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All Journal Jurnal Pilar Nusa Mandiri JTERA (Jurnal Teknologi Rekayasa) J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika) Sagu Journal Of Computer Science And Technology Journal of Data Analytics, Information, and Computer Science (JDAICS) Jurnal Computer and Technology
Rudi Muslim
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Other

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QUALITY EVALUATION OF RUBBER (Havea brasiliensis) SEED COOKING OIL Evy Rossi; Dewi Fortuna Ayu; Rudi Muslim
Jurnal Sagu Vol 12, No 1 (2013)
Publisher : Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (59.314 KB) | DOI: 10.31258/sagu.v12i1.2062

Abstract

The purpose of this research was to conduct physical optimation of chemical properties of rubber seed oilthat could be used as edible oil. This research was conducted by using the Complete Random Block Designconsists of 4 treatments with 3 replications. The treatments were duration of smoking, respectively 12, 16, 20and 24 hours. The data obtained then be analyzed statistically by using ANOVA. The Results of study showedthat duration of smoking a real effect (P <0.05) on yield and water content of rubber seed oil yield, whereastreatment did not affect significantly (P> 0.05) on acid, iodine, and peroxide values of oil and oil color.Based on the results it can be concluded that the duration of smoking for12 to 24 hours make the quality ofrubber seed oil was that oil not feasible as the cooking oil.Key Words: rubber seed, cooking oil, chemical properties
LOMBOK PEARL QUALITY CLASSIFICATION USING A COMBINATION OF FEATURE EXTRACTION AND ARTIFICIAL NEURAL NETWORKS BASED ON SHAPE Imran, Bahtiar; Yani, Ahmad; Muslim, Rudi; Zaeniah, Zaeniah
Jurnal Pilar Nusa Mandiri Vol 18 No 2 (2022): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i2.3507

Abstract

Lombok is attracted to the Moto GP event, which is held annually. Various tourism brands are owned by the island of Lombok, one of which is Mutiara. The ideal Pearl is perfectly round and smooth, but there are a variety of other shapes as well. One method that can be used to process Pearl's image is Computer Vision. For that, it is necessary to have a way to classify the quality of a Pearl based on its shape. The purpose of this study is to propose a system for pearl image classification by combining feature extraction with artificial neural networks. The method used in this study is GLCM feature extraction and Neural Networks. The proposed system can provide good classification results by combining the GLCM method and the Neural Network. This study uses Epochs 5, 10, 15, 30, 50, 100, 200, 300, and 500 with a learning rate of 0.5. The results of this study indicate that Epoch 100 gives the highest accuracy, 91.66%.
DECISION SUPPORT SYSTEM OF REWARDING ON LECTURER PERFORMANCE USING FUZZY TSUKAMOTO METHOD CASE STUDY AT MATARAM UNIVERSITY OF TECHNOLOGY Yani, Ahmad; Zenuddin, Z; Hambali, H; Muslim, Rudi; Imran, Bahtiar
Jurnal Pilar Nusa Mandiri Vol 18 No 2 (2022): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i2.3548

Abstract

To prepare quality and character human resources, Mataram Technological University strives to provide the best in carrying out the tridharma activities of higher education, one of which is by giving rewards in the hope that morale and loyalty can continue to be improved. However, the gift-giving system that the Mataram Technological University has implemented has not been able to bring about change because the gift-giving system is incorrect. This is because the applied reward-giving assessment system only refers to the assessment without paying attention to other criteria in the tridharma of higher education. Such as the implementation of learning, Research, and community service. Therefore, to overcome this problem, a decision support information system for awarding lecturer performance is needed, which is built using the fuzzy Tsukamoto method by considering several criteria such as Presence, Research Results, and Community Service Results. Lecturer Performance Index in carrying out the learning process. With this decision support system, the implementation of the Tridharma carried out by lecturers can continue to monitor the system and improve the quality and accreditation of study programs and universities.
MAPPING LOCATIONS AND SHORTEST ROUTE OF TOURISM OBJECTS IN CENTRAL LOMBOK USING GIS-BASED A-STAR ALGORITHM Muslim, Rudi; Hidayatullah, Beni Ari; Imran, Bahtiar; Yani, Ahmad; Salman, Salman
Jurnal Pilar Nusa Mandiri Vol 18 No 2 (2022): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i2.3927

Abstract

Central Lombok tourism is a tourism that foreign and domestic tourists often visit. There are many tourist objects offered by the Central Lombok Government, such as waterfall tours, beach tours, traditional village tours, cultural tours, and Pertamina Mandalika International Street Circuit. However, there are many tourist objects, and not all tourists know the location of these tourist objects. Tourists often experience constraints, are the location of tourist objects that is not quite right, it is still difficult to determine the shortest route to the location, and the lack of complete information about existing tourist objects, which can hinder the journey of tourists to the destination location. This study aims to map the location and shortest route of tourism objects in Central Lombok using an Android-based Geographic Information System by applying the A-Star algorithm. The results of this study are to develop an Android-based Geographic Information System or GIS by applying the star algorithm to Central Lombok tourism objects. So that the mapping of the location and information of tourist objects and obtain the search for the shortest route to tourist objects. The A-Star algorithm uses heuristic principles to find the shortest route to a tourism object and is optimal in finding the shortest route to tourism objects
Design and Implementation of IoT Based Smart Lecture Attendance System at Mataram University of Technology Akbar, Ardiyallah; Zaenudin, Zaenudin; Yani, Ahmad; Muslim, Rudi
Jurnal Pilar Nusa Mandiri Vol 19 No 2 (2023): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v19i2.4608

Abstract

Student attendance is one of the reporting activities that exist in educational institutions. The problem that occurs in educational institutions is that when entering the lecture, many students are late and often absent, which can cause discipline where students often do absenteeism, so lecturers cannot know the number of students who attend accurately. From these problems, a solution is needed to help lecturers recapitulate attendance data. This system uses ESP32 as a data manager, RFID for data reading, and ESP32 to validate student attendance by taking pictures of faces. The data is stored on the web server using ESP32CAM to cover the shortcomings of RFID, which is still card-based, so that it can emphasize the flaws. To simplify the attendance in this study, utilizing the website as an interface to facilitate lecturers in knowing the number of students who are present, late, or absent more efficiently and accurately
Disease Detection of Rice and Chili Based on Image Classification Using Convolutional Neural Network Android-Based Muslim, Rudi; Zaeniah, Zaeniah; Akbar, Ardiyallah; Imran, Bahtiar; Zaenudin, Zaenudin
Jurnal Pilar Nusa Mandiri Vol 19 No 2 (2023): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v19i2.4669

Abstract

The current development of machine learning makes it easier for humans to obtain information, especially from images. The presence of processing assistance from machines can increase the accuracy of the information provided to further convince the recipient of the information. Rice and chili farmers in Indonesia have experienced many disease attacks from several types of plant diseases. Not many farmers understand and are good at guessing the diseases that attack their rice and chili plants. So many rice and chili farmers experienced crop failure. This research aims to build a disease-detection system for rice and chili plants based on Android-based image classification. The machine learning method used is Convolutional Neural Network (CNN) with the Mobile Net version one model combined with the Sequential CNN and Tensor Flow Lite models. The results of the transfer learning evaluation on the Mobile Net version 1 model and the sequential CNN model obtained training accuracy of 0.88% with a loss of 0.34%, validation accuracy of 0.84% with a loss of 0.40%, and testing accuracy of 86% with a loss of 43%. Each uses batch 69 of the total training data stopping at epoch 30 from epoch 100. The results of field testing on the application of rice and chili disease detection on 20 images of rice and chili plants can detect Rice Neck Blast disease with a probability of 75% to 100% and Rice Hispa with a probability of 97% to 100%. It can also detect chili plant diseases such as Chili Yellowish with a probability of 83%, Chili Leaf Spot with a probability of 99%, Chili Whitefly with a probability of 91% to 95, Chili Healthy with a probability of 78% to 99%, and Chili Leaf Curl with a probability 75 to 76%. The probability obtained varies according to how likely damage is to rice and chili plants. CNN with the Mobile Net version one model and the Sequential model can extract and classify images so that it has maximum information processing capabilities. This research can make it easier to help farmers identify diseases that attack their rice and chili plants.
SISTEM INFORMASI E-COMMERCE PENJUALAN KERAJINAN ROTAN BERBASIS WEBSITE PADA DESA LOANG MAKA KECAMATAN JANAPRIA Febri, Elin Febriani; Imran, Bahtiar; Muslim, Rudi
Journal Computer and Technology Vol. 1 No. 1 (2023): Juli 2023
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v1i1.83

Abstract

Desa Loang Maka adalah salah satu desa yang berada di Kecamatan Janapria Kabupaten Lombok Tengah dimana desa tersebut teradapat banyak pengerajin rotan yang masih beroprasi. Saat ini, para pengerajin kesulitan dalam mempromosikan hasil kerajinan mereka sehingga perlu adanya inovasi untuk membantu dalam mempermudah pemasaran produk dan penemuan barang bagi konsumen. Segmentasi pasar yang mampu dicakup jika menggunakan sistem home industry terlalu sempit, karena masyarakat kurang mengetahui ketersediaan barang yang dibutuhkan. Selain itu, Belum adanya sistem informasi penjualan kerajinan tangan di home industry ini membuat pengrajin hanya bisa memasarkan di sekitar Desa Loang Maka. Berdasarkan dari permasalahan tersebut maka para pengerajin memerlukan suatu sistem yang memberikan layanan berbasis website dalam mempromosikan hasil kerajinan rotan.
CYBER BULLYING SENTIMENT ANALYSIS BASED ON SOCIAL CATEGORIES USING THE CHI-SQUARE TEST Hadi, Zulpan; Suryadi, Emi; Akbar, Ardiyallah; Zaenudin; Muslim, Rudi
Journal Computer and Technology Vol. 2 No. 1 (2024): Juli 2024
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v2i1.144

Abstract

This research evaluates various machine learning models in classifying sentiment in cyberbullying data across six categories: not_cyberbullying, gender, religion, other_cyberbullying, age, and ethnicity. Using a Bag of Words approach combined with Chi-Square feature selection (1000 features), models tested include SVM, Logistic Regression, Naïve Bayes, KNN, and Random Forest. Results show SVM and Logistic Regression achieving the highest accuracy at 83%, indicating their effectiveness in prediction. Naïve Bayes performed the poorest with 62% accuracy, suggesting a mismatch with the data or need for further tuning. KNN and Random Forest showed good performance with 75% and 81% accuracy respectively, though not as high as SVM and Logistic Regression. This multi-algorithm approach provides insights into each model's effectiveness and behavior on diverse data characteristics, essential for understanding the unique nuances of each cyberbullying category. Model selection should consider accuracy, interpretability, computational cost, and suitability to specific problem characteristics. This research aims to deepen understanding of cyberbullying to support more effective mitigation strategies.
Optimalisasi Keamanan Web Server Ubuntu dengan Teknologi IPS Berbasis Iptables Samsumar, Lalu Delsi; Imran, Bahtiar; Efendi, Muhamad Masjun; Muslim, Rudi; Muahidin, Zumratul; Mutaqin, Zaenul
JTERA (Jurnal Teknologi Rekayasa) Vol 9, No 2: December 2024
Publisher : Politeknik Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31544/jtera.v9.i2.2024.69-76

Abstract

Keamanan jaringan merupakan faktor krusial dalam melindungi data dan informasi penting dalam suatu organisasi. Salah satu metode untuk mengamankan web server adalah dengan menerapkan Intrusion Prevention System (IPS) berbasis iptables. Penelitian ini bertujuan untuk mengoptimalkan keamanan web server Ubuntu dengan menggunakan teknologi IPS berbasis iptables. Iptables berfungsi tidak hanya sebagai firewall, tetapi juga sebagai sistem deteksi dan pencegahan intrusi (IDS/IPS) yang efektif untuk melindungi server berbasis Linux. Dalam penelitian ini, Snort digunakan sebagai alat deteksi intrusi yang diintegrasikan dengan iptables untuk memantau dan memitigasi potensi serangan pada jaringan lokal. Metodologi penelitian ini mencakup analisis kebutuhan sistem, instalasi sistem operasi dan web server, serta konfigurasi iptables sebagai IPS untuk mendeteksi dan mencegah serangan yang mengancam integritas server. Pengujian dilakukan dengan mengidentifikasi kerentanannya dan menguji efektivitas implementasi IPS pada web server Ubuntu. Hasil penelitian menunjukkan bahwa iptables berhasil menjalankan fungsinya sebagai IPS dalam mengamankan web server dari serangan DDoS. Iptables efektif dalam memblokir serangan yang masuk ke dalam web server. Sistem ini juga berhasil mendeteksi serangan yang dilakukan menggunakan Snort yang berfungsi sebagai IDS. Snort mampu mendeteksi serangan yang masuk dan memberikan peringatan yang berguna dalam memperkuat lapisan keamanan pada web server.
IMPLEMENTASI VULNERABILITY ASSESSMENT OWASP (OPEN WEB APPLICATION SECURITY PROJECT) PADA WEBSITE UNIVERSITAS TEKNOLOGI MATARAM Supriadi, Dedi; Suryadi, Emi; Muslim, Rudi; Samsumar, Lalu Delsi
Journal of Data Analytics, Information, and Computer Science Vol. 1 No. 4 (2024): Oktober
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jdaics.v1i4.1368

Abstract

Teknologi informasi dan komunikasi mengalami peningkatan signifikan selama beberapa dekade terakhir. Website sering kali menjadi target serangan siber karena terdapat kerentanan yang bisa dimanfaatkan oleh penyerang. Penelitian ini bertujuan untuk melakukan Vulnerability Assessment (VA) pada website Universitas Teknologi Mataram dengan mengikuti panduan dari Open Web Application Security Project (OWASP). OWASP menyediakan daftar sepuluh besar kerentanan yang sering ditemukan didalam aplikasi web, seperti SQL Injection, XSS (Cross-Site Scripting), dan CSRF (Cross-Site Request Forgery). Penelitian ini menggunakan metode Vulnerability Assessment dan Penetration Testing (VAPT), yang terdiri dari beberapa tahap: pengumpulan informasi, pemindaian untuk mengidentifikasi celah keamanan, eksploitasi celah, serta pembuatan laporan. Tools yang digunakan antara lain OWASPZAP dan Burp Suite untuk mendeteksi dan pengujian kerentanan. Penelitian ini menghasilkan laporan yang mengidentifikasi tiga kerentanan dengan level sedang, empat kerentanan dengan level rendah, serta tidak ada kerentanan dengan level tinggi. Setelah pemindaian, hasil pengujian menunjukkan bahwa serangan Clickjacking berhasil dieksploitasi, sementara serangan XSS tidak berhasil dilakukan, menunjukkan adanya mekanisme pertahanan yang baik terhadap XSS. Selain itu, ditemukan beberapa kelemahan dalam konfigurasi aplikasi. Solusi perbaikan yang direkomendasikan disesuaikan dengan standar keamanan OWASP. Dengan dilakukannya VAPT ini, diharapkan pengelola website Universitas Teknologi Mataram dapat meningkatkan keamanan dan mengurangi risiko serangan siber yang berpotensi merugikan. Implementasi OWASP sebagai panduan pengujian keamanan terbukti efisien dalam mendeteksi serta mengatasi celah keamanan dalam aplikasi web.
Co-Authors ahmad yani Akbar, Ardiyallah Ardiyallah Akbar Azhuri Dedi Supriadi Dewi Fortuna Ayu Efendi, Muhamad Masjun Fachry Abda El Rahman Febri, Elin Febriani Hambali Hambali Hidayatullah, Beni Ari Imran, Bahtiar Lalu Delsi Samsumar, M.Eng. Muahidin, Zumratul Mutaqin, Zaenul Pratama, Ahmad Raf’ie Rossi, Evy Salman Salman Suryadi, Emi Taufiq Hidayat Zaeniah Zaeniah Zaenudin Zaenudin Zaenudin Zenuddin, Z Zulpan Hadi