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Universitas Methodist Indonesia Jl. Hang Tuah No. 8 Medan Sumatera Utara - Indonesia Kode Pos 20152
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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 361 Documents
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Penerapan Holt-Winters untuk Prediksi Harga Beras di Sumatera Utara Daniel Bakkara; Imelda Sri Dumayanti; Edward Rajagukguk
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).pp288-294

Abstract

In the base price of rice and world rice prices, crop failures that reduce rice stocks, and dependence on rice imports which are potential causes of rising rice prices. The use of the Holt-Winters method in predicting rice prices in North Sumatra has the potential to make a positive contribution to increasing economic stability and the welfare of farmers and rice consumers in the region. The results of applying the Holt-Winters method to predict rice prices in North Sumatra for 2023 show an upward trend in prices for both premium and medium rice. In this study, the parameter values are α = 0.8, β = 0.7, and γ = 0.3. The prediction of premium rice prices starts at Rp 13,783.995 in January and consistently increases to Rp 17,234.625 in December. The price of medium rice is also projected to increase, starting from Rp 12,463.088 in January and rising to Rp 15,094.911 in December. The multiplicative Holt-Winters method can predict rice prices in North Sumatra well, with forecasting accuracy values using the MAPE method of 9.17% for premium rice and 5.86% for medium rice. The significance level of the forecasting results conducted in this study falls into the Excellent category.
Sistem Informasi Arus Kas pada Credo Union Modifikasi (CUM) Talenta Saribu Dolok Berbasis Web Mira Naftalia Sijabat; Resianta Perangin-angin; Rena Nainggolan
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).pp241-248

Abstract

The data that has not been input is directly stored in the database. I have not been able to make online payments via bank transfer to Talenta because the commissioner and teller cannot be connected between accounts. The purpose of this is to produce a cash flow information system. Method of direct observation in more depth on an object to obtain more detailed and accurate information and Literature study is the process of collecting information from reliable readings or sources such as articles, books and scientific journals on topics related to the creation of website pages and databases. Able to input Member/Credit Customer Deposits. Confirm the bank transfer payment proof from the member. adding expenses in the office. Can view the account data used on Talenta. Adding Members, Credit Customers, and Employees. Input member deposits, credit deposits, Proof of Transfer, Payment Confirmation and Expenses in the office. View Member reports, Employee data reports, Member deposit reports, Member credit deposit reports, and Cash Flow statements. Conclusion The system can upload proof of payment that has been transferred by customer members to the Talenta account through the commissioner in the field. It can help and facilitate employees in inputting data on members, employees, member deposits, credit customers, and expenses. The information system built can present the required reports.
Pengembangan Sistem Informasi Manajemen Penjualan Aksesoris Motor Berbasis Web Julio Putra Tarigan; Abdi Dharma; Siti Aisyah; Delima Sitanggang; Yosua Morales Saragi; Mardi Turnip
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).pp216-219

Abstract

In this era of globalization, computerized systems have been used by many parties, both agencies, organizations and educational institutions. A computerized system is an information system that will design transaction data into useful information and aims to help make efficient decisions. However, at this time, PT. Surya Mandiri Motor does not yet use a computerized system, so errors often occur in recording, calculating transaction data, there are difficulties in searching for data and difficulties in making reports. This sales information system can be a solution that can simplify data processing so that the sales transaction process will be faster, more precise and accurate. This system was built using the PHP programming language and MySQL database.
Identifikasi Tingkat Kematangan Buah pada Tanaman Kelapa Sawit Menggunakan Algoritma Convolutional Neural Network dan Pendekatan Deep Learning William Owen Wijaya; Dhanny Rukmana Manday; Agrifa Insani Napitupulu; Mardi Turnip; Saroha Manurung
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).pp232-240

Abstract

Palm oil quality is largely determined by the free fatty acid (FFA) content, which is influenced by the ripeness of the fruit. Traditionally, determining the ripeness level of palm oil fruit relies on visual inspection by experts, which is time-consuming and dependent on individual skill. To address this, a system has been developed using the Convolutional Neural Network (CNN) method to automate the ripeness classification process. This study focuses on classifying palm oil fruit into three categories: ripe, unripe, and overripe, using a dataset of 1,380 images with 460 images per class. The dataset was split into 80% training data and 20% validation data. The CNN architecture employed was MobileNetV2, known for its simplicity and low computational complexity. Images were resized to 224 x 224 pixels, and two optimizers—Adam and RMSProp—were compared with learning rates of 0.001 and 0.0001 over 30 epochs. The best results were achieved using the Adam optimizer with a learning rate of 0.001, yielding a training accuracy of 91% and a test accuracy of 87%. This shows promising potential for automated palm oil fruit ripeness detection.
Seleksi dan Peringkat Kelulusan KIP Kuliah di Sumut I dengan ID3 dan Promethee Luhut Tony Sihotang; Alfonsus Situmorang; Margaretha Yohanna
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).pp273-287

Abstract

The selection of recipients of the Indonesia Smart Card (KIP) Lecture Program at the Dr. Sofyan Tan Aspiration House, North Sumatra, faces challenges in assessing the eligibility of prospective students efficiently and objectively. This research develops an artificial intelligence-based decision support system using the Iterative Dichotomizer 3 (ID3) algorithm and the PROMETHEE method. The ID3 method is applied in the initial administrative selection stage based on criteria such as parents' income, number of siblings, and home ownership, with an accuracy rate of 87.50%. Furthermore, the PROMETHEE method is used to rank prospective recipients who pass the initial selection according to the quota at the Methodist University of Indonesia. This hybrid system improves speed, accuracy, and transparency in selection, and supports a more equitable allocation of KIP Kuliah. This research contributes to the development of decision support systems for scholarship selection and can be used as a reference for future education policies.
Pembentukan Teamwork dengan Metode DBScan untuk Meningkatkan Kinerja Karyawan Feriani Astuti Tarigan; Leony Hoki
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).pp268-272

Abstract

CV. Surya Jaya Security System is a private company in the city of Medan that is engaged in the security system, which sells various brands of attendance machines, CCTV and accessories and doorstops, as well as various types of other security equipment. In doing work every day, it takes several employees who work together in completing the work of the customer. In one day, CV. SJSS can accept orders from several customers at once. Therefore, it is necessary to make arrangements for the formation of a work team (teamwork) to complete the work, so that all orders are completed on time and still maintain the quality of service from these employees. To carry out the process of grouping these employees, the data grouping method can be applied or often referred to as the clustering method. Density-Based Spatial Clustering Algorithm with Noise (DBSCAN) is one of the pioneering examples of the development of density-based clustering techniques or commonly known as density-based clustering. The result of this research is a website for the formation of teamwork by applying the DBSCAN method which is able to group employees, so as to improve employee performance.
Analisis Sentimen Komentar Publik Terhadap Program Makan Bergizi Gratis (MBG) di Platfrom TikTok Menggunakan Algoritma Support Vector Machine (SVM) Fauzi Faturohman; Asep Saeppani
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 6 No 1 (2026): 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.Vol6No1.pp57-63

Abstract

This study aims to analyze public sentiment towards the Free Nutritious Food Program (MBG) based on user comments on the TikTok platform using the Support Vector Machine (SVM) algorithm. Data were collected through a scraping process, resulting in 673 comments related to the MBG program. The research stages included text pre-processing consisting of data cleaning, case folding, normalization, tokenization, stopword removal, and stemming. The data were then labeled into positive, negative, and neutral sentiment categories using a lexicon-based approach and converted into numerical features using the Term Frequency–Inverse Document Frequency (TF-IDF) method. Sentiment classification was performed using the SVM algorithm to identify public perceptions of the program. The labeling results showed that neutral sentiment dominated with 539 comments, followed by 90 positive comments and 44 negative comments. The model evaluation showed good performance, achieving an accuracy of 82.96%, a precision of 82.95%, a recall of 82.96%, and an F1-score of 76.47%. These findings indicate that SVM is effective for analyzing public sentiment on social media and can assist the government in understanding public perceptions of policy programs.
Analisis Perbandingan DFA dan NFA Dalam Pencocokan String Muhammad Rafli Wijaya; Zulfahmi Indra; M. Gali Almahdi; Sebastian Saut Marulitua Sinaga
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 6 No 1 (2026): 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.Vol6No1.pp64-70

Abstract

String matching is a fundamental process in pattern recognition systems and large-scale text processing, where computational efficiency significantly affects system performance. This study analyzes the comparison between Deterministic Finite Automata (DFA) and Non-deterministic Finite Automata (NFA) in string matching using the pattern (a|b)*abb. The research was implemented through a web-based simulator developed with JavaScript, HTML, and CSS and evaluated using eight short test strings representing accepted and rejected inputs, as well as longer strings to observe execution time differences. The results indicate that DFA and NFA produce identical acceptance outcomes for all test cases, indicating that both automata recognize the same language. However, DFA demonstrates better computational efficiency because each input symbol is processed through a single deterministic transition, whereas NFA requires tracking a set of active states, which increases computational overhead. For longer strings, the execution time gap becomes more pronounced, with DFA remaining consistently faster than NFA. These findings suggest that DFA is more suitable for string matching applications requiring time efficiency, while NFA offers greater flexibility in transition design.
Transformasi Digital Sistem Informasi Akuntansi: Tinjauan Literatur Cloud, AI, dan Big Data Wa Ode Irma Sari; Nita Hasnita; Yuni Maimunah
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 6 No 1 (2026): 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.Vol6No1.pp90-103

Abstract

Digital transformation has significantly changed Accounting Information Systems (AIS) through the adoption of various digital technologies. This study aims to analyze the development of digital transformation in accounting information systems with a focus on cloud computing, artificial intelligence (AI), and big data during the 2020–2026 period. The study employed a systematic literature review (SLR) approach based on the PRISMA 2020 guidelines. Data were collected from relevant scientific articles and analyzed using descriptive content analysis to identify research trends, benefits, challenges, and future opportunities related to digital technologies in AIS. The findings indicate that cloud computing serves as the primary infrastructure for real-time financial information access and management; artificial intelligence improves efficiency through the automation of accounting processes, auditing, and fraud detection; while big data supports data-driven decision-making, risk management, and information quality enhancement. The review further reveals that the integration of these technologies enhances the effectiveness of accounting information systems, although challenges related to data security, privacy, data quality, algorithm transparency, and digital competencies remain significant. This study highlights that digital transformation plays a crucial role in improving the quality and effectiveness of accounting information systems in the digital era.
Sistem Pendukung Keputusan untuk Penentuan Siswa Lulus dengan Predikat Terbaik di SMA Negeri 9 Medan Menggunakan Metode SAW Muhammad Zidane; Elsa Aditya
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 6 No 1 (2026): 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.Vol6No1.pp104-111

Abstract

Determining the best graduating students at SMA Negeri 9 Medan has been carried out without an automated system and tends to focus more on academic aspects, potentially leading to subjectivity, inefficiency, and errors in the assessment process. Furthermore, non-academic criteria have not been optimally integrated in the decision-making process. Therefore, this study aims to design and develop a decision support system that can determine the best graduating students objectively, structured, and transparently using SAW. The SAW method is used to process student data based on a number of predetermined academic and non-academic criteria with certain weights. The system was developed using the PHP programming language with a MySQL database. The data used in this study were student assessment data at SMA Negeri 9 Medan for the 2024 academic year. The results of the system's calculations were compared with manual calculations to test the system's accuracy. The trial results showed that the implemented decision support system produced the same preference value as the manual calculation, namely 0.95 for students with the best predicate. The system's accuracy level reached 100%, indicating that the system is capable of implementing the SAW method appropriately. Thus, this system can help schools determine which students graduate with the best grades more efficiently, accurately, and responsibly.

Page 36 of 37 | Total Record : 361

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