cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Jamaluddin
Contact Email
jamaluddin@methodist.ac.id
Phone
+6281397181985
Journal Mail Official
jamaluddin@methodist.ac.id
Editorial Address
Universitas Methodist Indonesia Jl. Hang Tuah No. 8 Medan Sumatera Utara - Indonesia Kode Pos 20152
Location
Kota medan,
Sumatera utara
INDONESIA
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Published by Universitas Methodist Indonesia
ISSN : -     EISSN : 28281276     DOI : https://doi.org/10.46880/tamika
Core Subject : Economy, Science,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi merupakan Jurnal Penelitian Bidang Manajemen Informatika dan Komputerisasi Akuntansi yang dikelola ole Program Studi Manajemen Informatika dan Komputerisasi Akuntansi dan diterbitkan oleh Universitas Methodist Indonesia. TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi terbit per semester di bulan Juni dan Desember setiap tahun.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 269 Documents
 20   21   22   23   24 
Sistem Informasi Bel Sekolah Otomatis dengan Fitur Penjadwalan Dinamis Menggunakan Teknologi Mikrokontroler Pasaribu, Sutrisno Arianto; Pasaribu, Victor Patar; Rozy, Ahmad; Wijaya, Vera; Sari, Suci Amalia
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp103-107

Abstract

There are many innovations made to help students learn better due to advances in educational technology. One innovation is an automatic school bell application that has dynamic scheduling. This application aims to replace the manual bell system which often requires direct intervention from officers. With dynamic scheduling, schools can easily set schedules according to their needs, be it regular schedules or special schedules such as exams or other activities. The focus of this research is the design and development of an automatic school bell application that supports automatic bell time settings. With the dynamic scheduling feature, this system allows users to change or adjust the bell schedule without disrupting the lesson schedule or other important times. The implementation results show that this application works well and allows easy bell schedule settings and improves operational efficiency in the school environment. In addition, users will receive automatic notifications about schedule changes, which reduces errors or delays in ringing the bell. This application is expected to be a solution for schools that want to improve their time management and increase their operational efficiency.
Analisis Sentimen Tiktok: Wajib Militer dengan Metode Lexicon Based dan Naive Bayes Classifier Saprizal, Arpan Mualief; Nor Anisa
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2 (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2.pp242-246

Abstract

The issue of conscription in Indonesia has sparked a heated debate among the public, especially on the social media platform TikTok. This study aims to analyze public sentiment on the issue through analysis of TikTok user comments. The method used is lexicon-based sentiment analysis. Data of 5,212 comments were collected using web scraping techniques with the keyword "conscription in Indonesia". The results of the analysis showed that the majority of comments (53.28%) were positive, followed by neutral comments (35.79%), and negative comments (10.92%). This finding indicates that there is considerable support for the issue of military service among TikTok users. The research process includes data collection, data processing, sentiment analysis using a lexicon-based approach, and visualization of results. The results of this study are expected to provide a clearer picture of public perception of the issue of military conscription in Indonesia. 
Prediksi Gangguan Kesehatan Mental pada Kalangan Mahasiswa Menggunakan Metode Pseudo-Labeling dan Algoritma Regresi Logistik Sari, Anggraini Puspita; Prasetya, Dwi Arman; Aditiawan, Firza Prima; Al Haromainy, Muhammad Muharrom
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp40-48

Abstract

Mental illness is a health condition that alters a person's thoughts, feelings, or behaviors, leading to distress and difficulty in maintaining a normal life. Mental health issues should not be taken lightly due to the challenges associated with diagnosis. Many students tend to experience mental health problems at various stages of their education, from diploma programs to doctoral studies. This situation becomes more critical as students approach the end of their studies and anticipate future prospects. This article explores the mental health status of students through symptoms, using logistic regression methods for prediction based on the dataset used. In this study, two types of data are employed: labeled dataset and unlabeled dataset, which are combined to create a semi-supervised learning approach. Labeled dataset is classified using a logistic regression algorithm, while unlabeled dataset employs the pseudo-labeling method. The analysis and modeling of the dataset indicate that the comparison between labeled and unlabeled dataset can significantly affect accuracy and processing time. Furthermore, the use of the pseudo-labeling method with the logistic regression algorithm is well-suited for the mental health case study, achieving an accuracy of 98% with a labeled to unlabeled dataset ratio of 1:2.
Penerapan Metode Support Vector Machine untuk Pengenalan Pola Aksara Batak Toba Panjaitan, Efdi Sarjono; Rumapea, Humuntal; Jaya, Indra Kelana
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp49-55

Abstract

The usage of the Batak Toba script has declined, and its complex forms pose challenges in pattern recognition. This study employs the Support Vector Machine (SVM) method to classify Batak Toba script patterns, utilizing a Histogram of Oriented Gradients (HOG) as a feature extraction technique. The data used comes from various sources, totaling 285 script images. After preprocessing, SVM was applied to separate characters into two main classes, which were further subdivided into subclasses until final classification was achieved. The results show that the combination of HOG and SVM can classify Batak Toba script characters with an accuracy of 89,47%. This research makes a significant contribution to the preservation of the Batak Toba script and has broader potential applications in pattern recognition and image classification.
Analisis Data Judi Online di 5 Provinsi Indonesia Dengan Metode K-Means dan Decision Tree Saputra, Muhammad Bayu; Anisa, Nor
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2 (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2.pp254-258

Abstract

This study aims to analyze online gambling data detected in five provinces in Indonesia using the K-Means and Decision Tree methods. The data includes player counts, transaction values, and geographical distribution in West Java, Jakarta, Central Java, Banten, and East Java. The K-Means method was applied to cluster provinces based on player counts and transaction values, while the Decision Tree was used to identify classification rules. The results reveal three main clusters with distinct characteristics: provinces with high player counts and high transactions, provinces with low player counts and moderate transactions, and provinces with moderate player counts but low transactions. These findings provide critical insights into the patterns of online gambling activities in Indonesia and serve as a foundation for more effective policies in managing its impacts.
Analisa Model Clustering Untuk Pemetaan Kualitas Lulusan Mahasiswa Berdasarkan Dataset Tracer Study Yusda, Riki Andri; Risnawati, Risnawati; Santoso, Santoso; Siregar, Putri Zakiyah Maharani; Nurani, Widiya Putri
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp18-23

Abstract

Graduate data from the tracer study process is critical in assessing the quality of a university's graduates. From this data, universities can see an objective picture to measure and evaluate the curriculum, materials, and the achievement of learning competencies so far whether they are following what is expected by graduate users. This will provide input to university management in making strategies and policies to improve quality. However, the problem is that the amount of data available so far has not been maximized properly to assist management in making decisions. Data on graduates and users of existing graduates are only processed into semester and annual reports and there is no in-depth analysis. So management does not get information that helps improve graduates' quality in the future. Optimization of clustering methods using the elbow method with a comparison of other distance formulas such as Euclidean Distance, Mahalanobis Distance, and Manhattan City Distance to improve the performance of mapping results. The DBI result obtained is 1.89 for the number of 6 clusters.
Deteksi Kematanagan Buah Sawit dengan Menggunakan Algoritma Convolutional Neural Network Siregar, Muhammad Rizky Pratama; Al-Khowarizmi, Al-Khowarizmi
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp175-183

Abstract

This research aims to develop an automatic palm fruit ripeness detection system using the Convolutional Neural Network (CNN) algorithm. The dataset used consists of thousands of images of ripe and unripe palm fruits with varying lighting conditions and shooting angles. The CNN model used is MobileNetV2 which has been adapted for binary classification tasks. The training process is performed using data augmentation techniques to improve the generalization of the model. The evaluation results show that the developed CNN model is able to classify the ripeness of palm fruits with an accuracy of 84%. Comparison with conventional methods that rely on visual assessment shows that the CNN model provides more consistent and objective results. The implementation of this model has the potential to increase the efficiency of the harvesting and processing of palm fruits and reduce production costs.
Penerapan Network Monitoring di Dinas Komunikasi dan Informatika Kabupaten Asahan Saputra, Herman; Sahren, Sahren; Rahayu, Elly; Syah Putra, Aidil
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp78-83

Abstract

The implementation of network monitoring at the Asahan Regency Information and Communication Service using LibreNMS aims to increase network management efficiency and minimize downtime.  LibreNMS, as an open-source network monitoring platform, enables early detection of problems in network devices such as routers, switches, and servers.  During this deployment, various metrics such as bandwidth usage, device health, and network performance are monitored in Real-Time.  This system also supports automatic telegram notifications if a disruption occurs, thereby speeding up the processing process. With this comprehensive monitoring, agencies can optimize network infrastructure, reduce the risk of service disruptions, and improve the quality of public services. The results of this deployment show increased network stability and operational efficiency at the Asahan Regency Information and Communication Service.
Analisis Dampak Iklim Terhadap Produktivitas Tanaman Pangan dengan Model VAR dan GLM Kadir, Fitria; Yunis
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp56-63

Abstract

Food crops are essential for ensuring food security and combating hunger.  Climate change has emerged as a significant obstacle that is impacting the long-term viability of the agricultural industry, particularly in relation to food crops. The objective of this study is to examine the influence of climate conditions on the efficiency of food crop production in Sumatra. This will be accomplished through the utilization of VAR and GLM models, in addition to the OSEMN framework. The VAR model study shows that wind speed has a statistically significant influence on peanut production (p-value 0.000563). Similarly, the GLM model analysis reveals that wind speed has a statistically significant impact on rice (p-value 0.00095) and maize (p-value 0.000686) productivity. Based on the MAPE metric, the GLM model demonstrates superior performance compared to the VAR model in accurately predicting soybean production with an accuracy rate of 9.05% and peanut productivity with an accuracy rate of 8.84%. This study aims to provide assistance in reducing the effects of climate change and adapting to them in the agricultural industry, while also improving the production of food crops.
Prediksi Harga Cabe Rawit di Wilayah Provinsi Sumatera Utara dengan Metode Simple Exponential Smoothing Gracetira, Naomi; Simamora, Vony Melinda; Margareta, Nokia; Anata P., Josua Pedro; Lingga, Joy Syahputra; Ginting, Kevin Ginsigel; Sarkis S., Indra M.
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp73-77

Abstract

This study aims to predict the price of cayenne pepper in North Sumatra Province using the Simple Exponential Smoothing (SES) method with α = 0.2. The data used includes the price trend of cayenne pepper from January to July 2024, taken from Databoks and supported by BAPANAS (Badan Pangan Nasional). The analysis results show that the SES method can capture the upward trend in the price of cayenne pepper with a relatively high level of accuracy, indicated by the MAPE (Mean Absolute Percentage Error) value of 7.34%. The predicted average price of cayenne pepper on July 15, 2024 is estimated to reach Rp. 47,555.34. These findings suggest that the SES method is reliable for planning and decision-making regarding the price of cayenne pepper, although it is more sensitive to recent data. This research makes an important contribution to the government, farmers, and traders in dealing with fluctuations in agricultural commodity prices.

Page 22 of 27 | Total Record : 269

 20   21   22   23   24 

Filter by Year

2021 2025


Reset
Filter By Issues
All Issue Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 1 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2 (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt Vol 4 No 1 (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 3 No 2 (2023): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 3 No 1 (2023): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 2 No 2 (2022): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 2 No 1 (2022): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 1 No 2 (2021): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 1 No 1 (2021): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi More Issue