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Dewan Editor Editor-in-chief Ali Firdaus, Teknik Komputer, Politeknik Negeri Sriwijaya, Indonesia Managing Editor M. Miftakul Amin Section Editors Slamet Widodo, (Scopus ID=57202841454, Scopus H-Index=2), Teknik Komputer, Politeknik Negeri Sriwijaya, Palembang Adi Sutrisman, (Scopus ID=57201578740, Scopus H-Index=2), Teknik Komputer, Politeknik Negeri Sriwijaya, Palembang Ervi Cofriyanti, (Scopus ID=55848102300, Scopus H-Index=2), Teknik Komputer, Politeknik Negeri Sriwijaya, Palembang, Indonesia Ikhthison Mekongga, (Scopus ID=57194067236; Scopus h-index=1), Teknik Komputer, Politeknik Negeri Sriwijaya, Palembang, Indonesia Yulian Mirza, Teknik Komputer, Politeknik Negeri Sriwijaya, Indonesia Ema Laila, Teknik Komputer, Politeknik Negeri Sriwijaya, Indonesia Mustaziri ,, Teknik Komputer, Politeknik Negeri Sriwijaya, Indonesia Isnainy Azro, Teknik Komputer, Politeknik Negeri Sriwijaya, Indonesia Peer-Reviewers (Mitra Bestari) Muhammad Rahmat Widyanto, (Scopus ID=8921529200, Scopus H-index=6)Ilmu Komputer, Universitas Indonesia, Indonesia Admi Syarif, (Scopus ID=6508046463, Scopus H-index=6), Universitas Lampung, Lampung Andino Maseleno, (Scopus ID=55354910900, Scopus H-index=6), STMIK Pringsewu, Lampung Edy Winarno, (Scopus ID=56049606100, Scopus H-index=3), Universitas STIKUBANK, Semarang Joko Triloka, (Scopus ID=56401829500, Scopus H-index=2), IIB Darmajaya, Lampung Thamrin Latief, Universitas Sriwijaya, Indonesia Herlambang Saputra, Teknik Komputer, Politeknik Negeri Sriwijaya
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Jupiter
Published by Politeknik Negeri Sriwijaya
ISSN : 20852029     EISSN : 2622609X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science
Tentang Jurnal Ini Fokus dan Ruang Lingkup Bidang kajian yang dapat dimuat pada jurnal Jupiter meliputi dan tidak terbatas pada: Mobile Computing Image Processing Computer Graphic Artificial Intelligence Information Retrieval Computer Vision Algorithm & Complexity Data Mining Information System Distributed System Computer & Network Security Cloud Computing Cryptography Human Computer Interaction Speech Processing Natural Language Processing Pervasive Computing Social Media Semantic Web Technologies Game & Multimedia Proses Peer Review Artikel yang masuk ke dalam Jurnal JUPITER akan dilakukan review oleh editor dalam gaya selingkungnya dalam waktu sekitar maksimal 1 minggu. Dari proses review format maka akan dilanjutkan dengan proses review oleh tim reviewer Jurnal JUPITER. Dalam hal ini membutuhkan waktu sekitar 1 minggu - 2 bulan. Proses review artikel menggunakan Double Peer Review. Jika artikel dinyatakan Diterima, maka penulis tidak perlu untuk melakukan revisi. Namun jika artikel dinyatakan Diterima dengan perbaikan, penulis harus memperbaiki artikel sesuai dengan hasil review dan mengembalikan ke tim redaksi melalui OJS Jurnal JUPITER dalam kurun waktu 1 - 2 minggu. Sejarah Jurnal Jurnal Jupiter merupakan jurnal yang diterbitkan oleh Jurusan Teknik Komputer Politeknik Negeri Sriwijaya. Penerbitan jurnal ini bertujuan sebagai wahana komunikasi dan informasi ilmiah dalam bidang komputer yang diharapkan dapat membantu para dosen, peneliti, mahasiswa, dan para stakeholder untuk mempublikasikan hasil penelitian dan kajian ilmiah yang telah berhasil dilakukan. Sehingga hasilnya dapat dikonsumsi oleh berbagai komunitas ilmiah di seluruh Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 424 Documents
 33   34   35   36   37 
Perancangan Aplikasi Akademik Pe Perancangan Aplikasi Akademik Pembayaran Sumbangan Pembinaan Pendidikan Menggunakan Metode User Centered Design (UCD): Perancangan Aplikasi Akademik Pembayaran Sumbangan Pembinaan Pendidikan Menggunakan Metode User Centered Design (UCD) Sanjaya_Sjy, M rudi sanjaya Sanjaya; Lestari Ruskan, Endang; Wijaya Putra, Bayu; Arrijal Ismail, Ahmad; Izzatul Maula, Nurly; Saputra, Ariansyah
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13118515

Abstract

Abstract Technology is developing from year to year, so technology is needed in the form of an application, one of which is to simplify the academic administration process, one of which is designing an application for paying SPP donations (Payment of Academic Development Contributions). The design of this application aims to simplify the administration part for paying Educational Development Contributions (SPP). The research method uses interviews, observation and literature studies, then the method uses (User Centered Design) which consists of context analysis, defining requirements, design, evaluation. The design of this application is tested with the level of efficiency using the user centered design method. (UCD), The results of validity testing for the design of Educational Development Contribution (SPP) payment applications, where the efficient levels were obtained were (1) 0.646, (2) 0.772, (3) 0.595, (4) 0.853, (5) 0.514, ( 6) 0.831, (7) 0.554, (8) 0.872, (9) 0.62, (1) 0.852 stated that the efficiency level is valid. The results of reliability testing for designing the Education Development Contribution (SPP) payment application, where the efficient level is obtained is ( 1) 0.887, (2) 0.878, (3) 0.889, (4) 0.872, (5) 0.894, (6) 0.873, (7) 0.895, (8) 0.868, (9) 0.888, (10) 0.893 declared Level efficiency is declared Reliable, where the test Keywords— Aplication, Design Website, UCD, Validitas, Realibilitas.
Pengukuran Tingkat Kapabilitas Teknologi Informasi Pada Perum BULOG Kantor Cabang Lhokseumawe Angga Pratama; Rumagit, Bella Fadillah Rahmah; Muhammad Ikhwani
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13251052

Abstract

Information technology provides great benefits to every organization by facilitating decision making and streamlining operational activities and daily business processes. Perum BULOG Lhokseumawe Branch Office is a company that implements information technology. COBIT 2019 is the framework used in this research which has standards for implementing information technology governance. References from annual reports can be used as a reference in analyzing the level of information technology capabilities in companies using the COBIT 2019 design factor toolkit. After analyzing the questionnaire distributed using a Likert scale, process objectives that can be evaluated. The calculation results are obtained with the following capability level results, APO03 is at capability level 1 and has a gap of 2, APO12 is at capability level 2 and has a gap of 1, APO13 is at capability level 3 and has no gap, namely 0, BAI01 is at capability level 2 and has a gap of 1, BAI02 is at capability level 1 and has a gap of 2, BAI03 is at capability level 1 and has a gap of 3, BAI06 is at capability level 1 and has a gap of 3, BAI07 is at capability level 2 and has a gap worth 1, BAI10 is at capability level 1 and has a gap worth 3. Objectives that have a gap will be given recommendations.   Keywords—Information Technology, COBIT 2019, Capability Level, gap
Multimedia Interaktif Pengenalan Mamalia Indonesia Sebagai Tindakan Preventif Mencegah Kepunahan Metode MDLC Halim Pratama, Muhammad Fajrul; Hanugrah Surya Purwaka; Dasril Aldo
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12542958

Abstract

 Introduction to endangered mammals in Indonesia still only uses textbooks which are less effective and interesting. Then the lack of knowledge about Indonesian mammals which are threatened with extinction has resulted in a lack of awareness regarding these mammals, making the public less concerned about Indonesian mammals which are threatened with extinction. This research aims to design a learning media that introduces endangered Indonesian mammals with the hope of creating awareness about mammals. Using the Multimedia Development Life Cycle (MDLC) method which has stages of concept, design, material collection, assembly, testing and application distribution. The results obtained show that learning media applications consisting of text, images, sound and video can be accessed by users, especially children. The alpha and beta tests carried out obtained a score of 4.575 on a scale of 5, which indicates that the application is suitable for use. With this learning media, it is hoped that it can increase awareness of Indonesian mammals which are threatened with extinction.   Keywords—Mammals, MDLC, Learning Media, Extinction
JURNAL SISTEM PENDUKUNG KEPUTUSAN PENILAIAN EFEKTIVITAS PEMILIHAN DOSEN TERBAIK ITBA DIAN CIPTA CENDIKIA BANDAR LAMPUNG MENGGUNAKAN METODE AHP DAN TOPSIS: This study aims to select the best lecturer using the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The criteria used in this research include teaching experience, research quality or academic contribution, involvement in academic activities, presentation quality or abilit Pramodiyo Wilantara, Rangga; Wasilah, Wasilah; Triloka, Joko
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12177438

Abstract

The problem faced by ITBA Dian Cipta Cendikia is related to the assessment of the learning process which is currently still being carried out through filling out questionnaires by students and interviews. The assessment calculation process is still done manually, there needs to be a system that processes data on outstanding lecturers so that from this award all lecturers are motivated to develop their abilities.This research aims to select the best lecturer using the AHP and TOPSIS methods. The criteria used in this study include teaching experience, quality of research or academic contributions, involvement in academic activities, quality of presentation or ability to deliver material, openness to students, and the relevance of the material to the course. The weights for each of the seven criteria were determined through AHP, while TOPSIS was used to determine the best lecturer based on relative preference values. The results of the study indicate that Akni Widyastuti has the highest relative preference value, namely 0.700. The calculations carried out show that the AHP and TOPSIS methods provide structured and objective results in determining the best lecturers based on various relevant criteria.   Keywords: Analytic Hierarchy Process (AHP), TOPSIS, Decision Support System.
Pengembangan Perancangan Aplikas Pengembangan Perancangan Aplikasi Akademik Penjadwalan Mata Pelajaran Menggunakan Metode UML dan UCD (User Centered Design) Sanjaya, M. Rudi; Ruskan, Endang Lestari; Putra, Bayu Wijaya; Ismail, Ahmad Arrijal; Maula, Nurly Izzatul
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13764250

Abstract

Abstract Technological from time to time are increasingly needed, especially in the world of education, where the world of education still uses conventional methods, this method can be replaced by computerized methods or it can be said that technology is in the form of applications, with applications it can make work in schools or Islamic boarding schools easier. What will be built is a website for scheduling subjects in schools or Islamic boarding schools. The aim of this research is to design, build and develop an academic application for scheduling subjects using the UCD (User Centered Design) method. The benefit of this research is that it makes it easier to manage integrated subject scheduling based on website, the research method uses interviews, observation and literature studies, then the design method uses the UML (Unified Modeling Language) method, then for evaluation uses the UCD (User Center Design) method, the results of validity testing from questions L1 to L 10 are found df = n-2 =28-2 =26, r calculated to get L1 is 0.639, L2 = 0.735, L3= 0.511, L4=0.753, L5=0.486, L6=0.822, L7 =0.471, L8= 0.868, L9=0.620 , and L10 = 0.834 where r calculated > r table obtained r table is 0.3172, that validity testing produces valid data, then the total value for reliability testing if the Cronbach's alpha value is > 0.70 is reliable, the total for reliability testing is 0.908, meaning the data is reliable. Keywords—UCD, UML, Validity and Reliability.
Sistem Pakar Diagnosa Penyakit Pakcoy Hidroponik Pada Unit Usaha Sehati Farm Dengan Metode Forward Chaining Dan Naive Bayes Amara, Amara Dian Safitri; Hartono, Budi
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12625069

Abstract

The Sehati Farm Business Unit, located in Klidang Wetan Village, Batang Regency, is a vegetable growing business unit using hydroponic cultivation techniques. This cultivation was founded by Sajuri, S.P., M.P in 2017, when he was initially founded just to pursue a hobby, but finally, when he saw that the marketing prospects for hydroponic vegetables in urban areas were greatly increasing and good, the cultivation eventually developed into a hydroponic vegetable growing business unit. One of the vegetables grown in the Sehati Farm business unit is Pakcoy vegetables. This vegetable is a vegetable that looks similar to mustard greens, but Pak Choy has different leaf stems than mustard leaf stems, Pok Choy stems look wider and slightly smaller than mustard leaf stems. Pakcoy vegetables have plant diseases caused by pests such as; Leaf caterpillars, fleas, apids, grasshoppers and leaf rot. From this problem, the author created a system that is useful for detecting this problem, namely creating an Expert System that uses the PHP and MySQL programming languages so that this expert system can provide information about disease symptoms and treatment solutions for ordinary people or hydroponic farmers. Key words: hydroponic plants, disease symptoms, expert system
teknika DATA MINING TO PREDICTE STUDENT ACHIEVEMENT BASED ON SOCIO-ECONOMIC, MOTIVATION, DISCIPLINE AND PAST ACHIEVEMENT AT VOCATIONAL SCHOOL 1 PENAWARTAMA TULBABAG USING THE C4.5 ALGORITHM: DATA MINING UNTUK MEMPREDIKSI PRESTASI PESERTA DIDIK BERDASARKAN SOSIAL EKONOMI, MOTIVASI, KEDISIPLINAN DAN PRESTASI MASA LALU DI SMKN 1 PENAWARTAMA TULANG BAWANG MENGGUNAKAN ALGORITMA C4.5 Suroto, Suroto; Purnomo, Hendri; Estian Pambudi, Randi
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12743856

Abstract

SMK Negeri 1 Penawartama Tulang Bawang is a school whose students come from various villages in the district. Most of the students come from families with limited economic conditions and low levels of education. These factors often affect the students' learning motivation. The aim of this research is to predict students' academic performance based on parents' socioeconomic status, motivation level, discipline level, and previous academic achievements using data mining methods with the C4.5 algorithm. This research employs a quantitative approach involving 606 tenth-grade students at SMK Negeri 1 Penawartama Tulang Bawang. Data collection methods used include documentation and questionnaires. The research results show that the prediction analysis using decision trees has an accuracy rate of 98.02%, precision of 94.44%, and recall of 77.27%.   Keywords: data mining, C4.5 algorithm, accuracy, precision, and recall
teknika Perbandingan Performance Algoritma KNN dan Liner Regresi Dalam Percepatan Masa Tanam Sawi Berdasarkan Suhu air dan Nutrisi: Comparison of the Performance of the KNN and Liner Regression Algorithms in Accelerating Mustard Planting Period Based on Water Temperature and Nutrients Fanany, M. Zaky; Widi Nugroho , Handoyo
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12735462

Abstract

Hydroponics is a technological advancement in agriculture that allows planting without using soil and relying on water and nutrients for plant growth. This method is effective in overcoming problems in the agricultural sector such as drought and pests which can inhibit the growth of vegetable plants.This study investigates the use of K-Nearest Neighbors (KNN) and Linear Regression algorithms to predict the growth time of mustard greens based on water temperature and nutrient levels. The dataset used includes these variables measured during the growth period. Experimental steps included dividing the data into training and testing sets, feature standardization, model training, and evaluation using metrics such as Mean Squared Error (MSE): KNN model (3.69625) had lower MSE compared to Linear Regression (4.33562), Root Mean Squared Error (RMSE): KNN (1.92156) had lower RMSE compared to Linear Regression (2.08121), R^2 Score: KNN (0.96567) had a slightly higher R^2 Score compared to Linear Regression (0.95932).   Keywords:K-Nearest Neighbors, KNN, Linear Regression, growing time, mustard greens, prediction, model evaluation
Klasifikasi Persediaan Stok Darah Menggunakan Algoritma K-NN, Decision Tree, dan JST Backpropagation Rijal Fauzan, Yulis; Fajarendra, Yusril Iza; Ridha , M Noor Tasiur; 'Uyun, Shofwatul
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13755935

Abstract

The demand for blood is critical for various purposes, such as surgeries, transplants, cancer treatments, dialysis, and disaster victims. The availability of blood at the Blood Transfusion Unit (UTD) of the Indonesian Red Cross (PMI) is crucial, as a shortage of stock can endanger patients' lives. Therefore, this study aims to evaluate the condition of blood stock to determine whether it is safe or insufficient. This research focuses on comparing blood stock classification at PMI Kota Yogyakarta using three algorithms: K-Nearest Neighbor, Decision Tree, and Artificial Neural Network (Backpropagation). The study objects consist of 216 blood stock data point. Testing is conducted using the K-Fold Cross Validation method with a k value of 8 on 216 data points. The research results show that the K-Nearest Neighbors (KNN) algorithm achieves an Accuracy of 85.18%, Recall of 85.03%, Precision of 89.25%, F1-Score of 87.09%, and Specificity of 84.39%. The Decision Tree algorithm achieves an Accuracy of 84.72%, Recall of 88.18%, Precision of 86.15%, F1-Score of 87.15%, and Specificity of 78.08%. The Artificial Neural Network (Backpropagation) algorithm shows the best performance with an Accuracy of 93.05%, Recall of 96.06%, Precision of 92.42%, F1-Score of 94.20%, and Specificity of 89.35%. Thus, it can be concluded that the Artificial Neural Network (Backpropagation) algorithm outperforms the other algorithms in classifying blood stock availability.  Keywords—PMI, Blood, Classification, K-Nearest Neighbor, Decision Tree, Backpropagation
Deteksi Struktur Jantung pada anak menggunakan CNN Arsitektur YOLO versi 5 Pratama, Jimiria; Nurmaini, Siti; Fachrurrozi, Muhammad
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13762983

Abstract

 A major challenge in the medical field is detecting heart structures in children, which requires a high level of time and accuracy. To address this issue, the You Only Look Once version 5 (YOLO v5) method is employed to identify children's heart structures using a convolutional neural network (CNN). YOLO v5s, YOLO v5n, and YOLO v5x are three versions tested to identify children's heart structures. Standard evaluation metrics such as precision, recall, F1 score, mean average precision, and IoU threshold 0.5 (mAP_0.5) are used to assess the model's performance. Experimental results indicate that YOLO v5s demonstrates the best performance in detecting children's heart structures with high detection rates and accuracy. This model can effectively detect heart structures in various image positions and conditions, suggesting potential for more accurate and effective diagnostic use in identifying heart diseases in children. The development of heart structure detection models is highly relevant in the medical field. The deep learning model using YOLO v5s offers remarkable capabilities in various visual applications. This model can be an efficient and reliable solution in various fields, providing reliable and accurate performance to streamline data analysis processes and enhance work efficiency.  Keywords—Detection, Pediatric Cardiac Structures, Convolutional Neural Network, YOLO v5

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