Journal of Artificial Intelligence and Software Engineering (J-AISE)最新文献

{"title":"Rancang Bangun Aplikasi Machine Learning Pemilihan Varietas Bibit Jagung Unggul Menggunakan Algoritma Artificial Neural Network (ANN) Berbasis Web","authors":"Ainul Fitria, Salahuddin Salahuddin, Muhammad Rizka","doi":"10.30811/jaise.v4i1.5401","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5401","url":null,"abstract":"Jagung atau dalam bahasa latin Zea Mays merupakan adalah salah satu dari jenis tanaman pangan dari keluarga rumput-rumputan yang dikelompokkan dalam tanaman biji-bijian. Jagung memiliki banyak varietas. Adapun varietas yang telah dilepas oleh Menteri Pertanian hingga Oktober tahun 2022 sebanyak 361 varietas, yaitu jagung hibrida sebanyak 298 varietas, jagung komposit sebanyak 59 varietas, dan ada sebanyak 4 varietas jagung hibrida produk rekayasa genetik (PRG). Petani jagung biasanya memilih dan menentukan bibit jagung yang akan dibudidayakan berdasarkan rekomendasi pedagang bibit jagung atau dari rekan sesama petani jagung. Namun demikian sering dijumpai hasil panen jagung tidak sesuai dengan ekspektasi dan target yang diharapkan. Bahkan, tidak jarang petani jagung mengalami gagal panen yang disebabkan oleh beberapa faktor, salah satunya dikarenakan bibit jagung yang dipilih bukan merupakan varietas bibit jagung unggul. Sistem ini dirancang untuk membantu para petani jagung khususnya di daerah Aceh dalam memilih dan menentukan bibit jagung unggul untuk dibudidayakan dengan tujuan mendapatkan hasil panen yang memuaskan. Sistem ini menggunakan algoritma Artificial Neural Network untuk melakukan pemilihan. Artificial Neural Network (ANN) adalah algoritma Machine Learning dengan model komputasi yang terinspirasi dari prinsip kerja otak manusia. Artificial Neural Network digunakan dalam aplikasi ini karena dapat melakukan prediksi dengan akurat. Hasil yang diharapkan dengan adanya sistem ini petani dapat memilih varietas bibit jagung unggul untuk dibudidayakan, sehingga dapat memenuhi kebutuhan stok dalam negeri dengan memanfaatkan komputer dalam tahapan pemilihan bibit unggul. Penerapan algortima ANN Multi Layer Perceptron pada aplikasi ini menggunakan 21 data varietas jagung dengan 504 dataset yang dimasukkan mendapatkan hasil nilai tertinggi dengan persentase akurasi 90,47%. Dengan hasil tersebut, algortima Artificial Neural Network Multi Layer Perceptron dapat digunakan untuk Aplikasi Machine Learning dalam menentukan pemilihan varietas bibit jagung unggul Abstract Corn or in Latin Zea Mays is one of the types of food crops from the grass family which is grouped into grain crops. Corn has many varieties. The varieties that have been released by the Minister of Agriculture until October 2022 are 361 varieties, namely 298 varieties of hybrid corn, 59 varieties of composite corn, and there are as many as 4 varieties of genetically modified (PRG) hybrid corn. Maize farmers usually choose their maize seeds based on recommendations from maize seed traders or fellow maize farmers. However, maize yields are often not in line with expectations and targets. In fact, it is not uncommon for corn farmers to experience crop failure caused by several factors, one of which is because the corn seeds chosen are not superior corn seed varieties. This system is designed to help corn farmers, especially in the Aceh area, in choosing and determining superior corn seed","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 82","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141367399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementasi Aplikasi Enkripsi Dekripsi File Dokumen Menggunakan Algoritma Aes Pada Cloud Computing (Studi Kasus Prodi Teknologi Rekayasa Komputer Jaringan)","authors":"R. Arifa, H. Husaini, Fachri Yanuar Rudi","doi":"10.30811/jaise.v4i1.5382","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5382","url":null,"abstract":"Perkembangan teknologi sangat dibutuhkan oleh kehidupan manusia dalam setiap kegiatannya. Ilmu teknologi yang semakin berkembang khususnya dalam bidang ilmu komputer dan semakin meningkatnya penggunaan komputer dalam kehidupan sehari-hari. Selama ini pengguna banyak merasa tidak aman dalam proses pengiriman dan penyimpanan data melalui komputer. Untuk mengatasi permasalahan itu dapat dilakukan enkripsi dan dekripsi dengan memanfaatkan metode AES. Penelitian ini bertujuan mengetahui waktu yang dibutuhkan sistem dalam mengunggah dan mengunduh file dokumen melalui cloud. Dalam penelitian ini digunakan sebuah metode AES atau algoritma enkripsi yang dirancang untuk mengenkripsi dan mendekripsi informasi dengan tingkat keamanan yang tinggi.. Melalui implementasi aplikasi ini, dapat diketahui cara melindungi data yang ditransfer antara perangkat dan cloud, serta data yang disimpan di cloud, dengan menggunakan algoritma AES untuk enkripsi dan dekripsi. Dengan demikian, keamanan data dan privasi akan terjaga dengan baik. Pengujian dilakukan pada file berukuran 1,63 mb, waktu yang dibutuhkan untuk melakukan upload file yaitu 0,0203 detik dan waktu yang dibutuhkan untuk melakukan download file yaitu 0,0078 detik. Aplikasi ini memiliki kinerja yang sangat cepat dalam pengunggahan dan pengunduhan file, waktu yang dibutuhkan berdasarkan ukuran setiap file. Semakin besar ukuran file yang akan di unggah atau diunduh, maka semakin lama waktu yang dibutuhkan. Berdasarkan penelitian tersebut, aplikasi ini memiliki kinerja yang baik dalam melakukan transfer file serta aman dalam menjaga keamanan file dokumen.Kata kunci— Advanced Encryption Standard (AES), Cloud Computing, File Dokumen, KriptografiAbstract Technological developments are needed by human life in every activity. Technological science is increasingly developing, especially in the field of computer science and the increasing use of computers in everyday life. So far, many users feel unsafe in the process of sending and storing data via computer. To overcome this problem, encryption and decryption can be carried out using the AES method. This research aims to determine the time required for the system to upload and download document files via the cloud. In this research, an AES method or encryption algorithm is used which is designed to encrypt and decrypt information with a high level of security. Through the implementation of this application, it can be seen how to protect data transferred between devices and the cloud, as well as data stored in the cloud, by using AES algorithm for encryption and decryption. In this way, data security and privacy will be well maintained. The test was carried out on a file measuring 1.63 MB, the time required to upload the file was 0.0203 seconds and the time required to download the file was 0.0078 seconds. This application has very fast performance in uploading and downloading files, the time required is based on the size of each file. The larger the file size to be up","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141367055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Penerapan Metode Hybrid Case Based Dalam Diagnosa Gangguan Kehamilan","authors":"Muhammad Ilham Afif, Huzaeni Huzaeni, Muhammad Rizka","doi":"10.30811/jaise.v4i1.5397","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5397","url":null,"abstract":"Kehamilan adalah suatu proses di mana seorang wanita mengandung janin dalam rahimnya. Kurangnya pengetahuan tentang gejala-gejala yang terjadi selama kehamilan menjadi masalah yang perlu diatasi. Hasil Riset Kesehatan Dasar menunjukkan bahwa hanya sekitar 44% ibu hamil yang mengetahui tanda bahaya selama kehamilan, yang menyebabkan beberapa gejala penyakit kehamilan diabaikan dan menyebabkan risiko kematian ibu. Untuk mengatasi masalah ini, maka di bangun sebuah sistem pakar dengan menggunakan metode Hybrid Case Based yang mampu memberikan informasi dan diagnosa cepat serta tepat untuk masalah kesehatan gangguan kehamilan pada ibu hamil. Pada sistem ini terdapat 5 penyakit yang akan di diagnosa yaitu anemia, hyperemesis gravidarum, diabetes melitus gestasional, infeksi saluran kemih, dan perdarahan, serta terdapat 25 gejala. Sistem ini menerapkan rumus cosine similarity dalam mengukur similarity antara gejala penyakit yang dialami pasien dengan gejala penyakit yang ada dalam basis kasus. Berdasarkan pengujian tingkat kemiripan, antara gejala – gejala yang dialami pasien dengan basis kasus yang ada, sistem mampu mediagnosa jenis penyakit anemia dengan nilai 95%. Tingkat akurasi sistem pakar dengan total data uji sebanyak 20 didapatkan nilai akurasi sebesar 100%.Kata kunci: Gangguan Kehamilan, Diagnosa, Sistem Pakar, Hybrid Case BasedAbstractPregnancy is a process in which a woman carries a fetus in her womb. Lack of knowledge about the symptoms that occur during pregnancy is a problem that needs to be addressed. Basic Health Research results show that only about 44% of pregnant women know the danger signs during pregnancy, which causes some symptoms of pregnancy diseases to be ignored and causes the risk of maternal death. To overcome this problem, an expert system is built using the Hybrid Case Based method that is able to provide information and diagnose quickly and precisely for health problems of pregnancy disorders in pregnant women. In this system there are 5 diseases that will be diagnosed, namely anemia, hyperemesis gravidarum, gestational diabetes mellitus, urinary tract infection, and bleeding, and there are 25 symptoms. This system applies the cosine similarity formula in measuring the similarity between the symptoms of the disease experienced by the patient and the symptoms of the disease in the case base. Based on testing the level of similarity, between the symptoms experienced by the patient and the existing case base, the system is able to diagnose the type of anemia disease with a value of 95%. The accuracy of the expert system with a total of 20 test data obtained an accuracy value of 100%.Keywords: Pregnancy Disorders, Diagnosis, Expert System, Hybrid Case Based","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141366903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aplikasi Manajemen Literasi Membaca dan Rekomendasi Buku Berbasis Android Menggunakan Metode Content-Based Filtering","authors":"Sharhan Anhar, M. Khadafi, M. Abdi","doi":"10.30811/jaise.v4i1.5400","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5400","url":null,"abstract":"Membaca buku adalah sebuah kegiatan yang dapat membantu kita untuk menambah pengetahuan dan wawasan. Minat baca di Indonesia saat ini cenderung rendah, yang disebabkan oleh beberapa faktor seperti diantaranya kurangnya waktu luang, kurangnya referensi buku untuk menentukan buku yang ingin dibaca, dan semakin canggih kemajuan teknologi yang menyebabkan orang lebih suka menghabiskan waktu untuk bermain handphone. Untuk menyelesaikan permasalahan tersebut dapat dilakukan dengan menggunakan aplikasi manajemen literasi membaca dan rekomendasi buku berbasis Android. Tujuan dari aplikasi ini adalah untuk memudahkan dalam mengelola kegiatan membaca serta memberikan rekomendasi buku yang bisa dibaca selanjutnya dan mengingatkan pengguna untuk membaca buku. Metode yang digunakan pada sistem ini adalah Content-Based Filtering. Dengan adanya aplikasi ini, pengguna bisa dengan mudah men-track progress membaca buku. Penerapan algoritma Content-Based Filtering pada aplikasi ini dapat memberikan buku-buku rekomendasi yang relevan dengan pengguna berdasarkan pengujian kuesioner yang dilakukan pada 10 responden dengan nilai rata-rata 3.92 dari skala hingga 5. Dengan hasil tersebut algoritma Content-Based Filtering dapat digunakan untuk memberikan rekomendasi buku.  Abstract Reading books is an activity that can help us to increase knowledge and insight. Reading interest in Indonesia today tends to be low, which is caused by several factors such as lack of free time, lack of book references to determine which books to read, and increasingly sophisticated technological advances that cause people to prefer to spend time playing cellphones. To solve these problems, it can be done by using an Android-based reading literacy management and book recommendation application. The purpose of this application is to make it easier to manage reading activities and provide recommendations for books that can be read next and remind users to read books. The method used in this system is Content-Based Filtering. With this application, users can easily track the progress of reading books. The implementation of the Content-Based Filtering algorithm in this application can provide recommended books that are relevant to users based on questionnaire testing conducted on 10 respondents with an average value of 3.92 on a scale of up to 5. With these results the Content-Based Filtering algorithm can be used to provide book recommendations.","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141367440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rancang Bangun Aplikasi Chatbot Untuk Deteksi Pecandu Pornografi Menggunakan Metode Support Vector Machine (SVM)","authors":"Muhammad Fajar Al Fath, Salahuddin Salahuddin, Muhammad Arhami","doi":"10.30811/jaise.v4i1.5399","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5399","url":null,"abstract":"Pornografi adalah representasi seksual dalam media yang menampilkan aktivitas seksual dan bahan yang menekankan pada unsur-unsur seksual yang dapat menyebabkan kecanduan. Salah satu faktor penyebab banyaknya pecandu pornografi di masyarakat karena kurangnya kesadaran dan pemahaman terhadap dampak negatif pornografi. Kesadaran diri akan membantu masyarakat terutama generasi muda untuk dapat meninggalkan konten pornografi dan terhindar dari dampaknya dalam jangka panjang. Penelitian ini bertujuan untuk memberikan solusi bagi para pecandu dan masyarakat untuk menghentikan kebiasaan menikmati pornografi dengan cara membuat Chatbot Porn Addict Detection (ChatPAD) menggunakan metode Support Vector Machine(SVM) melalui pendekatan psikologi PAST(Porn Addiction Screening Tool) dengan model pertanyaan Cyber Pornography Inventory Use. Chatbot memiliki fitur untuk mendeteksi tingkat kecanduan seseorang terhadap pornografi sekaligus memberikan pemahaman terhadap dampak bahaya dan cara berhenti dari adiksi pornografi. Hasil penelitian ini, chatbot berhasil memprediksi tingkat kecanduan pornografi dari para pengguna menggunakan metode SVM  dengan akurasi yang baik dan akurat. Tingkat akurasi yang didapatkan berdasarkan pengujian confusion matrix mencapai 98.3% pada label_2 dan label_3 sedangkan tingkat akurasi terendah terletak pada label_1. Hasil presisi tertinggi dimiliki oleh label_1 dengan angka 98.4% diikuti label_0 sedangkan presisi terendah adalah label_4. Hasil recal tertinggi adalah 87.8% dari label_2 sedangkan terendah adalah 7.14% dari label_1. Hasil f1-score mencatatkan label_2 memiliki hasil tertinggi dengan score 91.1%. Berdasarkan hasil pengujian tersebut maka diperlukan peningkatan performa pada label_1 karena memiliki f1-score dan recall yang rendah.  AbstractPornography is a sexual representation in the media that displays sexual activities and materials that emphasize sexual elements that can cause addiction. One of the factors causing the number of pornography addicts in society is due to a lack of awareness and understanding of the negative effects of pornography. Self-awareness will help the community, especially the younger generation, to be able to leave pornographic content and avoid its impact in the long run. This research aims to provide solutions for addicts and the community to stop the habit of enjoying pornography by creating a Porn Addict Detection Chatbot (ChatPAD) using the Support Vector Machine (SVM) method through the PAST (Porn Addiction Screening Tool) psychology approach with the Cyber Pornography Inventory Use question model. The chatbot has features to detect the level of addiction of a person to pornography as well as provide understanding of the harmful effects and how to stop pornography addiction. The results of this study, the chatbot successfully predicts the level of pornography addiction of users using the SVM method with good and accurate accuracy. The accuracy level obtained based on confusion matrix testing ","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141366783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sistem Penilaian Mahasiswa Terhadap Fasilitas Kampus Politeknik Negeri Lhokseumawe Menggunakan Natural Language Processing","authors":"Muhammad Icshan, Huzaeni Huzaeni, Amirullah Amirullah","doi":"10.30811/jaise.v4i1.5404","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5404","url":null,"abstract":"Fasilitas, sebagai elemen pendukung dalam pelaksanaan tugas dan kegiatan, mendefinisikan sarana serta prasarana yang esensial untuk menunjang aktivitas suatu institusi. Studi ini dilakukan di Politeknik Negeri Lhokseumawe (PNL), di mana mahasiswa partisipan diminta untuk mengevaluasi fasilitas kampus melalui kuesioner Google. Kuesioner ini menyajikan 15 pertanyaan yang dapat diakses melalui tautan formulir kuesioner, mencakup aspek-aspek seperti ruang kelas, laboratorium, perabot belajar, peralatan pengajaran, dan layanan perpustakaan hingga teknologi e-learning. Saat ini, belum ada metode formal untuk mengklasifikasikan pandangan mahasiswa terhadap fasilitas kampus. Oleh karena itu, diperkenalkan metode klasifikasi sentimen dengan menggunakan Natural Language Processing (NLP) untuk membersihkan dan mengolah data teks. Setelah itu, data tersebut dimasukkan ke dalam model klasifikasi menggunakan Multi-layer Perceptron, yang mampu memberikan prediksi akurasi sebesar 80% berdasarkan 78 responden yang berpartisipasi dalam penelitian ini. Skenario eksperimen melibatkan 1023 data latih dan 105 data uji, termasuk ekstraksi fitur opini, menunjukkan bahwa model klasifikasi ini efektif dalam mengelola data berukuran besar dan kompleks. Abstract Facilities, as a supporting element in the implementation of tasks and activities, define the facilities and infrastructure that are essential to support the activities of an institution. This study was conducted at Politeknik Negeri Lhokseumawe (PNL), where participating students were asked to evaluate campus facilities through a Google questionnaire. The questionnaire presents 15 questions that can be accessed through the questionnaire form link, covering aspects such as classrooms, laboratories, learning furniture, teaching equipment, and library services to e-learning technology. Currently, there is no formal method to classify students' views on campus facilities. Therefore, a sentiment classification method is introduced by using Natural Language Processing (NLP) to clean and process the text data. Afterwards, the data was fed into a classification model using Multi-layer Perceptron, which was able to provide a prediction accuracy of 80% based on 78 respondents who participated in the study. Experimental scenarios involving 1023 training data and 105 test data, including opinion feature extraction, show that this classification model is effective in managing large and complex data.","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 31","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141367723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Konsumsi Daya Server Worker Dengan VM Live Migration Berbasis Proxmox","authors":"Muhammad Azzahari, Ibn Khaldun","doi":"10.30811/jaise.v4i1.5403","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5403","url":null,"abstract":"Live migration merupakan suatu teknik migrasi yang memindahkan server virtual machine (VM) ke server worker yang rendah CPU usage nya. Teknik migrasi ini dilakukan dengan memanfaatkan metode fuzzy mamdani sebagai pengambil keputusan berdasarkan hasil monitoring CPU usage pada masing-masing server worker. Pada setiap server worker akan ditentukan nilai batas (Threshold) yang berfungsi sebagai acuan kapan server vm akan bermigrasi ke server worker yang mengalami rendah CPU usage. Hasil pengujian yang dilakukan selama 30 menit menunjukkan bahwa teknik live migration VM dapat mengurangi konsumsi daya sebesar 0,26 Watt dibandingkan dengan tanpa teknik tersebut. Dengan demikian optimasi daya bisa terjadi jika proses migrasi server VM terlaksana dari server worker host asal ke server worker host tujuan sehingga server worker asal nantinya akan mengalami penurunan konsumsi daya atau mengalami dengan serendah-rendahnya konsumsi daya (idle).AbstractLive migration is a migration technique that moves a virtual machine (VM) server to a server worker with low CPU usage. This migration technique is carried out by utilizing the fuzzy mamdani method as a decision maker based on the results of monitoring CPU usage on each worker server. On each worker server, a threshold value will be determined which serves as a reference for when the VM server will migrate to a worker server that experiences low CPU usage. The results of tests carried out for 30 minutes show that the VM live migration technique can reduce power consumption by 0.26 Watts compared to without this technique. Thus, power optimization can occur if the VM server migration process is carried out from the original worker host server to the destination worker host server so that the original worker server will experience a decrease in power consumption or experience the lowest possible power consumption (idle).","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141368227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Penerapan E-Raport Kekurangan Energi Kronis (KEK) dengan Cloud Computing pada Smart Village di Desa Uteunkot","authors":"M. Muliawati, H. Hidayat, Safriadi Safriadi","doi":"10.30811/jaise.v4i1.5402","DOIUrl":"https://doi.org/10.30811/jaise.v4i1.5402","url":null,"abstract":"Berdasarkan data tahun 2023, Aceh masih menduduki peringkat kelima tertinggi di Indonesia dalam kategori kekurangan energi kronis (KEK). Saat ini, puskesmas Muara Dua Kota Lhokseumawe terutama di Desa Uteunkot, masih mengandalkan pencatatan KEK menggunakan buku, yang terbukti kurang efektif. Oleh karena itu, untuk mengatasi permasalahan ini, dibutuhkan pengembangan sebuah aplikasi mobile yang dapat digunakan untuk pencatatan dan pelaporan KEK guna meningkatkan efisiensi dan efektivitas proses tersebut. Penelitian ini bertujuan membuat aplikasi e-raport KEK dalam bentuk mobile agar dapat digunakan untuk melihat persentase yang didapatkan oleh masyarakat yang kekurangan gizi. Dalam penelitian ini digunakan metode blackbox testing untuk mengetahui kepuasaan pengguna terhadap aplikasi, untuk pengujian web service digunakan QoS. Tingkat kepuasan pengguna mencapai 97.4% akan tetapi dari ketidakpuasan pengguna mencapai 2.6%. Berdasarkan pengujian QoS diperoleh hasil 11,77/sec dalam waktu respon pada permintaan 1,10,50,100,250,500 dan 1000. Pada pengguna 10,50,250,500 dan 1000 mencapai rata-rata 21,28/sec dalam waktu respon dengan permintaan 1 pengguna. AbstractBased on data from 2023, Aceh is still ranked fifth highest in Indonesia in the category of chronic energy deficiency (CHD). Currently, the Muara Dua Health Center in Lhokseumawe City, especially in Uteunkot Village, still relies on recording SEZ using books, which has proven to be less effective. Therefore, to overcome this problem, it is necessary to develop a mobile application that can be used for recording and reporting SEZ to improve the efficiency and effectiveness of the process. This research aims to create a mobile application of SEZ e-raport so that it can be used to see the percentage obtained by malnourished people. In this study, the blackbox testing method was used to determine user satisfaction with the application, for web service testing used QoS. The level of user satisfaction reached 97.4% but from user dissatisfaction reached 2.6%. Based on QoS testing, the results obtained are 11.77/sec in response time on requests 1,10,50,100,250,500 and 1000. At users 10,50,250,500 and 1000 reached an average of 21.28/sec in response time with a request of 1 user.","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141367662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sistem Pendataan Sensus Penduduk Berbasis Digital Signature Studi Kasus: Badan Pusat Statistik Kabupaten Aceh Utara","authors":"Nurmala Hayati, Salahuddin Salahuddin, Musta’inul Abdi","doi":"10.30811/jaise.v3i2.4589","DOIUrl":"https://doi.org/10.30811/jaise.v3i2.4589","url":null,"abstract":"Sistem informasi memiliki peran penting dalam mendukung kegiatan operasional Badan Pusat Statistik (BPS), terutama dalam pengumpulan data untuk sensus dan survei. Unit kerja BPS, memiliki tantangan dalam mengumpulkan data yang representatif dan dapat dipertanggungjawabkan di wilayah yang luas dan padat penduduknya. Saat ini, BPS Kabupaten Aceh Utara masih menggunakan metode Paper and Pencil Interview (PAPI) yang kurang efektif dalam hal jumlah sampel yang cukup besar dan kontrol manajemen kualitas data. Untuk mengatasi permasalahan tersebut, BPS Kabupaten Aceh Utara membuat sistem yang dapat memvalidasi data pencacahan sensus penduduk dengan menggunakan digital signature. Digital signature atau tanda tangan digital adalah skema matematis yang digunakan untuk membuktikan keaslian pesan atau dokumen digital. Dalam pembuatan sistem pendataan tersebut digunakan algoritma DSA (Digital Signature Algorithm). DSA digunakan dalam aplikasi ini karena memenuhi DSS (Digital Signature Standard), yang telah diuji oleh NIST (National Institute of Standards and Technology) dan terbukti memiliki tingkat keamanan yang tinggi. Proses pembuatan tanda tangan digital diawali dengan pembuatan kunci publik dan kunci privat. Kunci publik akan digunakan untuk memverifikasi tanda tangan. Pada proses perhitungan nilai hash akan dihasilkan message diggest, yang akan digunakan dalam pembuatan tanda tangan. Proses penandatanganan menghasilkan sepasang tanda tangan (r,s). Pada proses verifikasi, akan mengecek apakah tanda tangan tersebut cocok atau tidak dengan menggunakan kunci publik dan menghitung nilai hash dokumen yang diterima. Adapun hasil akhir yang diperoleh adalah digital signature. Dari sebanyak 23 data yang sudah diuji dinyatakan sukses dan memperoleh hasil digital signature.Kata kunci— Sensus, Penduduk, Digital Signature, Pendataan.AbstactInformation systems have an important role in supporting the operational activities of the Central Bureau of Statistics (BPS), especially in collecting data for censuses and surveys. BPS work units have challenges in collecting representative and accountable data in a large and densely populated area. Currently, BPS Kabupaten Aceh Utara still uses the Paper and Pencil Interview (PAPI) method which is less effective in terms of a large enough sample size and data quality management control. To overcome these problems, BPS Kabupaten Aceh Utara created a system that can validate population census enumeration data using digital signature. Digital signature is a mathematical scheme used to prove the authenticity of a digital message or document. In making the data collection system, the DSA (Digital Signature Algorithm) algorithm is used. DSA is used in this application because it meets the DSS (Digital Signature Standard), which has been tested by NIST (National Institute of Standards and Technology) and proven to have a high level of security. The process of creating a digital signature begins with the creation of a public key and a ","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136158672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rancang Bangun Biodiversity Informatics dalam Analisa Sebaran Makhluk Hidup Berbasis Android dan GIS","authors":"Rizaldo Setiawan, Huzaeni Huzaeni, Muhammad Arhami","doi":"10.30811/jaise.v3i2.4590","DOIUrl":"https://doi.org/10.30811/jaise.v3i2.4590","url":null,"abstract":"Indonesia, yang sering disebut sebagai \"mega biodiversity country,\" menjadi rumah bagi lebih dari 17.000 spesies tumbuhan dan satwa liar yang mencakup ribuan jenis burung, reptil, amfibia, dan ikan. Kawasan hutan Aceh yang luas mencakup beragam ekosistem, dari hutan hingga lautan. Namun, pengelolaan data ekologi di wilayah ini menjadi suatu tantangan kompleks. Untuk mengatasi tantangan ini, pendekatan bio-informatika digunakan untuk mengelola data ekologi yang kompleks sehingga dapat dipahami oleh masyarakat umum. penelitian ini menggabungkan data ekologi sebagai sumber informasi utama dan data spasial sebagai dasar pemetaan spesies. Data ini kemudian diolah untuk menghasilkan analisis dalam bentuk grafik dan laporan yang berguna bagi peneliti dalam menjaga stabilitas ekosistem. Pendekatan bio-informatika ini tidak hanya membantu dalam mengumpulkan dan mengelola data ekologi, tetapi juga meningkatkan pemahaman kita tentang keanekaragaman hayati yang luar biasa di Aceh.Penelitian ini memiliki dampak besar dalam menjaga keberlanjutan lingkungan Aceh, membantu dalam pelestarian spesies yang terancam punah, dan memberikan dukungan penting bagi penelitian dan pemantauan ekologi di wilayah ini. Hasilnya dapat menjadi landasan penting dalam menjaga ekosistem Aceh tetap stabil dan berfungsi sebagai sumber informasi yang berharga bagi para peneliti dan masyarakat umum.Kata kunci - Keakenaragaman hayati, Aceh, ­bio-informaticsAbstractIndonesia, often referred to as a \"mega biodiversity country,\" is home to more than 17,000 species of plants and wildlife, including thousands of birds, reptiles, amphibians and fish. Aceh's vast forested areas encompass a diverse range of ecosystems, from forests to oceans. However, managing ecological data in this region is a complex challenge. To overcome this challenge, bio-informatics approaches have been used to manage complex ecological data so that it can be understood by the general public. This research combines ecological data as the main source of information and spatial data as the basis for species mapping. This data is then processed to produce analysis in the form of graphs and reports that are useful for researchers in maintaining ecosystem stability. This bio-informatics approach not only helps in collecting and managing ecological data, but also enhances our understanding of Aceh's extraordinary biodiversity. This research has a major impact in maintaining Aceh's environmental sustainability, assisting in the preservation of endangered species, and providing important support for ecological research and monitoring in the region. The results can serve as an important foundation in keeping Aceh's ecosystems stable and serve as a valuable source of information for researchers and the general public.Keyword - Biodiversity, Aceh, ­bio-informatics","PeriodicalId":474401,"journal":{"name":"Journal of Artificial Intelligence and Software Engineering (J-AISE)","volume":" 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136158663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}