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METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Published by Universitas Methodist Indonesia
ISSN : 25988565     EISSN : 26204339     DOI : 10.46880
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance
Sistem Informasi Sistem Informasi Manajemen Sistem Informasi Akuntansi Manajemen Basis Data Pengembangan Aplikasi Web dan Mobile Sistem Pendukung Keputusan Desain Grafis dan Multimedia Audit Sistem Informasi Topik-topik lain yang Relevan dengan bidang ilmu Manajemen Informatika Topik-topik lain yang Relevan dengan bidang ilmu Kompuerisasi Akuntansi
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 342 Documents
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Grade Classification of Diabetic Retinopathy Based on Single Model Convolutional Neural Network Fitriati, Desti; Nursari, Sri Rezeki Candra
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp50-55

Abstract

Diabetes Mellitus (DM) is one of the diseases that has attracted global attention because it ranks fourth as a non-communicable disease with the highest mortality rate after cardiovascular, cancer, chronic respiratory diseases. DR is a condition caused by diabetes that can cause permanent damage to the blood vessels of the retina which can lead to blindness. DR is divided into 2 stages, namely non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (DR), where each stage has different characteristics. From several studies that have been conducted previously, Convolutional Neural Network (CNN) has been widely used in recent years to segment medical images with remarkably consistent results. However, it is still necessary to find a suitable model to be able to adapt to all existing variables. For this reason, this study proposes a method as a modified model of CNN using seven layer. From the results of the research conducted, the proposed method uses four class models, namely 5 classes, 3 classes, 2 classes (Healthy & DR), and 2 classes (Healthy & Moderate). This research produced accuracy rates of 52%, 68%, 92% and 84% respectively.
Analisis Sentimen Masyarakat Terhadap Pelayanan Jasa Ekspedisi JNE dan J&T Express Menggunakan Metode Lexicon-Based Mola, Sebastianus Adi Santoso; Mbatu, Dinda Permata; Sihotang, Dony Martinus
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp56-65

Abstract

JNE and J&T Express are two of the largest and most popular courier companies in Indonesia, leading to various public opinions regarding the quality of their services. This research employs a lexicon-based method using the InSet dictionary, a simple scientific approach where the system calculates the weight of words and classifies them as positive, negative, or neutral sentiments. The analysis process begins with data collection of reviews using scraping techniques, followed by text processing including cleaning, case folding, normalization, tokenization, stemming, and stopword removal. Out of 3,565 reviews for JNE and 3,967 reviews for J&T, the sentiment analysis indicates that the majority of the public holds negative opinions towards the services of both courier companies. The analysis accuracy reaches 82% for JNE data, with a precision value of 95% for negative sentiment, 54% for positive sentiment, and 7% for neutral sentiment. The sensitivity values are 83% for negative sentiment, 82% for positive sentiment, and 15% for neutral sentiment. Data for J&T shows an accuracy of 78%, with a precision value of 97% for negative sentiment, 28% for positive sentiment, and 4% for neutral sentiment. Sensitivity values are 80% for negative sentiment, 82% for positive sentiment, and 4% for neutral sentiment.
Implementasi ISO-IEC 25010 untuk Analisis Kualitas Sistem Informasi Manajemen Kerja Praktik (SIM-KP) Dewi, Rosanti; Satyareni, Diema Hernyka; Kurniawan, Eddy
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp76-85

Abstract

The rapid development of technology has influenced various sectors, including education, where technology supports academic processes such as the Internship Management Information System (SIM-KP) at Universitas Pesantren Tinggi Darul Ulum Jombang. Despite its benefits, several issues have been identified, such as user interface complexity and unused features, necessitating a quality analysis. This study aims to analysis the quality of SIM-KP using the ISO/IEC 25010 standard. Compared to other methods, ISO/IEC 25010 offers the most comprehensive approach to analysis software system quality, focusing on aspects such as usability, functional suitability, reliability, efficiency, security, portability, compatibility, and maintainability. Data collection was conducted through questionnaires distributed to 53 Information Systems students via WhatsApp, using a Likert scale for assessment criteria. The research results show an average quality score of 71.3%, categorized as good. Performance efficiency achieved the highest score (80.7%), followed by functional suitability (77.2%), while maintainability (65.2%) and usability (65.0%) scored lower. Other scores include security (70.2%), portability (74.3%), and compatibility (69.2%). These findings indicate that the eight variables of ISO/IEC 25010 used in the analysis of SIM-KP achieved a good score.
Integrasi Algoritma YOLOv8 dan Streamlit untuk Visualisasi Real-Time dan Akurat dalam Penghitungan Kerumunan di Kawasan Stasiun Bekasi Prihandoko, Prihandoko; Rumapea, Sri Agustina; Pratama, Abdul Hanif
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp179-187

Abstract

Crowd management in public transportation areas has become a critical challenge with the rise of urban populations. This study develops a real-time web-based people detection and counting system by integrating the YOLOv8 algorithm with the Streamlit framework. A case study was conducted at the entrance of Bekasi Station. The model was developed using the AI Project Life Cycle approach, and the system was built following the Waterfall methodology. Data were obtained from video recordings, which were extracted into images, annotated, and processed into training and testing datasets. The YOLOv8 model was trained for 50 epochs, yielding strong performance with an mAP@0.5 of 91.7%, a maximum precision of 93.6%, and an F1-score of 87%. Tests on 15 images showed an average accuracy of 80.37% and an error rate of 19.63%. The model's performance declined on out-of-dataset images due to variations in lighting and extreme crowd density. The system was tested using black-box testing and demonstrated that all main features—image upload, object detection, visualization, and result download—functioned correctly. The system has been successfully deployed on Streamlit Cloud. These results indicate that the system offers a practical, lightweight, and responsive solution to support crowd monitoring in public areas. In future development phases, the system can be extended to support real-time video stream processing and integrated with an object tracking and classification module to accurately identify and differentiate the ingress and egress flow of individuals within a defined surveillance area.
Arsitektur Sistem Informasi Kinerja Guru Berbasis IASP2020 dengan Metode Togaf Framework Risanto, Joko; Bahri, Zaiful; Daqiqil, Ibnu; Elfizar, Elfizar
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp66-75

Abstract

In the national education standards, there are four factors that determine the quality of schools, namely the characteristics of the students, the competence of the teachers, the learning process and the leadership of the principal. To obtain quality teacher competence, effective, efficient and transparent teacher management is needed in the management of teaching and education personnel. To improve the quality of education, the government through the National Accreditation Board for Schools/Madrasahs has prepared the 2020 Education Unit Accreditation Instrument (IASP) containing standard instruments to measure school quality. Schools can implement IASP2020 to continuously monitor the performance of each factor to ensure school quality. In the teacher competence factor, a fast and responsive information system is needed so that the quality of teacher performance can be detected immediately to help schools immediately make the right decisions, immediately find the solutions needed for their problems so that teacher quality continues to maintain its competence. The design uses the Open Group Architecture Framework which has been proven to be reliable in solving information system governance problems. The results of this study are in the form of a recommendation for a strategic information system design that is worthy of being developed for teacher management.
Kosmu Sebagai Sistem Manajemen Kos Griya Muallimah Nur Hayati, Dian; Maryam, Maryam
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp99-105

Abstract

Information processing is currently greatly facilitated by the role of technology, so that it can be utilized in various sectors including temporary housing management. Kos Griya Muallimah is a boarding house specifically for women. Kos Griya Muallimah in its data management currently still uses a manual method, which is recorded in a book. The creation of KosMu can help Kos Griya Muallimah owners manage boarding house data more regularly and efficiently. This study aims to manage boarding house resident data, room data, payment confirmation data, and complaint data from Kos Griya Muallimah residents to be computerized so as to reduce human error, increase accuracy, and ease in finding the data needed. The development method used in this study is the prototype method. The prototype method is used so that developers can interact with users during website creation so that users can provide input and opinions regarding the website being developed. The system has been tested with Black Box testing to find out the system runs according to user expectations, the results of the features, menus, and buttons run well and based on usability testing with the System Usability Scale (SUS), a score of 74.5 was obtained, which means that the system is well received by users.
Meningkatkan Performa Ulasan Berbahasa Indonesia dengan Spelling Corrector Peter Norvig dan Pelabelan SentiStrength_id Asri, Yessy; Kuswardani, Dwina; Ferdinanda Purba TS, Josephine
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp92-98

Abstract

Digital transformation is driven by the increasing number of internet and mobile phone users in Indonesia, including public services such as the PLN Mobile application. The purpose of this study is to evaluate user sentiment towards PLN Mobile application reviews and find gaps between user ratings and reviews. Through web scraping on Google Play Store, with a total review data of 11,004 reviews between January 2022 and December 2023. During the preprocessing step, SentiStrength_id was used as the labeling approach, and Support Vector Machine was used for modeling. A spelling corrector using Peter Norvig was applied to correct spelling issues. The accuracy of sentiment analysis was much better with this procedure, reaching 82% at a data split ratio of 90:10. The percentage of sentiment obtained was 16.5% negative, 16.1% neutral, and 67.4% positive. The percentage of mismatched user ratings and reviews was 23.1% for negative reviews, 4.5% for neutral, and 72.49% for positive reviews.
Penerapan Logika Fuzzy Tsukamoto pada Rancang Bangun Sistem Deteksi Kekeruhan Air Budi Daya Ikan Lele Rizki, Muhammad; Darnila, Eva; Agusniar, Cut
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp112-120

Abstract

This study develops a water quality monitoring system for catfish farming using the Internet of Things (IoT) and Fuzzy Tsukamoto logic. This system consists of a Turbidity Sensor to measure turbidity levels, a DS18B20 sensor to monitor temperature, and a pH meter to measure water acidity levels. Data from the sensors is sent in Realtime to Firebase and displayed in an Android application based on Kodular. The Fuzzy Tsukamoto method is used to analyze data, determine the water quality status whether the water value is Clean, Normal, or Turbid based on predetermined parameters. Based on 14 tests, the system showed an accuracy level of 85.7%, with 12 matching results. In addition, this system is able to provide automatic notifications to users if there are significant changes in water conditions. As a result, this system can help fish farmers monitor water quality efficiently, as well as make decisions about when is the right time to change pond water.
Interplanetary File System for Custom Logging System Integrated with Smart Contract Parulian, Onesinus Saut; Saputra, Irwansyah
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp121-126

Abstract

The agricultural sector faces challenges in managing dynamic data during transactions, particularly price quotations between farmers and buyers. Traditional smart contract systems often lack the flexibility to handle real-time data changes. This research proposes a customized logging system that integrates smart contracts with the InterPlanetary File System (IPFS) within a web application. By storing data references (hashes) on the blockchain and actual logs on IPFS, the system ensures reliable data recording, flexibility in updating transaction logs, and improved storage efficiency. This integration enhances the system's ability to manage fluctuating agricultural transactions. The proposed method aims to create a robust framework for managing price quotations, which can be extended to other industries with similar requirements.
Klasifikasi Jenis Sampah Berbasis Convolutional Neural Network dengan Optimasi Hyperparameter Tuning Arsitektur Mobilenet Kuncoro, Dimas Febri; Wirasto, Anggit; Triwibowo, Deny Nugroho
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp130-144

Abstract

Waste management in Indonesia faces significant challenges with an increasing volume reaching approximately 175,000 tons per day. Public awareness of the dangers associated with improper waste disposal remains low, as many continue to litter indiscriminately. Waste sorting is the most effective method, involving separation based on waste types. Manual waste sorting is nonetheless inefficient, as it requires large spaces, substantial labor, and is prone to errors. This study aims to develop a waste classification model based on Convolutional Neural Network (CNN) with hyperparameter tuning optimization for the MobileNet architecture. The research adopts the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology and utilizes datasets from three waste categories organic, inorganic, and hazardous and toxic materials (B3) sourced from open Kaggle datasets. Model training was conducted using the MobileNet architecture with hyperparameter tuning optimization and resulting in optimal parameters Adam optimizer, learning rate of 0.01, batch size of 32, and 256 neurons. The results show that the model achieved 96% accuracy before optimization which increased by 2% to 98% after optimization. The model demonstrated high computational efficiency with the number of floating-point operations per second reaching 1.146 GFLOPS.

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