cover
Contact Name
Dede Kurniadi
Contact Email
dede.kurniadi@sttgarut.ac.id
Phone
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Journal Mail Official
informatika@sttgarut.ac.id
Editorial Address
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Location
Kab. garut,
Jawa barat
INDONESIA
Jurnal Algoritma
ISSN : 14123622     EISSN : 23027339     DOI : -
Core Subject : Science,
Jurnal Algoritma merupakan media publikasi hasil penelitian dosen maupun mahasiswa dalam kajian bidang Teknologi Informasi, Sistem Informasi, dan Rekayasa Perangkat Lunak.
Arjuna Subject : -
Articles 1,253 Documents
Analisis Disain Sistem Pengelolaan Dana Desa Menggunakan Model Proses SCRUM Ginting, Andre Chenaro
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1556

Abstract

Nagori Purba Dolok village office, Purba District, Simalungun Regency in resolving problems related to village fund management takes a relatively long time. Based on the results of the author's interview with village officials, Mr. Renhard Purba, this is because they still use a simple system, namely using Microsoft Office and village fund data in the office is still stored in an archive. To overcome this problem, additional staff can be done, but this is not appropriate because it will increase the agency's operational costs. So the author designed a village fund management system using HTML5 and PHP technology, which is expected to make it easier to resolve the problems faced by the Nagori Purba Dolok village office. With this system, officers can process village funds easily and provide input to leaders for developing a village fund management system in the future.
Pengembangan Aplikasi Diagnosa Penyakit Mata dengan Algoritma Teorema Bayes Agustin, Yoga Handoko; Asgara, Zidan; Baswardono, Wiyoga
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1564

Abstract

The eye is one of the senses that has great importance, because it functions in connection with the surrounding environment. If there are eye problems that are ignored, it will be an early sign of a potentially dangerous eye disorder. As the quality of life decreases and the level of stress received, complaints related to eye disease also increase. Human knowledge and skills are not eternal, they can be lost due to various reasons such as death, retirement, or job changes. When making conclusions, experts may be influenced by certain factors that have the potential to influence the final outcome of that conclusion. So that society can prevent and treat eye diseases, an expert system application is needed to assist eye polyclinic officers and the public in diagnosing eye diseases using the Bayes Theorem inference method. Bayes' theorem is a mathematical equation used to estimate the possibility of future events or their probabilities. This probability refers to the chance of an outcome occurring based on previous information. Its function is to update existing predictions or hypotheses. The results of this research are conclusions about the type of eye disease suffered based on the symptoms chosen by the patient and have been calculated using Bayes calculations. Based on testing 50 patient sample data, the percentage of conformity between the system and experts was 86% of the test data.
Implementasi Metode Multi Objective Optimization by Ratio Analysis dalam Menentukan Lahan dengan Jumlah Pupuk Terbanyak Ikhwan, Ali; Yuanda, Ary Santri; Shiddiq Siregar, Fahreza; Lesmana, Reza Kurnia
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1568

Abstract

PTPN III (Persero) is a plantation company that has a strategic role in managing agricultural resources in Indonesia. With a main focus on the plantation sector, PTPN III manages various types of crops such as oil palm, rubber and tea, which are the country's main export commodities. However, to get the best quality, accumulation must be taken into account in order to increase agricultural yields. This research aims to optimize agricultural management at PTPN III through the implementation of a Decision Support System (SPK) which utilizes the Multi-Objective Optimization by Ratio Analysis (MOORA) method. Decision Support Systems (DSS) are very helpful in determining and making decisions that cannot be chosen randomly. This system is designed to provide recommendations based on evaluation criteria. The aim of this system is to determine the blocks or sections that require the most fertilizer without any effort and efficiency. It is hoped that the results of this system will provide assistance to PTPN III. Experimental results show that implementing SPK using the MOORA method can help PTPN III identify the most suitable land and determine the largest amount of fertilizer to increase agricultural yields and serve as reference data. This system not only increases the efficiency of fertilizer use but also supports environmental sustainability. It is hoped that the accuracy and reliability of the SPK can become the basis for smarter and more adaptive decision making in modern agricultural management. The final result aimed at is to obtain land that uses the most fertilizer based on the final results, namely Block LL32 AFD IX (A4) with a score of 0.3334 and is in first position.
Analisis Sentimen Pengguna Twitter dalam Pemilihan Presiden (PILPRES) 2024 dengan Menggunakan Algoritma K-Means Amin, Abdusy Syakur; Kurniadi, Dede; Nurzaman, Muhammad Zein; Nurfadillah, Rifa Sri; Khoerunisa, Sarah; Khaerunisa, Nisrina; Ajiz, Rafi Nurkholiq; Jembar, Tegar Hanafi; Faisal, Ridwan Nur
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1596

Abstract

One form of upholding democracy carried out by the Unitary State of the Republic of Indonesia is through holding presidential elections or often known as presidential elections. which is held every five years to elect the next President. Apart from that, in this digital era, people are increasingly actively using social media to convey their views, opinions and sentiments regarding the presidential election. Ahead of the 2024 presidential election, many groups such as political parties, success teams, buzzers and supporters are using social media as a campaign medium to increase the popularity and electability of their prospective candidates. One of the social media that is widely used in political party promotion media is Twitter. Which is used by people to post various comments that can be positive or negative regarding the election. Sometimes, people also express hoax opinions before or during the election. Considering that comments on Twitter are currently difficult to categorize as positive or negative, sentiment analysis is needed to understand public attitudes towards the presidential election. This research aims to evaluate text documents and determine whether the documents have a positive or negative sentiment orientation. Apart from that, the method used is K-Means to cluster the data. The results of this weighting are in the form of positive and negative sentiment. Data taken from Twitter regarding the 2024 presidential election (pilpres) totaling 1015 tweet data.
Investigasi Model Machine Learning Regresi Pada Senyawa Obat Sebagai Inhibitor Korosi Rosyid, Muhammad Reesa; Mawaddah, Lubna; Akrom, Muhamad
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1598

Abstract

Korosi merupakan tantangan signifikan bagi daya tahan material, yang seringkali menyebabkan kerugian ekonomi yang besar. Penelitian ini memanfaatkan teknik Machine Learning (ML) untuk memprediksi efektivitas senyawa obat sebagai inhibitor korosi. Kami menggunakan lima algoritma ML yang menonjol: Regresi Linear, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Random Forest, dan XGBoost. Model-model ini dilatih dan dievaluasi menggunakan dataset yang terdiri dari 14 fitur molekuler dengan efisiensi inhibisi korosi (IE%) sebagai variabel target. Hasil pelatihan model awal mengidentifikasi Random Forest dan XGBoost sebagai yang berkinerja terbaik berdasarkan metrik seperti Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), dan R-squared (R²). Penyetelan hiperparameter lebih lanjut menggunakan GridSearchCV menunjukkan bahwa XGBoost, setelah penyetelan, secara signifikan mengungguli model lainnya, mencapai kesalahan terendah dan nilai R² tertinggi, menunjukkan akurasi prediktif yang superior untuk aplikasi ini. Temuan ini menegaskan potensi ML, khususnya XGBoost, dalam meningkatkan pemodelan prediktif inhibitor korosi, sehingga memberikan wawasan berharga bagi bidang ilmu korosi.
Technology Acceptance of GoFood Services Suseno, Novie Susanti
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1603

Abstract

The millennial generation, who are familiar with electronic devices and the internet, have become accustomed to ordering food via applications. Because the use of applications for ordering food has expanded due to the digital economy era. Where economic activities have begun to be based on the use of information technology. However, this certainly needs to be researched further to find out more about how technology through online orders can influence interest behavior and repurchase decisions among the millennial generation. This research aims to identify factors that influence consumers to make repurchase decisions, including perceived ease of use, perceived usefulness, trust, and purchase decisions. In this research, the population used as a sample was 100 respondents. The author uses primary data, namely by distributing questionnaires to GoFood users. This study uses a quantitative approach. The data processing technique used is by using a t-test on each path of partial direct influence. The research results show that perceived ease of use influences purchase intention, perceived usefulness influences purchase decision, trust influences purchase decision. perceived ease of use influences the intention to repurchase decision, perceived usefulness influences the intention to repurchase decision, trust influences the intention to repurchase decision, and Purchase intention (purchase decision) influences the intention to repurchase (repurchase decision). The implications of this research further clarify how the role of technology applied in the culinary business influences people's interest in using the Gofood application.
Implementasi User Centered Design dan Software Requirements Specification pada Perancangan Website Kurniawan, Dedy; Passarella, Rossi; Fardinelly, Syahria; Anggraini, Febrina Hedy; Mattjik, Hani Alifia; Rahmayuni, Septa
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1608

Abstract

Significant changes in learning approaches, methods and tools in the digitalization era have given rise to the need for Student E-Worksheets (E-LKPD) which can advance students' critical and creative thinking abilities. This research designs E-LKPD based on government regulations using the User Centered Design (UCD), Software Requirements Specification (SRS) and System Usability Scale (SUS) methods. Through the UCD design stages, E-LKPD succeeded in creating a user-friendly website that complies with the learning rules for students in secondary schools. This research aims to produce digital-based teaching materials in the form of E-LKPD by implementing User Centered Design (UCD) and Software Requirements Specification (SRS). The results were proven through Usability Testing using the System Usability Scale (SUS) approach, obtaining a score of 80.667 with the grade A category, Excellent in Adjective, Acceptable, and the Promoter category in the Net Promoter Score (NPS) which shows that E-LKPD has been successfully designed with good usability and suitable for use according to user needs.
Komparasi Layanan Video Live Streaming Menggunakan Metode Quality of Service Hardiyanti, Fitri; Bintoro, Panji; Ratnasari, Ratnasari; Herdian Andika, Tahta; Ardhy, Ferly; Eko Setiawan, Agustinus
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1610

Abstract

Video streaming is growing very rapidly nowadays, many people use it in their daily lives, especially since the pandemic, video streaming has become an important need. Video conferencing applications such as Zoom, Google Meet, and Cisco Webex have become increasingly important in facilitating remote communications, allowing people to communicate, collaborate, and hold virtual meetings without geographic restrictions. This research uses the QoS method to analyze the comparison of service quality from video streaming such as Zoom, Cisco Webex and Google Meet. From the results of the research carried out, each video stream was assessed with QoS. The research carried out was by testing 3 applications, namely Zoom, Cisco Webex and Google Meet, the best results were obtained, namely Zoom with a Throughput value of 6685842, a Delay value of 47ms, a Jitter value of 47 ms and a Packet Loss value of 0.004%. The QoS method can be applied in comparative quality analysis in testing video streaming service applications.
Teknik K-Fold Cross Validation untuk Mengevaluasi Kinerja Mahasiswa Wijiyanto, Wijiyanto; Pradana, Afu Ichsan; Sopingi, Sopingi; Atina, Vihi
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1618

Abstract

A student's ability to complete courses is influenced by various factors, including academic and non-academic aspects. Understanding the factors that influence it is very important to know in order to anticipate and prevent the possibility of failure in the study. It turns out that non-academic factors also have a big influence on student success, especially family factors, such as the level of education obtained by parents, the employment status of parents and the income of both parents. To be able to understand these factors, studies are needed to predict student performance based on family background factors using machine learning models, support vector machine algorithms, naïve Bayes, neural networks and decision trees. The data used was 365 records and 11 attributes, separated by 70% for train data and 30% for test data, which was then used by kfold cross validation to evaluate the results using the parameters n_split=10 and random_state=42. In the confusion matrix parameters, the average (mean) accuracy value for the support vector machine model was 87.68%, naïve Bayes was 90.97%, neural network was 87.95% and decision tree was 85.75%. Meanwhile, the best fold result for SVM is located at the 10th fold with an accuracy of 94.44%, for NB it is located at the 4th fold with an accuracy value of 97.29%, for NN it is located at the 4th fold with an accuracy value of 94.59% and for DT is located on the 5th fold with an accuracy value of 91.89%. Thus, evaluation using k-fold cross validation can be used to predict student performance based on family attributes using the 4th fold which has the highest accuracy of 97.29% in the naïve Bayes model algorithm in order to graduate on time.
Pengembangan E-Portofolio Berbasis Web untuk Career Development Center Fitriani, Leni; Setiawan, Ridwan; Hamdi, Wildan Hidayatul
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1619

Abstract

This research aims to develop an e-portfolio system for students and alumni of the Garut Institute of Technology, which is provided by the Career Development Center (CDC). This system allows users to archive digital work or proof of achievement which can be in the form of achievements, awards, certifications, work history, education, and involvement in organizations, as an e-portfolio. Agile methodology with a Scrum approach is used in this research, and this system is designed as a website using the React JS Framework. The result of this research is an alternative system that makes it easier for users to create and access e-portfolios digitally and helps the Career Development Center increase opportunities for students and alumni to find jobs that suit their skills and interests. This system allows users to manage and share e-portfolio results online or download them in pdf format.