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Jurnal Riset Informatika

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Published by KresnaMedia Publisher

ISSN : 26561743 EISSN : 26561735 DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal Riset Informatika, merupakan Jurnal yang diterbitkan oleh Kresnamedia Publisher. Jurnal Riset Informatika, berawal diperuntukan menampung paper-paper ilmiah yang dibuat oleh peneliti dan dosen-dosen program studi Sistem Informasi dan Teknik Informatika.

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Articles 432 Documents

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SENTIMENT ANALYSIS OF MENTAL HEALTH REVIEWS USING MACHINE LEARNING ALGORITHMS Wati, Risa; Ernawati*, Siti
Jurnal Riset Informatika Vol. 8 No. 1 (2025): Desember 2025
Publisher : Kresnamedia Publisher

Mental health is a significant issue in the modern era due to lifestyle changes, social pressures, and technological advancements that introduce new challenges. These problems affect various aspects of life, including education, employment, social relationships, and overall quality of life. Technological development enables the use of machine learning to automatically classify large amounts of data. This study aims to analyze and compare the performance of Support Vector Machines (SVM), K-Nearest Neighbor (K-NN), Naïve Bayes (NB), Logistic Regression (LR), Decision Tree (DT), and Random Forest (RF) in sentiment classification on mental health issues, while simultaneously contributing to scientific development and supporting the understanding of public psychological conditions. The dataset used in this research was obtained from Kaggle and consists of 20,364 mental health–related reviews in .CSV format, processed using Google Colab with the Python programming language. The data were categorized into two groups—depression and suicidewatch—and then underwent preprocessing, data splitting into training and testing sets with an 80:20 ratio, and TF-IDF weighting. The results indicate that the SVM algorithm outperforms the other methods. Using an RBF kernel and a C parameter of 15, SVM achieved an accuracy of 72.09%, a precision of 72.11%, a recall of 72.09%, and an F1-score of 72.09%. This study not only provides scientific contributions but also supports efforts to better understand the psychological conditions experienced by society.

DETERMINATION OF PRIORITIES OF ELEMENTARY SCHOOL REHABILITATION AT ASAHAN USING SIMPLE ADDICTIVE WEIGHT Dian Aprillia; William Ramdhan; Wan Mariatul Kifti
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

In the budgeting process for school building rehabilitation activities in Asahan Regency, there are still inaccuracies in selecting prioritized primary schools for rehabilitation. This study aimed to apply the Simple Additive Weighting (SAW) method to determine five primary schools that were prioritized for repair. This research method uses quantitative methods. The data source comes from the East Kisaran and West Kisaran Elementary Schools. The data were analyzed using the SAW method based on the criteria weight depending on the matrix value and normalization. The results showed the 5 largest criteria weights, namely UPTD SDN 010097 Selawan (0.940), UPTD SDN 014689 Lestari (0.884), UPTD SDN 010039 Sentang (0.880), SD Taman Kasih Karunia (0.847), and UPTD SDN 018453 Siumbut-Umbut (0.820). ). This study concluded that the double exponential smoothing method could make it easier to determine which primary school decisions are prioritized for rehabilitation.

CLASSIFICATION OF COFFEE LEAF SPOT DISEASES USING THE RESIDUAL NEURAL NETWORKS Pinasthika, Stanislaus Jiwandana; Hizham, Fadhel Akhmad; Harvyanti, Annisa Fitri Maghfiroh
Jurnal Riset Informatika Vol. 8 No. 2 (2026): Maret 2026
Publisher : Kresnamedia Publisher

Coffee is one of the competitive commodities that requires detailed quality control. The common diseases that attack coffee plants are miner, rust, and phoma. Despite their visual similarity, the diseases differ in symptoms and treatments, requiring precise identification aided by computer vision. Miner and phoma have similar image features that are challenging in this study. Avoiding treatment error, several deep learning approach is needed to help classify the diseases. One of the robust methods is the Residual Network. Considering the number of datasets and alignment with the state-of-the-art, this study picked ResNet50 and ResNet101 to be observed. This study employed ResNet50 and ResNet101 in two scenarios. The first scenario was training the models on datasets without preprocessing, while the second scenario trained models on processed datasets. The preprocessing involved converting the color model to HSV and taking the range of leaf spot color from light red to dark brown for color segmentation. This study successfully achieved accuracy, precision, and F1-score at 89,16%, 89,42%, and 89,15% respectively, for the ResNet50 model trained on preprocessed data, slightly higher than the metrics of ResNet101. The ResNet101 achieved 87.95% of accuracy, 88.05% of precision, and 87.98% of F1-Score. These results indicate that ResNet50 is more robust for classifying the leaf spot, and the color segmentation helped the model to optimize the performance

IMPLEMENTATION OF SIMPLE ADDITIVE WEIGHTING TO DETERMINE THE BEST EMPLOYEES IN THE CAMAT TINGGI RAJA OFFICE Cindy Eka Putri; Havid Syafwan; Muhammad Ihsan
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

Decision-making for the best employees in Camat Tinggi Raja Tinggi Office requires objective and transparent considerations to select the best employees. This study aimed to apply the Simple Additive Weighting (SAW) method to determine the best employees in Camat Tinggi Raja Tinggi Office. This research method used quantitative methods. The data collected was in the form of employee data of the Raja Tinggi Subdistrict Office in the form of names, attitudes, work discipline, loyalty, responsibilities, and task completion. Data were analyzed using the SAW method based on preference values. The results showed that the employee with the name S had the highest preference value, 0.88. This research concludes that the SAW method decides the best employee in Camat Tinggi Raja Tinggi Office, namely the employee with the name S

IOT-BASED HOME AUTOMATION USING NODEMCU ESP8266 Paulus K A Windesi; Mingsep Rante Sampebua; Remuz MB Kmurawak
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

Home automation is an automation technology that focuses on managing circuits and electronic equipment in homes, offices, and others. Home automation is a form of Internet of Things (IoT) development that allows communication and control through devices while connected to the internet. This study aims to design a Home Automation prototype on lighting devices such as lamps, light sensors to activate lights, and several lights controlled using mobile devices. The research method uses the prototype method, where system development is focused on the results of input from customers who will be evaluated for software development. The stages in this research begin with analyzing device requirements, literature study, system design, hardware design, user interface design testing, and arriving at the results. This research output will be made in the form of a prototype, where all components will be placed based on the layout described in the design. This system can help users control the equipment in the house from anywhere and anytime, including using light sensors to provide input to turn the lights on or off.

BITCOIN PRICE VOLATILITY ANALYSIS: A DEEP LEARNING APPROACH TO X (FORMERLY TWITTER) SENTIMENT Puji Astuti; Sidiq Endrasmoyo, Rangga; Syawalluddin; Fitria, Yesi; Budiyono, Pungkas
Jurnal Riset Informatika Vol. 8 No. 1 (2025): Desember 2025
Publisher : Kresnamedia Publisher

This study investigates the relationship between social media sentiment and Bitcoin price volatility using advanced natural language processing techniques. We collected X data from April 10-29, 2025, analyzing cryptocurrency-related tweets alongside Bitcoin price movements obtained through the CoinGecko API. Five sentiment analysis methodologies were comparatively evaluated: VADER, TextBlob, BERTweet, RoBERTa Base, and RoBERTa Large. Bitcoin price volatility was measured using log returns to capture market fluctuations accurately. Correlation analysis revealed significant differences in methodological effectiveness. Traditional lexicon-based approaches (VADER and TextBlob) demonstrated weak correlations with volatility (r = -0.2232 and r = -0.0710 respectively). Transformer-based models showed superior performance, with RoBERTa Large achieving the strongest correlation (r = 0.4569, p = 0.0428), representing the only statistically significant relationship. The positive correlation indicates that increased social media sentiment corresponds to higher Bitcoin price volatility rather than directional price movements. These findings demonstrate that sophisticated deep learning models can effectively capture sentiment-driven market dynamics, providing valuable insights for cryptocurrency investors, trading platforms, and market analysts seeking to understand social media influence on digital asset markets.

SMART DOOR LOCK SYSTEM DEVELOPMENT PROTOTYPE USING RFID TECHNOLOGY ID-12 Siti Aisyah; Yusmar Ali; Komda Saharja; Suhendra Suhendra; Asrul Sani
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

This innovative door lock system is designed to make it easier to control security in certain homes or rooms. This system can also be used in government offices and factories to restrict someone from entering a room that just anyone can not enter. In this system, the automatic door lock uses an ID-12 type RFID reader, Tag/Transponder, Arduino UNO R3, 5v Buzzer, Drop Bolt Lock, Relay Module, and LCD. The RFID reader ID-12 is used as a receiver, and the tag/transponder as a transmitter. This system works when the scanned RFID tag/card/transponder sends hexadecimal data to the RFID Reader ID-12, which then, from the RFID Reader, will receive and send data to the Arduino. Then the Arduino UNO will process it by reading the program module (data from the RFID tag/card/transponder) and giving commands to the buzzer to make a sound or notification. The relay module is a connector or breaker for the deadbolt lock or solenoid to open and lock the door and a 16x2 LCD to display the status of the scanned RFID card. On standby, the LCD displays the words "Smart Door Lock Scan Your RFID." When the scanned RFID card is registered and the bolt lock or solenoid is open, the LCDs the words "Welcome". When the scanned RFID card is not registered, and the drop bolt lock or solenoid is not open, then the words "Your Card is Unregistered." The push button is used to reset the Arduino when the Arduino is hanging and when the 16x2 LCDs have an error display

ANALYSIS OF CONTENT MANAGEMENT SYSTEM DEVELOPMENT FOR TAMAN MINI ONLINE TICKETING LANDING PAGE Sahid Triambudhi; Ihsan Doni Irawan; Faisal Yusuf Fadhilah
Jurnal Riset Informatika Vol. 8 No. 1 (2025): Desember 2025
Publisher : Kresnamedia Publisher

Taman Mini Indonesia Indah (TMII), an iconic Indonesian cultural theme park focusing on education and recreation, exhibits high promotional and event dynamics post-revitalization, necessitating its online ticket sales landing page (tiket.tamanmini.com) to present updated information rapidly. Despite having an efficient booking system for transaction management, TMII's main landing page faces a serious operational constraint: every addition of a new ticket (ticket ID), modification, or creation of a new menu section must be executed via manual source code modification (hard code). This practice causes significant inefficiency, delays in publishing promotional tickets (e.g., school holiday bundles), and high risks of errors, directly impacting business revenue potential. This research aims to conduct a comprehensive needs analysis for designing a dedicated Content Management System (CMS) module for TMII's ticket sales landing page, thereby eliminating the reliance on hard coding. The methodology employed is qualitative descriptive, using observation and interviews with the website and operational management teams for data collection. The primary result of this analysis is a detailed specification of the functional and non-functional requirements for the CMS module, including independent CRUD (Create, Read, Update, Delete) capabilities for tickets and banners. The CMS design is expected to significantly enhance the operational efficiency of the management team, ensure content accuracy, and accelerate business response to market opportunities, ultimately making content management for online tickets independent and efficient.

APPLICATION LIDAR AND POINT CLOUDS FOR 3D MODELING OF MUSEUM OBJECT Ika Asti Astuti; Ahmad Subekti
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

A museum is an institution intended for the general public that collects, cares for, presents, and preserves the community's cultural heritage for study, research, and pleasure or entertainment. The museum is undoubtedly one of the educational places for the community because it has many historical objects. It provides an opportunity to make the museum a vital place to be developed in a virtual form, such as Augmented Reality or Virtual Reality. However, one problem in developing virtual media is the 3D modeling of objects for interior design in museums. LiDAR (Light Detection And Ranging) is a near real-time 3D positioning technology. A point cloud collects data points in a 3D coordinate system, generally defined by x, y, and z coordinates. Both of these technologies can be used to create 3D object models quickly. The final result of this research is applying LiDAR & point cloud as a 3D modeling technique and assessing the accuracy of using these techniques for 3D modeling of the museum object

ASSESSMENT EFFECTIVENESS ANALYSIS SYSTEM USING G-FORM WITH TAM METHOD AT SD GALATIA3 JAKARTA BARAT Asrul Sani; Agus Budiyantara; Rizaldy Khair; Siti Aisyah
Jurnal Riset Informatika Vol 4 No 4 (2022): Period of September 2022
Publisher : Kresnamedia Publisher

In late December 2019 it took the world by storm by transmitting very quickly through the human respiratory tract. Since this happened the World Health Organization (WHO) has stated that Covid-19 is called a pandemic. The Covid-19 outbreak affects almost all aspects of life, including the aspect of education in Indonesia, which is also not spared from the Covid-19 outbreak and also feels the consequences of the spread of the virus. Students feel the impact of the spread of Covid-19 such as changes in the provision of services in educational institutions, such as formal education at all levels, non-formal education, to academics (Baety and Munandar 2021). Based on the announcement of the Ministry of Education and Culture Number 4 of 2020 concerning the Implementation of Education Policies during the Emergency Period of the Spread of the Coronavirus (Covid-19). The government began to implement an online learning system (online). The problem that arises during this online learning period is that there are still many people who are not ready to face technology, both in terms of teachers and students, this happened in the early days of the pandemic. So that the learning process that has been carried out normally, both in terms of teaching and providing assessments, also experiences obstacles. This is because the teaching staff (teachers) always have daily assessment data that is usually carried out daily during normal learning. However, during this PJJ period, teachers became confused about giving daily assessments to their students. The purpose of the research is to analyze and evaluate the online learning system using a platform that is easy to operate by teachers and can be accessed anywhere, namely, google form. In the Google Form application, there is an automatic calculation system in the form of student feedback where teachers do not bother to manually calculate the results of student learning evaluations (Munawaroh, Prastowo, and Nurjanah 2021). The analysis method used is the Technology Acceptance Model (TAM) which is able to find out the attitudes of users towards the technology used, so that teachers can easily find out whether the tasks given to students are done by the students themselves, not the help of parents.

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Tati Mardiana

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