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Jurnal Ilmu Komputer
Published by Universitas Pamulang
ISSN : -     EISSN : 3031125X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Jurnal Ilmu Komputer merupakan jurnal ilmiah dalam bidang Ilmu Komputer, Informatika, IoT, Network Security dan Digital Forensics yang diterbitkan secara konsisten oleh Program Studi Teknik Informatika S-2, Program Pascasarjana, Universitas Pamulang, Indonesia. Tujuan penerbitannya adalah untuk memberikan informasi terkini dan berkualitas kepada para pembaca yang memiliki ketertarikan terhadap perkembangan ilmu pengetahuan dan teknologi di bidang-bidang tersebut. Setiap artikel yang dimuat dalam Jurnal Ilmu Kompute merupakan hasil kegiatan penelitian, tinjauan pustaka, dan best-practice. Jurnal Ilmu Komputer terbit dua kali dalam setahun, tepatnya pada bulan Juni dan Desember. Jumlah artikel untuk setiap terbitan adalah 10 artikel.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 63 Documents
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Analisis Minat Siswa Dalam Memilih Kompetensi Keahlian Dengan Metode Simple Additive Weighting (SAW) dan Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) Pahira, Wulan; Anggai, Sajarwo; T., Thoyyibah
Jurnal Ilmu Komputer Vol 1 No 2 (2023): Jurnal Ilmu Komputer (Edisi Desember 2023)
Publisher : Universitas Pamulang

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Abstract

Every student who graduates from middle school plans to continue their education to the high school/vocational school level. Vocational Schools are schools that develop and prepare students to be able to work in their respective fields. There are 3 Skill Competencies, namely, 1) Institutional Financial Accounting, 2) Office Management and Business Services, and 3) Computer Network and Telecommunications Engineering. Of these 3 skill competencies, prospective students need to consider them in choosing skill competencies that suit their interests and talents, because after choosing skill competencies students will carry out education for approximately 3 years. In creating this skill competency selection system, the author used 2 methods, namely the SAW method and the MOORA method with 6 criteria: mathematics scores, ICT scores, English scores, math test scores, computer knowledge, and psychological tests. Based on the results of research using these two methods, the results obtained with preference values A1=0.782, A2=0.72, A3= 0.725, then the MOORA method obtained preference values A1=0.601, A2=0.53, and A3=0.527 with these two methods showing the same results as The highest preference value is A1. So that students enter the Institution's Financial Accounting Skills Competency. After testing the system using the SUS method, the percentage results were 75.9% (Acceptable) so that this system can be accepted and used effectively and efficiently in selecting skill competencies.
Analisis Aplikasi Iuran Pengelolaan Lingkungan Berbasis Web Dengan Proses Monitoring dan Evaluasi COBIT 4.1 (Studi Kasus Perumahan Metro Residence) Edlianto, Dionisius Riyan; Susanto, Agung Budi; Tukiyat
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

Metro Residence Housing has a total of 381 houses. The sales admin manually inputs environmental management contribution data into Excel every month. To address this, an application was created using the Scrum method, chosen for its adaptability and efficiency. Sprints one to three, each lasting two weeks, completed in six weeks. Post-development, a black box test with eight menu tests confirmed the system's functionality, with all tests passed. Subsequent direct testing with the admin over a month led to application acceptance. An IT governance audit followed, involving five respondents: sales admin, estate admin, admin manager, branch IT staff, and HO IT staff. The COBIT 4.1 audit rated Bogor Metro Residence at level three, indicating standardized, documented, and communicated IT procedures. Limited IT staff understanding prevented a higher score. The application can be further developed into a mobile app for residents to monitor bills and make payments.
Pengembangan Prototipe Alat Sortir Berdasarkan Warna Berbasis Internet of Things (IoT) Menggunakan Thingspeak Imron, Ali; Anggai, Sajarwo
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

Manual sorting processes in the agriculture and manufacturing industries often require significant costs, time, and labor, impeding production efficiency and increasing the risk of errors. The proposed solution is to utilize an automated sorting device based on the color of the objects. This sorting prototype was developed using IoT technology with the ThingSpeak platform through a Research and Development method. The development steps included needs analysis, system design, prototype implementation, testing, and performance evaluation. The prototype incorporates a TCS 3200 color sensor, Nodemcu ESP8266 IoT module, servo motor, and the ThingSpeak platform. Testing was conducted using red, green, orange, and black objects. The test results demonstrated that the prototype achieved high accuracy in color identification, rapid data processing response, and consistent data transmission to ThingSpeak. The prototype was successfully developed according to the plan. Performance evaluation indicated its effectiveness in supporting color-based sorting processes in the agriculture and manufacturing industries. This prototype significantly contributes to the automation of industrial processes, particularly in using color as the primary criterion for object separation.
Analisis Prediksi Hasil Pemilu Legislatif DPR RI DKI Jakarta Tahun 2024 Menggunakan Metode Random Forest dan Gradient Boosting Effendy, Rangga Febrian; Susanto, Agung Budi; Anggai, Sajarwo
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

In general elections, it is closely related to predictions, predictions play an important role in obtaining results in future legislative elections. Predicting general election results can be done through a series of processes to find patterns and knowledge from a set of data using data mining techniques. To get accurate prediction results in the future, a method is needed that can be used as predictive modeling. This research aims to find out the results of model testing and predictions for the 2024 DPR RI DKI Jakarta legislative election using random forest and gradient boosting methods and to find out patterns and knowledge from the prediction results themselves. Based on the model testing results, the gradient boosting method has an accuracy value of 95.8%, precision 72.2% and recall 61.9%. Meanwhile, random forest has an accuracy value of 95.4%, precision 63.6% and recall 33.3%. The pattern and knowledge from the prediction results is that the elected legislative candidates on average are in serial numbers 1 and 2, have valid votes starting from 63,529, are male and have a doctoral degree.
Ekstraksi Topik dalam Dataset Menggunakan Teknik Pemodelan Topik Anggai, Sajarwo; Tukiyat; Rivai, Abu Khalid; Zain, Rafi Mahmud
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

The issue in this research is the lack of understanding regarding the main topics and their changes in speeches and media publications related to President Joko Widodo. This study aims to identify, analyze, and predict changes in key topics within speeches, statements, and media publications related to President Joko Widodo using Latent Dirichlet Allocation (LDA) topic modeling techniques. The research employs a quantitative approach to analyze President Joko Widodo's speech texts using the Latent Dirichlet Allocation (LDA) method. The process began with scraping documents from the official website of the Republic of Indonesia's Secretariat, resulting in 5,988 speech transcripts from October 20, 2014, to March 2, 2024. Text preprocessing involved tokenization, stopword removal, and stemming/ lemmatization, followed by dictionary-term formation. The findings indicate that the model with k=16 has the highest coherence (0.554) and the best perplexity at k=21 (-13.130). The main topics identified include Nationalism and National Values, Regional Government, and Education and Children. Topic visualization with PyLDAvis aids in the exploration and identification of topics, providing insights for decision-making and policy development. To enhance understanding of topic changes, it is recommended to conduct trend analysis on key topics over time. This will help identify how President Joko Widodo's priorities shift and respond to new issues. By monitoring these trends, the research can provide deeper insights into the evolution of policies and the President's focus.
Pengembangan Sistem Employee Self Service (ESS) Berbasis Web Terintegrasi Dengan Kinerja Karyawan (Studi Kasus: Astrido Group) Wibowo, Satria Ardi; Susanto, Agung Budi; Anggai, Sajarwo
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

Technological developments in the 4.0 era require humans to act effectively and efficiently. Astrido Group is a company operating in the automotive sector, especially car sales and services. The expected goal of this research is to build an information sistem that makes it easier for employees to update personal data, download attendance reports, process leave applications and approvals and obtain employee performance information. The sistem development method is Rapid Application Development (RAD) and modeled using the Unified Modeling Language (UML). Focus Group Discussion (FGD) Used as validation testing. The resulting software quality test is based on the four software quality characteristics of the ISO 9126 model, namely: functionality, reliability, usability and efficiency which are combined using the questionnaire method. The Black Box test results were 100%, which indicates the system was well received by users, while testing with Acunetix WVS was at Threat Level 2, which indicates the application being built is quite safe.
Analisis Disaster Recovery Plan Keamanan Data dan Informasi Menggunakan NIST Framework (Studi Kasus: Biro Teknologi Informasi Yayasan Pendidikan Internal Audit) Muhamad, Faruk; Tukiyat; Anggai, Sajarwo
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

Disasters are unexpected and potentially significant risks to the continuity of company and organization operations, especially those related to information systems and information technology (IS/IT). The Internal Audit Education Foundation (YPIA) in handling disasters related to data and information security often faces obstacles that cause problems that become more widespread in the future. Therefore, a disaster recovery plan (DRP) becomes an urgent need. The purpose of this study is to evaluate resilience to disasters and data and information security attacks, and to ensure better business continuity in the face of emergency situations. Researchers use the National Institute of Standards and Technology (NIST) Framework in conducting a DRP analysis of security and data. The study begins by identifying and evaluating risks, conducting risk assessments, conducting Business Impact Analysis (BIA) determining preventive controls, and formulating contingency strategies. This study produces priority handling of high maturity risks in data damage, with an initial risk value of 3.8 and an impact of 4.4. After the control was carried out, there was a residual risk with a risk value of 1.6 and an impact of 3, with a very low maturity level and a residual value of 13.5 (80%). The reduction in the risk of data damage was significant with a very low residual value, indicating that the implementation of DRP using the NIST Framework in risk mitigation on critical assets of the Internal Audit Education Foundation was quite effective.
Analisis Klasifikasi Gambar Deteksi Merokok dengan Metode CNN yang Ditingkatkan Menggunakan Model Fine Tuning pada Arsitektur MobileNetV3L, EfficientNetV2M, dan Vision Transformer Nuriyadin
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

Smoke detection faces challenges in detecting small and common events such as smoking, using deep learning techniques. Issues like these have resulted in unsatisfactory privacy and accuracy models. In the EfficientNetV2M model, the author first uses data augmentation to increase the amount and diversity of training data by carrying out transformations of existing data. A lower learning rate allows smoother parameter updates and can improve the final performance of the model, fine-tune the EfficientNetV2M Layer, and Find the Ideal Learning Rate with the LearningRateScheduler Callback. The improved performance in terms of accuracy and robustness shows that this method can be used in related fields and represents significant progress in the field of burn detection with an accuracy rate of up to 97%. In the MobileNetV3L model, the author obtained lower resource usage results, namely with an accuracy rate of 87%. In the Vision Transformer model, the author uses a custom ViT (Vision Transformer) model for the feature extraction stage, then applies PCA for dimensional problems, and finally uses the XGBoost model for the classification stage and gets very satisfying results, namely with an accuracy level of 96 %. Future efforts will focus on improving this technology and finding ways to use it in broader contexts.
Penerapan Data Mining Dalam Menentukan Pelajaran yang Diminati Dengan Metode Support Vector Mechine (SVM) Sulistilawati, Iis; Musyafa , Ahmad; Zain, Rafi Mahmud
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

This research focuses on predicting students' grades and learning interests using the Support Vector Machine (SVM) method in education. It is crucial for students to determine the subjects they are most interested in to achieve optimal results. Data mining, particularly through the SVM method, can help identify students' learning interests based on historical data. SVM analyzes various variables related to students' academic performance, such as test scores, assignments, attendance, and class participation. By analyzing this data, SVM builds a model that predicts students' interest in specific subjects. This model provides insights into students' potential academic performance. The predictions generated by this SVM model can be used by educators to design more personalized learning strategies. By understanding students' interests and potential, educators can offer lesson recommendations that align with individual needs, enhancing students' motivation and academic performance. Moreover, these predictions assist students in making more informed decisions regarding subject selection, optimizing their potential and achieving better educational outcomes. This research aims to provide a tool that helps direct students' learning interests effectively, thereby improving the overall quality of education and academic results.
Perbandingan Efisiensi Metode Simple Additive Weighting (SAW) dan Weighted Product (WP) Dalam Sistem Penilaian Kinerja Guru Honorer Maulana, Romdon; Handayani, Murni; Anggai, Sajarwo
Jurnal Ilmu Komputer Vol 2 No 1 (2024): Jurnal Ilmu Komputer (Edisi Juli 2024)
Publisher : Universitas Pamulang

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Abstract

The teacher is the key to the success of the quality of education in this country with the main task of educating, teaching, guiding, directing, training, assessing, and evaluating students in early childhood education through formal education, basic education and secondary education. Teachers with honorary teacher status are the beginning of a career path for a teacher. assessment of teacher performance as an illustration of the results of the performance and teaching ability of a teacher. In addition to encouraging motivation, dedication, loyalty, professionalism, and improving the quality of education, teacher performance assessments are also used as a reference, and recommendation for raising the teacher's career path. The methods used in teacher performance assessment research or with similar objects are the SAW method, WP method, Fuzzy Logic, Analytical Hierarchy Process (AHP) method, Decision Tree method, Composite Performance Index (CPI) method and TOPSIS method. However, there has been no research comparing the SAW method with the WP method in terms of the efficiency of the calculation process time, so it is not yet known which method is more efficient in terms of calculation process time in the teacher performance appraisal system, so in this research, we will compare the SAW method with the WP method in honorary teacher performance assessment system, so that it can be seen which method is more efficient in terms of the calculation process for honorary teacher performance assessment.

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