal Sistem Komputer dan Informatika (JSON) is a journal to managed of STMIK Budi Darma, for aims to serve as a medium of information and exchange of scientific articles between practitioners and observers of science in computer. Focus and Scope Jurnal Sistem Komputer dan Informatika (JSON) journal: Embedded System Microcontroller Artificial Neural Networks Decision Support System Computer System Informatics Computer Science Artificial Intelligence Expert System Information System, Management Informatics Data Mining Cryptography Model and Simulation Computer Network Computation Image Processing etc (related to informatics and computer science)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 492 Documents
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Web-Based Academic Information and Monitoring System at Kudus State Madrasah Ibtidaiyah Putri, Sevara Humaira; Rhoedy Setiawan; Yudie Irawan
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 1 (2025): September 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i1.9070

Abstract

This research is based on the needs of Madrasah Ibtidaiyah Negeri Kudus to improve communication and academic management in the digital age. The main issues raised are suboptimal grade recording systems, absenteeism, and the rapid and structured dissemination of important information. The objective of this research is to create and develop a web-based academic information system that can be monitored via WhatsApp. This system will enable teachers, parents, and school administrators to easily access information. The Waterfall software development model, which consists of the stages of needs analysis, design, implementation, testing, and maintenance, is the methodology used in this research. Data was collected through interviews and direct observation of academic activities on the school campus. This system enables the recording of student grades and attendance data on a daily basis. It also allows parents to receive automatic notifications about learning activities, class schedules, and other important information. This research resulted in a web-based application that has the ability to improve academic recording and reporting, enhance communication between schools and parents, and support real-time transparency of academic information. By using this system, the State Elementary School in Kudus is expected to be better prepared to face the digital transformation occurring in the world of education.
Perbandingan Algoritma Naive Bayes, Decision Tree, dan KNN untuk Klasifikasi Produk Populer Adidas US dengan Confusion Matrix Firdaus, Lazuardi; Setiadi, Tedy
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6124

Abstract

Adidas America, Inc. (also known as Adidas US) is a company that produces shoes, clothing, and accessories as a subsidiary of Adidas AG, which is known worldwide for its trademark three stripes on its products. Product popularity is very important in increasing sales, especially for products that are frequently purchased, positively reviewed by customers, and reviewed by customers. In this case, there are Adidas US products whose popularity is still unknown. Therefore, in this case, popular Adidas US products will be classified as business needs of Adidas US. The classification algorithm used to classify popular products is Naive Bayes, Decision Tree, and KNN for classifying the popularity of Adidas products in the United States using the CRISP-DM method on the dataset. The data mining process is performed to discover patterns in the data set with the stages of business understanding, data pre-processing, and classification modeling with three different algorithms. The results of the three algorithms are tested with a confusion matrix, and the highest accuracy value is achieved by Decision Tree with 92.42%, making it the best algorithm for classifying popular Adidas US products.
Pemanfaatan Metode Decision Tree dengan Algoritma C4.5 Untuk Prediksi Potensi Kunjungan Wisatawan Iman, Hadad Karsa Nur; Latifah, Noor; Supriyono, Supriyono; Nugraha, Fajar
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.6684

Abstract

This research aims to predict potential tourism visits in Pati Regency, Indonesia, utilizing data mining methods, specifically the Decision Tree with the C4.5 algorithm. The significance of the tourism sector in a region's economy and sustainability, along with the potential of data in formulating more effective and targeted strategies and decisions, motivated this objective. The initial experiment results demonstrated the superior performance of the Decision Tree C4.5 method in predicting potential tourism visits in Pati Regency, with an accuracy of 96.42%, precision of 96.42%, and recall of 96.66%. This performance exceeded the Naive Bayes method, which yielded an accuracy of 82.14%, precision of 84.49%, and recall of 83.07%. The research highlights the potential of data mining methods in the tourism sector, especially for predicting tourism visits. The results are expected to assist stakeholders in formulating more effective strategies and decisions, contributing positively to the wider development of the tourism sector.
Sistem Pendukung Keputusan Seleksi Data Terpadu Kesejahteraan Sosial Menggunakan Metode K-Means dan SAW Praningki, Tutus; Poernomo, Moyo Hady; Suban, Ignasius Boli
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6845

Abstract

Indonesia as a developing country cannot be free from problems related to poverty, Some people still have income that is not sufficient for a decent life. The Indonesian government has several programs that are useful for reducing poverty, namely the Bantuan Pangan Non Tunai (BPNT) atau Program Keluarga Harapan (PKH). Often in the process of distributing aid there are obstacles or problems, the obstacle that often arises is determining the right family to receive assistance. Sub-districts or villages are at the forefront of the data collection process and selection for recommendation into the Data Terpadu Kesejahteraan Sosial (DTKS). This research aims to develop an application product that can help the Ngronggo Kediri sub-district to accurately determine which families are entitled to assistance. The K-Means and SAW methods are used to determine which families are included in the DTKS. The K-Means method is used for the clustering process and SAW is used for the weighting process. The final weight shows that the highest recommended family weight is 91,2%, and the lowest is 51.4%.
Analisis Perbandingan Kinerja Clustering Data Mining Untuk Normalisasi Dataset Saqila, Siti Emalia; Ferina, Intan Putri; Iskandar, Agus
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6919

Abstract

Nowadays, the development and influence of technology in human life is very important, where the role of technology greatly influences the activities carried out by humans. In a company organization, technology is not only used as a process to speed up the processes carried out. The use of such important technology also increases the size or volume of available data information. A dataset is a collection of data obtained in a data warehouse. Data mining is a technique that is part of Knowledge Discovery in Database (KDD). Clustering is a grouping process carried out in data mining. The first problem that is central to the research is that the values obtained from the clustering process are sometimes still not considered optimal. The performance results of the data mining clustering algorithm cannot yet be fully used as a basis for decision making. Comparisons made in clustering data mining are used to assist in the decision making process. In this research, the algorithms that will be used for comparison of performance are the K-Means and K-Medoids algorithms. Another problem that needs special attention is the problem of data quality. The results obtained from the data mining process can be seen from the quality of the data stored or used in the data processing process. Normalization is part of preprocessing data mining which aims to re-reason it based on a new scale. Z-Score is a normalization carried out on data based on statistical functions. The results obtained in the research The role of normalization in the research is very important, this is because using Z-Score normalization can improve the performance of the K-Means and K-Medoids algorithms, this can be seen from the DBI value obtained which is smaller when normalization is carried out compared to before it is carried out normalization, which indicates that performance is better after normalization. In the comparison of algorithms, the K-Medoids algorithm gets better performance, this can be seen from the DBI value obtained at 0.773 at K=9 after normalization. Meanwhile, the K-Means algorithm obtained a value of 0.783 at K=9 after normalization as well
Penerapan Metode EXPROM II Dalam Menentukan Tempat Wisata Pantai Terbaik Mesran, Mesran; Triayudi, Agung; Nofrisa, Dini; Fadillah, Rizkah
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6925

Abstract

Tourism is an activity or activity carried out by humans in order to find pleasure or provide space for themselves to rest themselves from daily fatigue. The word tourism describes the expression of pleasure for someone who will enjoy a holiday by going somewhere. Many beaches in Indonesia in various regions make people confused in choosing which place to visit while on vacation. To assist visitors in choosing which beaches should be visited, a system is needed. A good system used in this problem is a decision support system. A decision support system is a system that has the same working procedures as a computer system. DSS requires a method. The method used in this study is the EXPORM II method. The EXPORM II method is a modified method of the PROMITHE II method. Where the EXPORM II method is easier than the PROMITHE II method. However, it has the same accurate results as the PROMITHE ll method. The results of this study are that the best alternative is Cemara Kembar Beach as an alternative to A7 with a value of 0.69889 which in the end is suggested to be the best beach resort.
Implementasi Dempster-Shafer Theory Sebagai Mesin Inferensi Pada Sistem Pakar Diagnosa Penyakit Cerebral Palsy Erkamim, Moh.; Tonggiroh, Mursalim; Munti, Novi Yona Sidratul; Rahmanto, Yuri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6940

Abstract

Early diagnosis and appropriate intervention are very important to minimize the long-term impact of Cerebral Palsy in children. Currently, the diagnosis of Cerebral Palsy in children is often based on clinical observations, developmental tests, and brain imaging. It requires medical knowledge and careful observation by an experienced health professional, which is often difficult to access in many areas. For this reason, early diagnosis by parents is very important for taking action against children suffering from Cerebral Palsy. This research aims to develop an expert system that can diagnose Cerebral Palsy in children using the Dempster-Shafer Theory algorithm as an inference engine to make it easier to diagnose and produce the right diagnosis. The Dempster-Shafer Theory approach works by calculating the level of confidence or belief in a hypothesis or certain event based on existing evidence. An expert system built on a website has the ability to make diagnoses based on symptoms and display diagnosis results, definitions of the type of Cerebral Palsy disease in children, as well as actions or methods of treating it. Based on the test results, the accuracy level obtained was a value of 90% and was classified as "Good" criteria.
Otomatisasi Pengontrolan Kualitas Air Pada Akuarium Ikan Arwana Berbasis IOT Menggunakan Logika Fuzzy Tsukamoto Nurhadi, Ade Muhamad; Midyanti, Dwi Marisa; Suhardi, Suhardi
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6947

Abstract

Arowana fish is an ornamental fish that has a beautiful body shape and color that makes it have a high price, and requires excellent care. The quality of the water in the aquarium must be maintained so that the Arowana fish are not stressed, sick, or die. However, many Arowana owners do not monitor water conditions closely. Therefore, a system is needed that can monitor the state of the aquarium environment, including automatic and manual water changes from the website. In this study using Arduino uno as a microcontroller connected to a pH and turbidity sensor, then NodeMCU ESP32 was used to send data to the internet and to perform the calculation process of Tsukamoto's fuzzy logic. The test results obtained an average accuracy on pH sensors of 96.62%, on turbidity sensors an average accuracy of 92.84%, on ultrasonic sensors an average accuracy of 99.62%. The system also tested Tsukamoto's fuzzy logic where the results were fuzzy with an accuracy of 83%. Testing of the system as a whole was carried out for 4 days. From the tests carried out, the average water pH per day results are 7.1 and turbidity of 18 NTU and all water quality conditions can be met according to the desired output using 9 rule bases.
Implementasi Speech Recognition Menggunakan Long Short-Term Memory untuk Software Presentasi Adhitama, Satriya; Avianto, Donny
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6950

Abstract

Presentation is one of the methods for delivering thoughts, ideas, and concepts to an audience verbally. Presentation activities can be supported by presentation software that can be used to organize the sequence of material to be presented with visually appealing visuals. Operating presentation software requires technical assistance such as a remote, mouse, keyboard, and even a personal assistant, which can be distracting to the presenter as it limits their freedom in delivering the material. This distraction can be addressed through the implementation of speech recognition as a command to operate presentation software, making it easier for the presenter. A speech recognition system is developed using Long Short-Term Memory (LSTM), which can handle the issues of long-term dependency and vanishing gradient associated with Recurrent Neural Networks (RNN). There are 10 command words used to operate the presentation software. LSTM demonstrates superior performance when compared to alternative techniques like DNN, CNN, and SimpleRNN, achieving a training accuracy of 96.5%, a validation accuracy of 94.8%, and a testing accuracy of 94%. The LSTM method can be effectively used for sequential data to recognize real-time speech.
Sistem Keamanan Kendaraan Bermotor Berbasis IoT dan Web dengan Fitur Pelacakan GPS dan Pemutusan Aliran Listrik Secara Otomatis Hidayat, Tofiq Nur; Ardiani, Farida
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.6956

Abstract

In general, motorcycle vehicles only have security such as conventional safety locks or only an alarm system. Unlike vehicles such as modern cars that already have GPS (Global Positioning System) devices. There are many ways to improve motorized security systems, one of which is embedding GPS devices in vehicles that do not yet have similar security. So Internet of Things (IoT) technology and GPS devices such as Ublox Neo are used to help monitor the whereabouts of vehicles in real time. IoT technology allows smart sensors to be connected to the internet network. Tracking systems that use IoT can utilize data from sensors to provide information to users about the whereabouts of their vehicles. the use of this technology aims to increase efficiency and security on vehicles so that cases of vehicle theft rates can be suppressed. The results of the test there are several conditions when the device cannot work properly. However, 80% of the test results show the success of the device in tracking vehicles. The average response time in receiving satellite data is about 1-5 seconds. The user can also turn off the vehicle so that the user can more easily chase the perpetrator so as to minimize the occurrence of vehicle theft. the response time of the device in turning off the vehicle is about 5-10 seconds due to alternating in sending and receiving data with the GPS module. It is hoped that criminals who steal vehicles will find it more difficult to steal motorcycles equipped with IoT-based security systems.

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