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Darwis Robinson Manalu
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METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi
Published by Universitas Methodist Indonesia
ISSN : 24427861     EISSN : 26143143     DOI : https://doi.org/10.46880/mtk
Core Subject : Science,
Computer Science & IT
JURNAL METHODIKA diterbitkan oleh Program Studi Teknik Informatika dan Program Studi Sistem Informasi Fakultas Ilmu Komputer Universitas Methodist Indonesia Medan sebagai media untuk mempublikasikan hasil penelitian dan pemikiran kalangan Akademisi, Peneliti dan Praktisi bidang Teknik Informatika dan Sistem Informasi. Jurnal ini mempublikasikan artikel yang berhubungan dengan bidang ilmu komputer, teknik informatika dan sistem informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 212 Documents
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KOMBINASI PAKET MENU MAKANAN DENGAN ALGORITMA APRIORI PADA CAFE HABITAT COFFEE Sitorus, Betti Elvi Deliana; Manalu, Darwis Robinson; Rumapea, Yolanda Yulianti Pratiwi
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 1 (2024): Volume 10 Nomor 1
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i1.2599

Abstract

Habitat Coffee adalah salah satu kafe yang menawarkan berbagai jenis menu minuman dan makanan dengan harga yang beragam yang disajikan kepada pelanggan. Habitat coffee dapat menjual ratusan transaksi dalam sebulan yang mengakibatkan penumpukan data transaksi yang kerap tidak digunakan dikarenakan terbatasnya waktu dan jumlah data yang besar sehingga sulit dalam pengelolaan data. Untuk mengubah penumpukan data transaksi tersebut menjadi sebuah informasi tentang menu yang dibeli pelanggan secara bersamaan maka dibutuhkan sebuah metode atau teknik sehingga pihak Habitat Coffee dapat berinovasi dengan membuat paket menu makanan baru yang dapat meningkatkan keuntungan penjualan karena dapat menjual banyak menu dalam sebuah paket makanan dan mengetahui bahan baku apa saja yang harus di siapkan atau disediakan menggunakan teknik data mining yaitu metode algoritma apriori. Dari pengujian yang telah dilakukan sebanyak 4 kali menggunakan 150 data transaksi dengan menetapkan nilai minimum support, minimum confidence serta lift ratio untuk menentukan tingkat kevalidan suatu aturan maka menghasilkan kombinasi menu yaitu jika membeli lontong spesial maka akan membeli es teh manis dan kentang goreng, jika membeli nasi soto betawi maka akan membeli es teh tawar dan es teh manis.
PERBANDINGAN OPENSHIFT DAN CLOUD FOUNDRY SEBAGAI PLATFORM-AS-A-SERVICE SOFTWARE : STUDI LITERATUR Silitonga, Agnes Irene; Chintia Ni; Haryadi
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 1 (2024): Volume 10 Nomor 1
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i1.2601

Abstract

Penelitian ini bertujuan untuk melakukan analisis perbandingan antara dua aplikasi cloud terkemuka, yaitu OpenShift dan Cloud Foundry. Analisis ini mencakup beberapa aspek kunci, termasuk arsitektur, integrasi, pengembangan aplikasi front-end, Vendor Outlook and Evolution, skalabilitas, bahasa dan teknologi, komunitas dan dukungan, biaya dan lisensi, serta fleksibilitas deployment. Melalui penelitian ini, disajikan perbandingan yang komprehensif antara OpenShift dan Cloud Foundry, mempertimbangkan kelebihan dan kelemahan masing-masing platform. Artikel ini memberikan wawasan yang berguna bagi organisasi atau pengembang yang sedang mempertimbangkan antara kedua platform ini, membantu dalam membuat keputusan yang tepat untuk kebutuhan cloud, dan mengembangkan aplikasi.
PENERAPAN DATA MINING UNTUK MEMPREDIKSI PENDAPATAN PERUSAHAAN DENGAN METODE DOUBLE EXPONENTIAL SMOOTHING DAN TRIPLE EXPONENTIAL SMOOTHING Nur Abdurrahman, Dhimas; Rachman, Rizal
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 1 (2024): Volume 10 Nomor 1
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i1.2611

Abstract

Perusahaan telah memiliki data laporan terkait pencapaian pendapatan perusahaan, tetapi informasi dari data tersebut tidak digunakan dengan semestinya. Oleh karena itu penelitian ini bertujuan untuk mengetahui penerapan data mining untuk memprediksi pendapatan perusahaan. Metode penelitian yang digunakan adalah metode DES dan TES, yang memproses sekumpulan data pendapatan yang belum diolah dan belum dikembangkan untuk menciptakan informasi baru yang bernilai dan berguna bagi perusahaan, khususnya untuk perolehan pendapatan perusahaan. Hasil penelitian menunjukan perhitungan MAPE metode DES memperoleh MAPE 98,5 sedangkan metode TES memperoleh MAPE 5,42. Dengan perolehan MAPE yang lebih kecil metode TES lebih relevan dalam penelitian ini di bandingkan dengan metode DES, karena metode TES mempunyai tren dan musiman sehingga lebih akurat dalam perhitungannya di bandingkan dengan metode DES yang hanya mempunyai tren. Dari hasil perolehan MAPE tersebut, penggunaan metode TES dengan perolehan MAPE 5,42. Berdasarkan kriteria MAPE, maka kemampuan untuk memprediksikannya adalah sangat baik.
PENGEMBANGAN WEB MANAJEMEN STOCK PADA TOKO SPAREPART KATAJI MOTOR DENGAN METODE WATERFALL Sukmara, Nazal Nuharram; Ignatius Wiseto Prasetyo Agung
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 1 (2024): Volume 10 Nomor 1
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Web manajemen stok telah menjadi elemen penting dalam operasi toko sparepart, membantu meningkatkan efisiensi, akurasi, dan pengelolaan stok agar lebih baik. Penelitian ini bertujuan mengembangkan web manajemen stok yang disesuaikan dengan kebutuhan Sparepart Kataji Motor. Metode pengembangan digunakan metode Waterfall, terdiri dari tahapan yang terstruktur, termasuk analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Studi ini dimulai dengan melakukan analisis mendalam. Hasil analisis ini digunakan untuk merancang sistem manajemen stok yang baru. Selanjutnya, implementasi sistem dilakukan sesuai dengan desain yang telah dirancang dengan menggunakan teknologi modern. Pengujian dilakukan untuk memastikan kinerja sistem yang baik. Hasil dari penelitian adalah pengembangan aplikasi web yang memungkinkan Toko Sparepart Kataji Motor untuk mengelola stok mereka dengan lebih efisien. Sistem ini dapat membantu dalam pemantauan stok, pengelolaan pemesanan, dan peningkatan layanan pelanggan. Dengan metode Waterfall yang digunakan, proses pengembangan sistem ini dilakukan secara terstruktur dan terdokumentasi dengan baik.Penelitian ini diharapkan memberikan kontribusi positif untuk meningkatkan efisiensi operasional menjadi referensi bagi toko serupa yang ingin mengembangkan sistem manajemen stok berbasis web. hasil penelitian ini dapat memberikan pemahaman lebih baik mengenai penerapan metode Waterfall dalam pengembangan sistem perangkat lunak.
ANALISIS CLUSTERING STUNTING DENGAN DISTANCE EUCLID Buaton, Realita
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 1 (2024): Volume 10 Nomor 1
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Entering the Industrial Revolution Era 4.0, human resources must be supported by healthy and intelligent human resources so that they can increase competitiveness. The world still faces the problem of hunger and malnutrition today. According to a Unicef report, many people suffer from malnutrition in the world. The World Health Organization (WHO) says that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster stunting so as to produce patterns that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid, the Euclid algorithm is able to cluster stunting prevalence data into 3 clusters with a little category of 66%, a medium category of 28%, a lot of category of 6%. The results of the classification and clustering of the best stunting prevalence in cluster two with a small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide patterns for handling and optimizing stunting. in each district/city. Malnutrition is estimated to be the main cause of 3.1 million child deaths every year. Therefore, efforts need to be made to minimize stunting by predicting stunting sufferers. The prediction results can be used as an early prevention effort.
PERENCANAAN STRATEGIS SISTEM INFORMASI MENGGUNAKAN METODE WARD AND PEPPARD DI STAI ATTANWIR Makhabbatillah, Vina
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.2849

Abstract

This research focuses on strategic planning of information systems (IS) at STAI Attanwir by applying the Ward and Peppard method. The main objective of this research is to increase the effectiveness of data management, management efficiency, and organizational competitiveness through an IS strategy that is integrated with business objectives. Through SWOT, PEST and Porter's Five Forces analysis, this research identifies the strengths, weaknesses, opportunities and threats faced by STAI Attanwir in the context of the internal and external business environment. The results of this analysis are used to develop an IS/IT strategy that includes application portfolio development, information architecture and comprehensive IT management. In addition, this research emphasizes the importance of strong technological infrastructure and information security in supporting institutional operations. By implementing the right IS/IT strategy, it is hoped that STAI Attanwir can increase its efficiency, transparency and competitiveness through the effective and relevant use of information technology
PENERAPAN METODE REGRESI DALAM ANALISIS TINGKAT KONSUMSI IKAN DI JAWA TIMUR AKBAR fitransyah, Hikmal; Muhamad Ashari, Mahathir; Rahaditya Aryadi, Naufal; Aprizal Arifin, Willdan
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.2982

Abstract

The Indonesian marine ecosystem, rich in water resources, makes the fishing sector important for the economy, food, and jobs. East Java, with the highest catch production in Indonesia, has huge potential in the fishing sector. Despite its high potential, fish consumption in Indonesia is still relatively low due to lack of awareness, unoptimal distribution, and other factors. The study aims to analyze the level of fish consumption in Eastern Java and determine the best regression method to predict the rate of fish intake based on the region and the types of available commodities. This study uses three regression methods, namely Linear Regression, Support Vector Regression (SVR), and Gradient Boosting Machine. (GBM). Data visualization is done using bar diagrams, and results are validated using the determination coefficient R2 which is then analyzed descriptively. The Sumenep region has the highest level of fish consumption in East Java during the period 2018-2020. Whereas the commodities with the highest consumption are Tuna, Tongkol, Cakalang (TTC) Diawetkan. The GBM method showed its best performance and proved to be the most effective and accurate in predicting the level of fish consumption in East Java with a perfect determination coefficient (0,9999), compared to Linear Regression (0,8755) and SVR (0,9825).
PENGUJIAN USABILITY WEBSITE DOKUMENTASI MENGGUNAKAN SYSTEM USABILITY SCALE (SUS) Fathiyah Nopriani; Muhammad, Maulana Asykari
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.2987

Abstract

Documentation websites are a means for programmers to find solutions to the problems they face. Documentation websites that generally provide detailed information regarding how to use a particular framework. The documentation website used in this research is the documentation website from Tailwind CSS. Tailwind CSS is a CSS framework that has a utility-based component principle. With these principles, the website development process will be shorter, more flexible, responsive, and use code more efficiently. However, the convenience provided forces writing CSS code to be inline-CSS. This results in confusion arising from website programmers regarding CSS terms that are changed by Tailwind CSS. The Tailwind CSS website, which provides information related to the Tailwind CSS framework documentation, is in practice less intuitive, making it difficult for novice programmers to find solutions to the problems they face. This research aims to determine the usability of the Tailwind CSS website, from a student's perspective. The method used in this journal is SUS which is carried out by asking 10 questions related to the Tailwind CSS website to 30 respondents consisting of 87% men and 13% women. The selected respondents were students majoring in technology who used the documentation website from Tailwind CSS. The results of this research found that the Tailwind CSS website received a score of 70 on the SUS and could be categorized as Grade C or Fair.
PENERAPAN ALGORITMA YOLO UNTUK MENDETEKSI KUALITAS TELUR AYAM BERDASARKAN WARNA CANGKANG Sri Ayu Ningsih; Resti Ajeng Sutiani; Ni Made Sri Ulandari; Rizal Adi Saputra
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.3062

Abstract

In the poultry industry, chicken egg quality is a crucial factor influencing the price and market appeal of the product. Manual assessment of egg quality based on shell color requires significant time and labor and is prone to human error. Therefore, the implementation of automation technology through artificial intelligence (AI) is necessary to enhance the efficiency and accuracy of this process. The YOLO (You Only Look Once) algorithm is a fast and accurate object detection method that can be applied to classify chicken eggs based on shell color. This research aims to develop an automatic detection system using YOLO to identify and categorize the quality of chicken eggs based on shell color. Images of chicken eggs were collected and annotated to train the YOLO model. After training, the model was tested on a new dataset to evaluate its detection and classification performance. The results of the study indicate that the YOLO algorithm can detect and classify chicken eggs with high accuracy, reducing the need for manual labor and speeding up the quality assessment process. The implementation of this system is expected to improve operational efficiency in the poultry industry, ensure consistent product quality, and provide an innovative solution to the challenges in chicken egg quality assessment.
KLASIFIKASI KUALITAS UDARA MENGGUNAKAN METODE EXTREME LEARNING MACHINE (ELM) Jannah, Rachma Raudhatul; Sholahuddin, Muhammad Zulfikar; Haq, Dina Zatusiva; Novitasari, Dian C Rini
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 2 (2024): Volume 10 Nomor 2
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i2.3066

Abstract

Air quality is a critical factor affecting both ecological and human well-being. Air pollution is a global epidemic that poses a threat to human health and the environment. High population density resulting from industrial expansion and the increased number of motor vehicles are two primary causes of declining air quality in metropolitan areas. Air pollutants include surface ozone (O3), dust particles (PM 10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO). Researchers have begun exploring the use of Extreme Learning Machine (ELM) to classify air quality. The ELM method assesses air quality as either very good or poor. In this study, we compare datasets to evaluate the effectiveness of hidden node parameters using the split method. Our tests indicate that the split method impacts accuracy, sensitivity, and specificity. The ideal model with a 70:30 split ratio and 15 hidden nodes achieved a 90% success rate.  

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