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Arief Hidayat
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INDONESIA
Jurnal Informatika dan Rekayasa Perangkat Lunak
Published by Universitas Wahid Hasyim Semarang
ISSN : 26562855     EISSN : 26855518     DOI : http://dx.doi.org/10.36499/jinrpl
Core Subject : Science,
Computer Science & IT
Journal of Informatics and Software Engineering accepts scientific articles in the focus of Informatics. The scope can be: Software Engineering, Information Systems, Artificial Intelligence, Computer Based Learning, Computer Networking and Data Communication, and Multimedia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Lunak
Articles 20 Documents
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Search results for , issue "Vol. 6 No. 2 (2024): September" : 20 Documents clear
Penentuan Penerima BSM Secara Objektiv Berdasarkan Metode Decision Support System VIKOR Tundo, Tundo; Akbar, Riolandi; Nugroho, Agung Yuliyanto; Saidah, Andi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Abstract

This research was conducted because of complaints from several parents regarding the BSM decision at SDN Kalanganyar ABC, however there were several students who were less well off because the choice of BSM was still subjective. SDN Kalanganyar ABC always holds activities related to BSM admissions once a year. It is hoped that this activity can also provide benefits for students who are poor but have excellent grades so they can carry out activities without being burdened by financial needs. In reality, there are still many students who do not receive BSM, even though according to the requirements, these students should be entitled to receive BSM. Therefore, there is a very irrational subjectivity in the ongoing elections. To overcome this problem, researchers tried to develop an application that applies the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, namely a method that makes decisions based on a rational compromise of criteria. These criteria include student reports, parents' income, academic achievement, dependents, home conditions, parents' relatives, and activity. From the results of the analysis and application of the VIKOR decision support system, subjective results were obtained for students whose evaluation standards and final decisions were lower than several other students, but the school provided BSM recommendations. To prevent the recurrence of this incident, VIKOR was able to answer objective findings with results of 76.57% with subjective findings of 23.43% in the previous system.
Klasterisasi Wilayah Kabupaten/Kota di Sulawesi Tenggara berdasarkan Produksi Bahan Pangan menggunakan Algoritma K-Means Clustering Mursawal, Mursawal; Saputra, Rizal Adi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Abstract

Food ingredients are ingredients produced from agricultural products that are used to make food. These foods consist of vegetables, meat, nuts, sweet potatoes, and so on. Southeast Sulawesi Province is one of the provinces that has a fairly high amount of food production in Indonesia. The application of the K-Means clustering algorithm is used to group districts/cities in Southeast Sulawesi based on food production results. The method used in this study is CRISP-DM with the K-Means clustering algorithm. There are 17 districts/cities in Southeast Sulawesi used in this study. There are 7 types of food ingredients that will be used in the study, namely rice, corn, cassava, sweet potatoes, peanuts, soybeans, and green beans. The results of this study are 1 district/city that has a high level of food production, 4 districts/cities have a moderate level of food production, and 12 districts/cities have a low level of food production. The test results using the Davies Bouldin index are cluster 2 which has the best cluster quality because the results obtained from cluster 2 are 0.30, where the smaller the results obtained, the better the cluster.
Penerapan Algoritma Convolution Neural Network untuk Klasifikasi Jenis Cabai Berdasarkan Warna dan Bentuk buah Rohman, Rizal Abdur; Dasuki, Moh.; Muharom, Lutfi Ali; Rahman, Miftahur
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Abstract

Chili is one of the main agricultural commodities in Indonesia with significant economic value. Various types of chili, such as large chili, bird's eye chili, and green chili, are often difficult to distinguish manually due to their physical similarities. To support advancements in the agricultural sector, this study utilizes artificial intelligence technology, specifically the Convolutional Neural Network (CNN) with VGG-16 architecture, to automatically identify chili types through image analysis based on color and shape. This study aims to measure the accuracy, sensitivity, and specificity of the model in classifying chili types. The results show that the VGG-16 architecture achieved 100% accuracy in training data testing, indicating the model’s ability to detect and classify chili types optimally. In the model evaluation (fold 5), the accuracy was 91.8%, sensitivity was 88%, and specificity was 93.8%. This study confirms that CNN with VGG-16 is effective for image classification, especially when test data shares similar characteristics with training data. This system offers significant potential for application in the agricultural sector, particularly in improving the efficiency and accuracy of identifying other agricultural commodities.
Analisis Implementasi SEO (Search Engine Optimization) dalam Kebutuhan Promosi Online pada Website Masteriwak.id Haris, Achmad; Dasuki, Mohammad; Arifianto, Deni
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Abstract

Digital marketing is the main key in reaching a wider market in the digital era, especially through the use of websites. This research focuses on the implementation of Search Engine Optimization (SEO) to increase the visibility of the Masteriwak.id website, a platform engaged in online koi fish sales. This research uses a quantitative approach with the main stages being an initial performance audit, on-page and off-page SEO optimization, and evaluation of results using Google Search Console and SERPRobot. On-page SEO optimization involves improving internal elements such as meta title, meta description, and website speed, while off-page SEO focuses on strengthening backlinks from quality external sources. The implementation results show a significant increase in impressions, clicks, and keyword rankings on SERPs. For example, the keyword “where to sell koi fish nearby” rose from no rank to position 13 with 35 impressions and 4 clicks. Statistical evaluation using paired-samples t-test shows the difference before and after SEO optimization. The t-test values for the impression parameters were -1.641 (p = 0.243), clicks -2.524 (p = 0.128), and SERP rank -2.535 (p = 0.127), which showed improvement but not yet statistically significant. This study confirms the importance of systematically implementing SEO, although continuous optimization is still required for maximum results.
Prediksi Jumlah Penjualan melalui Live Stream dan Affiliate di TikTok Shop dengan Machine Learning Putri, Nabila Agustina Cahyani; Patrisiane, Viena
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Abstract

Sales techniques have evolved rapidly from conventional methods to online methods often referred to as e-commerce. One of the types of e-commerce that exists in Indonesia is TikTok Shop, on TikToc Shop there are many sales supporting factors. The two sales supporting factors available on TikTok Shop are live stream and affiliate but there is no research to discuss the two factors simultaneously to the volume of sales. The aim of this study is to create a model to predict sales with live stream and affiliate factors on TikTok Shop. The method used in this research is by comparing the results of RMSE (Root Mean Squared Error) formed from the application of machine learning models multiple linear regression and random forest regression. The results of the study show that the best model based on RMSE for predicting sales with the live stream factor and the affiliate on TikTok shop is a multiple linear regression algorithm with RMSE(Root mean squared error) of 39.306882.
Pengelompokan Penyebaran Covid-19 di Provinsi Jawa Barat menggunakan Metode Clustering K-Medoids Luthfiyyah, Ibtihal Qomariyyah; Sari, Betha Nurina
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Covid-19 is a disease that infects the human respiratory system and has a high-speed transmission ability. West Java Province is one of the areas affected by the Covid-19 pandemic. The number of people confirmed with the Covid-19 virus in West Java is still increasing daily. Therefore, it is necessary to group the level of vulnerability to the spread of Covid-19, especially in West Java Province, using data from the official website of the West Java Provincial Government using 5 attributes, namely district_city_name, total_confirmation, confirmed_recovered, confirmed_death, and confirmed_active. This study aims to identify the pattern of the spread of Covid-19 to support more effective decision-making at the regional level. The research method involves a data mining process, namely business understanding, data understanding, data preparation, modeling, evaluation, and deployment based on the CRISP-DM methodology. The modeling process uses the K-Medoids algorithm with 3 clusters according to the government's color zone. The results of this study show 3 clusters, namely the green cluster is the minimum number of cases with 16 districts/cities. The yellow cluster is starting to be alert to the number of cases with 6 districts/cities. The red cluster is a very severe case with 5 districts/cities. The results of the Silhouette Coefficient test that tested n_cluster = 2, 3, 4, and 5 showed that n_cluster = 3 is the best cluster with a value of 0.77.
Klasterisasi Tukang Gigi di Jakarta dengan Algoritma K-Means berdasarkan Daerah Asal Zulkarnain, Iskandar; Fauziyah, Fauziyah
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Tukang gigi registered with the Indonesian tukang gigi Union (STGI) DPW DKI Jakarta organization are 625 members. STGI is an organization that has been incorporated by the Ministry of Law and Human Rights number AHU-000083. AH.01.08.Year 2020. In the distribution of tukang gigi in Jakarta consisting of various regions of origin, the researcher conducted clustering research to find out the distribution of the origin of Tukang Gigi in the Jakarta area. The scope of the research data area is: North Jakarta, West Jakarta, East Jakarta, South Jakarta and Central Jakarta. The results of the clustering of the K-Means Algorithm using the RapidMiner application are as follows: Cluster 0 (C0) : 1 Member, Cluster 1 (C1) : 16 Members, Cluster 2 (C2) : 1 Member. The results included in C0 are the Regency/City of origin of the most tukang gigi, namely: Pamekasan. The results included in C1 are the most diverse Regencies/Cities of the origin of tukang gigi, consisting of 16 Regencies/Cities, including the 3rd most Tukang Gigi' origin areas, namely: Jakarta. While those included in C2 are the 2nd most tukang gigi from origin, namely: Jember.
Metode System Development Life Cycle dalam Perancangan Sistem Informasi Kuliah Kerja Kemasyarakatan Hidayat, Taufik; Mobarrok, Abi; Sukisno, Sukisno; Nugroho, Asep Hardiyanto
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
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Our annual activity, Community Service Internship, will be conducted this semester. Previously, this reporting activity was carried out by sending pictures via WhatsApp. So, we created a reporting system to make it more efficient. Now, the reporting process will be handled through a website and monitoring will also be done through the website. This will make it easier for both participants and mentors to carry out the activity," he said. The methodologies used are SDLC (System Development Life Cycle) for documentation and Prototype methodology for system design. ISO 9126 has been used for system testing with a functionality score of 84% and a usability score of 89.45%. So, from testing to system design to documentation, everything was done as per the requirements.
Klasifikasi Penentuan Kualitas Kayu Jati Berdasarkan Citra Digital Menggunakan Algoritma K-Nearest Neighbour Kamaruddin, Kamaruddin; Umar, Najirah; Wahyuningsih, Pujianti; Sudarsono, Firman
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
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The increase in demand for goods made from wood cannot be limited, especially the demand for table furniture, cupboards and so on. Along with development, teak wood production has shifted to superior types of teak wood because the growth period is faster, but this condition means that the quality of teak wood is not like the old type of teak wood. Difficulty in seeing the quality of wood is a problem faced by craftsmen and furniture makers. The aim of this research is to determine the quality of wood species which are divided into 3 class categories, namely class A, class B and class C. To produce a classification of wood quality, researchers use the KNN method by carrying out HSV color segmentation then analyzing the color value of each image pixel based on the tolerance value on HSV color dimensions. The results of this research were using 65 teak wood training data for each class. Testing was carried out using 27 teak wood test data with an accuracy level of 85.19%, precision reaching 85.46%, recall reaching 85.18% and F1 score reaching 85.3%.
Aplikasi E-voting Berbasis Blockchain dengan Metode Smart Contract Junaedi, Junaedi; Fernando, Albert; Hermawan, Aditiya
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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Voting is an important process in many contexts, such as in organizational decisions and the selection of leaders. With the development of technology, the concept of electronic voting emerged, where humans can cast their votes electronically. Electronic voting has become an important alternative in organizational decision making and leader selection, but often faces challenges related to security and fraud. In this study, a blockchain-based electronic voting application has been developed using the Smart Contract method. Blockchain technology was chosen because of its decentralized and public nature, which can provide a high level of security and transparency to voting data. Evaluation of the application was carried out through a questionnaire filled out by 39 respondents. The results showed a high level of agreement, with 91.46% of respondents stating that they strongly agreed with the effectiveness of this application. This indicates that the implementation of a blockchain-based electronic voting system has the potential to increase trust and integrity in the election process. In addition, this application also offers easy access and data transparency, which is expected to increase public participation in the democratic process. By continuing to conduct further research and development, this blockchain-based electronic voting application has great potential to become the standard in future elections.

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