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Tri Anggraeni
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INDONESIA
Journal of Information Technology and its Utilization
Published by Sekolah Tinggi Multi Media Yogyakarta
ISSN : 29854067     EISSN : 2654802X     DOI : https://doi.org/10.56873/jitu
Core Subject : Science, Engineering,
Computer Science & IT Engineering
To explore scientific developments in the field of information technology and its utilization, including data mining, IoT, Artificial Intelligence, Digital Processing, and Information Systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 80 Documents
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Expert System for Pest Diagnosis on Local Black Rice Plant in East Kalimantan Using the Naive Bayes Method Novianti Puspitasari; Anindita Septirini; Rian Bintang Paripurna; Lalu Delsi Samsumar
Journal of Information Technology and Its Utilization Vol 6 No 2 (2023): December 2023
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.6.2.5271

Abstract

Rice plant is a food crop that produces rice as the staple food for the majority of Indonesian people. Local rice which significantly contributes to fulfill the national rice consumption is black rice produced in East Kalimantan. However, local black rice often experiences crop failure due to pest attacks and environmental factors. The amount of local black rice production also continues to decrease due to limited human resources who have the skills and knowledge to diagnose pests in black rice plants. Therefore, one effort that can be made to overcome this problem is to create an expert system that can diagnose pests and diseases in black rice plants. The expert system in this research uses the Naive Bayes method, which identifies 11 types of pests that attack black rice plants and 34 symptoms caused by these pest attacks. Naive Bayes can provide information about the percentage of pests that rice plants might experience. Based on the results of the test cases, an accuracy value of80% was obtained, so the expert system built in this research can diagnose pests on black rice plants quite well.
Implementation of K-means Clustering Algorithm to Analyze the Familial Sentiments Towards COVID-19 Vaccination For Elementary School Students in Kalawat District Indah Kairupan; Liza Wikarsa; Audreyvia Kembuan
Journal of Information Technology and Its Utilization Vol 6 No 2 (2023): December 2023
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.6.2.5280

Abstract

Due to the Ministry of Health's policy, the Indonesian government mandates the public to receive the COVID-19 vaccination as a form of immunity against the coronavirus. This vaccination is not only for adults but also for children of a certain age. Regarding the provision of vaccination for elementary school students aged between 6 to 11 years, the families' responses to this predicament can cause significant barriers to those students being fully vaccinated. Thus, this research developed a web-based application that incorporated the K-means clustering method to group the sentiments of the families into three clusters, namely positive, neutral, and negative. The results showed that the application can identify and cluster the different familial responses from 279 respondents in Kalawat District toward the administration of COVID-19 vaccination to their underage children. The most dominant familial sentiment is positive followed by neutral and negative sentiments with the number of respondents as many as 120 respondents (43%), 113 respondents (41%), and 46 respondents (16%) respectively. This research can help the Health Office in North Minahasa Regency to evaluate public sentiments about vaccination for elementary school students as well as look for better ways to encourage vaccine trust and confidence in this district.
Geographical Information System for Mapping Flood-Prone Areas in Manado City Using the K-Means Clustering Method Aurelia Koagouw; Debby Paseru; Indah Kairupan
Journal of Information Technology and Its Utilization Vol 7 No 1 (2024): June 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.1.5403

Abstract

Floods are natural events or phenomena that can cause environmental damage, loss of property, psychological effects, and death or casualties. One way to control flooding non-structurally is by mapping areas that are prone to flooding. This study builds a geographic-based information system to map flood-prone areas in Manado City using the K-Means Clustering algorithm. The main objective of this research is to identify and map areas with a high risk of flooding using spatial data. Slope, land cover type, soil type, water discharge (discharge), and rainfall are independent variables that will be used and processed using the K-Means Clustering algorithm. There are four clusters in the mapping results of flood-prone areas, namely: high vulnerability, medium vulnerability, low vulnerability, and not vulnerable. By using the K-Means method, the results obtained are Paal Dua and Wenang sub-districts are high-vulnerability groups, followed by Mapanget, Tuminting, and Singkil subdistricts with medium vulnerability groups. Tikala District is the only area with low vulnerability. Meanwhile, Bunaken, Sario, Wanea, and Malayayang sub-districts are areas that are not potentially prone to flooding.
Application of Importance Performance Analysis Method for Service Identification in the Learning Process Michael George Sumampouw; Liza Wikarsa; Axl Marselino Rumondor
Journal of Information Technology and Its Utilization Vol 7 No 1 (2024): June 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.1.5577

Abstract

The learning process is a series of activities and interactions that occur as individuals acquire new knowledge, skills, attitudes or understanding through various means. Responses and feedback in the context of the classroom, practical experience or other learning resources are integral to this process. The Importance Performance Analysis (IPA) method is used to identify, measure, and evaluate the importance and performance of components in a system or organization. This study proposes a web-based application, namely Application of Importance Performance Analysis Method, to digitize the process of identifying service attributes in learning at the Faculty of Engineering, De La Salle Catholic University Manado. Using the IPA method, this application assists decision makers in formulating effective strategies and policies to improve the quality of education. The method used to develop this application is the Rapid Application Development method. This solution overcomes complicated data processing problems and provides convenience in compiling reports on the learning process every semester.
Peningkatan Cakupan Indoor dengan Femtocell dalam Jaringan 5G pada Frekuensi 3500 MHz Menggunakan Radiowave Propagation Simulator Desi Rianti; Muntaqo Alfin Amanaf; Alfin Hikmaturokhman; Ade Wahyudin
Journal of Information Technology and Its Utilization Vol 7 No 1 (2024): June 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.1.5610

Abstract

In the landscape of 5G mobile networks in Indonesia, one of the prominent frequency candidates is 3.5 GHz. The frequency is anticipated to be the initial choice for operators to deploy 5G networks. The research focuses on designing an indoor cellular network to address indoor network degradation issues using Small Cells, specifically Femtocells, within buildings such as schools, companies, hospitals, and airports. The design is implemented at PT. Sutanto Arifchandra Electronic (PT. SAE) based on the COST 231 Multi-Wall Propagation model using the Radiowave Propagation Simulator (RPS) 5.4 application. The required parameters for designing the indoor cellular network include residential building specifications and a Link Budget parameter to determine the number of Femtocell Access Points needed to cover all areas adequately. The coverage calculations determined that 2 Femtocell Access Points are required. The simulation uses three scenarios, with the optimal outcome observed in scenario 2 (employing 2 Femtocell Access Points positioned on the middle right and left sides of the walls). This scenario yields a signal power level of -25.60 dBm and a Signal to Interference Ratio (SIR) of 14.80 dB.
CLUSTERING THE HAPPINESS LEVEL OF PROVINCES IN INDONESIA USING K-MEANS Heti Mulyani; Ricak Agus Setiawan
Journal of Information Technology and Its Utilization Vol 7 No 2 (2024): December 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.2.5854

Abstract

Community welfare is a government goal related to the fulfillment of basic needs, education and employment, which can be measured through the happiness index. The purpose of this research is to cluster provinces in Indonesia based on their resident’s happiness level. The data obtained from the Indonesian Central Bureau of Statistics website. The method used in this research is K-means clustering. There are 2 dimensions used, namely the personal dimension which includes education, employment, household income, health, housing conditions and, assets. The social dimension includes social relations, environmental conditions, security conditions, family harmony, and availability of free time. Based on the results of the study, 2 provincial groups were obtained based on the level of happiness. Testing is done using the Davies Bouldin Index (DBI). The optimal K is obtained, namely K = 2 with a DBI value of = 0.776. The first group is the happiest group including the provinces of North Maluku, Maluku, North Sulawesi, North Kalimantan, Gorontalo, Central Sulawesi, West Papua, Riau Islands, East Kalimantan. The other provinces are in the second group. The unhappiest groups are Banten, Bengkulu and Papua.
Mountain Selection for Beginner Climbers:a Simple Additive Weighting (SAW) Method Liza Wikarsa; Michael George Sumampouw; Christofel Mario Tore
Journal of Information Technology and Its Utilization Vol 7 No 2 (2024): December 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.2.5859

Abstract

Over the years, mountain climbing has become more popular among ordinary people, with interest suddenly spiking during this recent time. A well-prepared and route-knowledgeable climber is most likely to win half the battle. The task of selecting a mountain for first-time climbers can be a daunting one. The Simple Additive Weighting (SAW) method can help beginner climbers determine which mountain is best for them. This method enables users to assign weights to each criterion and alternative based on their preferences, facilitating direct comparisons between options, and calculating all possible combinations, making the process faster and more accurate. According to this study, a campsite, mountain height, natural resources, mountain beauty, and terrain difficulty are major factors to consider when choosing a mountain. The alternatives consist of six mountains in North Sulawesi—Mount Klabat, Lokon, Soputan, Mahawu, Empung, and Tampusu—assessed according to the established criteria. In conclusion, the Decision Support System using the SAW method was successfully developed to help beginner climbers choose mountains based on their preferences. This system includes features such as mountain search, SAW calculations, and top recommendations. Future updates could consist of more detailed mountain specifications and a broader selection of mountains.
An Assistive Technology for A Deaf Student: Many-to-One System Using Button Board Speech-to-Image Based On Microcontroller ESP8266 Kristian Dame; Lianly Rompis; Julie Rante; Ryan Singgeta
Journal of Information Technology and Its Utilization Vol 7 No 2 (2024): December 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.2.5865

Abstract

Education is the right of every nation and society including disable students which have physical, emotional, mental, intellectual and social disorders. In an effort to facilitate proper education for students with special needs, especially deaf students, our research team consisting of permanent lecturers from Electrical Engineering Study Program Universitas Katolik De La Salle Manado were called to care and commit to conduct research on assistive technology for deaf students. Our team designed and created a Button Board Speech-to-Image tool based on the ESP8266 microcontroller which is intended for Deaf Students to make it easier for them to communicate and interact with teachers while in class, especially during exams or learning process activities. The research method used for this research was system design and data mining. The assistive technology development method used is Research and Development (R&D). The inputs on the Button Board were processed into sound (speech) which was sent to the recipient wirelessly so that what the Deaf Student wants to convey in class can be understood by the Teacher through the speaker. The assistive technology development method used is Research and Development (R&D). The technology operates well with WiFi network and well accepted for learning process and communication.
PENENTUAN PRIORITAS PEMBANGUNAN DESA RENGEL BERBASIS SISTEM PENDUKUNG KEPUTUSAN DENGAN METODE FAHP-WP Izra Noor Zahara Aliya; Rizka Hadiwiyanti; Reisa Permatasari
Journal of Information Technology and Its Utilization Vol 7 No 2 (2024): December 2024
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.7.2.5887

Abstract

Villages play a strategic role in national development, particularly in improving the quality of life and community welfare. Rengel Village, located in Tuban Regency, East Java, holds significant potential for development. However, decision-making in development through the “Musrenbangdes” (village development planning forum) is often hindered by conflicts of interest between neighborhood units (RT and RW) and the lack of an objective system to assess priorities. Therefore, a Decision Support System (DSS) utilizing the Fuzzy Analytic Hierarchy Process (F-AHP) and Weighted Product (WP) methods is needed to prioritize development. F-AHP determines criterion weights based on relative importance and addresses uncertainty in assessments, while WP ranks alternatives based on these weights. This study involves data collection, calculation of criterion weights, alternative development ranking, system development, and deriving conclusions. The results show that the CR value of 0.033 indicates a good level of consistency in comparisons, yielding the following criterion weights: RPJM (0.331), Urgency Level (0.278), Impact and Benefits (0.237), Regulatory Compliance (0.14), and Budget (0.014). Meanwhile, the alternative development ranking results indicate the following priority order: AP41 (1), AP06 (2), AP33 (3), AP49 (4), AP12 (5), AP40 (6), AP13 (7), AP11 (8), AP43 (9), and AP28 (10).
Learning Difficulty Levels Prediction of Elementary School Student Mathematics Using Machine Learning Model Rismayani, Rismayani; Sambo Layuk, Novita; Patasik, Madyana; Endang, Andi Hutami
Journal of Information Technology and Its Utilization Vol 8 No 1 (2025): June 2025
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.8.1.5906

Abstract

Difficulty learning mathematics in elementary school students is a significant problem and requires serious attention. This study aims to predict the difficulty level in elementary school students learning mathematics using a machine learning model, namely KNN. Exam scores, assignments, quizzes, and characteristics of students' difficulty level in learning mathematics were used as data in this study. A study used the KNN model to divide students into three categories of difficulty in learning mathematics: easy, moderate, and challenging. The results showed that the KNN model can accurately predict student’s difficulty levels in mathematics. Thus, applying this model can help teachers provide appropriate and effective interventions to students experiencing difficulties. Using machine learning technology, especially the KNN model, we found an accuracy of 95%. In addition, we can still accurately predict the difficulty level of elementary school students' mathematics learning. This study uses anonymous student data, the distribution of assignments, quizzes, and exam score ranges, and characteristics of mathematics learning difficulty levels. There are three prediction classes: high, medium, and low.

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