Pub Date : 2023-12-08DOI: 10.30989/teknomatika.v16i2.1249
Ferlinda Yuyung Kusumaningrum, Andika Bayu Saputra, A. Priyanto, Nurul Fatimah
Lansia merupakan suatu siklus hidup yang pasti dialami oleh manusia dan hampir setiap orang. Terdapat permasalahan yang dihadapi oleh lansia dari menurunnya kondisi fisik sampai tidak dapat bekerja, Pemerintah mengeluarkan program untuk mendukung lansia. Bantuan lansia yang dapat diterima setiap tiga bulan atau sesuai informasi dari pemerintah. Namun saat ini program yang ada masih belum efektif karena terdapat kendala seperti belum ada sebuah sistem yang dapat menginputkan data, sehingga pendataan bantuan lansia masih secara manual menggunakan pencatatan di buku yang dapat menghambat waktu pendataan dan perhitungan data. Penelitian ini bertujuan untuk membangun sebuah sistem pendukung keputusan dalam menentukan penerima bantuan lansia guna membantu dalam proses pengambilan keputusan. Algoritma weighted product yang merupakan suatu algoritma yang sering digunakan untuk menganalisa sebuah keputusan. Hasil penelitian ini berupa sebuah Implementasi Penggunaan Algoritma Weighted Product untuk Sistem Pendukung Keputusan Penerima Bantuan Lansia. Sistem diharapkan membantu dalam menentukan keputusan dari barbagai pilihan yang mempertimbangkan beberapa macam kriteria dan dapat diterapkan untuk membantu menyelesaikan permasalahan mengidentifikasi penerima bantuan lansia secara cepat, tepat dan efektif.
{"title":"Implementasi Penggunaan Algoritma Weighted Product untuk Sistem Pendukung Keputusan Bantuan Lansia","authors":"Ferlinda Yuyung Kusumaningrum, Andika Bayu Saputra, A. Priyanto, Nurul Fatimah","doi":"10.30989/teknomatika.v16i2.1249","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i2.1249","url":null,"abstract":"Lansia merupakan suatu siklus hidup yang pasti dialami oleh manusia dan hampir setiap orang. Terdapat permasalahan yang dihadapi oleh lansia dari menurunnya kondisi fisik sampai tidak dapat bekerja, Pemerintah mengeluarkan program untuk mendukung lansia. Bantuan lansia yang dapat diterima setiap tiga bulan atau sesuai informasi dari pemerintah. Namun saat ini program yang ada masih belum efektif karena terdapat kendala seperti belum ada sebuah sistem yang dapat menginputkan data, sehingga pendataan bantuan lansia masih secara manual menggunakan pencatatan di buku yang dapat menghambat waktu pendataan dan perhitungan data. Penelitian ini bertujuan untuk membangun sebuah sistem pendukung keputusan dalam menentukan penerima bantuan lansia guna membantu dalam proses pengambilan keputusan. Algoritma weighted product yang merupakan suatu algoritma yang sering digunakan untuk menganalisa sebuah keputusan. Hasil penelitian ini berupa sebuah Implementasi Penggunaan Algoritma Weighted Product untuk Sistem Pendukung Keputusan Penerima Bantuan Lansia. Sistem diharapkan membantu dalam menentukan keputusan dari barbagai pilihan yang mempertimbangkan beberapa macam kriteria dan dapat diterapkan untuk membantu menyelesaikan permasalahan mengidentifikasi penerima bantuan lansia secara cepat, tepat dan efektif.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139185068","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}
Pub Date : 2023-12-08DOI: 10.30989/teknomatika.v16i2.1248
Danang Prihanto, Adkhan Sholeh, Chanief Budi Setiawan, M. Abu, Amar Al Badawi
Abstrak - Di Indonesia, terdapat beberapa fenomena yang menunjukkan rendahnya tingkat keamanan digital. Pada tahun 2021, terdapat 5.940 kasus web defacement dari beberapa sektor yang menjadi sasaran. Salah satunya dari sektor akademik, yaitu perguruan tinggi dengan total 2.217 kasus, menjadikannya sektor dengan kasus terbanyak. Oleh karena itu, peneliti melakukan pemindaian pada ketiga website FTTI. Penelitian dilakukan dengan tujuan dapat menganalisis dan mengetahui tingkat keamanan serta bentuk-bentuk kerentanan pada website FTTI di Universitas Jenderal Achmad Yani Yogyakarta, yaitu ftti.unjaya.ac.id, elearning.ftti.unjaya.ac.id, dan app.ftti.unjaya.ac.id. Dengan hasil yang diperoleh dari analisis, peneliti harus melaporkan kepada Kepala Pusat Sistem Informasi (PUSI) FTTI. Menggunakan metode vulnerability assessment dengan beberapa alat seperti Nmap, Nessus, dan WPScan. Pada metode ini terdapat beberapa tahapan, seperti persiapan (instalasi alat dan pengumpulan data yang diperlukan), mengidentifikasi kerentanan, dan analisis. Hasil penelitian ini menunjukkan bahwa dari ketiga website, terdapat berbagai tingkat kerentanan seperti Critcal, High, Medium, Low, dan Info. Pada website ftti.unjaya.ac.id yang menggunakan WordPress, tidak terdapat kerentanan yang parah setelah dilakukan pemindaian menggunakan ketiga alat yang digunakan. Sementara itu, pada elearning.ftti.unjaya.ac.id dan app.ftti.unjaya.ac.id, menunjukkan hasil penilaian VPR Top Threats bahwa keduanya berada pada tingkat Medium. Pada ketiga website yang telah dipindai, ditemukan bahwa ftti.unjaya.ac.id adalah website dengan tingkat kerentanan paling aman. Menurut hasil pemindaian, website elearning.ftti.unjaya.ac.id maupun app.ftti.unjaya.ac.id memiliki beberapa kerentanan dengan tingkat risiko High bahkan Critical.
{"title":"Analisis Kerentanan Menggunakan Vulnerability Assessment pada Situs Web Perguruan Tinggi","authors":"Danang Prihanto, Adkhan Sholeh, Chanief Budi Setiawan, M. Abu, Amar Al Badawi","doi":"10.30989/teknomatika.v16i2.1248","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i2.1248","url":null,"abstract":"Abstrak - Di Indonesia, terdapat beberapa fenomena yang menunjukkan rendahnya tingkat keamanan digital. Pada tahun 2021, terdapat 5.940 kasus web defacement dari beberapa sektor yang menjadi sasaran. Salah satunya dari sektor akademik, yaitu perguruan tinggi dengan total 2.217 kasus, menjadikannya sektor dengan kasus terbanyak. Oleh karena itu, peneliti melakukan pemindaian pada ketiga website FTTI. Penelitian dilakukan dengan tujuan dapat menganalisis dan mengetahui tingkat keamanan serta bentuk-bentuk kerentanan pada website FTTI di Universitas Jenderal Achmad Yani Yogyakarta, yaitu ftti.unjaya.ac.id, elearning.ftti.unjaya.ac.id, dan app.ftti.unjaya.ac.id. Dengan hasil yang diperoleh dari analisis, peneliti harus melaporkan kepada Kepala Pusat Sistem Informasi (PUSI) FTTI. Menggunakan metode vulnerability assessment dengan beberapa alat seperti Nmap, Nessus, dan WPScan. Pada metode ini terdapat beberapa tahapan, seperti persiapan (instalasi alat dan pengumpulan data yang diperlukan), mengidentifikasi kerentanan, dan analisis. Hasil penelitian ini menunjukkan bahwa dari ketiga website, terdapat berbagai tingkat kerentanan seperti Critcal, High, Medium, Low, dan Info. Pada website ftti.unjaya.ac.id yang menggunakan WordPress, tidak terdapat kerentanan yang parah setelah dilakukan pemindaian menggunakan ketiga alat yang digunakan. Sementara itu, pada elearning.ftti.unjaya.ac.id dan app.ftti.unjaya.ac.id, menunjukkan hasil penilaian VPR Top Threats bahwa keduanya berada pada tingkat Medium. Pada ketiga website yang telah dipindai, ditemukan bahwa ftti.unjaya.ac.id adalah website dengan tingkat kerentanan paling aman. Menurut hasil pemindaian, website elearning.ftti.unjaya.ac.id maupun app.ftti.unjaya.ac.id memiliki beberapa kerentanan dengan tingkat risiko High bahkan Critical.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139185212","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}
Pub Date : 2023-12-08DOI: 10.30989/teknomatika.v16i2.1250
Indah Daila Sari, Dedy Hariyadi, R. Sahtyawan, Netania Indi Kusumaningtyas
Phishing is a sort of cybercrime that involves obtaining sensitive information through the use of email, SMS, or compromised websites. The effects of phishing are caused by factors in the Technology Threat Avoidance Theory. The single best way to stop phishing attacks is to increase awareness of the risk of them happening among users or end users (human firewall). To determine the next steps in raising user knowledge, it is necessary to measure cybersecurity awareness, particularly against phishing assaults. Identify a few significant cybersecurity awareness of FTTI University of Jenderal Achmad Yani students in Yogyakarta. The investigation in this case included a phishing test and also employed online observation using observers who were asked questions based on the Technology Threat Avoidance Theory (TTAT). Using the MANOVA analysis method, factors influencing cybersecurity awareness analysis is conducted. Based on the analysis and testing of phishing tests as well as online questionnaires from the sample population, it shows that the sample is at a poor level of awareness. While the analysis of cybersecurity influence factors using the MANOVA analysis method shows that the results of the sig.> 0.05 value so that h0 is rejected. Based on the results of the study, it was concluded that FTTI students were still vulnerable to phishing attacks. Factor analysis using the MANOVA method shows that the dependent factor affects the level of cybersecurity awareness of the respondents but there is no significant difference between the dependent factors.
网络钓鱼是一种网络犯罪，涉及通过使用电子邮件、短信或受损网站获取敏感信息。网络钓鱼的影响是由技术威胁规避理论中的因素造成的。阻止网络钓鱼攻击的唯一最佳方法就是提高用户或最终用户对发生网络钓鱼攻击风险的认识（人类防火墙）。为确定提高用户知识的下一步措施，有必要衡量网络安全意识，尤其是针对网络钓鱼攻击的意识。确定日惹 Jenderal Achmad Yani FTTI 大学学生的几个重要网络安全意识。本案例的调查包括网络钓鱼测试，还采用了在线观察法，观察者根据技术威胁规避理论（TTAT）提出问题。利用 MANOVA 分析方法，对影响网络安全意识的因素进行了分析。根据对网络钓鱼测试以及样本人群在线问卷的分析和检测，结果显示样本人群的网络安全意识水平较低。而利用 MANOVA 分析方法对网络安全影响因素进行分析，结果显示 sig.>0.05 值，因此拒绝 h0。根据研究结果，可以得出结论：快三学院学生仍然容易受到网络钓鱼攻击。利用 MANOVA 方法进行的因子分析显示，因果因子会影响受访者的网络安全意识水平，但因果因子之间没有显著差异。
{"title":"Analisis Tingkat Security Awareness-Personal Threat Terhadap Ancaman Phishing Dengan Metode Technology Threat Avoidance Theory (TTAT)","authors":"Indah Daila Sari, Dedy Hariyadi, R. Sahtyawan, Netania Indi Kusumaningtyas","doi":"10.30989/teknomatika.v16i2.1250","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i2.1250","url":null,"abstract":"Phishing is a sort of cybercrime that involves obtaining sensitive information through the use of email, SMS, or compromised websites. The effects of phishing are caused by factors in the Technology Threat Avoidance Theory. The single best way to stop phishing attacks is to increase awareness of the risk of them happening among users or end users (human firewall). To determine the next steps in raising user knowledge, it is necessary to measure cybersecurity awareness, particularly against phishing assaults. Identify a few significant cybersecurity awareness of FTTI University of Jenderal Achmad Yani students in Yogyakarta. The investigation in this case included a phishing test and also employed online observation using observers who were asked questions based on the Technology Threat Avoidance Theory (TTAT). Using the MANOVA analysis method, factors influencing cybersecurity awareness analysis is conducted. Based on the analysis and testing of phishing tests as well as online questionnaires from the sample population, it shows that the sample is at a poor level of awareness. While the analysis of cybersecurity influence factors using the MANOVA analysis method shows that the results of the sig.> 0.05 value so that h0 is rejected. Based on the results of the study, it was concluded that FTTI students were still vulnerable to phishing attacks. Factor analysis using the MANOVA method shows that the dependent factor affects the level of cybersecurity awareness of the respondents but there is no significant difference between the dependent factors.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139185243","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}
Pub Date : 2023-12-08DOI: 10.30989/teknomatika.v16i2.1254
Muhamad Arabi Rizki Angkotasan, A. Murdiyanto, A. Himawan, Fajar Syahruddin
Abstract - Do Up uses the website as online learning. users complain about the accessibility of the website with some minimal features and an unattractive UI when accessed via a smartphone will make the UX limited and will limit user interaction in using Do Up. Designing UI and UX prototypes of mobile learning at startup Do Up, using the design thinking method to solve problems and find the right solution according to the user's wishes. The author applies design thinking in this research. The author makes an illustration in the form of a Do Up mobile learning UI design that is in accordance with user needs and provides the design to Do Up stakeholders. In SEQ there are 4 scales given by users, namely 4.5, 6 and 7 scale. Most users give a 7 scale on the UI/UX design of the Do Up mobile learning prototype. On SUS which shows that the final score is 87 It means that the prototype has been well received by the users. The author has applied design thinking which consists of empathize, define, ideate, prototype and test stages in this study.
摘要--Do Up 使用网站作为在线学习平台。用户抱怨网站的可访问性差，功能少，通过智能手机访问时用户界面不美观，这将使用户体验受到限制，并限制用户在使用 Do Up 时的互动。在初创公司 Do Up 设计移动学习的用户界面和用户体验原型，使用设计思维方法解决问题，并根据用户的意愿找到正确的解决方案。作者在本研究中应用了设计思维。作者以图解的形式，设计了符合用户需求的Do Up移动学习用户界面，并将设计方案提供给Do Up的利益相关者。在 SEQ 中，用户给出了 4 个等级，即 4.5、6 和 7 级。大多数用户对 Do Up 移动学习原型的 UI/UX 设计给出了 7 分。在 SUS 中，最终得分是 87 分。作者在本研究中运用了设计思维，包括移情、定义、构思、原型和测试等阶段。
{"title":"Desain User Interface Dan User Experience Prototype Mobile Learning Menggunakan Metode Design Thinking Metode Design Thinking","authors":"Muhamad Arabi Rizki Angkotasan, A. Murdiyanto, A. Himawan, Fajar Syahruddin","doi":"10.30989/teknomatika.v16i2.1254","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i2.1254","url":null,"abstract":"Abstract - Do Up uses the website as online learning. users complain about the accessibility of the website with some minimal features and an unattractive UI when accessed via a smartphone will make the UX limited and will limit user interaction in using Do Up. Designing UI and UX prototypes of mobile learning at startup Do Up, using the design thinking method to solve problems and find the right solution according to the user's wishes. The author applies design thinking in this research. The author makes an illustration in the form of a Do Up mobile learning UI design that is in accordance with user needs and provides the design to Do Up stakeholders. In SEQ there are 4 scales given by users, namely 4.5, 6 and 7 scale. Most users give a 7 scale on the UI/UX design of the Do Up mobile learning prototype. On SUS which shows that the final score is 87 It means that the prototype has been well received by the users. The author has applied design thinking which consists of empathize, define, ideate, prototype and test stages in this study.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139185217","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}
Pub Date : 2023-12-08DOI: 10.30989/teknomatika.v16i2.1251
Anas Sufi, Hasan Manahingati, Puji Winar Cahyo, Kartika Kusumaningtyas, Alfun Roehatul Jannah
Amidst the fluctuations in computercomponent prices brought about by the Covid-19pandemic, a comprehensive analysis platform hasbeen developed to address this challenge. Thisinnovative platform harnesses historical datasourced from prominent e-commerce platforms suchas Shopee, Blibli, and Tokopedia, presenting userswith insightful average price graphs categorized bycomponent series and types. The researchmethodology adopted follows a prototype approach,encompassing meticulous phases ranging fromneeds analysis, application design, prototyping,testing, evaluation, prototype refinement, through toimplementation and ongoing maintenance. Thesuccessful implementation of this system, powered bythe Python programming language, features robustfunctionalities including product search anddynamic graphical representations derived fromhistorical data. The data retrieval process, utilizingthe Scraping method, occurs at regular intervals ona weekly basis. Upon meticulous analysis ofhistorical data spanning from January to July 2022,a noteworthy trend emerged, highlighting thatShopee and Tokopedia consistently offer computercomponents at relatively more affordable pricescompared to Blibli. The conclusive findings of thisresearch underscore the platform's efficacy inproviding an essential tool for users navigating thecomplex landscape of computer component pricedynamics, particularly in the unprecedented contextof the ongoing pandemic. This platform not onlyfacilitates monitoring but also empowers users withvaluable insights crucial for informed purchasingdecisions based on stable and budget-friendly pricingstructures.
{"title":"CParts Platform Analisis Harga Komponen Komputer pada Marketplace","authors":"Anas Sufi, Hasan Manahingati, Puji Winar Cahyo, Kartika Kusumaningtyas, Alfun Roehatul Jannah","doi":"10.30989/teknomatika.v16i2.1251","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i2.1251","url":null,"abstract":"Amidst the fluctuations in computercomponent prices brought about by the Covid-19pandemic, a comprehensive analysis platform hasbeen developed to address this challenge. Thisinnovative platform harnesses historical datasourced from prominent e-commerce platforms suchas Shopee, Blibli, and Tokopedia, presenting userswith insightful average price graphs categorized bycomponent series and types. The researchmethodology adopted follows a prototype approach,encompassing meticulous phases ranging fromneeds analysis, application design, prototyping,testing, evaluation, prototype refinement, through toimplementation and ongoing maintenance. Thesuccessful implementation of this system, powered bythe Python programming language, features robustfunctionalities including product search anddynamic graphical representations derived fromhistorical data. The data retrieval process, utilizingthe Scraping method, occurs at regular intervals ona weekly basis. Upon meticulous analysis ofhistorical data spanning from January to July 2022,a noteworthy trend emerged, highlighting thatShopee and Tokopedia consistently offer computercomponents at relatively more affordable pricescompared to Blibli. The conclusive findings of thisresearch underscore the platform's efficacy inproviding an essential tool for users navigating thecomplex landscape of computer component pricedynamics, particularly in the unprecedented contextof the ongoing pandemic. This platform not onlyfacilitates monitoring but also empowers users withvaluable insights crucial for informed purchasingdecisions based on stable and budget-friendly pricingstructures.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139185087","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}
Badan Penyelenggara Jaminan Sosial (BPJS) Ketenagakerjaan adalah badan aturan publik yang dibuat melalui Undang-Undang No 24 Tahun 2011 Tentang Badan Penyelenggaran Jaminan Sosial menggunakan tujuan untuk mewujudkan terselenggaranya pemberian jaminan terpenuhinya kebutuhan dasar yang layak bagi setiap peserta atau anggota keluarganya. Dalam pelaksanaannya terdapat informasi yang tersebar khususnya pada tweet di Twitter mengenai keputusan Kementrian Kesehatan yaitu mengenai Jaminan Hari Tua (JHT) yang hanya bisa dicairkan/diambil setelah peserta (BPJS) Ketenagakerjaan menginjak usia 56 tahun, menyebabkan adanya pro dan kontra yang ada dikalangan masyarakat. Berdasarkan tweet-tweet pada Twitter yang belum dianalisis maka perlu di analisis secara mendalam untuk mendapatkan informasi yang sesuai berdasarkan opini netizen. Berdasarkan hasil penelitian ini diperoleh nilai akurasi data testing sebesar 92% untuk metode Lexicon Based dan 95% untuk data testing pada metode Naïve Bayes Classifier lalu untuk data training Naïve Bayes Classifier mendapatkan akurasi 82%. Penelitian ini mendapatkan kesimpulan bahwa jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan mendapat sentimen negatif dari netizen yang banyak membahas mengenai penolakan peraturan baru dimana jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan, hanya bisa dicairkan atau diambil ketika peserta BPJS Ketenagakerjaan menginjak usia 56 tahun.
{"title":"Metode Hybrid Menggunakan Pendekatan Lexicon Based dan Naive Bayes Classifier Untuk Analisis Sentimen Terkait Jaminan Hari Tua","authors":"Rizky Fauzi Akbar, Muhammad Habibi, Puji Winar Cahyo, Nafisa Alfi Sa'diya","doi":"10.30989/teknomatika.v16i2.1247","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i2.1247","url":null,"abstract":"Badan Penyelenggara Jaminan Sosial (BPJS) Ketenagakerjaan adalah badan aturan publik yang dibuat melalui Undang-Undang No 24 Tahun 2011 Tentang Badan Penyelenggaran Jaminan Sosial menggunakan tujuan untuk mewujudkan terselenggaranya pemberian jaminan terpenuhinya kebutuhan dasar yang layak bagi setiap peserta atau anggota keluarganya. Dalam pelaksanaannya terdapat informasi yang tersebar khususnya pada tweet di Twitter mengenai keputusan Kementrian Kesehatan yaitu mengenai Jaminan Hari Tua (JHT) yang hanya bisa dicairkan/diambil setelah peserta (BPJS) Ketenagakerjaan menginjak usia 56 tahun, menyebabkan adanya pro dan kontra yang ada dikalangan masyarakat. Berdasarkan tweet-tweet pada Twitter yang belum dianalisis maka perlu di analisis secara mendalam untuk mendapatkan informasi yang sesuai berdasarkan opini netizen. Berdasarkan hasil penelitian ini diperoleh nilai akurasi data testing sebesar 92% untuk metode Lexicon Based dan 95% untuk data testing pada metode Naïve Bayes Classifier lalu untuk data training Naïve Bayes Classifier mendapatkan akurasi 82%. Penelitian ini mendapatkan kesimpulan bahwa jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan mendapat sentimen negatif dari netizen yang banyak membahas mengenai penolakan peraturan baru dimana jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan, hanya bisa dicairkan atau diambil ketika peserta BPJS Ketenagakerjaan menginjak usia 56 tahun.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139185381","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}
Pub Date : 2023-11-29DOI: 10.30989/teknomatika.v16i1.1139
M. Irwansyah, Muhammad Habibi, Fajar Syahruddin
In this background discusses the topic of tweet about Flooding on Twitter using the keyword "Flood". Tweet data was taken from June 1, 2021 to June 2, 2021 with the number of tweet data obtained, which was 2000 tweets. The number of tweets related to flooding has not been analyzed so that the topics contained in it are not yet known. Research . Modeling topics related to floods in Indonesia on Twitter social media with the LDA method. Research. This study uses experimental methods with several variables to test hypotheses. Then the data is processed with stages, namely web data extraction, preprocessing, feature extraction, topic modeling using latent dirichlet allocation algorithms, visualization, and analysis. Research. The results of the topic coherence stage were carried out a search for the most optimal topic from the 20 topics that had been determined at the beginning. The results of topic coherence for 20 topics concluded that for topic 10 it has a total topic value of 0.41 and has an ideal topic modeling result and is in accordance with the provisions. Conclusion : Based on the results of the discussion of topic coherence, it can be concluded that the most ideal number of topics is topic 10 because it has the highest value compared to other topics. The advice here is to be able to display or get flood information in Indonesia in real time and accurately.
{"title":"PEMODELAN TOPIK TERKAIT BANJIR PADA TWITTER DENGAN MENGGUNAKAN LATENT DIRICHLET ALLOCATION","authors":"M. Irwansyah, Muhammad Habibi, Fajar Syahruddin","doi":"10.30989/teknomatika.v16i1.1139","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i1.1139","url":null,"abstract":"In this background discusses the topic of tweet about Flooding on Twitter using the keyword \"Flood\". Tweet data was taken from June 1, 2021 to June 2, 2021 with the number of tweet data obtained, which was 2000 tweets. The number of tweets related to flooding has not been analyzed so that the topics contained in it are not yet known. Research . Modeling topics related to floods in Indonesia on Twitter social media with the LDA method. Research. This study uses experimental methods with several variables to test hypotheses. Then the data is processed with stages, namely web data extraction, preprocessing, feature extraction, topic modeling using latent dirichlet allocation algorithms, visualization, and analysis. Research. The results of the topic coherence stage were carried out a search for the most optimal topic from the 20 topics that had been determined at the beginning. The results of topic coherence for 20 topics concluded that for topic 10 it has a total topic value of 0.41 and has an ideal topic modeling result and is in accordance with the provisions. Conclusion : Based on the results of the discussion of topic coherence, it can be concluded that the most ideal number of topics is topic 10 because it has the highest value compared to other topics. The advice here is to be able to display or get flood information in Indonesia in real time and accurately.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139211994","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}
Pub Date : 2023-11-29DOI: 10.30989/teknomatika.v16i1.1133
Budi Wardoyo, Puji Winar Cahyo, Muhammad Habibi, M. Abu, Amar Al Badawi
The accumulated data, which consists of facts and transaction events in a business, should be processed and utilized for the progress of business development. Currently, the data owned by AHASS THM has not been optimized and further processed to provide broader benefits, such as promotion and forming loyal AHASS customers. The objective of this research is to analyze the existing transaction data to identify consumer transaction patterns at AHASS THM. The research methodology used is Market Basket Analysis (MBA), a method for analyzing consumer transaction data by finding associative relationships between different items in the consumer's shopping cart. By applying a minimum parameter limitation of support = 0.001, confidence = 0.8, and sorting based on the magnitude of the confidence parameter, 62 associative rules of consumer transaction patterns in AHASS THM business were obtained. By selecting the top 10 associative rules based on the highest confidence values, generally, these associative rules have a confidence parameter greater than 0.95 or 95%. Additionally, there are 3 associative rules with a confidence value of 1 or 100%, indicating that consumers will purchase Bearing Needle 20x29x218 after buying Bearing Ball 6902U, or a combination of Bearing Ball 6902U with CVT Grease 10 gr or Oli MPX2 0.8 lt.
{"title":"Analisis Pola Konsumen Dalam Bertransaksi Bisnis di Bengkel Resmi AHASS Total Honda Motor","authors":"Budi Wardoyo, Puji Winar Cahyo, Muhammad Habibi, M. Abu, Amar Al Badawi","doi":"10.30989/teknomatika.v16i1.1133","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i1.1133","url":null,"abstract":"The accumulated data, which consists of facts and transaction events in a business, should be processed and utilized for the progress of business development. Currently, the data owned by AHASS THM has not been optimized and further processed to provide broader benefits, such as promotion and forming loyal AHASS customers. The objective of this research is to analyze the existing transaction data to identify consumer transaction patterns at AHASS THM. The research methodology used is Market Basket Analysis (MBA), a method for analyzing consumer transaction data by finding associative relationships between different items in the consumer's shopping cart. By applying a minimum parameter limitation of support = 0.001, confidence = 0.8, and sorting based on the magnitude of the confidence parameter, 62 associative rules of consumer transaction patterns in AHASS THM business were obtained. By selecting the top 10 associative rules based on the highest confidence values, generally, these associative rules have a confidence parameter greater than 0.95 or 95%. Additionally, there are 3 associative rules with a confidence value of 1 or 100%, indicating that consumers will purchase Bearing Needle 20x29x218 after buying Bearing Ball 6902U, or a combination of Bearing Ball 6902U with CVT Grease 10 gr or Oli MPX2 0.8 lt.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139209254","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}
Pub Date : 2023-11-27DOI: 10.30989/teknomatika.v16i1.1099
Yusriyah Isnaini Mufidah, A. Saputra, Netania Indi Kusumaningtyas
The Coronavirus disease outbreak caused by severe acute respiratory syndrome by coronavirus 2 was first reported in Wuhan, Hubei province, China in December 2019, until March 2, 2020, President Joko Widodo announced the first case of an Indonesian citizen who was confirmed positive for COVID-19. The development of new cases of COVID-19 patients in Indonesia is still being reported even though the pandemic has lasted for almost two years. Then need a way to determine predictions or predict the number of increases in Indonesia’s COVID-19 cases in the future using machine learning technology with the Linear Regression algorithm. Estimating the number of active cases adding positive COVID-19 cases in Indonesia over the next 3 months using the machine learning method using the Linear Regression algorithm. This study predicts COVID-19 cases using machine learning with the Linear Regression algorithm. The model results have a linear coefficient, so the model predicts very well for linear data on days 0 – 300, and on the day after that, the number of positive cases of the national COVID-19 virus does not continue to show a linear relationship, the model becomes inaccurate again. The results of the parameter evaluation show that the level of accuracy is low, but this model can be used as a reference for case predictions for the next month with the results of comparison of predicted data and actual data not much different.
{"title":"Sistem Prediksi Kasus Covid-19 di Indonesia Menggunakan Algoritma Linear Regression","authors":"Yusriyah Isnaini Mufidah, A. Saputra, Netania Indi Kusumaningtyas","doi":"10.30989/teknomatika.v16i1.1099","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i1.1099","url":null,"abstract":"The Coronavirus disease outbreak caused by severe acute respiratory syndrome by coronavirus 2 was first reported in Wuhan, Hubei province, China in December 2019, until March 2, 2020, President Joko Widodo announced the first case of an Indonesian citizen who was confirmed positive for COVID-19. The development of new cases of COVID-19 patients in Indonesia is still being reported even though the pandemic has lasted for almost two years. Then need a way to determine predictions or predict the number of increases in Indonesia’s COVID-19 cases in the future using machine learning technology with the Linear Regression algorithm. Estimating the number of active cases adding positive COVID-19 cases in Indonesia over the next 3 months using the machine learning method using the Linear Regression algorithm. This study predicts COVID-19 cases using machine learning with the Linear Regression algorithm. The model results have a linear coefficient, so the model predicts very well for linear data on days 0 – 300, and on the day after that, the number of positive cases of the national COVID-19 virus does not continue to show a linear relationship, the model becomes inaccurate again. The results of the parameter evaluation show that the level of accuracy is low, but this model can be used as a reference for case predictions for the next month with the results of comparison of predicted data and actual data not much different.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139233265","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}
Pub Date : 2023-11-27DOI: 10.30989/teknomatika.v16i1.1105
Siti Fatimah, Ahmad Hanafi, Kharisma, Alfun Roehatul Jannah
The sragenkab.go.id website serves as a vital platform supporting the operations of the Sragen district government, disseminating accurate and prompt information to the public. However, various issues hamper its functionality, such as interface display problems, unclear layout, non-functional links, excessively simple design, and slow response times. To address these concerns, this study aims to evaluate the sragenkab.go.id website's usability and accessibility aspects using the Website Usability Evaluation (WEBUSE) method and the Web Content Accessibility Guideline (WCAG) 2.1 method, respectively. Using the WEBUSE method, a survey questionnaire was distributed to 100 respondents from Sragen to assess the usability level of the website. The obtained score of 0.65 indicated that the website's usability is categorized as "good" and has been accepted by the users. On the other hand, the accessibility evaluation using the WCAG 2.1 method, with the assistance of the WAVE tool and accessibilitychecker, revealed a score below 75%, indicating a significant risk of non-compliance with international accessibility standards. In conclusion, the sragenkab.go.id website exhibits commendable usability; however, it falls short in terms of accessibility. The findings emphasize the importance of optimizing the website's accessibility to adhere to international regulatory standards, ensuring equitable access to information and services for all users. Future improvement efforts should focus on rectifying accessibility issues to enhance the overall user experience and inclusivity of the website.
{"title":"EVALUASI PADA WEBSITE SRAGENKAB.GO.ID MENGGUNAKAN METODE WEB USABILITY EVALUATION (WEBUSE) DAN WEB CONTENT ACCESSIBILITY GUIDELINES (WCAG) 2.1","authors":"Siti Fatimah, Ahmad Hanafi, Kharisma, Alfun Roehatul Jannah","doi":"10.30989/teknomatika.v16i1.1105","DOIUrl":"https://doi.org/10.30989/teknomatika.v16i1.1105","url":null,"abstract":"The sragenkab.go.id website serves as a vital platform supporting the operations of the Sragen district government, disseminating accurate and prompt information to the public. However, various issues hamper its functionality, such as interface display problems, unclear layout, non-functional links, excessively simple design, and slow response times. To address these concerns, this study aims to evaluate the sragenkab.go.id website's usability and accessibility aspects using the Website Usability Evaluation (WEBUSE) method and the Web Content Accessibility Guideline (WCAG) 2.1 method, respectively. Using the WEBUSE method, a survey questionnaire was distributed to 100 respondents from Sragen to assess the usability level of the website. The obtained score of 0.65 indicated that the website's usability is categorized as \"good\" and has been accepted by the users. On the other hand, the accessibility evaluation using the WCAG 2.1 method, with the assistance of the WAVE tool and accessibilitychecker, revealed a score below 75%, indicating a significant risk of non-compliance with international accessibility standards. In conclusion, the sragenkab.go.id website exhibits commendable usability; however, it falls short in terms of accessibility. The findings emphasize the importance of optimizing the website's accessibility to adhere to international regulatory standards, ensuring equitable access to information and services for all users. Future improvement efforts should focus on rectifying accessibility issues to enhance the overall user experience and inclusivity of the website.","PeriodicalId":508475,"journal":{"name":"Teknomatika: Jurnal Informatika dan Komputer","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139234175","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}
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