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Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi
Published by Asosiasi Riset Teknik Elektro Dan Informatika Indonesia
ISSN : 30318998     EISSN : 3031898X     DOI : 10.61132
Core Subject : Science,
Computer Science & IT
hasil-hasil penelitian di bidang Ilmu Komputer Dan Teknologi Informasi. Neptunus : Jurnal Ilmu Komputer Dan Teknologi Informasi berkomitmen untuk memuat artikel berbahasa Indonesia yang berkualitas dan dapat menjadi rujukan utama para peneliti dalam bidang Ilmu Komputer Dan Teknologi Informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 183 Documents
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Diagnosa Penyakit Radang Sendi Menggunakan Metode Dempster Shafer William Jhonatan; Novriyenni Novriyenni; Marto Sihombing
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1013

Abstract

Rapid technological advancements have brought convenience to various fields, including healthcare. Osteoarthritis (OA) is a chronic degenerative joint disease that often affects the knees and hips, particularly in the elderly, and is a major cause of pain, joint dysfunction, and reduced quality of life. The prevalence of OA increases with age, with risk factors such as obesity, excessive activity, and muscle weakness. Early and accurate diagnosis is essential for appropriate treatment. This study aims to develop a diagnostic system for inflammatory arthritis, specifically osteoarthritis, using the Dempster-Shafer method. This method was chosen because of its ability to combine various evidence and expert beliefs to produce a more accurate diagnosis. By utilizing mathematical proof theory, this system is expected to assist medical personnel in detecting OA symptoms more efficiently. The research findings are expected to contribute to the healthcare sector, particularly in improving the accuracy of osteoarthritis diagnosis, allowing for earlier and more appropriate treatment. This system can also be a supporting tool for doctors and patients in understanding joint health conditions.
Penerapan Metode Analytical Hierarchy Process (AHP) dalam Pemilihan Subkontraktor Terbaik pada PT. Tatha Group Rio Ferdinand Situmeang; Yoshida Sary
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1019

Abstract

Subcontractor selection is a crucial factor in determining the success of a construction project. The selected subcontractor not only plays a role in expediting the completion of the work but also influences the overall quality, cost, and timeliness of the project. Mistakes in decision-making, such as selecting a less competent subcontractor, can result in delays in completion, increased project costs, and even decreased construction quality. Therefore, a systematic, measurable, and objective method is needed to support the subcontractor selection process. This study aims to implement the Analytical Hierarchy Process (AHP) method as an approach in a decision support system for subcontractor selection. AHP was chosen because it can decompose complex problems into simpler structures by determining criteria weights and comparing alternatives. The criteria used in this study include expertise, work experience, timeliness of work, equipment availability, and bid price. By assigning weights to each criterion, the selection process can be carried out more transparently and measurably. The case study was conducted at PT. Tatha Group, a company engaged in the construction services sector. In this study, AHP was used to prioritize alternative subcontractors to be selected to assist in project implementation. The research results show that the AHP method produces clear, structured results and supports more accurate decision-making. Thus, the application of AHP not only minimizes subjectivity in assessments but also provides accountable recommendations for selecting the best subcontractor for the project's needs.
Deteksi Warna Dasar Menggunakan Metode Thresholding HSV dengan OpenCV Zidanul Akbar; Asrul Suwondo; Rizky Ramadhan; Abdul Halim Hasugian
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1020

Abstract

Digital image processing is a rapidly developing branch of computer science and has many applications in everyday life. One of the fields that most often utilizes this technique is object detection and color identification in images and videos. This study specifically aims to implement the thresholding method in the HSV (Hue, Saturation, Value) color space to detect three basic colors, namely red, green, and blue, in digital images. The research process begins with uploading images using the Google Colab platform, a cloud-based computing environment that makes it easy for users to run Python programs without requiring additional software installation. After the image is uploaded, the next step is to convert it from the RGB (Red, Green, Blue) color space to the HSV color space. This conversion is important because the HSV color space is more suitable for use in the color segmentation process. The Hue value represents the type of color, Saturation shows the level of saturation, while Value describes the level of brightness. Once the image is in the HSV color space, the next step is to determine the HSV value range for each basic color. This range is determined based on experimental results and references from related literature. Using this range, masking is performed to extract the appropriate pixels so that only the red, green, or blue portions of the image are visible, while the other colors are reduced. The results show that the thresholding method in the HSV color space is capable of detecting primary colors with a good level of visual accuracy, especially in simple images with contrasting backgrounds. The implementation of this program is relatively lightweight, easy to run directly in Google Colab, and does not require high-spec hardware. Therefore, this method is very suitable for use as basic learning material for digital image processing, both for students and novice researchers.
Sistem Pendukung Keputusan untuk Rekomendasi Obat Luar dengan Menggunakan Metode Simple Additive Weighting (SAW) Rudi Hermawan; Rahman Abdillah; Wawan Hermawansyah; Nur Alam
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 2 (2025): Mei: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i2.1026

Abstract

Quality health services are an important factor in increasing patient trust in medical facilities and health workers. One of the crucial aspects is accuracy in providing drug recommendations that suit the patient's needs. Drug recommendations are influenced by various criteria, including effectiveness, safety, price, availability, and potential side effects. However, in practice, there is often a gap between the patient's expectations and the reality of the treatment received. This can affect patient satisfaction and perception of health services. To overcome these challenges, a Decision Support (SPK) is needed that is able to provide drug recommendations in a more objective, measurable, and structured manner. This study uses the Simple Additive Weighting (SAW) method because of its advantages in processing various complex and diverse criteria. SAW works by giving weight to each attribute, normalizing the data, and then calculating the preference value to determine the best alternative from several available drug options. The results of the study show that the SAW method is able to produce more structured and consistent recommendations than manual determination. In this study, the drug with the highest preference value, which is 92.00, was recommended as the top choice. These findings confirm that SPK and SAW-based approaches can be an effective solution in supporting medical personnel, especially in the selection of external drugs. In addition to improving decision accuracy, this SPK also has the potential to be further developed, for example by integrating into an electronic medical record (EMR) or based on a mobile application, so that its use becomes more practical and accessible. Thus, the implementation of the SAW method in SPK not only provides benefits on the technical aspect, but also contributes to improving the quality of health services as a whole.
Sistem Pendukung Keputusan Penilaian Kinerja Karyawan Menggunakan Fuzzy Logic Tsukamoto Haryatno Saputra; Andi Yulia Muniar; Mashud Mashud
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1028

Abstract

Employee performance appraisal is an important process in human resource management that aims to evaluate individual work achievements based on certain criteria set by the organization. This process not only serves to assess the extent to which an employee meets work standards, but also serves as a basis for strategic decision-making, such as job promotions, bonus awards, and career development planning. However, in practice, CV. Surya Perkasa Makassar faces serious obstacles in the form of subjectivity in the assessment process, because the benchmarks used still tend to be based on the likes or dislikes of superiors. This causes the evaluation results to be less objective, inconsistent, and potentially reduce employee work motivation. To overcome these problems, this study aims to develop a decision support system for employee performance appraisal using the Tsukamoto Fuzzy Logic method. This method was chosen because it is able to accommodate uncertainty in the assessment, resulting in more objective, measurable, and consistent decisions. This study uses a Research and Development (R&D) approach with a Black Box Testing method to ensure system functionality. The assessment criteria used include five main aspects, namely work quality, work quantity, discipline, responsibility, and cooperation. Data from these criteria is processed through fuzzification, inference, and defuzzification stages to obtain the final employee performance score. Test results indicate that all system features function as expected. The system is able to prevent data duplication, validate input, and produce accurate final performance scores. The implementation of the Tsukamoto Fuzzy Logic method has proven effective in reducing the level of subjectivity that typically occurs in manual assessments. Therefore, this system can be used as a reliable tool in managerial decision-making, both regarding promotions, bonus awards, and planning employee future career development.  
Penerapan Metode Teorema Bayes untuk Memprediksi Penyakit pada Tanaman Kopi Zulkifli Zulkifli; Relita Buaton; I Gusti Prahmana
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1025

Abstract

Coffee is a leading commodity in Indonesia's agricultural sector, possessing high economic value and providing a livelihood for many farmers. However, coffee plant productivity often declines significantly due to various diseases affecting the leaves, stems, and berries. This situation is exacerbated by the lack of knowledge among most farmers in recognizing early disease symptoms, resulting in delayed treatment. Consequently, crop losses are unavoidable. Based on these challenges, this study aims to design and build an expert system capable of diagnosing coffee plant diseases quickly, precisely, and accurately using the Bayesian Theorem method. This method was chosen because it can calculate the probability of a disease occurring based on observed symptoms in plants. The Bayesian approach allows the system to provide more reliable diagnostic results by updating the probability values ​​as new evidence is introduced. The developed expert system is web-based, making it easily accessible to users, both farmers and other interested parties. Users simply select the symptoms observed in coffee plants, and the system will then provide a diagnostic result in the form of possible diseases and their probability levels. Test results indicate that the system is capable of providing fairly accurate diagnostic results and can be used as a basis for farmers in making initial decisions regarding coffee plant disease management. With this expert system, farmers are expected to improve their ability to detect coffee plant diseases early, thereby maintaining crop productivity. This expert system is expected to be an effective decision support tool for farmers to reduce crop losses and improve agricultural sustainability.
Penerapan Sistem Informasi Pemasaran Toko Oleh-Oleh Makanan Khas Danau Maninjau Berbasis WEB Wizra Aulia; Stefani Hardiyanti Putri; Imelda Juniarta Emin
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1035

Abstract

Lake Maninjau specialty food souvenir shop is one of the micro businesses that sells a variety of traditional regional food products. So far, the marketing process and transaction management are still done manually, which causes limited market reach, difficulty in recording sales, and lack of effectiveness in product promotion. This research aims to design a web-based marketing information system to support the sales process, promotion, and data management in a more efficient and integrated manner. The system development method uses the System Development Life Cycle (SDLC) approach of the waterfall model, which includes the planning, needs analysis, system design, implementation, and testing stages. Data collection was conducted through field observations, interviews with business owners, questionnaires to customers, and literature studies related to information systems and digital marketing strategies. The designed information system includes various main features such as product data management, sales transaction recording, automatic sales report generation, social media integration, and product promotion pages. In the marketing aspect, this system allows businesses to display product catalogs online, provide real-time promotional information, and establish direct interaction with customers through contact and ordering features. In addition, the use of this system allows stores to reach a wider market, including potential customers from outside the Lake Maninjau area, through an integrated digital marketing strategy. The implementation results show that this web-based system can increase the effectiveness of product promotion, speed up the transaction process, and improve the quality of customer service. With this system, souvenir shops can compete more competitively in the digital era, as well as strengthen brand image and customer loyalty through more structured and sustainable marketing.
Analisis Kerusakan pada Beton dengan Citra Digital Menggunakan Metode Edge Canny Detection M. Naufal Syahputra; Achmad Fauzi; Melda Pita Uli Sitompul
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 4 (2025): November: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1047

Abstract

This study aims to design and implement a damage analysis system for concrete surfaces by utilizing digital image processing based on the Canny edge detection method. The developed system allows users to upload images of concrete surfaces, which are then processed through several stages: conversion to grayscale, transformation to binary images, and crack edge detection using the Canny operator. This process aims to automatically detect crack patterns on the concrete surface. The detection results, represented as edge lines, are used to calculate the percentage of the damaged area. Based on this percentage value, the system automatically classifies the damage level into light, moderate, or severe categories. System testing shows that the Canny method can accurately identify crack patterns, with sufficient detection levels to be used in monitoring the condition of concrete surfaces. The analysis results are then presented in both visual and numerical forms, providing valuable information for assessing the structural condition of concrete. Thus, this system can serve as an efficient and effective tool for early detection of structural damage in concrete infrastructure, ultimately supporting better maintenance and repair efforts.
Implementasi Sistem Pakar Diagnosa Penyakit Tifus dengan Metode Certainty Factor Bintang Wicaksana; Novriyenni Novriyenni; Suci Ramadani
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 4 (2025): November: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1048

Abstract

Typhoid fever is a significant health issue caused by the Salmonella Typhi bacteria, leading to symptoms such as fever, abdominal pain, diarrhea, muscle pain, and serious complications if not treated promptly. A common challenge faced by society is limited access to medical professionals, especially in remote areas, and delays in recognizing symptoms. To address this problem, this study designs and implements a web-based expert system using the Certainty Factor (CF) method, which helps diagnose typhoid fever quickly and accurately. The Certainty Factor method is used to calculate the certainty level of the symptoms experienced by the patient, providing a diagnosis result in the form of early-stage typhoid, mild typhoid, or severe typhoid. The system was developed using PHP programming language and MySQL database, and tested at RSUD Djoelham Binjai City. The research data was obtained from patients at RSUD Djoelham Binjai with a case study on patient number 22. The processing of symptoms through Certainty Factor calculation showed that the patient is most likely to have severe typhoid with a certainty value of 0.9443 or 94.43%. This result proves that the Certainty Factor method can be used to assist in providing an accurate early diagnosis of typhoid fever with a high degree of accuracy.
A Car Booking Method Using K-Means : Case Study: Car Rental Tsalits Wildan Hamid; Mufti Ari Bianto
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 4 (2025): November: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1055

Abstract

This study discusses the application of the K-Means Clustering algorithm in the car rental ordering system. The objective is to help group booking data based on certain patterns such as car type, booking frequency, and rental duration. The clustering results are expected to improve service efficiency and help companies better understand customer preferences. The research was conducted using historical car rental booking data from a rental company. The results show that the K-Means method can successfully cluster booking data into several useful clusters for business decision-making. This extended paper also explores theoretical concepts of clustering, related studies, limitations of the method, and potential future enhancements such as integrating predictive analytics. It highlights the importance of transforming large volumes of raw booking data into actionable business intelligence to support marketing strategies, fleet management, and customer segmentation.  

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