Jurnal Teknologi Informasi dan Ilmu Komputer最新文献

{"title":"Analisis Interaksi Aktivitas Pembelajaran Daring Berdasarkan Data Log Aktivitas pada Learning Managemefnt System (LMS) Menggunakan Educational Process Mining","authors":"Novriani Dewi Anwar, N. Setiawan, W. Purnomo","doi":"10.25126/jtiik.1077987","DOIUrl":"https://doi.org/10.25126/jtiik.1077987","url":null,"abstract":"Perpaduan perkembangan teknologi di bidang pendidikan telah mengembangkan suatu inovasi yang disebut LMS (Learning Management System) yang dapat diakses dari mana saja dan kapan saja tanpa harus melakukan pertemuan secara fisik di kelas. Kegiatan interaksi pada LMS memiliki event log yang dapat diekstraksi untuk mengidentifikasi analisis menggunakan Educational Process Mining (EPM). Kami mengekstrak event log dari ELING, platform LMS yang disediakan oleh fakultas kami. Selanjutnya, kami melakukan Process Mining menggunakan metode Heuristic Miner dari tiga dosen kelas mata kuliah Data Warehouse yang berbeda. Analisis yang dilakukan yaitu melihat gambaran kegiatan pembelajaran yang diberikan oleh masing-masing dosen dan pendekatannya dalam mengarahkan mahasiswa untuk berinteraksi dengan modul materi pada ELING apakah sesuai urutan dalam Rencana Pembelajaran Semester (RPS). Kami memvariasikan dependency threshold untuk mengidentifikasi modul pembelajaran mana yang memiliki tingkat ketergantungan yang lebih tinggi antar event yang menjadi inti pembelajaran mata kuliah tersebut. Pada dependency threshold 0,6, jumlah kegiatan dari model yang ditemukan untuk semua dosen adalah 21. Sementara pada threshold 0,8, jumlah kegiatan bervariasi antara 12 dan 20. Dengan variasi dependency threshold ini juga akan mengidentifikasi modul mana yang tetap muncul yang berhubungan dengan bentuk model aktivitas pembelajaran dan apakah model yang dihasilkan sesuai dengan urutan RPS.   Abstract   The combination of technological developments in the field of education has developed an innovation called LMS (Learning Management System) that can be accessed from anywhere and anytime without having to conduct physical meetings in class. Interaction activities in the LMS have event logs that can be extracted to identify analysis using Educational Process Mining (EPM). We extract event logs from ELING, an LMS platform provided by our faculty. Next, we conducted Process Mining using the Heuristic Miner method from three different Data Warehouse course class lecturers. The analysis carried out is to see an overview of the learning activities provided by each lecturer and their approach in directing students to interact with the material modules on ELING whether in the order in the Semester Learning Plan (RPS). We vary the dependency threshold to identify which learning modules have a higher level of dependency between events that are at the core of the course's learning. At a dependency threshold of 0.6, the number of activities from the model found for all lecturers was 21. While at the threshold of 0.8, the number of activities varies between 12 and 20. With dependency threshold variations, it will also identify which modules still appear that relate to the shape of the learning activity model and whether the resulting model matches the RPS sequence.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"9 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147976","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 Teknologi Blockchain dengan Sistem Smart Contract pada Klaim Asuransi","authors":"Baihaqsani, Arif Kusyanti, Primantara Hari Trisnawan","doi":"10.25126/jtiik.1078016","DOIUrl":"https://doi.org/10.25126/jtiik.1078016","url":null,"abstract":"Perkembangan sistem klaim pada asuransi di Indonesia umumnya masih menerapkan pengajuan klaim dengan menggunakan sistem secara manual dengan metode cashless dan reimbursement. Penerapan sistem klaim pada asuransi tersebut memiliki proses administrasi yang cukup panjang sehingga dapat memakan waktu yang lama dan penerapan sistem tersebut tidak dapat memberikan proses tranparansi transaksi pada klaim asuransi. Dengan permasalahan tersebut dapat menimbulkan permasalahan terkait dengan keamanan informasi berupa integritas data, kerahasiaan data, dan transparansi data pada klaim asuransi. Penelitian ini mengusulkan pengembangan sistem klaim pada asuransi yang dapat dilakukan secara online dengan menerapkan teknologi blockchain. Teknologi blockchain menggunakan sistem penyimpanan data dengan menerapkan sistem desentralisasi aplikasi yang berfungsi untuk memberikan kendali penuh terhadap pengguna atas data mereka dengan tidak adanya perantara terpusat. Dengan menerapkan desentralisasi aplikasi tersebut dapat diwujudkan integritas, kerahasiaan dan transparansi transaksi pada klaim asuransi. Penelitian ini mengajukan usulan implementasi teknologi blockchain dengan sistem smart contract pada proses klaim asuransi untuk dijadikan solusi terhadap masalah yang terdapat pada proses klaim asuransi.   Abstract The development of the insurance claim system in Indonesia generally still applies the submission of claims using a manual system with cashless and reimbursement methods. The application of the insurance claim system has a fairly long administrative process that can take a long time and the application of the system cannot provide a transparent transaction process for insurance claims. With these problems can cause problems related to information security in the form of data integrity, data confidentiality, and data transparency on insurance claims. This research proposes the development of an insurance claim system that can be done online by applying blockchain technology. Blockchain technology uses a data storage system by implementing a decentralized application system that functions to give users full control over their data in the absence of a centralized intermediary. By implementing a decentralized application, integrity, confidentiality and transaction transparency in insurance claims can be realized. This study proposes the implementation of blockchain technology with a smart contract system in the insurance claim process to be used as a solution to problems in the insurance claim process","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139142728","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":"Kombinasi Intent Classification dan Named Entity Recognition pada Data Berbahasa Indonesia dengan Metode Dual Intent and Entity Transformer","authors":"Zahrah Annisa, R. Perdana, Putra Pandu Adikara","doi":"10.25126/jtiik.1077985","DOIUrl":"https://doi.org/10.25126/jtiik.1077985","url":null,"abstract":"Pelayanan pelanggan atau customer service adalah sebuah bentuk upaya pemenuhan keinginan dan kebutuhan pelanggan yang disertai dengan ketepatan penyampaian sesuai standar perusahaan demi memenuhi harapan pelanggan. Pada beberapa kasus seperti layanan perbankan, diperlukan layanan pelanggan yang dapat diakses setiap saat dengan ketepatan dan daya tanggap tinggi. Atas kebutuhan pelayanan dengan kualitas tinggi ini, perusahaan dapat mengaplikasikan konsep pelayanan prima. Salah satu penerapan konsep kecerdasan buatan demi pelaksanaan pelayanan prima adalah penggunaan chatbot, yang memerlukan metode yang tepat bagi proses klasifikasi intensi pengguna maupun Named Entity Recognition (NER). Salah satu kekurangan dari pelaksanaan klasifikasi intensi dan NER secara terpisah terletak pada representasi numerik yang digunakan dalam tiap model. Meski menggunakan data latih dan arsitektur model yang serupa, model dapat menghasilkan representasi numerik yang berbeda dalam tahap fiturisasi, sehingga berpotensi mengurangi tingkat generalisasi model. Untuk mengatasi masalah tersebut, klasifikasi intensi dan NER dapat digabungkan dengan menggunakan mekanisme multi-task learning dalam bentuk model Dual Intent and Entity Transformer (DIET). Penelitian dilakukan dengan memanfaatkan data sekunder dari Helpdesk TIK UB, merancang model DIET menggunakan pustaka PyTorch dan Transformers, lalu mengevaluasi model DIET menggunakan f1-score. Kombinasi hyperparameter terbaik yang didapatkan adalah warm-up step sebesar 70, early stopping patience sebesar 15, weight decay sebesar 0,01, bobot loss NER sebesar 0,6, dan bobot loss klasifikasi intensi berupa 0,4. Kombinasi hyperparameter yang telah diperoleh menghasilkan kapabilitas yang berbeda apabila terdapat perubahan dalam data yang digunakan, karena kapabilitas model DIET baik dalam melakukan klasifikasi intensi maupun NER sangat bergantung terhadap data.   Abstract   Customer service is a way to fulfill the wants and needs of customers accompanied by the accuracy of delivery according to company standards in order to meet customer expectations. In some cases such as banking services, customer service is needed that can be accessed at any time with high accuracy and responsiveness. For this high-quality service requirement, companies can implement the concept of excellent service. One application of artificial intelligence for service excellence is the use of a chatbot, which requires an appropriate method for the classification of user intent and Named Entity Recognition (NER). One of the drawbacks of performing intent classification and NER separately lies in the different numerical representations used in each model. Despite using similar training data and model architecture, the models may produce different numerical representations in the featurization stage, potentially reducing the generalization ability of the model. To overcome this problem, intent and NER classification can be combined using a multi-task learning mec","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139144580","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":"Optimasi Weight AHP Menggunakan Genetic Algorithm untuk Rekomendasi Platform Media Sosial Sebagai Sarana Promosi Digital","authors":"Risqy Siwi Pradini, M. Anshori, M. Haris","doi":"10.25126/jtiik.1078011","DOIUrl":"https://doi.org/10.25126/jtiik.1078011","url":null,"abstract":"Tim pemasar suatu perusahaan dapat memanfaatkan media sosial untuk memperluas jangkauan pemasaran dan berinteraksi secara lebih intens dengan para pelanggan. Salah satu tantangan utama yang dihadapi tim pemasar untuk promosi digital adalah bagaimana memilih platform sosial media yang paling tepat agar dapat mencapai tujuan promosi yang optimal. Keputusan untuk memilih platform sosial media ini melibatkan sejumlah kriteria seperti content, impression, cost, look and feel, dan audience fit. Urutan rekomendasi platform media sosial sebagai sarana promosi yang dihasilkan penelitian ini adalah Facebook, Instagram, YouTube, Twitter, Pinterest, TikTok, dan LinkedIn. Urutan rekomendasi tersebut berhasil didapatkan dengan pendekatan optimasi weight Analytical Hierarchy Process (AHP) menggunakan Genetic Algorithm (GA) untuk rekomendasi platform media sosial sebagai sarana promosi digital. Optimasi yang dilakukan terbukti dapat meningkatkan keakurasian peringkat dari 95% ke 97% yang dihasilkan melalui perhitungan fitness yang menggunakan rumus Spearman Correlation. Penelitian ini juga berhasil menarik kesimpulan terkait bidang AHP-GA yang menyatakan bahwa popsize mempengaruhi nilai fitness. Semakin tinggi popsize, maka semakin besar potensi nilai fitness yang dihasilkan, namun peningkatan popsize itu sendiri tidak menjamin perolehan nilai fitness yang lebih baik sehingga perlu memikirkan faktor lainnya pula. Selain itu, semakin banyaknya jumlah generasi maka proses evolusi akan semakin sering terjadi. Tiap generasinya akan melakukan crossover dan mutasi, sehingga hal ini berpengaruh pada semakin beragamnya individu yang dihasilkan dan pada akhirnya dapat membantu menemukan solusi yang lebih baik.   Abstract A company's marketing team can use social media to expand marketing reach and interact more intensely with customers. One of the main challenges faced by marketers for digital promotion is how to choose the most appropriate social media platforms to achieve optimal promotional goals. The decision to choose a social media platform involves several criteria such as content, impression, cost, look and feel, and audience fit. The order of recommendations for social media platforms as a means of promotion resulting from this research are Facebook, Instagram, YouTube, Twitter, Pinterest, TikTok, and LinkedIn. The sequence of recommendations was successfully obtained using the weight Analytical Hierarchy Process (AHP) optimization approach using Genetic Algorithm (GA) for social media platform recommendations as a means of digital promotion. The optimization carried out was proven to increase ranking accuracy from 95% to 97% which was produced through fitness calculations using the Spearman Correlation formula. This study also succeeded in drawing conclusions related to the AHP-GA field which stated that popsize affects fitness values. The higher the popsize, the greater the potential fitness value generated, however increasing the popsize itself does not guar","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"34 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147238","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 Decision Tree dan Random Forest dalam Deteksi Tingkat Stres Manusia Berdasarkan Kondisi Tidur","authors":"Sza Sza Amulya Larasati, Elok Nuraida Kusuma Dewi, Brahma Hanif Farhansyah, F. Bachtiar, F. Pradana","doi":"10.25126/jtiik.1077993","DOIUrl":"https://doi.org/10.25126/jtiik.1077993","url":null,"abstract":"Masalah kesehatan mental menjadi isu global yang sangat umum terjadi, termasuk perubahan suasana hati, perbedaan kepribadian, ketidakmampuan mengatasi masalah, serta mengisolasi diri dari keramaian. Berdasarkan data dari World Health Organization (WHO), gangguan kecemasan dan stres menjadi gangguan mental yang paling sering terjadi dari 970 juta kasus yang dilaporkan sepanjang tahun 2019. Stres telah banyak dikaitkan dengan tidur. Penelitian ini akan mengungkap hubungan kondisi tidur pada manusia dengan tingkat stres yang sedang diderita dengan 5 tingkatan: normal, stres ringan, stres sedang, stres tinggi, stres sangat tinggi. Data yang digunakan merupakan data kontinyu dengan 8 fitur: ‘sr’ (snoring rate), ‘rr’ (respiration rate), ‘t’ (body temperature), ‘lm’ (limb movement), ‘bo’ (blood oxygen), ‘rem’ (rapid eye movement), ‘sh’ (sleeping hours), dan ‘hr’ (heart rate). Setiap fitur memiliki rentang nilai yang tidak sama, sehingga dilakukan normalisasi untuk menyeragamkan rentang tersebut. Hyperparameter tuning dilakukan dengan teknik k-fold cross validation dan model dirancang dengan algoritma klasifikasi Decision Tree serta Random Forest. Hasilnya, 5 fitur: tingkat mendengkur, laju respirasi, pergerakan anggota tubuh termasuk bola mata, serta detak jantung saat tidur berbanding lurus dengan tingkat stres. Semakin tinggi nilai kelima fitur tersebut mengindikasikan tingkat stres yang lebih tinggi. Sedangkan dengan 3 fitur lainnya: suhu tubuh, kadar oksigen, dan waktu tidur memberikan hasil sebaliknya. Dengan kata lain, ketiga nilai tersebut berbanding terbalik dengan tingkat stres yang diderita. Model Decision Tree memiliki akurasi 0,99 dan Random Forest memiliki akurasi 1,0. Hasil penelitian ini diharapkan dapat memberikan insight bagi peneliti lain pada bidang yang sama dan dapat menjadi acuan dalam mendeteksi stres yang sedang diderita.       Abstract Stress is often associated with sleep. This research aims to uncover the relationship between human sleep conditions and the level of stress experienced, categorized into five levels: not stressed, very mildly stressed, mildly stressed, highly stressed, and very highly stressed. The data used consists of continuous data with eight features: 'snoring rate' (snoring rate), 'respiration rate' (respiration rate), 'body temperature' (body temperature), 'limb movement' (limb movement), 'blood oxygen' (blood oxygen), 'rapid eye movement' (rapid eye movement), 'sleep hours' (sleep hours), and 'heart rate' (heart rate). Each feature has a different value range, so normalization is performed to standardize these ranges. Hyperparameter tuning is done using k-fold cross-validation, and the model is designed using the Decision Tree and Random Forest classification algorithms. The results show that five features: snoring rate, respiration rate, limb movement including eye movement, and heart rate during sleep are directly proportional to the level of stress. Higher values for these five features indicate higher","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"6 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147247","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":"Klasifikasi Intensi dengan Metode Ling Short-Term Memory pada Chatbot Bahasa Indonesia","authors":"Faiz Aulia Al Farisi, R. Perdana, Putra Pandu Adikara","doi":"10.25126/jtiik.1078000","DOIUrl":"https://doi.org/10.25126/jtiik.1078000","url":null,"abstract":"E-government merupakan sebuah konsep pemerintahan yang menyelenggarakan layanan publik secara digital yang didukung oleh teknologi informasi, sehingga menjadi lebih prima. Salah satu bentuk layanan publik digital yang umum ada di berbagai sektor adalah helpdesk. Helpdesk memungkinkan pengguna dapat bertanya atau melaporkan sesuatu untuk kemudian dijawab oleh staf. Permasalahan yang ada adalah ketersediaan staf yang hanya dapat menjawab pada jam kerja, sedangkan pengguna bisa jadi menemukan permasalahan yang urgent di luar jam kerja. Oleh karena itu, solusi yang ditawarkan adalah penerapan chatbot, sehingga dapat melayani kapan pun, sekaligus meringankan kerja dari staf. Penelitian ini mencoba untuk merancang salah satu komponen pada chatbot, yaitu model klasifikasi intensi, dengan metode Long Short-Term Memory. Data yang digunakan merupakan 501 teks riwayat pertanyaan dari database Helpdesk TIK UB yang termasuk ke dalam 7 kelas intensi yang ditentukan. Data akan melalui beberapa tahap prapemrosesan sebelum kemudian dilakukan pemodelan dan beberapa pengujian. Tahap pengujian meliputi pemilihan embedding yang digunakan, pemilihan teknik augmentasi data, dan penyetelan hyperparameter. Hasil dari keseluruhan pengujian, didapatkan model terbaik yang mampu menghasilkan akurasi sempurna untuk data latih dan data uji, serta loss 0,004 untuk data latih dan 0,044 untuk data uji.   Abstract   E-government is a government concept that organizes digital public services supported by information technology, so that they become more excellent. One form of digital public service that is common in various sectors is the helpdesk. Helpdesk allows users to ask questions or report something to be answered by staff. The problem that exists is the availability of staff who can only answer during working hours, while users may find urgent problems outside of working hours. Therefore, the solution offered is the implementation of a chatbot, so that it can serve at any time, while easing the work of staff. This study attempts to design one of the components of the chatbot, namely the intention classification model, using the Long Short-Term Memory method. The data used are 501 question history texts from the Helpdesk TIK UB database which fall into the 7 specified intensity classes. The data will go through several pre-processing stages before then being modeled and tested. The testing phase includes selecting the embedding used, data augmentation techniques selection, and hyperparameter tuning. The best model is obtained which can produce perfect accuracy for training data and test data, as well as a loss of 0.004 for training data and 0.044 for test data.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"28 51","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147446","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":"Redesain Aplikasi Mobile Supervisi Observasi Kelas untuk Meningkatkan Tingkat Usability","authors":"Muhammad Ifa Amrillah, Retno Indah Rokhmawati, F. Bachtiar","doi":"10.25126/jtiik.1078006","DOIUrl":"https://doi.org/10.25126/jtiik.1078006","url":null,"abstract":"Aplikasi LESON, yang kini berganti nama menjadi EDVISOR merupakan aplikasi berbasis mobile yang dikhususkan untuk merekam suasana pembelajaran dan mendukung kegiatan supervisi observasi kelas. Meskipun telah mengalami pembaharuan, pada penelitian sebelumnya mengungkapkan masih terdapat 24 permasalahan pada aplikasi yang perlu perbaikan dan pengembangan lebih lanjut. Metode Usability Testing dipilih untuk dapat mengidentifikasi permasalahan secara lebih mendalam dan memahami pengalaman pengguna dalam menggunakan aplikasi. Penelitian ini melibatkan 10 Mahasiswa dan 3 Dosen yang diberikan tugas khusus untuk menguji aplikasi. Pengujian dilakukan sebanyak 2 kali, yaitu sebelum dan setelah dilakukan perbaikan desain. Hasil observasi dan wawancara pada pengujian awal mengungkapkan adanya 42 permasalahan baru, yang kemudian menjadi dasar rekomendasi perbaikan desain. Perbaikan desain menghasilkan prototype yang mendekati hasil akhir dari aplikasi. Setelah perbaikan desain, prototype diuji kembali kepada pengguna yang sama dengan pengujian awal. Hasil pengujian menunjukkan peningkatan usability aplikasi, dengan peningkatan completion rate sebesar 13,19%, peningkatan efficiency sebesar 0,016 goals/sec, dan peningkatan satisfaction sebesar 1,21.   Abstract   The LESON application, now renamed EDVISOR, is a mobile-based application devoted to recording the learning atmosphere and supporting classroom observation supervision activities. Although it has undergone updates, previous research revealed that there are still 24 problems in the application that need further improvement and development. Usability Testing method was chosen to be able to identify problems more deeply and understand the user experience in using the application. This research involved 10 students and 3 lecturers who were given a special task to test the application. Testing was carried out twice, namely before and after design improvements were made. The results of observations and interviews in the initial test revealed 42 new problems, which then became the basis for recommendations for design improvements. Design improvements resulted in a prototype that was close to the final result of the application. After the design improvements, the prototype was tested again with the same users as the initial test. The test results showed an increase in application usability, with an increase in completion rate of 13.19%, an increase in efficiency of 0.016 goals/sec, and an increase in satisfaction of 1.21.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139144431","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":"Perencanaan Strategis Sistem Informasi Pada Lembaga Amil Zakat Menggunakan Analisis SWOT Berbasis Lima Faktor Seni Perang Sun Tzu Berdasarkan Anita Cassidy","authors":"Ucky Pradestha Novettralita, R. Rizal Isnanto, Catur Edi Widodo","doi":"10.25126/jtiik.20231057222","DOIUrl":"https://doi.org/10.25126/jtiik.20231057222","url":null,"abstract":"Lembaga Amil Zakat (LAZ) memanfaatkan strategi Sistem Informasi/Teknologi Informasi (SI/TI) untuk meningkatkan daya saing. Seni Perang Sun Tzu telah banyak digunakan dalam penelitian untuk menyusun strategi bisnis dan strategi penjualan. Sayangnya, belum ada penelitian dengan menggunakan Seni Perang Sun Tzu untuk perencanaan strategis Sistem Informasi (SI). Kontribusi penelitian adalah penyusunan analisis SWOT berbasis lima faktor Seni Perang Sun Tzu sehingga dapat menjadi dasar untuk penelitian selanjutnya. Tujuan dari penelitian ini adalah untuk mengidentifikasikan kondisi lingkungan internal bisnis dan eksternal bisnis sehingga memberikan rekomendasi strategi kunci kepada LAZ dalam domain strategi bisnis, strategi SI/TI, dan strategi infrastruktur SI/TI berdasarkan analisis SWOT berbasis lima faktor Seni Perang Sun Tzu yang disusun berdasarkan metode Anita Cassidy. Beberapa strategi kunci yang dihasilkan dari peneitian ini adalah promosi dan edukasi zakat melalui media sosial dan media daring lainnya; menyediakan teknologi untuk memudahkan masyarakat membayar zakat dengan membuat aplikasi seperti Mobile Zakat, Customer Relationship System (CRS); dan mengembangkan kemampuan dalam memanfaatkan teknologi 5G dan teknologi baru. Abstract Amil Zakat Institution (LAZ) uses Information System/Information Technology (IS/TI) strategy to improve competitiveness. Sun Tzu's Art of War has been widely used in research to develop business strategies and sales strategies. Unfortunately, there has been no research using Sun Tzu's Art of War for Information System (IS) strategic planning. The contribution of the research is the preparation of a SWOT analysis based on the five factors of Sun Tzu's Art of War so that it can be the basis for future research. This research aims to identify the condition of the internal business and external business environment to provide key strategy recommendations to LAZ in the domains of business strategy, SI/TI strategy, and SI/TI infrastructure strategy based on SWOT analysis based on five factors Sun Tzu's Art of War compiled based on the Anita Cassidy method. Some of the key strategies obtained from this research are the promotion and education of zakat through social media and other online media; providing technology to make it easier for people to pay zakat by creating applications like Mobile Zakat application, Customer Relationship System (CRS); and developing capabilities in utilizing 5G technology and new technologies.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"25 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136067590","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 Identifikasi Kesehatan Berdasarkan Detak Jantung, Kadar Oksigen, dan Suhu Tubuh Menggunakan Metode Fuzzy Mamdani","authors":"Arsal Wildan Naviaddin, Barlian Henryranu Prasetio, Rakhmadhany Primananda","doi":"10.25126/jtiik.20231056956","DOIUrl":"https://doi.org/10.25126/jtiik.20231056956","url":null,"abstract":"Kesehatan merupakan faktor penting dalam kehidupan manusia. Oleh karena itu, dalam paper ini kami menawarkan pendekatan efektif dan efisien dalam mendeteksi dini kesehatan. Deteksi dini dapat menghindari berbagai faktor risiko penyakit dan dapat terhindar dari komplikasi, serta menghemat biaya pengobatan. Sebagian besar alat deteksi kesehatan menggunakan metode invasif, sementara sistem kami menggunakan pendekatan contactless. Sensor pulse Oximater MAX30100 dan sensor suhu MLX90614 digunakan untuk mengukur tingkat saturasi oksigen, detak jantung dan suhu tubuh. Kemudian, kedua data sensor tersebut dikirim ke Google Firebase dengan memanfaatkan fitur layanan realtime database sehingga data dapat ditampilkan secara langsung di aplikasi android. Kedua sensor dihubungkan pada mikrokontroler NodeMCU ESP8266, lalu data hasil pengukuran sensor beserta perhitungan fuzzy dikirim ke database Firebase agar dapat ditampilkan pada smartphone. Hasil dari penelitian ini adalah akurasi pembacaan sensor suhu MLX90614 dan pulse oximater MAX30100 dibandingkan alat yang sudah ada didapatkan pengukuran suhu mendapatkan nilai MAPE sebesar 0.964 %, pengukuran saturasi mendapatkan nilai MAPE 0 %, dan pengukuran detak jantung didapatkan MAPE 1.581 %. Dari ketiga pengukuran didapatkan nilai MAPE dibawah 10% sehingga dapat dikategorikan pengukuran akurat dan kinerja metode fuzzy mamdani dalam mengklasifikasikan kondisi kesehatan sangat baik dan akurat. Abstract Health is an important factor in human life. Therefore, in this paper we offer an effective and efficient approach in early detection of health. Early detection can avoid various risk factors for disease and can avoid complications, as well as save on medical costs. Most medical detection systems use invasive methods, while our system uses a contactless approach. The MAX30100 Oximater pulse sensor and MLX90614 temperature sensor are used to measure oxygen saturation level, heart rate and body temperature. Then, the two-sensor data are sent to Google Firebase by utilizing the real-time database service feature so that the data can be displayed directly in the Android application. The two sensors are connected to the NodeMCU ESP8266 microcontroller, then the sensor measurement results data along with the fuzzy calculations are sent to the Firebase database so that they can be displayed on a smartphone. The results of this study are the accuracy of the readings of the MLX90614 temperature sensor and the MAX30100 pulse oximeter compared to existing devices, the temperature measurement gets a MAPE value of 0.964 %, the saturation measurement gets a MAPE value of 0 %, and the heart rate measurement gets a MAPE of 1.581 %. From the three measurements, the MAPE value was below 10% so that it could be categorized as an accurate measurement and the performance of the Mamdani fuzzy method in classifying health conditions was very good and accurate.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"51 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136104798","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 Algoritma AES 256 CBC, BASE 64, Dan SHA 256 dalam Pengamanan dan Validasi Data Ujian Online","authors":"Ferzha Putra Utama, Gusman Wijaya, Ruvita Faurina, Arie Vatresia","doi":"10.25126/jtiik.20231056558","DOIUrl":"https://doi.org/10.25126/jtiik.20231056558","url":null,"abstract":"Terdapat berbagai macam cara untuk melaksanakan ujian di tingkat perguruan tinggi, selama masa pandemi Covid-19 metode ujian online menjadi banyak digunakan. Meskipun ujian online dapat dilaksanakan di mana saja dan kapan saja, sayangnya masih banyak terjadi kecurangan seperti bocornya soal ujian, tersebarnya kunci jawaban secara ilegal, dan pengubahan pada data hasil ujian. Salah satu solusi dalam menjaga integritas hasil ujian berbasis online adalah mengenkripsi data ujian dengan metode kriptografi. Penelitian ini mengusulkan menerapkan beberapa metode kriptografi sebagai upaya dalam mengamankan dan memastikan keaslian data ujian online menggunakan algoritma AES 256 CBC, Base 64, dan SHA 256. Penelitian ini menghasilkan aplikasi ujian online berbasis website yang dibangun menggunakan teknologi MERN Stack. Hasil pengujian dalam memvalidasi data ujian online yang telah dienkripsi menggunakan sistem dan OpenSSL menunjukkan nilai hash yang sama. Hal ini menunjukkan sistem telah mampu mengenkripsi, mendekripsi, dan memvalidasi data ujian online dengan efektif. Abstract There are various ways to organize exams at the higher education level. During the Covid-19 pandemic, the online examination method has become widely used. Although online exams can be held anywhere and anytime, unfortunately, many violations and fraud exist, such as leaking exam questions, spreading answer keys illegally, and changing exam result data. One solution for maintaining the integrity of online-based exam results is to encrypt exam data with cryptographic methods. This study proposes applying several cryptographic methods to secure and ensure the authenticity of online exam data using AES 256 CBC, Base 64, and SHA 256 algorithms. This research resulted in a website-based online exam application built using MERN Stack technology. The test results in validating online exam data that has been encrypted using the system and OpenSSL show the same hash value. This shows that the system has been able to encrypt, decrypt, and validate online exam data effectively.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135781414","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}