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Indonesian Journal of Computer Science最新文献

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Penentuan Keabsahan Dokumen KHS Dengan Menggunakan QR Code dan Digital Signature di Politeknik Negeri Manado 在万鸦老理工学院使用 QR 码和数字签名确定 KHS 文件的有效性
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3603
Heaven Lordan Kimbal, Amang Sudarsono, Idris Winarmo
{"title":"Penentuan Keabsahan Dokumen KHS Dengan Menggunakan QR Code dan Digital Signature di Politeknik Negeri Manado","authors":"Heaven Lordan Kimbal, Amang Sudarsono, Idris Winarmo","doi":"10.33022/ijcs.v13i1.3603","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3603","url":null,"abstract":"The change in the KHS process from manual to computerized has positive impacts such as integration with the judicial system, ease of inputting and printing data, and in recapitulating data. However, there are risks in this concept, namely loss and damage to data which can cause doubts about the validity of KHS data. Departing from this problem, an idea emerged to create a system that can prove the validity of KHS printed documents by applying QR Code technology and Digital Signature. With Digital Signature, information about the contents of KHS when it is first printed is encrypted first so that it cannot be changed by unauthorized parties, then the encryption results will be stored on the QR Code. So that the determination of document validity is done by comparing the contents of the current document with the contents of the document in the QR Code, if the information from both is the same then the printed document is declared an original document and vice versa. The verification process will use hash logic which is one of the functions of providing verification and authentication because it produces a unique value for each input. This result is expected to help Politeknik Negeri Manado to check the validity of KHS printed by students.","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"55 7-8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140499341","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}
引用次数: 0
Platform Budidaya Perairan Ekosistem Tambak Berbasis Internet Of Things 基于物联网的池塘生态系统水产养殖平台
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3627
Rossi Arisdiawan, Setiawardhana, Agus Indra Gunawan
{"title":"Platform Budidaya Perairan Ekosistem Tambak Berbasis Internet Of Things","authors":"Rossi Arisdiawan, Setiawardhana, Agus Indra Gunawan","doi":"10.33022/ijcs.v13i1.3627","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3627","url":null,"abstract":"Indonesia has a potential pond area of 2,963,717 hectares. Ponds are a place for breeding ecosystems such as shrimp. The digitalization system in ponds is very necessary for management and development and has an impact on economic growth. Development in the field of aquaculture involves extensification and intensification. One of the intensification programs is to utilize Internet of Things (IoT) technology to identify various parameters from the Pond which are sent to the Webserver. This research is to produce a webserver-based platform to serve as a data center and monitor several IoT devices on the farm. This platform uses an internet network with HTTP and MySql protocols. Operations related to web servers and devices refer to standard quality settings from pond farmers.","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"21 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140500554","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}
引用次数: 0
Data Mining Implementation in Admission of New Students Using Zone Systems 利用区域系统在新生录取中实施数据挖掘
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3631
Jln. Khatib, Sulaiman Dalam, Indonesia Padang, Hikmat Nurhidayat, Chirstina Juliane
{"title":"Data Mining Implementation in Admission of New Students Using Zone Systems","authors":"Jln. Khatib, Sulaiman Dalam, Indonesia Padang, Hikmat Nurhidayat, Chirstina Juliane","doi":"10.33022/ijcs.v13i1.3631","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3631","url":null,"abstract":"Every aspect of education that is now in place has to be continuously improved by the government. The Admissions Process for New Students (PPDB) in schools that have a zoning system in place is examined in this study. The primary goal of the study is to use the clustering approach to calculate the distance between students and schools. Analyzing, gathering, processing, and evaluating data are all steps in the research methodology. The study's findings demonstrate how the zoning system has a big impact on school enrollment trends. These results highlight how crucial it is to keep the PPDB's zoning system under constant review in order to provide equitable access to education for all pupils without sacrificing educational quality. The investigation ultimately discovered clustering in the distance, classified as the closest and farthest radius, between the student's home and the school. as well as the significance of a more comprehensive study.","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"51 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140499707","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}
引用次数: 0
Desain Sistem Keamanan terhadap Spoofing GPS pada Aplikasi Android: Integrasi Program Perlindungan dalam Source Code 针对 Android 应用程序中 GPS 欺骗的安全系统设计：在源代码中集成保护程序
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3630
Zaim Irfansyah Arbi, Banu Santoso
{"title":"Desain Sistem Keamanan terhadap Spoofing GPS pada Aplikasi Android: Integrasi Program Perlindungan dalam Source Code","authors":"Zaim Irfansyah Arbi, Banu Santoso","doi":"10.33022/ijcs.v13i1.3630","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3630","url":null,"abstract":"Perkembangan aplikasi Android berbasis lokasi menghadapi ancaman serius dari serangan spoofing GPS yang semakin canggih. Penelitian ini mengusulkan sebuah sistem keamanan yang responsif dengan mengintegrasikan perlindungan langsung ke dalam source code aplikasi Android. Fokusnya adalah memblokir akses opsi pengembang, yang sering dimanfaatkan oleh aplikasi spoofing GPS di Play Store. Metode ini diharapkan dapat meningkatkan keamanan aplikasi Android berbasis lokasi. Tujuan utama adalah mencegah serangan spoofing dengan melindungi integritas data lokasi. Hasil penelitian menunjukkan efektivitas sistem dalam mengatasi celah keamanan yang spesifik ini, memberikan kontribusi penting dalam menjaga keamanan aplikasi Android di era serangan spoofing GPS yang semakin mengancam.","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"271 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140499976","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}
引用次数: 0
Pemanfaatan Analisis Sentimen Terhadap Kasus Bunuh Diri Mahasiswa Menggunakan Naïve Bayes Classifier 利用 Naïve Bayes 分类器对学生自杀案例进行情感分析
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3605
Ainnur Rafli, Kusnawi Kusnawi
{"title":"Pemanfaatan Analisis Sentimen Terhadap Kasus Bunuh Diri Mahasiswa Menggunakan Naïve Bayes Classifier","authors":"Ainnur Rafli, Kusnawi Kusnawi","doi":"10.33022/ijcs.v13i1.3605","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3605","url":null,"abstract":"Suicide is currently a serious problem in higher education, especially among university students, and special approaches and attention are required to prevent it. With  today's advances in technology, emotion analysis techniques can be an effective way to understand students' feelings and thoughts that may lead to suicidal behavior or indicate a risk of suicide. For this study, we scraped the data for his 1,151 tweets on Twitter and cleaned it up to 817. Of these, there are 745 negative tweets and 72 positive tweets. Additionally, the data is implemented in an algorithm that performs a data split of 80:20 with an accuracy of 90,24%. That's the \"depression\" that often appears when visualizing Lata data. Especially in Indonesia, there are many suicides due to depression. The purpose of this study is to understand the factors associated with student suicide and to determine the effectiveness and accuracy of this algorithm. Additionally, this study is expected to provide insights into educational and mental health settings to improve prevention strategies and more effective approaches","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"55 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140499823","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}
引用次数: 0
Machine Learning on Opinion Mining of Netizen's Hate Speech 对网民仇恨言论进行舆情挖掘的机器学习
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3617
Mutiana Pratiwi, Rima Liana Gema
{"title":"Machine Learning on Opinion Mining of Netizen's Hate Speech","authors":"Mutiana Pratiwi, Rima Liana Gema","doi":"10.33022/ijcs.v13i1.3617","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3617","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000  \u0000  \u0000 \u0000 \u0000Netizen comments written in an online news portal through social media platforms, one of which is Instagram, can be used as material in the sentiment analysis process, which can be classified into positive, negative, or neutral sentiments. Sentiment analysis is part of the study of text mining, the science of discovering unknown knowledge by automatically extracting information from large volumes of unstructured text into useful information. The resulting information is in the form of sentiment towards a topic, whether it tends to be positive, negative, or neutral. The classification method used in this research is Support Vector Machine (SVM) and TF-IDF data weighting to classify text. Stages to perform data analysis are pre-processing to clean data, word weighting, labeling data into positive, negative, or neutral classes, and classifying and visualizing data with graphs. Accuracy tests using 70:30 split data showed that the accuracy reached 98%. Tests with 80:20 and 90:10 split data also showed high accuracy of 98% and 99%. \u0000 \u0000 \u0000 \u0000","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"261 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140500827","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}
引用次数: 0
Optimalisasi Metode Naive Bayes Classifier Untuk Prediksi Persetujuan Kredit 优化用于信贷审批预测的 Naive Bayes 分类器方法
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3622
Achmad Syakur, Rendri Purwandi Putra, Christina Juliane
{"title":"Optimalisasi Metode Naive Bayes Classifier Untuk Prediksi Persetujuan Kredit","authors":"Achmad Syakur, Rendri Purwandi Putra, Christina Juliane","doi":"10.33022/ijcs.v13i1.3622","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3622","url":null,"abstract":"Kredit adalah bentuk pembiayaan yang banyak orang ajukan ke bank atau perusahaan penyedia kredit. Dalam proses pengajuan kredit, dilakukan analisis untuk menentukan apakah kredit yang diajukan layak atau tidak. Penelitian ini bertujuan untuk membantu bank atau perusahaan penyedia kredit dalam melakukan persetujuan kredit dengan efektif dan akurat dalam menentukan status pengajuan. Penelitian ini menggunakan teknik data mining dan kumpulan dataset yang berasal dari kaggle.com. Terdapat 12 atribut dan 2 kelas yang digunakan dalam penelitian ini. Dalam penelitian ini, metode klasifikasi Naive Bayes dan optimasi kelompok partikel (PSO) digunakan. Prediksi persetujuan kredit dengan metode naïve bayes classifier menghasilkan nilai akurasi sebesar 80,00% dengan nilai AUC 0,884. Sebaliknya, prediksi persetujuan kredit dengan metode particle swarm optimization (PSO) menghasilkan nilai akurasi sebesar 96,67% dengan nilai AUC 0,69.","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"57 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140500525","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}
引用次数: 0
Deteksi Penyakit Tanaman Padi Berbasis Android Melalui Pemanfaatan Teachable Machine 利用可教机器进行基于安卓的水稻病害检测
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3643
H. Saputra, Ilfa Stephane, T. Sundara, Aulia Hidayatul Bahri
{"title":"Deteksi Penyakit Tanaman Padi Berbasis Android Melalui Pemanfaatan Teachable Machine","authors":"H. Saputra, Ilfa Stephane, T. Sundara, Aulia Hidayatul Bahri","doi":"10.33022/ijcs.v13i1.3643","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3643","url":null,"abstract":"Padi adalah tanaman pangan utama di banyak negara, termasuk Indonesia, dan pertumbuhannya sangat dipengaruhi oleh faktor lingkungan dan kualitas tanah. Namun, petani sering menghadapi tantangan dalam mengelola Organisme Pengganggu Tanaman (OPT) yang dapat merusak tanaman dan mengurangi produktivitas. Untuk membantu petani mengatasi tantangan ini, penelitian ini memanfaatkan Teachable Machine, sebuah aplikasi berbasis web untuk mendeteksi penyakit pada daun padi. Penelitian ini menggunakan dataset dari Kaggle dan melatih model dengan gambar daun padi yang terinfeksi. Hasilnya menunjukkan bahwa aplikasi ini efektif dalam mendeteksi penyakit daun padi dan dapat membantu petani dalam mengidentifikasi dan menangani hama pada tanaman padi mereka. Namun, efektivitas aplikasi ini sangat bergantung pada kualitas dan jumlah data yang digunakan untuk melatih model","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"18 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140499512","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}
引用次数: 0
Analisis Kinerja Algoritme WRR dengan WLC pada Load Balancing Nginx 带有 WLC 的 WRR 算法在 Nginx 负载平衡上的性能分析
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3577
Rama Baeturohman, Banu Santoso
{"title":"Analisis Kinerja Algoritme WRR dengan WLC pada Load Balancing Nginx","authors":"Rama Baeturohman, Banu Santoso","doi":"10.33022/ijcs.v13i1.3577","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3577","url":null,"abstract":"Semakin meningkatnya pengunjung website mengakibatkan web server menjadi sibuk merespons permintaan klien. Untuk mengatasi masalah kelebihan beban, penggunaan load balancing menjadi solusi yang efektif. Nginx merupakan aplikasi web server memiliki keunggulan sebagai perangkat lunak sumber terbuka, ringan, dan berkinerja tinggi sebagai HTTP dan reverse proxy. Dalam konteks ini, algoritma penjadwalan menjadi penting untuk menyeimbangkan beban Algoritma penjadwalan seperti Weighted Round Robin (WRR) dan Weighted Least Connection (WLC) menjadi pilihan yang relevan. Pengujian dilakukan dengan mengirimkan 1000, 2000, dan 5000 permintaan dengan bobot server 10:15:20, analisis throughput menunjukkan bahwa algoritma WLC lebih unggul daripada algoritma WRR. WLC mencapai waktu throughput terbaik dengan nilai 108.988 Kbits/sec. Parameter respon time menunjukkan bahwa algoritma WRR memiliki kinerja lebih baik, dengan waktu rata-rata respon sebesar 2.761ms. Untuk parameter packet loss, algoritma WRR juga menunjukkan hasil yang lebih baik, dengan rata-rata nilai packet loss sebesar 56%.","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"350 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140500776","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}
引用次数: 0
Analisis Keamanan Jaringan Komputer Menggunakan Metode IDS dan IPS dengan Notifikasi Telegram 利用 IDS 和 IPS 方法与电报通知进行计算机网络安全分析
Indonesian Journal of Computer Science Pub Date : 2024-01-22 DOI: 10.33022/ijcs.v13i1.3505
Taufiq Syaiful Huda, Subektiningsih Subektiningsih
{"title":"Analisis Keamanan Jaringan Komputer Menggunakan Metode IDS dan IPS dengan Notifikasi Telegram","authors":"Taufiq Syaiful Huda, Subektiningsih Subektiningsih","doi":"10.33022/ijcs.v13i1.3505","DOIUrl":"https://doi.org/10.33022/ijcs.v13i1.3505","url":null,"abstract":"Penelitian ini bertujuan untuk menganalisis keamanan jaringan komputer dengan memanfaatkan metode Intrusion Detection System (IDS) dan Intrusion Prevention System (IPS) yang dilengkapi dengan notifikasi melalui platform Telegram. IDS dan IPS merupakan teknologi yang penting dalam menjaga integritas dan keamanan jaringan komputer dari ancaman serangan jaringan komputer. Penelitian ini mencoba mengintegrasikan kedua sistem ini untuk mendeteksi potensi intrusi dan secara aktif mencegah serangan sambil memberikan notifikasi real-time melalui Telegram, memungkinkan administrator untuk segera mengambil tindakan responsif. Metodologi yang digunakan mencakup implementasi dan konfigurasi IDS/IPS, serta pengujian terhadap skenario intrusi yang mungkin terjadi. Hasil penelitian ini diharapkan dapat memberikan wawasan yang lebih baik tentang tingkat keamanan jaringan komputer dan mengidentifikasi cara-cara yang lebih efektif dalam menghadapi ancaman serangan jaringan komputer.","PeriodicalId":52855,"journal":{"name":"Indonesian Journal of Computer Science","volume":"51 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140499701","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}
引用次数: 0
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