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Perbandingan Teknik Pengkodean Langsung dan Tidak Langsung Pada Kasus Penjadwalan Jobshop Rathomi, Muhamad Radzi
Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Vol 6 No 1 (2017): Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Development of technology help human life in problem solving. Scheduling is a one of the problem which could be solved with it. In scheduling research, jobshop case is frequently used to test the scheduling problem solving algorithm. This study provide the comparison between direct encoding and indirect encoding approach. These approach are choices in jobshop secheduling problem research. The apparent differences of these approach are in used technique. Genetic algorithm is used as the testing algorithm. The Cases which will be used are the common cases from OR-Lib. The testing is done by looking the makespan, processing time, and objective value transformation. Testing result shows the direct encoding approach found more small makespan. Whereas indirect encoding approach can found optimal makespan in running with large number of generation.

A coarse-grained parallelization of genetic algorithms Muhamad Radzi Rathomi; Reza Pulungan
International Journal of Advances in Intelligent Informatics Vol 4, No 1 (2018): March 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v4i1.137

Genetic algorithms are frequently used to solve optimization problems. However, the problems become increasingly complex and time consuming. One solution to speed up the genetic algorithm processing is to use parallelization. The proposed parallelization method is coarse-grained and employs two levels of parallelization: message passing with MPI and Single Instruction Multiple Threads with GPU. Experimental results show that the accuracy of the proposed approach is similar to the sequential genetic algorithm. Parallelization with coarse-grained method, however, can improve the processing and convergence speed of genetic algorithms.

Predictive Adaptive Test with Selective Weighted Bayesian Through Questions and Answers Patterns to Measure Student Competency Levels Tekad Matulatan; Martaleli Bettiza; Muhamad Radzi Rathomi; Nola Ritha; Nurul Hayaty
Jurnal Teknologi dan Sistem Komputer Volume 7, Issue 2, Year 2019 (April 2019)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Computer Assisted Testing (CAT) system in Indonesia has been commonly used but only to displaying random exam questions and unable to detect the maximum performance of the test participants. This research proposes a simple way with a good level of accuracy in identifying the maximum ability of test participants. By applying the Bayesian probabilistic in the selection of random questions with a weight of difficulties, the system can obtain optimal results from participants compared to sequential questions. The accuracy of the system measured on the choice of questions at the maximum level of the examinee alleged ability by the system, compared to the correct answer from participants gives an average accuracy of 75% compared to 33% sequentially. This technique allows tests to be carried out in a shorter time without repetition, which can affect the fatigue of the test participants in answering questions.

Peningkatan High Order Thinking Skill Siswa Melalui Pendampingan Computational Thinking Ferdi Chahyadi; Martaleli Bettiza; Nola Ritha; Muhamad Radzi Rathomi; Nurul Hayaty
Jurnal Anugerah Vol 3 No 1 (2021): Jurnal Anugerah: Jurnal Pengabdian kepada Masyarakat Bidang Keguruan dan Ilmu Pen
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Maritim Raja Ali Haji

Persaingan global yang dihadapi saat ini, menuntut adanya perubahan di dalam pembelajaran agar kecakapan dan keterampilan anak didik semakin berkembang. Kemampuan literasi matematika menjadi salah satu yang harus dimiliki para siswa dalam menghadapi tantangan global tersebut. Kegiatan pelatihan dan pendampingan Computational Thinking dengan menerapkan High Order Thinking Skill (HOTS) yang dilakukan diharapkan dapat menambah wawasan siswa terhadap pemahaman dalam melakukan problem solving. Serta, menumbuhkan kreativitas siswa, budaya informasi, algoritma dan berpikir komputasional dalam menyelesaikan suatu permasalahan dalam bentuk tantangan yang dikenal dengan nama Bebras Challenge. Dalam tahapan pelaksanaannya dilakukan tahapan-tahapan yakni pre-test, pelatihan & pendampingan, serta post-test. Pre-test terhadap 15 siswa menunjukkan rerata siswa dalam menjawab soal secara benar adalah sebanyak 60%. Pelatihan-dan pendampingan dilakukan melalui aplikasi daring. Pertemuan dilaksanakan sebanyak 5 kali pertemuan. Sedangkan hasil dari post-test mengalami peningkatan yakni menjadi 78%. Hal ini menunjukkan tingkat keberhasilan siswa dalam memecahkan persoalan mengalami peningkatan yang baik.

Peningkatan High Order Thinking Skill Siswa Melalui Pendampingan Computational Thinking Ferdi Chahyadi; Martaleli Bettiza; Nola Ritha; Muhamad Radzi Rathomi; Nurul Hayaty
Jurnal Anugerah Vol 3 No 1 (2021): Jurnal Anugerah: Jurnal Pengabdian kepada Masyarakat Bidang Keguruan dan Ilmu Pen
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Maritim Raja Ali Haji

Persaingan global yang dihadapi saat ini, menuntut adanya perubahan di dalam pembelajaran agar kecakapan dan keterampilan anak didik semakin berkembang. Kemampuan literasi matematika menjadi salah satu yang harus dimiliki para siswa dalam menghadapi tantangan global tersebut. Kegiatan pelatihan dan pendampingan Computational Thinking dengan menerapkan High Order Thinking Skill (HOTS) yang dilakukan diharapkan dapat menambah wawasan siswa terhadap pemahaman dalam melakukan problem solving. Serta, menumbuhkan kreativitas siswa, budaya informasi, algoritma dan berpikir komputasional dalam menyelesaikan suatu permasalahan dalam bentuk tantangan yang dikenal dengan nama Bebras Challenge. Dalam tahapan pelaksanaannya dilakukan tahapan-tahapan yakni pre-test, pelatihan & pendampingan, serta post-test. Pre-test terhadap 15 siswa menunjukkan rerata siswa dalam menjawab soal secara benar adalah sebanyak 60%. Pelatihan-dan pendampingan dilakukan melalui aplikasi daring. Pertemuan dilaksanakan sebanyak 5 kali pertemuan. Sedangkan hasil dari post-test mengalami peningkatan yakni menjadi 78%. Hal ini menunjukkan tingkat keberhasilan siswa dalam memecahkan persoalan mengalami peningkatan yang baik.

Optimasi Pemilihan Takjil Berbasis Multi-Attribute Decision Making dengan Model Yager Muhamad Radzi Rathomi; Ritha, Nola; Hayaty, Nurul
JISTech : Journal of Information Systems and Technology Vol. 2 No. 1 (2025): Juni 2025
Publisher : Perhimpunan Ahli Teknologi Informasi dan Komunikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71234/jistech.v2i1.52

The choice of takjil as an iftar dish is frequently decided subjectively, neglecting certain elements that could affect the optimality of the decision. This study employs Multi-Attribute Decision Making (MADM) utilizing the Yager Model to identify the optimal takjil alternative based on established criteria. The five primary criteria employed in this analysis are flavor, cost, nutritional value, accessibility, and feasibility. The calculating method initiates with data standardization, weight allocation, and the implementation of the Yager Model to derive the preference value for each choice. Of the seven evaluated alternatives, the findings demonstrate that Kolak Pisang is the most advantageous option, attaining the maximum minimum value of 0.919. Consequently, this strategy serves as a more rational and objective means of selecting takjil that corresponds with consumer preferences and requirements. The utilization of the Yager Model in alternative contexts offers prospects for additional research in multi-criteria decision-making

Prediksi Temperatur Maksimum di Kota Tanjungpinang Menggunakan Model CNN-LSTM Nurfalinda; Fiani, Mia Al; Rathomi, Muhamad Radzi
Komputa : Jurnal Ilmiah Komputer dan Informatika Vol 14 No 1 (2025): Komputa : Jurnal Ilmiah Komputer dan Informatika
Publisher : Program Studi Teknik Informatika - Universitas Komputer Indonesia (UNIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputa.v14i1.15377

The prediction of maximum temperature is important for supporting decision process related to public activities and reducing the consequences of climate change. The goal of this study is to analyze the performance of the CNN-LSTM hybrid method in forecasting maximum temperature in Tanjungpinang City by utilizing average humidity and rainfall as input variables. Historical weather data was obtained through the BMKG website, covering the period from January 1, 2022, to November 30, 2024, and was used as the research dataset. The CNN-LSTM model was developed by optimizing the advantages of CNN in recognizing spatial patterns and the capability of LSTM in capturing temporal patterns. The model was trained using an optimal configuration consisting of 128 CNN filters, a kernel size of 7, 200 LSTM units, a batch size of 16, and 120 epochs. Performance evaluation was conducted using two key metrics: Root Mean Squared Error (RMSE) of 1.65 and Mean Absolute Percentage Error (MAPE) of 4.19%. The findings indicate that the model can be used to predict maximum temperature based on available historical weather data. Additionally, the model has been implemented in a web-based platform that allows users to input historical data and select prediction periods ranging from 1, 3, 7, to 10 days ahead. The prediction results are presented in tables and graphical visualizations to facilitate users in understanding and evaluating the generated information.

IMPLEMENTASI TEKNIK WORD EMBEDDING UNTUK REKOMENDASI HASIL PENCARIAN KATALOG ONLINE MENGGUNAKAN ALGORITMA WORD2VEC Raja Azian; Nola Ritha; Muhamad Radzi Rathomi
Sustainable Vol 12 No 2 (2023): Jurnal Sustainable : Jurnal Hasil Penelitian dan Industri Terapan
Publisher : Fakultas Teknik Universitas Maritim Raja Ali Haji

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31629/nytmnn37

The purpose of this study is to apply the word2vec algorithm to recommend search results in online catalogs. The reason for taking this title is because, based on the results of observations and the observations of researchers, the data search process, especially in online catalogs, only reaches the syntactic level. So that the results are given only up to the syntactic level. Therefore, researchers utilize the word2vec algorithm, which has the ability to represent words at the semantic level, to carry out a search process where the results of this process are used as alternative search results or recommendations for search results. The data that the researchers used was data on 12,701 book titles in the Raja Ali Haji Maritime University library. To evaluate the recommendations for the search results obtained, the researcher tested the recommendation system for search results using several scenarios, and then the results were measured using a precision test on the k document (P@k). From the results of the precision test measurements on the k document, various results were found. Scenarios 1 and 2 show a fairly high precision value with a value of 0.53 and 0.59, while for testing in scenarios 3, 4, and 5, the resulting precision value is relatively low with a value of 0.50, 0.42, and 0.14.

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