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Andry Fajar Zulkarnain
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JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat)
Published by Universitas Lambung Mangkurat
ISSN : 25275399     EISSN : 25282514     DOI : http://dx.doi.org/10.20527
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) is intended as a media for scientific studies on the results of research, thinking and analytical-critical studies regarding research in Systems Engineering, Informatics / Information Technology, Information Management and Information Systems. As part of the spirit of disseminating knowledge from the results of research and thought for service to the wider community and as a reference source for academics in the field of Technology and Information.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 142 Documents
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APPLICATION OF RANDOM FOREST METHOD TO PREDICTION OF STUDENT CANDIDATES ACCEPTED IN THE SNMPTN PATHWAY (CASE STUDY AT UNIVERSITAS LAMBUNG MANGKURAT) Vicka Karina
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 1 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i1.209

Abstract

Academic planning is an essential aspect that needs to be carried out to plan the teaching and learning process in a campus, such as the admission of new students through the SNMPTN. At Lambung Mangkurat University, it is known that the partici- pants who took the SNMPTN during the 2021 admission period amounted to 7,703. It is recognized that selecting candidates is not easy due to many prospective students passing the selection but choosing to withdraw. Therefore, a system is needed to predict the graduation of prospective students through the SNMPTN. This research utilizes the Random Forest method to predict the graduation of prospective students through the SNMPTN. The data will be divided into 90% for training data and 10% for testing data, then using classification parameters with 300 n-estimators. The research yielded a precision value of 0.72, recall value of 0.46, and system accuracy of 89.3% For further research recommendations, other prediction methods can be explored to forecast the graduation rate of students through the SNMPTN, or a comparison of methods can be con- ducted to determine which method is more effective.
CLASSIFICATION OF STUDENT STUDY PERIOD USING NEURAL NETWORK BACKPROPAGATION ALGORITHM BASED ON ENTRY PATH (CASE STUDY: FACULTY OF ENGINEERING, UNIVERSITAS LAMBUNG MANGKURAT) Eka Setya Wijaya; Mochamad Fajar Al-Amin
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 1 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i1.210

Abstract

Comparison of Arima Model with The Addition of Linear Quadratic Estimation Algorithm for Prediction The Spread of Covid-19 in Kotabaru District Eka Setya Wijaya; Bara Nugraha Putra Suryana
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 2 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i2.211

Abstract

Coronavirus disease 2019 (Covid-19) has been declared by WHO as a pro-longed global pandemic which has caused signif- icant public health problems, deaths and economic losses, therefore it is necessary to carry out prevention and control ef- forts to break the chain of transmission of Covid-19. One effort that can be done is to estimate the additional number of posi- tive cases of Covid-19, so that the number of isolation rooms and the need for medical personnel can be estimated. In this study the prediction of an increase in the number of positive cases of Covid-19 was carried out using the Linear Quadratic Estimation (Kalman Filter) approach based on the state space model formed from the ARIMA model (0,1,4). Based on train- ing data from March 23, 2020 to April 4, 2023, the best time series model is the ARIMA model (0,1,4) which was chosen based on the smallest AIC value and satisfies the residual test hypothesis
Examining IT Service Management Service Operations Utilizing The ITIL V3 Framework: A Case Study of Dana Zulkarnain; Anthony; Elvin Valentino; Keaton Yoputra; Mulyanto; Nellsen Purwandi
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 2 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i2.212

Abstract

This paper presents a comprehensive analysis of IT service management (ITSM) service operations within the context of the ITIL v3 framework, focusing on a case study of Dana, a digital wallet company. Employing a quantitative research approach through a questionnaire, the study delves into Dana's implementation of ITIL v3 practices in managing its IT services. It investigates various aspects of IT service operations, encompassing event management, incident management, problem management, request fulfillment, and access management, within the framework of ITIL v3 and maturity model. By scrutinizing Dana's ITSM service operations, this study aims to offer insights into the effectiveness and challenges of applying the ITIL v3 framework in real-world organizational settings. The research findings contribute to the existing knowledge on IT service management practices and provide practical recommendations for organizations striving to optimize their IT service operations using ITIL v3 principles.
IoT-Based Door Security System as A Countermeasure and Theft Prevention Raditya Koesyan Dipo Pramukti; Afu Ichsan Pradana; Rudi Susanto
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 2 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i2.216

Abstract

A security system is very necessary when creating a system. One of them is a door lock system. There are several security systems that can be used when creating an automatic door locking system, namely using alarms and application notifications. A good security system also requires how quickly the tool or system works to give signs that someone is breaking in. By applying IoT (Internet of Things) and also the ESP32 microcontroller, we can monitor an event in real-time. With IoT-based security systems, the system can continuously operate with just stable internet and electricity. The ESP32 microcontroller is also widely used in IoT projects due to its ease of operation and affordable price. An alarm that is responsive can help us prevent criminal activities. An alarm functions to alert us of something or a situation. By combining the concepts of the ESP32 microcontroller and alarm notifications in the form of messages on Telegram, we can create a reliable system. This becomes an effective solution for securing properties and the safety of its occupants.
Mapping of Food Crop Commodity Production Areas in Indonesia Using The Average Linkage Method Hery Priandoko; Alva Hendi Muhammad; Anggit Dwi Hartanto
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 2 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i2.219

Abstract

Indonesia consists of several regions that have the potential to meet food needs. One of the main sectors that meet food needs is the agricultural sector. The agricultural sector is a sector that needs significant attention from the central and regional governments in meeting national food needs. Food needs are currently often scarce so people find it difficult to obtain these food needs. The problem of dependence on food needs can endanger the availability of the country's food supply. Importing food crop commodities is one solution to maintaining food availability in Indonesia. Imports of food crop commodities carried out by Indonesia show that the amount of food commodity availability cannot meet national food needs. In Indonesia, some regions have food crop commodity production so that they can help in the availability of these food needs. From the existing problems, researchers tried to conduct research by mapping the regions or areas in Indonesia to find out which regions have food crop commodity production. In this study, the mapping that will be used is using the hierarchical cluster method. The hierarchical cluster method that will be used is the agglomerative hierarchical cluster method with the average linkage method. The results of this study will be formed into 3 clusters with the following details: high cluster, medium cluster, and low cluster. The highest cluster obtained 2 members, namely the Provinces of East Java and Central Java. The Medium Cluster obtained 1 member, namely the Province of West Java. The Low Cluster obtained 31 members, namely the Provinces of Aceh, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Bangka Belitung Islands, Riau Islands, DKI Jakarta, DI. Yogyakarta, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, East Kalimantan, North Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku, North Maluku, West Papua, and Papua.
Application of K-Means and K-Medoids Algorithms for Clustering Chili Commodity Trade Distribution in Indonesia Febri Widianto; Elika Thea Kirana; Nurahman; Depi Rusda
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 2 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i2.220

Abstract

Chili is one of the important commodities in agriculture and food, which is a product of the capsicum plant that has significant economic value in international trade. This study aims to identify an effective distribution strategy for red chili commodities in Indonesia through the use of the K-means and K-medoids clustering algorithms. The data used comes from the Central Statistics Agency (BPS) in 2022, including parameters-production, consumption, surplus/deficit, trade margin, and the impact of market operations and natural disasters. The implementation of K-means and K-medoids uses the RapidMiner application to form six provincial clusters based on the characteristics of red chili distribution. The results of the analysis show that K-medoids consistently outperforms K-means in cluster formation, with lower Davies-Bouldin Index (DBI) values ​​indicating better clusters. The conclusion of this study confirms that K-medoids is more effective in grouping red chili distribution areas in Indonesia, potentially providing a stronger foundation for strategic decision making in the distribution management of this commodity. Therefore, this study recommends the use of K-medoids as a more appropriate approach for planning and implementing red chili distribution strategies in Indonesia.
MSME AI Readiness Analysis Using The AIRI Framework: Analisis Kesiapan AI UMKM Menggunakan Kerangka Kerja AIRI Muhammad Husein Budiraharjo; Alva Hendi Muhammad; Kusnawi
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 2 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i2.307

Abstract

AI is expected to become one of the key technologies supporting the development of MSMEs, which represent a major pillar of Indonesia's economy. Successful adoption and implementation of AI require the right strategies, one of which stems from an analysis of a company’s AI readiness. In this study, an AI readiness analysis was conducted using the AIRI framework on six MSMEs from various business sectors. The results of the analysis provided the AI readiness levels of each MSME, along with comparisons to similar industries and to industries of comparable business scale (MSME). The analysis also yielded several recommendations for AI adoption and strategies to enhance the AI readiness of each MSME. All the MSMEs involved in the study positively accepted the AI readiness analysis and the adoption recommendations provided. The study did not produce any feedback for improvements to the AIRI framework itself; however, there were suggestions for further development of the AIRI application to better assist MSMEs in determining AI readiness targets and appropriate AI implementation strategies in the future..
Classification of Mental Disorders Using Modified Balanced Random Forest And Feature Selection Arsad; Alva Hendi Muhammad; Tonny Hidayat
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 9 No. 2 (2024)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v9i2.320

Abstract

This study employs the Modified Balanced Random Forest (MBRF) algorithm and Correlation-based Feature Selector (CfsSubsetEval) for mental disorder classification. The "Mental Disorder Classification" dataset from Kaggle was used with the aim of improving accuracy, evaluating feature selection, and assessing MBRF's performance in handling data imbalance. The study compares the performance of Random Forest (RF) and MBRF, and examines the impact of feature selection using CFS on mental disorder classification. The results indicate that MBRF outperforms RF with an 8.33% improvement in accuracy, 8.61% in precision, 8.33% in recall, and 9.08% in F1-Score. Additionally, the comparison between MBRF and MBRF with CFS reveals that while accuracy and recall remain the same, MBRF achieves 0.23% higher precision and 0.81% higher F1-Score than MBRF with CFS. In conclusion, the use of MBRF proves to be superior to the standard RF in addressing data imbalance for mental disorder classification, significantly improving accuracy, precision, recall, and F1-Score. However, feature selection with CFS does not significantly enhance performance. While accuracy and recall remain unchanged, MBRF without CFS demonstrates higher precision and F1-Score, indicating that the model performs better without feature selection in maintaining the balance between precision and recall.
Design of Website-Based E-Commerce Information System Using Extreme Programming Method (Case Study: Belv Boutique) Syihan Achmad; Arief Ichwani
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 1 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i1.328

Abstract

The purpose of this research is to provide a REST API-based web service for an online fashion product ordering platform, using butik belv as a case study. The purchase process carried out at butik belv At this time, consumers must visit butik belv directly to complete their purchase because it is currently still processed offline, where payments are still made in cash and buyers must visit the store directly to complete the purchase. Payments and transactions are still paid in cash. In addition, sales transactions are still recorded manually which are prone to errors. This research aims to create a web application that utilizes REST API technology. With the help of this application, users can order products online and pay directly through the website without having to visit the store. In addition, the transaction recording system is automated, thus ensuring that all sales data is recorded accurately, this reduces the possibility of recording errors and simplifies the sales reporting process. Extreme programming is the software development methodology used. It includes design, coding, testing, and planning phases. The system also uses Blackbox testing which is expected the test results show that each functionality works as intended, indicating that the use of web services can increase the speed of the application and streamline the purchasing process and assist buyers in the purchasing process. Butik butik belv anticipates increased operational effectiveness and provides this solution.

Page 12 of 15 | Total Record : 142

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