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Jurnal Teknologi dan Manajemen Informatika
Published by Universitas Merdeka Malang
ISSN : 16936604     EISSN : 25808044     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
Jurnal Teknologi dan Manajemen Informatika (JTMI) diterbitkan oleh Fakultas Teknologi Informasi Universitas Merdeka Malang. JTMI terbit 2 edisi per tahun pada Januari - Juni dan Juli - Desember dengan scope ilmu komputer yang mencakup teknologi informasi, sistem informasi, dan manajemen informatika.
Arjuna Subject : -
Articles 141 Documents
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Evaluasi Faktor Keberhasilan dan Kepuasan Pengguna Sistem Informasi Pengaduan Online Kota Malang Kanthi, Yekti Asmoro; Aminah, Siti
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.11036

Abstract

An online complaint application has been launched to bridge the aspirations, complaints, and grievances of the community to the municipal government of Malang. This application is used to facilitate the public in submitting their complaints with the hope of receiving prompt responses and immediate follow-up actions. Although the online complaint application can be accessed by users, in reality, the administrators responding to public complaints still undergo a very lengthy process, and some complaints are left unanswered. There are many obstacles, both within and outside the system, suspected to be the causes of the slow response by administrators to public complaints. For example, the lack of a super administrator, budget constraints, frequent personnel turnover in the Diskominfo apparatus, some regional devices lacking synchronization, and challenges related to commitment guidance and inadequate socialization. This is due to many operational and managerial aspects that may not have been running as they should. Therefore, an evaluation of the success factors of the use of the online complaint system needs to be conducted using the HOT-Fit Model (Human Organization Technology—Net Benefits). The aim of this research is to identify the factors that hinder the effectiveness of the online complaint system.
Klasifikasi Daun Herbal Menggunakan K-Nearest Neighbor dan Convolutional Neural Network dengan Ekstraksi Fourier Descriptor Basri, Haerunnisa; Purnawansyah, Purnawansyah; Darwis, Herdianti; Umar, Fitriyani
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.10350

Abstract

The number of herbal plants in Indonesia is 30,000, but only about 1,200 plants are used in medicine. The large number of herbal plants makes it difficult for people to distinguish one type of herbal plant from another. From these conditions, this research has conducted tests to compare the performance of the K-Nearest Neighbor (KNN) and Convolutional Neural Network (CNN) methods using Fourier Descriptor (FD) feature extraction on herbal plants, namely moringa (moringa oleifera) and katuk (sauropus androgynus). The amount of data used is 480 data using image conditions, namely dark and light images which are then divided into 20% testing data and 80% training data. Classification is done using the KNN method using 5 distance calculations (Euclidean, Chebyshev, Manhattan, Minkowski, and Hamming) and CNN with FD feature extraction. From the tests that have been carried out, it is found that the use of FD feature extraction for the KNN method produces the best performance on both light and dark image data. While the use of the CNN method, for dark image data, the best accuracy results are obtained with FD feature extraction and CNN. Meanwhile, for bright image data, the best performance accuracy results are obtained in the CNN method without going through feature extraction. Of these three methods, using FD and KNN feature extraction is more recommended because it produces 100% accuracy in moringa and katuk images with light and dark intensity.
Development and Evaluation of Android-based Infrastructure Rental Application: A Design Science Research Approach Kandami, Joshua Hans; Inan, Dedi Iskandar; Juita, Ratna; Baisa, Lorna Yertas; Sanglise, Marlinda; Indra, Muhamad
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.13004

Abstract

This study developed and evaluated a mobile application for infrastructure rental at the Quality Assurance Agency for Education (BPMP) in West Papua using the Design Science Research (DSR) approach in the field of Information Systems (IS). This application, the first designed specifically for the needs of BPMP West Papua and integrated with the existing system, was assessed based on usability and user acceptance through interviews, black box testing, and effectiveness testing using Structural Equation Modeling (SEM) with the Technology Acceptance Model (TAM) approach. The black box testing results indicated successful application development. Evaluation with 64 respondents through hypothesis testing showed that social influence and technological anxiety significantly affect attitudes toward accepting the use of the application. This highlights the importance of considering these factors for the successful implementation of the mobile application at BPMP West Papua, potentially enhancing the efficiency of infrastructure rental.
A Comparative Study of YOLOv8 and YOLO - NAS Performance in Human Detection Image Hendrawan, Nofrian Deny; Kolandaisamy, Raenu
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.12192

Abstract

In the realm of computer vision, object detection holds immense importance across applications such as surveillance and autonomous vehicles. This study addresses the critical challenge of human detection under low-light conditions, essential for nocturnal surveillance and autonomous driving systems. Focusing on the evolution of YOLO models, particularly YOLO - NAS and YOLOv8, a research gap is identified concerning their performance in low-light scenarios. The research conducts a detailed analysis of YOLO - NAS and YOLOv8 effectiveness in human detection under reduced ambient illumination. Object detection, vital in computer vision, faces challenges in low-light scenarios. This study concentrates on human detection due to its significance in night-time surveillance and autonomous driving. Despite YOLO models' evolution, a research gap exists in comparing their performance in low-light conditions. The study aims to fill this gap, providing insights for enhancing human detection methodologies in challenging lighting environments.
Moderasi Promosi pada Pengaruh Perceived Ease of Use Terhadap Minat Penggunaan Paylater Prajogo, Uke; Maulana, Moh. Zulfiqar Naufal
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.11172

Abstract

This research aims to analyze the influence of perceived ease of use on interest in using pay-later with the moderation of promotion. The research object is SMEs (small and Medium Enterprises) affiliated with ABM Preneur. The sampling method used is stratified purposive random sampling. The researcher determined the sample criteria as follows: 1. SMEs affiliated with ABM Preneur, 2. Awareness or prior use of Paylater. To determine the minimum sample size, the researcher used the Slovin Technique. The population size in this study is 71 SMEs, and a sample of 60 individuals was obtained. The sample size was determined using the Slovin formula. Data analysis was conducted using SmartPLS 3, where variable X1 is perceived ease of use, variable Y is interest in using pay-later, and variable Z is promotion. The research results show that H1 and H2 are accepted. Therefore, perceived ease of use has a positive and significant influence on interest in using pay-later. Promotion moderates the influence of perceived ease of use on interest in using pay-later. The limitation of this research is that it only analyzes the moderation of promotion and the influence of perceived ease of use on the interest in using pay-later in SMEs affiliated with ABM Preneur in Malang City.
Aplikasi Go Tour Sekitar Tugu Yogyakarta Berbasis Augmented Reality Putri, Revanda Silva Astianto; Rahmawati, Yunianita; Busono, Suhendro; Eviyanti, Ade
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.10587

Abstract

The Covid pandemic has impacted the tourism industry in Central Java Province, resulting in a decrease in the number of tourists. This research aims to create an application as an information media using Augmented Reality technology and developed through SketchUp, combining text, audio, and images. This application serves as an information source for the Tugu Yogyakarta tourist attraction and its surrounding areas in Central Java. Additionally, it also serves as an alternative to introduce tourist attractions to both the local and non-local communities in and outside of Central Java Province. The application utilizes the Marker Based Tracking method. The research output is an Augmented Reality application for information media that displays 4 tourist attractions, with audio-based information for each attraction. The testing scenario is conducted using the black box testing method (testing the system or its features). Based on the response evaluation, it can be concluded that this information media is considered suitable with a percentage of 94.8%. Therefore, this application can be used as an effective information media.
Enhancing Sales Prediction for MSMEs: A Comparative Analysis of Neural Network and Linear Regression Algorithms Taufiqih, Rahmad; Ambarwati, Rita
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.11875

Abstract

The increasingly fierce competition in the Micro, Small, and Medium Enterprises (MSME) industry has made business actors predict sales to find out future sales predictions and prepare strategies to deal with market trends that will occur in the future. Most MSMEs still do not have a prediction system. So, to set sales targets each year, they always use manual estimates by reviewing the previous year's sales data. Therefore, this research aims to predict sales and analyze the error value of sales data forecasting so that it can provide recommendations for strategies to increase sales. This research will apply neural network and linear regression algorithms to predict sales from 2020 to 2022. Based on the results of method testing, the artificial neural network algorithm is more suitable for forecasting sales than the linear regression algorithm. The test results obtained an RMSE value of 40,070 in the neural network method using one hidden layer and an RMSE value of 66,998 derived from the feature selection T-test and iterative T-test with a minimum tolerance value of 0.05 in the linear regression method.
Analisis Clustering Data Penyandang Disabilitas Menggunakan Metode Agglomerative Hierarchical Clustering dan K-means Sujjada, Alun; Insany, Gina Purnama; Noer, Silvia
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.10654

Abstract

Disability issues are still a major concern in society due to the discrimination often faced by people with disabilities. Many of them have abilities that are equal to individuals without physical limitations. Through this case study, this research aims to Cluster disability data by considering three types of disabilities: physical, visual and hearing, and hearing and speech using agglomerative hierachical Clustering and kmeans methods. This research was conducted by analyzing data from people with disabilities in 7 provinces in Indonesia. K-means to group data and agglomerative hierarchical Clustering as a centroid determinant in k-means. to enrich the results of data analysis, the EDA (Exploratory Data Analysis) process is used to identify outliers and anomalies. The results of the data analysis show that there are three main Clusters. The first Cluster has a high level of disability and includes 62 cities and districts, the second Cluster has a medium level of disability with 37 cities and districts, and the third Cluster has a low level of disability with 27 cities and districts. The best evaluation using the Davies Bouldin Index method resulted in two Clusters, indicating a better quality of Cluster division. The results of this study provide a better understanding of the distribution of disability in Indonesia, which can be used as a foundation to improve inclusion and accessibility for people with disabilities. Further recommendations can be made based on these findings to improve their situation in terms of employment and education.
Penerapan Algoritma K-Nearest Neighbor untuk Menentukan Potensi Ekspor Komoditas Pertanian di Provinsi Sulawesi Tengah Ngemba, Hajra Rasmita; Raivandy, I Made Randhy; Hendra, Syaiful; Ardiansyah, Rizka; Dwi Wijaya, Kadek Agus; Nugraha, Deny Wiria; Irfan, Mohamad
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.10235

Abstract

Agriculture is a highly robust sector in Indonesia. This is evidenced in Central Sulawesi Province, where the gross domestic product (GDP) from the agricultural sector, based on constant prices from 2018 to 2021, continues to experience growth. Such conditions suggest that commodities in the agricultural sector have the potential to become export products, enabling a greater economic boost for the region. Before engaging in exports, it is necessary to identify which commodities have potential. One way to determine this is by applying Klassentypology. To simplify the process, it can be implemented in machine learning using the K-Nearest Neighbor algorithm. K-Nearest Neighbor is chosen because this algorithm can handle data containing noise and has good adaptability when given new data. In this research, two machine learning models were developed. The first model is used to classify whether a commodity is advancing or lagging, while the second model is used to classify commodities that grow rapidly and slowly. The highest accuracy obtained from the first model is 96.23%. Meanwhile, the highest accuracy from the second model is 93.49%.
Rancang Sangkar Burung Pintar Berbasis IoT Tutuko, Aryo Bagus Kusumadewa; Hidayahtullah, Maulana Syarief; Hamkah, Nafarul; Nilofar, Rafli Alfian; Pramudhita, Agung Nugroho
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 2 (2023): Desember 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i2.10613

Abstract

Raising birds for hobby and breeding is currently trending in the community. With the general business of the public, a common challenge faced by bird enthusiasts is the process of caring for birds, especially providing timely and accurate feeding and watering. To address this issue, research has been conducted to create a smart bird cage. The smart bird cage is designed to automatically provide food and water with remote control via mobile internet. This research applies modules such as ESP8266-01, servo motor, Relay 2 module, water level sensor, mini water pump, ultrasonic sensor, and the Blynk application that can be integrated as a control service using IoT. The result of this research is the specification of the cage for providing food and water that can be controlled automatically with specific measurements so that the feeding and watering patterns can be more organized.

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