Articles
<![CDATA[Model Gamifikasi Menggunakan Logika Fuzzy untuk Penentuan Reward Pelanggan pada E-Commerce ]]>
<![CDATA[Ichwan Setiarso]]>;
<![CDATA[Moch. Sjamsul Hidajat]]>
<![CDATA[ Techno.Com Vol 19, No 1 (2020): Februari 2020 ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.33633/tc.v19i1.3382
<![CDATA[Inovasi menggunakan gamifikasi diperlukan untuk menghadapi persaingan antar e-commerce. Gamifikasi berguna untuk meningkatkan pengalaman, menjaga kesetiaan pelanggan, penguatan merk dan melengkapi motivasi pembeli dan melakukan transaksi di e-commerce. Bentuk yang umum dari gamifikasi adalah pemberian reward bagi pelanggan dengan kondisi tertentu. Kondisi ini contohnya adalah lama menjadi pelanggan, besar transaksi, jenis transaksi. Masalah yang terjadi berkaitan dengan pemberian reward kepada pelanggan adalah reward yang tidak sesuai dan monoton atau mudah ditebak sehingga unsur kejutan yang menjadi salah satu elemen penting dari reward menjadi menurun kualitasnya. Penelitian ini bertujuan membentuk model gamifikasi yang tidak monoton menggunakan kecerdasan buatan dengan metode logika fuzzy. Logika fuzzy mampu membentuk perilaku reward yang dinamis sehingga meningkatkan kualitas reward yang diberikan kepada pelanggan. Input yang digunakan untuk menentukan reward adalah banyaknya transaksi, banyak produk dipilih dan total biaya pesanan. Hasil dari penelitian ini, logika fuzzy dapat menghasilkan perilaku reward yang lebih dinamis. Kata kunci: gamifikasi, reward, logika fuzzy, e-commerce]]>
<![CDATA[Securing Digital Color Image based on Hybrid Substitution Cipher ]]>
<![CDATA[Moch Sjamsul Hidajat]]>;
<![CDATA[Ichwan Setiarso]]>
<![CDATA[ Journal of Applied Intelligent System Vol 4, No 2 (2019): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[Universitas Dian Nuswantoro and IndoCEISS ]]>
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DOI: 10.33633/jais.v4i2.3380
<![CDATA[This study proposes securing digital color images with hybrid substitution cryptographic methods combined with the Vigenere and Beaufort methods. The hybrid process is carried out using the help of two randomly generated keys. The first key is a matrix with an 8-bits value and the second key is a matrix with a binary value. The binary key is used to determine the Vigenere or Beaufort process, while the 8-bit key is used for modulus operations based on the Vigenere or Beaufort algorithm. At the test stage used a standard image that has an RGB color channel as a dataset. The quality of the cryptographic method is measured by several measuring instruments such as MSE, PSNR, and SSIM to determine the quality of encryption visually and the perfection of decryption, besides that it is used Entropy, NPCR and UACI to determine the probability of encryption resistance and quality against differential attacks. The TIC TOC function is also used to measure the computing speed of the encryption and decryption process. Measurement results using all measuring instruments indicate that the proposed method has very satisfying results and has fast computing. Keywords – Cryptography, Substitution Cipher, Modulus Function, Encryption, Decryption, Image Transmission ]]>
<![CDATA[Classification and Regression Trees (CART) Algorithm for Employee Selection ]]>
<![CDATA[Aulia Rahmawati]]>;
<![CDATA[Rizal Muhammad Affandi]]>;
<![CDATA[Dea Debora Aprillia]]>;
<![CDATA[Daffa Maulana]]>;
<![CDATA[Zudha Pratama]]>;
<![CDATA[Moch. Sjamsul Hidajat]]>
<![CDATA[ Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[Universitas Dian Nuswantoro and IndoCEISS ]]>
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DOI: 10.33633/jais.v7i3.7201
<![CDATA[Recruitment is the main key in an effort to improve the quality of human resources in a company. Good or bad employees greatly affect the quality of the company. Therefore, it is necessary to be thorough and take a long time in screening applicants in order to get competent, professional and as expected prospective employees. The absence of professional staff to conduct employee selection is the background of this research. So the researcher uses the CART algorithm for the classification of employee recruitment, so it is hoped that it can help companies in conducting employee selection. The dataset was obtained from the selection of freelance daily workers at the Pati Regency Civil Service Police Unit in 2018, totaling 290 prospective employees. Based on calculations on 5-fold cross validation, the resulting accuracy is 98.27%, precision is 99.13% and recall is 96.88%.]]>
<![CDATA[Expert System for Detecting Diseases of Potatoes of Granola Varieties Using Certainty Factor Method ]]>
<![CDATA[Bonifacius Vicky Indriyono]]>;
<![CDATA[Moch. Sjamsul Hidajat]]>;
<![CDATA[Tri Esti Rahayuningtyas]]>;
<![CDATA[Zudha Pratama]]>;
<![CDATA[Iffah Irdinawati]]>;
<![CDATA[Evita Citra Yustiqomah]]>
<![CDATA[ International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 4 No. 2 (2022): November 2022 ]]>
Publisher : <![CDATA[Informatics Department-Universitas Dr. Soetomo ]]>
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DOI: 10.25139/ijair.v4i2.5312
<![CDATA[The low productivity of potatoes is caused by many factors, including the very low quality of the seeds used, poor storage, climate, capital, limited farmer knowledge, and attacks by plant-disturbing organisms, especially diseases. Not only that, many farmers are still unfamiliar with the various diseases that can attack potato plants, or their knowledge about potato plant diseases is incomplete. This study aims to design and develop an expert system web-based application technology using the Certainty Factor (CF) method to detect potato disease symptoms. The CF method defines a measure of the capacity of a fact or provision to express the level of an expert's belief in a matter experienced by the concept of belief or trust and distrust or uncertainty contained in the certainty factor. The results showed that the CF method could function optimally in detecting potato plant diseases which can help farmers based on the symptoms that appear with an accuracy value of 94%.]]>
<![CDATA[Strategi Manajemen Perusahaan Menyongsong Era Society 5.0 ]]>
<![CDATA[Angel Frilyaningrum]]>;
<![CDATA[Ainun Muhtadin]]>;
<![CDATA[M. Sjamsul Hidajat]]>;
<![CDATA[Ery Mintorini]]>
<![CDATA[ Seminar Nasional Teknologi dan Multidisiplin Ilmu (SEMNASTEKMU) Vol 1 No 1 (2021): SEMNASTEKMU ]]>
Publisher : <![CDATA[Universitas Sains dan Teknologi Komputer ]]>
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DOI: 10.51903/semnastekmu.v1i1.144
<![CDATA[Menghadapi dan menyonsong era society 5.0, penggunaan digitalisasi atau teknologi informasi menjadi perhatian tersendiri dalam aspek-aspek manajemen perusahaan mengenai proses kegiatan dalam menyelesaikan permasalahan yang dihadapi di masa datang. Tujuan dari penelitian ini adalah untuk mengetahui dan menganalisa strategi manajemen memasuki era society 5.0 dengan berbasis tata kelola manajemen perusahaan yang tepat. Metode penelitian menggunakan pendekatan kualitatif dengan pengambilan sumber datanya secara sekunder yang berasal dari beberapa pustakan dan referensi terdahulu diantara buku, berbagai jurnal, serta dokumen yang berkaitan sesuai kajian dan tema penelitian dan dianalisis. Temuan studi ini menunjukkan bahwa Perusahaan telah melakukan persiapan dan penguatan strategi manajemen dengan memperhatikan tata kelola perencanaan manajemen. Namun, penguatan strategi manajemen memasuki era society 5.0 banyak mengalami kendala terkait masih dominannya budaya birokrasi perusahaan akan memanfaatkan teknologi digital dan komunikasi informasi dalam orientasi proses kegiatan manajemen sebuah perusahaan. Dengan demikian bahwa perencanaan perusahaan dalam menghadapi era Society 5.0 sedini mungkin dipersiapkan secara tepat dan cepat memgambail tindakan sesaui kendala dan segala bentuk perubahan lingkungan dan perkembangannya.]]>
<![CDATA[Konsep Algoritma Forward Chaining dan Faktor Kepastian untuk Mendiagnosa serta Pencarian Solusi Masalah Kulit Wajah ]]>
<![CDATA[Ery Mintorini]]>;
<![CDATA[Moch. Sjamsul Hidajat]]>
<![CDATA[ Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Vol 14, No 2 (2023): Desember ]]>
Publisher : <![CDATA[Universitas Bandar Lampung (UBL) ]]>
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DOI: 10.36448/jsit.v14i2.3436
<![CDATA[Saat ini banyak orang terutama para wanita yang mendambakan kulit yang sehat dan juga wajah yang bersih serta terawat. Banyak cara yang dilakukan agar kulit mereka bersih seperti yang didambakan. Namun, tidak jarang juga diantara mereka yang tidak memiliki cara tepat untuk mengatasinya. Hal ini disebabkan adanya keterbatasan pengetahuan tentang perawatan kulit wajah dan biaya konsultasi ke pakar. Konsultasi tentunya membutuhkan dana yang tidak sedikit, sehingga tidak semua dapat melakukan upaya ini. Untuk mengatasi kendala keterbatasan dana untuk melakukan konsultasi ini adalah dengan membuat suatu sistem yang mampu beraktifitas selayaknya seorang ahli yang dikenal sebagai sistem pakar. Sistem pakar dapat didefiisikan sebagai suatu sistem yang mengadopsi kemampuan seorang pakar dengan memasukkan semua kemampuann pakar kedalam sistem. Ada banyak metode yang dapat diterapkan dalam sistem pakar diantaranya adalah forward chaining dan faktor kepastian. Penelitian kali ini bertujujan untuk membuat sistem pakar yang dapat diterapkan untuk diagnosa masalah- kulit wajah serta pencarian solusi penyelesaian menggunakan metode runut maju dan faktor kepastian. Hasil pengujian yang dilakukan dalam sistem ini membuktikan keakuratan sistem pakar dalam mendeteksi masalah yang dihadapi dan mampu memberikan solusi atas masalah tersebut dengan baik.]]>
<![CDATA[PENGOPTIMALAN KEBUTUHAN GIZI PADA MENU MAKANAN PENDERITA DIABETES (Studi Kasus Rumah Sakit Ratih, Kediri) ]]>
<![CDATA[Wibowo, Dibyo Adi]]>;
<![CDATA[Hidajat, Moch Sjamsul]]>
<![CDATA[ MAp (Mathematics and Applications) Journal Vol 5, No 2 (2023) ]]>
Publisher : <![CDATA[Universitas Islam Negeri Imam Bonjol Padang ]]>
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DOI: 10.15548/map.v5i2.7078
<![CDATA[Rumah Sakit Ratih di Kediri mungkin menghadapi masalah untuk menyusun menu makanan yang memenuhi kebutuhan nutrisi pasien diabetes melitus dengan biaya yang rendah. Untuk menyelesaikan masalah ini, metode programing linier dengan metode branch and bound digunakan untuk menghasilkan porsi makanan berupa integer yang awalnya dianalisis menggunakan pemrograman linier. Hasil perhitungan menggunakan metode branch and bound menunjukkan bahwa menu makanan untuk penderita diabetes melitus yang melakukan aktivitas olahraga dan tanpa aktivitas olahraga memiliki kebutuhan gizi optimal sebesar 7, 2 porsi bening labu siam, wortel, sup buncis, wortel, dan kentang, dan 12 porsi bening bayam, kecambah. Selama seminggu, penderita diabetes melitus tanpa melakukan aktivitas olahraga memiliki kebutuhan gizi optimal sebesar 7, 2 porsi.]]>
<![CDATA[Poverty Modeling in East Java Province Using the Spatial Seemingly Unrelated Regression (Sur) Method ]]>
<![CDATA[Wibowo, Dibyo Adi]]>;
<![CDATA[Hidajat, Moch Sjamsul]]>;
<![CDATA[Widyatmoko, Widyatmoko]]>
<![CDATA[ Journal of Applied Intelligent System Vol. 8 No. 2 (2023): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[Universitas Dian Nuswantoro and IndoCEISS ]]>
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DOI: 10.33633/jais.v8i2.8178
<![CDATA[Poverty is a complex problem because it relates to various aspects of human life. In Indonesia, there is one province that has a very high percentage of poverty, namely East Java Province. Although from year to year the poverty rate has decreased, when viewed from the national level it is still very far from the government's expectations of reducing the poverty rate. Cases of poverty can be modeled by Econometrics. Econometric models are often applied to problems involving one or more related equations. One method that can be used to solve several interrelated equations because there is a correlation error regression between one another, namely Seemingly Unrelated Regression which is usually abbreviated as SUR, in this case Spatial Seemingly Unrelated Regression (SUR-Spatial) is development that takes into account the spatial influence between locations. From the results of tests conducted in the SUR-Spatial Lagrange Multiplier model, the poverty data generated by the East Java Province is the SUR-Spatial Autoregressive Model (SUR-SAR). So with the SUR-SAR model it can be seen that the variable that has a significant effect on the percentage of poor people is the growth rate of Gross Regional Domestic Product based on the constant price of the minimum wage for each district, as well as the average length of school years. Meanwhile, the Poverty Depth Index has an effect because of the growth rate of Gross Regional Domestic Product on the basis of constant prices and the average length of schooling. The Poverty Severity Index is influenced by the growth rate of Gross Regional Domestic Product at constant prices and average years of schooling.]]>
<![CDATA[Covid-19 Classification using Convolutional Neural Networks Based on Adam, RMSP, and SGD Optimalization ]]>
<![CDATA[Hidajat, Moch Sjamsul]]>;
<![CDATA[Wibowo, Dibyo Adi]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.33633/jais.v8i3.9492
<![CDATA[In this comprehensive study, a meticulous analysis of the application of Convolutional Neural Network (CNN) methodologies in the classification of Covid-19 and non-Covid-19 cases was conducted. Leveraging diverse optimization techniques such as RMS, SGD, and Adam, the research systematically evaluated the performance of the CNN model in accurately discerning intricate patterns and distinct features associated with Covid-19 pathology. the implementation of the RMS and Adam optimization methods resulted in the highest accuracy levels, with both models achieving an impressive 98% accuracy in the classification of Covid-19 and non-Covid-19 cases. Leveraging the robust capabilities of these optimization techniques, the study successfully demonstrated the effectiveness of the RMS and Adam models in enhancing the precision and reliability of the Convolutional Neural Network (CNN) for the accurate identification and differentiation of Covid-19 patterns within the medical imaging datasets. The notable achievement of 98% accuracy further emphasizes the potential of these optimization methods in advancing the capabilities of CNN-based diagnostic tools, thus contributing significantly to the ongoing efforts in Covid-19 diagnosis and management. ]]>
<![CDATA[Predicting Gold Price Movement Using Long Short-Term Memory Model ]]>
<![CDATA[Nagata, Azaria Beryl]]>;
<![CDATA[Hidajat, Moch Sjamsul]]>;
<![CDATA[Wibowo, Dibyo Adi]]>;
<![CDATA[Widyatmoko, Widyatmoko]]>;
<![CDATA[Yaacob, Noorayisahbe Bt Mohd]]>
<![CDATA[ (JAIS) Journal of Applied Intelligent System Vol. 9 No. 1 (2024): Journal of Applied Intelligent System ]]>
Publisher : <![CDATA[LPPM Universitas Dian Nuswantoro ]]>
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DOI: 10.62411/jais.v9i1.10305
<![CDATA[Gold, as a valuable commodity, has been a primary focus in the global financial market. It is often utilized as an investment instrument due to the belief in its potential price appreciation. However, the unpredictable and complex movement of gold prices poses a significant challenge in investment decision-making. Therefore, this research aims to address this issue by proposing the use of the Long Short-Term Memory (LSTM) model in time series analysis. LSTM is a robust approach to understanding patterns and trends in gold price data over time. In the context of time series analysis, historical gold price data includes daily, weekly, and monthly datasets. Each model with its respective dataset is useful for identifying patterns in gold prices. The daily model achieves an MSE of 452.2284140627481 and an RMSE of 21.26566279387379. The weekly model achieves an MSE of 1346.1816584357384 and an RMSE of 36.69034830082345. The monthly model achieves an MSE of 11649.597907584808 and an RMSE of 107.93330305139747. With these RMSE results, the LSTM model can predict gold prices effectively. Based on the trained models, it can also be concluded that gold prices exhibit long-term temporal dependence.]]>
