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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,170 Documents
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New Method For Classifying Heart In Multiview Echocardiographic Images Mohamad Walid Asyhari; Riyanto Sigit; Bima Sena Bayu Dewantara; Anwar
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3078

Abstract

Echocardiography is a test that uses high-frequency sound waves to describe the structure of the heart. Echocardiography is used by doctors to analyze the movement of the walls in the heart chambers and identify heart disease. Several images, including the long-axis, short-axis, 2-chamber and 4-chamber left ventricle, can be used to check heart function. Many studies that have been carried out, including cardiac evaluation, are still carried out conventionally and require a certain level of accuracy. In this research, several methods proposed to achieve object extraction are used to build a classification system, the steps start with image enhancement, segmentation, tracking, extraction, output characteristics, validation and classification. Imaging enhancement aims to improve the echocardiographic image, thereby clarifying the edges of the heart wall. In addition, the images are reprocessed to separate the left ventricle from the heart wall and generate ventricular contours, at the segmentation stage. The contours are obtained by looking for the good features on each heart wall. In this approach, good features are identified only on the first image of the left ventricular slice. The good feature points used are 24 point which will be grouped into 6 segments. In addition, all images will be processed using the optical flow method to track the movement of the walls of the heart. Optical flow tracing will generate direction and distance feature extraction values that can be used to describe the resulting data features and find a suitable classification algorithm that is combined using different validation techniques, namely K-fold and Leave-one-out. In its implementation, Classifier Support Vector Machine (SVM) with rbf core achieves the highest accuracy. The SVM classification algorithm with validation techniques, namely k-fold cross-validation and leave-one-out cross-validation, reaches an accuracy value of 100% and 100%.
Analisis Pengaruh Diversifikasi Skripsi Terhadap Produktivitas Menulis Mahasiswa Program Studi Sistem Informasi UIN Sumatera Utara Suendri; Santoso, Heri; Andriani, Mega
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3079

Abstract

The form of the final project at the State Islamic University of North Sumatra, Medan is not only in the form of a thesis but can also be in the form of a journal article. Final thesis and journal articles have different forms, ranging from writing formats, templates, to the number of pages that must be completed. In terms of writing, students sometimes experience difficulties and obstacles ranging from difficulty finding data, running out of ideas, writer's block, discipline to unproductive writing. Therefore, to see the effect of journal articles as a substitute for thesis on student writing productivity, it is necessary to conduct research using three indicators, namely completion targets, processing time, and the number of references used. This study uses mix method research methods with data collection through questionnaires and literature study. After conducting research, which was based on productivity indicators, it was found that there was no effect of journal articles as a substitute for thesis on the writing productivity of each student.
Prediksi Kelancaran Pembayaran Angsuran Pada Koperasi Dengan Metode Naive Bayes Classifier Suwati; Yesputra, Rolly; Sapta, Andy
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3080

Abstract

This study aims to predict the smoothness of installment  payments in cooperatives, making it easier for staff to analyze credit lending. Lack of prudence in analyzing credit results in customers who are in arrears in paying installments, resulting in bad credit. To minimize errors that exist, it is necessary to evaluate the provision of loans to prospective debtors. By utilizing past member criteria data in the past that will be used to predict smooth payments using data mining. The data mining technique used is the Naive Bayes classifier method. The prediction process uses the naive Bayes method, namely by determining the probability or opportunity based on the previous member's data, and the results are used to help make a decision. The criteria used are member data: employment, income, house status, number of credits, and type of credit. Based on the naive Bayes method, the results obtained are 90.00% accuracy, 0.880% AUC, 83,33% recall, and 100% precision.
Perancangan Sistem Penerbitan dan Verifikasi E-Ijazah dan E-Transkrip Menggunakan Teknologi Blockchain pada Universitas Dinamika Bangsa Toscany, Afrizal; Bustasmi, M.Irwan; Saputra, Chindra
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3082

Abstract

With the development of increasingly sophisticated technology, the act of counterfeiting becomes an easy thing to do. An image editor application intended to heed a work of art, has now turned its function into a tool for document forgery.  Forgery of a diploma is a form of deviant behavior that violates the rule of law and makes the perpetrator criminal. Economic conditions, low education and the need to get a job are reasons for perpetrators to commit forgery. In addition, political motives are also often a reason to get political office.  One of the technologies to anticipate this problem is to apply blockcerts to electronic diplomas. Blockcert is built using blockchain technology that provides transparency and accountability in the storage of certificates and diplomas. This research resulted in a system of publishing and validating e-diplomas and e-transcripts at the University of Dinamika Bangsa which are stored on a private blockchain. The system has been tested and all modules are running properly according to the expected output.
Pendekatan Metode Weighted Moving Average Untuk Meramal Jumlah Penjualan Keripik Fitri, Adela; Yesputra, Rolly; Nasution, Akmal
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3086

Abstract

Teknik peramalan digunakan untuk memperhitungkan keadaan di masa mendatang atau melakukan prediksi kondisi di masa depan. Metode WMA atau weighted moving average adalah salah satu metode yang umum digunakan untuk melakukan peramalan. Akurasi dari suatu peramalan diukur melalui nilai eror terhadap ramalan yang diperoleh. Teknik peramalan dapat diterapkan dalam penjualan keripik. Dengan memperoleh data peramalan penjualan keripik dimasa mendatang dapat memberikan gambaran untuk langkah-langkah kerja kedepannya, sehingga dapat meningkatkan produktivitas kerja unit usaha. Proses perhitungan peramalan secara manual tentunya harus menguasai keahlian khusus terutama dibidang matematis. Untuk itu peneliti bermaksud membangun sebuah sistem peramalan sehingga dapat digunakan oleh semua orang dengan mudah dan cepat. Melalui sistem peramalan ini diperoleh data penjualan keripik ubi kayu untuk bulan selanjutnya adalah 40 kg dengan akurasi yang diukur menggunakan MSE sebesar 0,96 kg. Dimana dengan proses perhitungan manual juga diperoleh nilai yang sama dengan sistem yang dibuat. Nilai eror juga bisa dikatakan kecil, sehingga kriteria penggunaan metode ini termasuk akurat dan dapat dipercaya.
Meningkatkan Kinerja Decision Tree C4.5 dengan Seleksi Fitur Korelasi Pearson pada Deteksi Penyakit Diabetes Mohammad Burhan Hanif; Galet Guntoro Setiaji
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3087

Abstract

Diabetes sebuah penyakit yang menjadi momok seluruh dunia. Kerugianya tidak hanya pada penderita sendiri tetapi juga merambah ke banyak sektor. Baik di sektor pelayanan kesehatan dan sektor financial yang sangat menjadi beban tinggi yang perlu ditangani dengan baik dengan jalan pendeteksian penyakit diabetes sejak dini. Salah satu pendeteksian dini penyakit diabetes dapat memanfaatkan algoritma machine learning pada bidang data mining. Algoritma C4.5 merupakan algoritma machine learning yang memiliki tingkat akurasi dan kecepatan perhitungan tinggi dalam klasifikasi. Namun demikian algoritma C4.5 terganggu dengan data tak seimbang dan fitur data berdimensi tinggi. Pemanfaatan seleksi fitur menjadi salah satu penyelesain masalah data berdimensi tinggi. Algoritma Korelasi Pearson memiliki kemampuan dalam mengukur informasi antar fitur dan diterapkan dalam penelitian ini. Penggunaan Korelasi Pearson dianggap berhasil dalam meningkatkan kinerja algoritma C4.5 dalam deteksi awal penyakit diabetes. Keberhasilan ini terlihat pada hasil akurasi sebesar 95.31% tanpa korelasi pearson menjadi 96.16% dengan pemanfaatan korelasi pearson.
Optimasi Nilai K Pada Algoritma k-Means untuk Klasterisasi Data Pasien Covid-19 Moh. Fatkuroji; Fajrizal; Taslim; Eka Sabna; Kursiah Warti Ningsih
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3088

Abstract

With the spread of Covid-19 to various countries, it is difficult for Governments and Health Agencies in the world to handle Covid-19 cases to date. The prevention carried out by the Government and Health Agencies in the world is carried out by giving vaccines to the public. However, in some places it is not implemented in accordance with PMK Number 84 of 2020 which prioritizes providing vaccines to the elderly. With the current density of the population in Indonesia, the administration of vaccines does not see who is prioritized first. The application of the k-means algorithm is carried out to cluster patients affected by Covid-19 on the Covid-19 case data obtained from kaggle.com in the form of patient data from January 1, 2020 to May 31, 2020 as many as 139119 cases. The results of clustering data on cases affected by Covid-19 with k=3 yielded a WCSS value of 6801292.2. Calculations of the K-Means Algorithm using the Google Collaboratory Tools resulted in clusters with the cases of patients affected by Covid-19 in Cluster-0 as many as 58.237 cases, in Cluster-1 as many as 53.932 cases, and in Cluster-2 as many as 26.950 cases.  
Utilizing Machine Learning and Cloud Services to Improve Disaster Information Systems Arief, Lathifah; Sundara, Tri
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3090

Abstract

Cloud services have enabled various information system developments. In this paper, we explore the use of Amazon Sagemaker cloud services and AWS Data Exchange in disaster information systems. We proposed cloud architecture for a disaster information system and found some of the datasets provided on AWS Data Exchange could be leveraged for such system.
Analisa Komparasi Metode Pembagian Trafik Jaringan (Load Balancing) antara Metode PCC dan Metode ECMP: Studi Kasus pada Jaringan USM Soiful Hadi; Surono; Basworo Ardi Pramono
The Indonesian Journal of Computer Science Vol. 11 No. 3 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i3.3095

Abstract

Di era modern saat ini, kebutuhan akan akses internet di kampus merupakan hal yang mutlak dibutuhkan oleh mahasiswa dan dosen saat ini. Sehingga administrator jaringan kampus akan menerapkan berbagai alternatif cara untuk mencukupi kebutuhan akses internet untuk pengguna di universitas semarang. Pada kenyataannya administrator sering menggunakan satu gateway line ISP unutk satu network range meski memiliki dua atau lebih line ISP. ,Hal ini menyebabkan ketimpangan trafik jaringan ketika jumlah pengguna yang terhubung ke line ISP satu atau lebih banyak dari line ISP yang terhubung dengan ISP 2 atau sebaliknya. Pada penelitian ini dilakukan studi analisis komparasi metode pembagian trafik jaringan ( load balancing ) antara metode PCC (Per Connection Classifier) dan metode ICMP (Internet Control Message Protocol) untuk diterapkan di trafik jaringan universitas semarang dengan menggunakan perangkat routerboard mikrotik. Diharapkan melalui penelitian ini di dapatkan metode yang cocok untuk diterapkan di jaringan universitas semarang.
Sistim Pendukung Keputusan Menentukan Volume Produksi Keripik Tempe Menggunakan Metode Simplek Susanti, Evi Yulia
The Indonesian Journal of Computer Science Vol. 11 No. 3 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i3.3096

Abstract

Tempe can be processed to be used as a variety of dishes and snacks. Tempe chips are processed tempeh made from the main raw material of tempe which is thinly sliced ​​then seasoned and then fried until it has a crunchy texture. Tempe chips have become a business opportunity for Rimbo Ilir, Tebo Regency, Jambi Province with four flavors, Balado, cheese, BBQ and original flavors. The purpose of this study is to help the manager determine the production volume of tempeh chips according to the flavor variant in order to get the expected profit and minimize losses. The method used in this study is linear programming simplex method, using this method the manager is advised to produce tempe chips with Balado flavor of 18,225 pcs and cheese flavored with 6,795 pcs, with a profit of Rp. 24,493. From the sensitivity analysis, it does not mean that BBQ and cheese flavors should not be produced, but that they have a maximum production limit, for BBQ flavors a maximum of 6,286 pcs and original flavors 5,744 pcs.

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