Article Per Year (5 Year)
p-Index From 2020 - 2025
3.673
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Jurnal Pilar Nusa Mandiri ILKOM Jurnal Ilmiah Jurnal Ilmiah Mandala Education (JIME) EXPLORE Community Development Journal: Jurnal Pengabdian Masyarakat Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Journal Software, Hardware and Information Technology Explore Jurnal Karya untuk Masyarakat (JKuM) E-Amal: Jurnal Pengabdian Kepada Masyarakat Sasambo: Jurnal Abdimas (Journal of Community Service)
Zaeniah Zaeniah
Universitas Teknologi Mataram
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search

 1   2   3 
DESIGNING CLASS SCHEDULE INFORMATION SYSTEM BY USING TABOO-SEARCH METHOD Zaeniah, Zaeniah; Salman, Salman
Jurnal Pilar Nusa Mandiri Vol 16 No 2 (2020): 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.v16i2.1661

Abstract

Drafting of class schedule at the Faculty of Information and Communication Technology, Mataram University of Technology (FTIK UTM) is still done manually. So that, there are some problems such as lecturer teaching schedule at the same time at one time as well as student learning time at the same time at one time and studying more than 3 times a day. Therefore, manual scheduling requires a lot of time and it must be done very carefully. The method used to solve this problem is the Taboo- Search Method which is used to solve the problem of scheduling. The Taboo-Search Method is a method that seeks the best solution from existing solutions by creating a list of solutions or taboo lists, solutions that have been used previously will no longer be displayed for the next problem. The research method used in this research is the method of research and research and development which starts from the preliminary stage to find problems that occur up to the implementation stage so that it is generated an information system of course schedule at the Faculty of Information and Communication Technology, Mataram University of Technology. The purpose of this research is to produce a class schedule information system so that it can help arrange class schedules more quickly and precisely.
DATA MINING USING RANDOM FOREST, NAÏVE BAYES, AND ADABOOST MODELS FOR PREDICTION AND CLASSIFICATION OF BENIGN AND MALIGNANT BREAST CANCER Imran, Bahtiar; Hambali, Hambali; Subki, Ahmad; Zaeniah, Zaeniah; Yani, Ahmad; Alfian, Muhammad Rijal
Jurnal Pilar Nusa Mandiri Vol 18 No 1 (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.v18i1.2912

Abstract

This study predicts and classifies benign and malignant breast cancer using 3 classification models. The method used in this research is Random Forest, Naïve Bayes and AdaBoost. The prediction results get Random Forest = 100%, Naïve Bayes = 80% and AdaBoost = 80%. Results using Test and Score with Number of Folds 2, 5 and 10. Number of Folds 2 Random Forest model Accuracy = 95%, Precision = 95% and Recall = 95%, Naïve Bayes Accuracy = 93%, Precision = 93% and Recall 93%, AdaBoost Accuracy = 90%, Precision = 90% and Recall = 90%. With Number of Folds 5 with Random Forest = 96%, Precision = 96% and Recall 96%. Naïve Bayes Accuracy value = 94%, Precision = 94% and Recall = 94%, AdaBoost Accuracy value = 93%, Precision = 93% and Recall = 93%. With Number of Folds 10 Random Forest model = 96%, Precision = 96% and Recall 96%. Naïve Bayes Accuracy value = 94%, Precision = 94% and Recall = 94%, AdaBoost Accuracy value = 92%, Precision = 92% and Recall = 92%. Of the 3 models used, Random Forest got the best classification results compared to the others.
IMPLEMENTATION OF SUPPORT VECTOR REGRESSION IN THE PREDICTION OF THE NUMBER OF TOURIST VISITS TO THE PROVINCE WEST NUSA TENGGARA (NTB) 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.v18i2.3454

Abstract

Abstract — Indonesia has a variety of interesting tourist destinations to visit in each region. One area that is used as a favorite tourist destination is the Province of West Nusa Tenggara (NTB). Data The number of tourists visiting the NTB province from 2014 to 2020 tends to change based on data obtained from the Website of the NTB Provincial Tourism Office. The data on the number of visitors will continue to change, even if there is a possibility that it will increase. This can lead to the unpreparedness of the government and other tourism actors in providing the facilities and infrastructure needed by visitors when there is an increase in the number of tourist visits coming to NTB. Therefore, it is necessary to predict the number of tourist visits to NTB with accurate results. In this study, predictions of the number of tourist visits to the Province of NTB were made using the support vector regression method. This research resulted in an application to predict the number of tourist visits to NTB based on Event, Month, and Year. so that it can provide predictive results that are close to the actual value under normal conditions. The data used in this study is data on the number of tourist visits in 2017-2021 and events held in 2017-2021.
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%.
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.
Crack Detection of Concrete Surfaces with A Combination of Feature Extraction and Image-Based Backpropagation Artificial Neural Networks Wahyudi, Erfan; Imran, Bahtiar; Subki, Ahmad; Zaeniah, Zaeniah; Samsumar, Lalu Delsi; Salman, Salman
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.2249.228-235

Abstract

Concrete surface imperfections can signify a structure undergoing severe degradation. It deteriorates when concrete is exposed to elemental reactions such as fire, chemicals, physical damage, and calcium leaching. Due to its structural degradation, concrete deterioration poses a risk to the surrounding environment. Structural buildings can collapse due to severe concrete decline. To prevent concrete cracks early, it is imperative to identify the concrete surface. This requires the development of a technique for detecting the image-based concrete surface. One way to detect concrete surfaces is to create artificial neural networks. The purpose of this study is to combine feature extraction and artificial neural networks to detect cracks in concrete surfaces. The data used is concrete surface image data divided into two classes, namely cracked class and uncracked class. The total data is 600 data points, 300 data points, and 300 data points. The technique used is feature extraction from GLCM and Backpropagation Artificial Neural Network. Test results using epoch five show 95% accuracy, epoch 10 shows 95% results, epoch 100 shows 83% accuracy, and epoch 250 shows 73% results. The test results that have been carried out show a decrease in lower accuracy results when the epoch is determined to be higher. The results of this study epoch that shows the highest accuracy results are epoch 5 with 95% accuracy and epoch 10 with 95% accuracy.
Analysis of Early Childhood Social Development Achievement Levels Aerani, Aerani; Haliza, Siti; Muslihanah, Muslihanah; Hafizatulumah, Hafizatulumah; Zaeniah, Zaeniah; Dewi, Denda Cindera; Harmayanti, Windi Ayu; Sahid, Lintia Purnama; Suryani, Irma
Jurnal Ilmiah Mandala Education (JIME) Vol 11, No 1 (2025): Jurnal Ilmiah Mandala Education (Januari)
Publisher : Lembaga Penelitian dan Pendidikan Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/jime.v11i1.8040

Abstract

The purpose of writing this article is to understand the developmental process in early childhood. Writing this article uses the literature method, namely collecting reading sources from previous journals to find out actions in social development in early childhood. The results of this article were obtained from sources from journals covering early childhood social issues as well as social behavior which includes actions such as: sharing, cooperation, helping, donations, honesty. Where this social behavior is very influential in the social development of children, especially early childhood. The characteristics of early childhood social development include the ability to interact, children are able to share and take turns, and children have a sense of empathy.
Perancangan sistem E-Learning berbasis website untuk mendukung pembelajaran di SDN kalaki Wahyuni, Wenti Ayu; Fahrurrazikin, Fahrurrazikin; Zaeniah, Zaeniah
Journal Software, Hardware and Information Technology Vol 5 No 1 (2025)
Publisher : Jurusan Sistem Informasi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/shift.v5i1.163

Abstract

Technology plays a significant role in enhancing the quality of education, especially in remote areas such as SDN Kalaki. This school faces challenges like inadequate infrastructure and distractions from non-academic activities, such as horse racing, which divert students' focus from education. This study aims to design and develop a web-based e-learning information system accessible to students and teachers from various locations. The system is designed to improve teacher-student interaction and increase learning interest. The research employs a prototyping approach, involving interviews, observations, and iterative development. The results indicate that the developed e-learning system effectively enhances the efficiency of the learning process and provides a relevant solution to the limitations of educational access in the region.
Pelatihan Pengelolaan Website Pada Kantor Desa Duman Zaeniah Zaeniah; Zaenudin Zaenudin; Masjun Efendi; M Multazam
Sasambo: Jurnal Abdimas (Journal of Community Service) Vol. 4 No. 1: February 2022
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/sasambo.v4i1.619

Abstract

Tujuan kegitan Pengabdian kepada Masyarakat (PkM) adalah untuk meningkatkan kemampuan perangkat desa duman dalam mengelola website. Mitra kegitan adalah Desa Duman (perangkat desa) yang berjumlah 7 orang. Metode pelaksanaan knowledge transfer melalui kegiatan Ceramah dan praktik. Tahapan kegitan penagbdian perencanaan, pelaksanaan dan evaluasi. Kegitan pengabdian telah memberikan pengalaman, pemahaman dan keterampilan mitra dalam mengelola website dengan indikator mitra dapat membuat akun, mengisi konten dalm bentuk teks, foto, dan video secara mandiri. Kegitan pelatihan perlu dilakaukan secara berkesinambungan agar perangkat desa dapat secara mandiri dalam pengelolaan website sehingga dapat memberikan dampak pada pelayanan informasi kepada masyarakat dan pemerintah tentang kemajuan dan kedala-kendala di desa. Website Management Training in the Office Duman Village  The purpose of this training is to improve the ability of Duman village officials in managing websites. The activity partner is Duman Village (village apparatus) which consists of 7 people. The method of implementing knowledge transfer is through lectures and practice activities. Stages of activity planning, implementation, and evaluation. Service activities have provided partners experience, understanding, and skills in managing websites with indicators that partners can create accounts, fill out content in the form of text, photos, and videos independently. Training activities need to be carried out on an ongoing basis so that village officials can independently manage the website so that they can have an impact on information services to the community and government about progress and obstacles in the village.  
PELATIHAN MANAJEMEN PENGELOLAAN USAHA BENGKEL LAS DI DESA PAOKMOTONG KECAMATAN MASBAGIK KABUPATEN LOMBOK TIMUR Ahyat, Muhammad; Zaenudin, Zaenudin; Zulkarnaen, Zulkarnaen; Zaeniah, Zaeniah
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 6 No. 3 (2025): Volume 6 No 3 Tahun 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v6i3.47841

Abstract

Pelatihan manajemen pengelolaan usaha bagi kelompok usaha bengkel las di Desa Pakmotong Kecamatan Masbagik Kabupaten Lombok Timur Nusa Tenggara Barat ini bertujuan untuk   meningkatkan  pengetahuan,  keterampilan dan kecakapan sehingga kelompok usaha bengkel las ini memiliki kompetensi dalam memecahkan  masalah manajemen pengelolaan usaha. Pelatihan  ini diikuti sebanyak 10 orang anggota kelompok usaha bengkel las ini, dengan berbagai kegiatan yang dilaksanakan meliputi : 1) Pelatihan Manajemen Produksi, 2) Pelatihan Administrasi Keuangan dan 3) Pelatihan pemasarn dengan menggunakan teknologi informasi.Metode yang digunakan dalam pelaksanaan pelatihan ini menggunakan pendekatan partisipatif dan difusi ilmu pengetahuan, yang dirancang untuk meningkatkan keterlibatan peserta dan memastikan transfer pengetahuan yang efektif. Hasil dari pelaksanaan kegiatan ini dapat meningkatkan   kompetensi   kelompok usaha usaha bengkel las di Desa Pakmotong Kecamatan Masbagik Kabupaten Lombok Timur terutama dalam hal peningkatkan pengetahuan, keterampilan dan kecakapan pengrajin dalam hal pemahaman tentang manajemen produksi, administrasi keuangan dan manajemen pemasaran dengan menggunakan teknologi informasi.
Co-Authors Aerani, Aerani ahmad yani Ahyat, Muhammad Akbar, Ardiyallah Dewi, Denda Cindera Erniwati, Surni Fahrurrazikin, Fahrurrazikin Hafizatulumah, Hafizatulumah Haikal Wahyudi Haliza, Siti Hambali Hambali Harmayanti, Windi Ayu Imran, Bahtiar indriana, pathul Irma Suryani Lalu Delsi Samsumar, M.Eng. Lalu Isnaeni Rahman M Multazam M. Budiamin M. Yusuf Masjun Efendi Muhammad Ahyat Muhammad Masjun Efendi Muhammad Rijal Alfian Muslihanah, Muslihanah Rudi Muslim Sahid, Lintia Purnama Salman Salman Salman Salman Selamet Riadi Subki, Ahmad Surni Erniwati Suryadi, Emi wahyuni, wenti ayu Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenul Muttaqin Zulkarnaen Zulkarnaen Zulpahmi, M.