Jurnal Teknologi Informasi dan Ilmu Komputer最新文献

{"title":"Perancangan Arsitektur Sistem dan Teknologi Informasi Menggunakan TOGAF ADM (Studi Kasus Kantor Pertanahan ABC)","authors":"Indah Dewi Murti Suyoto, Indra Indra, Surya Wedi, Kurnia Setiawan","doi":"10.25126/jtiik.20241046220","DOIUrl":"https://doi.org/10.25126/jtiik.20241046220","url":null,"abstract":"Dalam rangka mewujudkan visi dan misi Kantor Pertanahan ABC dalam penataan ruang dan pengelolaan pertanahan yang terpercaya melayani masyarakat, perlu untuk dapat memahami permasalahan yang dihadapi agar dapat mencapai tujuannya. Meningkatkan kualitas layanan publik dan memberikan kemudahan pelayanan kepada masyarakat adalah inovasi yang terus menerus dilakukan oleh Kantor Pertanahan. Salah satu permasalahan yang dihadapi, bagaimana meningkatkan pelayanan dengan memberikan ketepatan dan kecepatan waktu dalam pengurusan sertipikat. Minimnya pemahaman masyarakat terkait prosedur pengurusan sertifikat secara mandiri menjadi salah satu kendala yang dihadapi dalam pelayanan sertipikat. Menanggapi permasalahan tersebut perlu memahami kebutuhan untuk membangun suatu perancangan arsitektur sistem dan teknologi informasi agar Kantor Pertanahan ABC dapat mewujudkan pengelolaan pertanahan yang terpercaya dalam melayani masyarakat. Penelitian ini diharapkan dapat menghasilkan Enterprise Architecture (EA) Layanan Pengurusan Sertifikat Tanah yang Terintegrasi menggunakan framework TOGAF ADM yang dapat menguraikan proses bisnis dan kebutuhan sistem dalam rangka pencapaian visi dan misi yang akan diwujudkan melalui perancangan arsitektur bisnis, sistem informasi dan teknologi informasi pada Kantor Pertanahan ABC.AbstractIn order to realize the vision and mission of the ABC Land Office in spatial planning and land management that is trusted to serve the community, it is necessary to be able to understand the problems faced in order to achieve its goals. Improving the quality of public services and providing ease of service to the community is an innovation that is continuously carried out by the Land Office. One of the problems faced is how to improve services by providing accuracy and timeliness in managing certificates. The lack of public understanding regarding the procedures for administering certificates independently is one of the obstacles faced in certificate services. Responding to these problems, it is necessary to understand the need to build a system architecture design and information technology so that the ABC Land Office can realize reliable land management in serving the community. This research is expected to produce an Enterprise Architecture (EA) Integrated Land Certificate Management Service using the TOGAF ADM framework which can describe business processes and system requirements in order to achieve the vision and mission that will be realized through the design of business architecture, information systems and information technology at the Land Office ABC.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48618125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Kualitatif Elemen Gamifikasi dalam Games Berbasis ICT untuk Anak Usia Dini","authors":"Rimantoko Aditya, Aldilla Iradianty, Nyoman Darma Kotama","doi":"10.25126/jtiik.20241046285","DOIUrl":"https://doi.org/10.25126/jtiik.20241046285","url":null,"abstract":"Pembelajaran berbasis gamifikasi menghadirkan pengalaman baru bagi peserta didik. Tren penggunaan pendekatan gamifikasi ini semakin diminati di semua level pendidikan, terutama untuk level pendidikan anak usia dini. Penelitian ini bertujuan untuk mengidentifikasi elemen gamifikasi yang paling relevan dalam lingkungan pendidikan anak usia dini (PAUD) melalui kegiatan Focus Group Discussion (FGD) bersama guru PAUD di Indonesia. Hasil analisis temuan menunjukkan bahwa guru PAUD memiliki persepsi dan preferensi positif terhadap pembelajaran PAUD berbasis gamifikasi. Selain itu, hasil penelitian juga mengkonfirmasi bahwa terdapat sembilan elemen gamifikasi yang cocok untuk diterapkan pada pembelajaran berbasis gamifikasi di lingkungan PAUD, yaitu poin dan penghargaan, papan peringkat, lencana, tantangan, levelisasi, penanda progres, avatar, mata uang, dan kejutan. Hasil penelitian ini dapat menjadi dasar untuk penelitian masa depan dalam kaitannya dengan pengembangan prototipe sistem pembelajaran PAUD berbasis gamifikasi dengan fokus pada interaksi, pemberian penghargaan, pemecahan masalah, dan pemberian tantangan. AbstractGame-based learning brings new experiences for students. The trend of using the gamification approach is increasingly in demand at all levels of education, especially for early childhood education. This study aims to identify the most relevant gamification elements in early childhood education through Focus Group Discussion activities with early childhood teachers in Indonesia. The results of the analysis of the findings indicate that teachers have positive perceptions and preferences toward game-based learning in early childhood education. In addition, the results also confirm that there are nine elements of gamification that are suitable to be applied to in the early childhood environment, namely points and rewards, leaderboards, badges, challenges, leveling, progress bar, avatars, currency, and surprises. The results of this study can be used as the basis for further research in relation to developing a prototype of a game-based learning system in early childhood education with a focus on interaction, rewarding, problem solving, and challenges.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46677331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Efek Augmentasi Dataset dan Fine Tune pada Algoritma Pre-Trained Convolutional Neural Network (CNN)","authors":"T. B. Sasongko, Haryoko Haryoko, Agit Amrullah","doi":"10.25126/jtiik.20241046583","DOIUrl":"https://doi.org/10.25126/jtiik.20241046583","url":null,"abstract":"Kemajuan teknologi deep learning seringkali berbanding lurus dengan keterkaitan metode yang dapat diandalkan dalam penggunaan jumlah data yang besar. Convolutional Neural Network (CNN) adalah salah satu algoritma deep learning yang paling popular saat ini guna pengolahan citra. Pada era deep learning model CNN yang kompleks seperti saat ini memiliki tantangan-tantangan yang baru baik gradient vanishing, overfitting yang dikarenakan keterbatasan dataset, optimasi parameter hingga keterbatasan perangkat keras. Penelitian ini bertujuan mengukur pengaruh teknik fine tuning dan augmentasi dataset pada model transfer learning CNN Mobilenet, Efficientnet, dan Nasnetmobile dengan dataset yang variasi jumlah dataset yang memiliki jumlah yang terbatas. Pada hasil dari penelitian ini, dari ketiga dataset yang digunakan sebagai dalam melakukan training pada model efisien transfer learning baik MobileNet, EfficientNet, dan NasNetmobile, teknik augmentasi zoom range ataupun random erase dapat meningkatkan akurasi pada dataset dengan jumlah 56 citra dan 222 citra, sedangkan pada dataset dengan jumlah 500 data citra, semua teknik augmentasi terbukti dapat meningkatkan akurasi pada model arsitektur MobileNetV2 dan NasNetMobile. Sedangkan teknik fine tuning terbukti efektif dalam meningkatkan akurasi pada semua skala data yang kecil. AbstractToday deep learning technology is often associated with reliable processes (methods) when we have large amounts of data. In deep learning CNN (Convolutional Neural Network) plays a very important role which is often used to analyze (classify or recognize) visual images. In the era of deep learning models such as the complex Convolutional Neural Network (CNN) as it is today, it has new challenges such as gradient vanishing, overfitting due to dataset limitations, parameter optimization to hardware limitations. The MobileNet architecture was coined in 2017 by Howards, et al, which is one of the convolutional neural networks (CNN) architectures that can be used to overcome the need for excessive computing resources. This study aims to measure the effect of fine tune and dataset augmentation techniques on CNN mobilenet, efficientnet, and nasnetmobile transfer learning models with very small datasets. The results of this study are that of the three datasets used as the basis for training in efficient transfer learning models (mobilenet, efficientnet, and nasnetmobile), random erase and zoom range augmentation techniques dominate the increase in model accuracy. The amount of increase in accuracy after random erase or zoom range augmentation that occurs is about 0.03% to 0.1%.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41720294","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 Rute Rencana Perjalanan Pesawat Menggunakan Algoritma Late Acceptance Hill Climbing (Studi Kasus : Travelling Salesman Challenge 2.0)","authors":"Ahmad Muklason, I. Gusti, Agung Premananda","doi":"10.25126/jtiik.20241046842","DOIUrl":"https://doi.org/10.25126/jtiik.20241046842","url":null,"abstract":"Permasalahan Traveling Salesman Problem (TSP) merupakan permasalahan klasik yang popular diteliti dalam bidang optimasi kombinatorika. Permasalahan ini bertujuan menentukan rute perjalanan terpendek untuk  mengunjungi setiap lokasi tepat satu kali dan diakhir perjalanan harus kembali ke lokasi awal perjalanan dimulai. Permasalahan ini telah digolongkan sebagai permasalahan NP-Hard, sehingga membutuhkan algoritma non-deterministic untuk dapat menyelesaikan permasalahan ini. Dalam permasalahan nyata, salah satu penerapan TSP ada pada permasalahan untuk menentukan rute perjalanan termurah untuk mengunjungi beberapa kota di beberapa negara. Kompetisi Travelling Salesman Challenge 2.0 (TSC 2.0) mengangkat permasalahan ini dalam sebuah kompetisi pada tahun 2018. Untuk menyelesaikan studi kasus tersebut, penelitian ini menyembangkan algoritma Late Acceptance Hill Climbing (LAHC) menggunakan metode hiper-heuristik. Algoritma LAHC merupakan algoritma yang sederhana namun telah terbukti mampu mengoptimasi dengan baik pada beberapa permasalahan TSP. Algoritma LAHC diuji coba pada 14 dataset dari TSC 2.0. Hasil penelitian menunjukan algoritma LAHC menghasilkan solusi yang kompetitif dengan mampu menurunkan biaya perjalanan dengan rata-rata 58% dan menghasilkan hasil yang lebih baik dengan rata-rata 9% dari algoritma Threshold Acceptance (TA) yang digunakan sebagai algoritma pembanding. AbstractThe Traveling Salesman Problem (TSP) is a classic problem that is popularly researched in the field of combinatorics optimization. This problem aims to determine the shortest travel route to visit each location exactly once and, at the end of the trip, must return to where the trip started. This problem has been classified as an NP-Hard problem. Therefore it requires a non-deterministic algorithm to solve it. In the real world, one of the applications of TSP is the problem of determining the cheapest travel routes to visit several cities in several countries. The Traveling Salesman Challenge 2.0 (TSC 2.0) competition raised this issue in a competition in 2018. This study developed the Late Acceptance Hill Climbing (LAHC) algorithm using the hyper-heuristic method to complete the case study from TSC 2.0. The LAHC algorithm is simple but has been proven to optimize well for several TSP problems. The LAHC algorithm was tested on 14 datasets from TSC 2.0. The results show that the LAHC algorithm produces competitive solutions by reducing travel costs by an average of 58% and making better results by an average of 9% than the Threshold Acceptance (TA) algorithm used as a comparison algorithm.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44388568","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":"Peningkatan Performa Ensemble Learning pada Segmentasi Semantik Gambar dengan Teknik Oversampling untuk Class Imbalance","authors":"Arie Nugroho, M. A. Soeleman, R. A. Pramunendar, Affandy Affandy, Aris Nurhindarto","doi":"10.25126/jtiik.20241046831","DOIUrl":"https://doi.org/10.25126/jtiik.20241046831","url":null,"abstract":"Perkembangan teknologi dan gaya hidup manusia yang semakin tinggi menghasilkan data-data yang berlimpah. Data-data tersebut dapat berbentuk data yang terstruktur dan tidak terstruktur. Data gambar termasuk dalam data yang tidak terstruktur. Aktifitas dan objek yang terekam dalam suatu gambar beraneka ragam. Secara normal, mata manusia dapat dengan mudah membedakan antara foreground dan background dari suatu gambar, tetapi komputer membutuhkan pembelajaran dalam membedakan keduanya. Segmentasi gambar adalah salah satu bidang dalam computer vision yang membahas bagaimana cara komputer mempelajari dan mengenali segmen dari suatu gambar sesuai label yang ditentukan. Dalam kenyataannya banyak data yang mempunyai class atau label yang tidak seimbang, tentunya akan mempengaruhi tingkat akurasi dari suatu prediksi. Dalam riset ini membahas bagaimana meningkatkan akurasi segmentasi semantik gambar pada metode ensemble learning untuk menangani masalah data yang tidak seimbang dalam segmentasi gambar. Teknik yang digunakan adalah sintetis oversampling sehingga menghasilkan data yang seimbang dan akurasi yang tinggi. Metode ensemble learning yang digunakan adalah Random Forest dan Light Gradien Boosting Machine (LGBM). Dengan menggunakan dataset Penn-Fudan Database for Pedestrian yang mengandung imbalanced class. Penggunaan teknik sintetis oversampling dapat memperbaikki tingkat akurasi pada class minoritas. Pada algoritma random forest mengalami peningkatan akurasi sebesar 37 % sedangkan pada algoritma LGBM meningkat sebesar 41 %. AbstractThe development of technology and the increasingly high lifestyle of humans produce abundant data. These data can be in the form of structured and unstructured data. Image data is included in unstructured data. The activities and objects recorded in a picture are varied. Normally, the human eye can easily distinguish between the foreground and background of an image, but computers need learning to distinguish between the two. Image segmentation is one of the fields in computer vision that discusses how computers learn and recognize segments of an image according to specified labels. In reality, a lot of data has unbalanced classes or labels, of course, it will affect the accuracy of a prediction. This research discusses how to improve the accuracy of image semantic segmentation in the ensemble learning method to deal with the problem of unbalanced data in image segmentation. The technique used is synthetic oversampling so as to produce balanced data and high accuracy. The ensemble learning methods used are Random Forest and Light Gradient Boosting Machine (LGBM). By using the Penn-Fudan Database for Pedestrian dataset which contains a imbalanced class. The use of synthetic oversampling techniques can improve the level of accuracy in minority classes. The random forest algorithm experienced an increase in accuracy by 37% while the LGBM algorithm increased by 41%.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41572789","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 Deteksi Dini Penyakit Preeklampsia Melalui Perubahan Warna Urine Berdasarkan Protein dengan Menggunakan Metode Naïve Bayes Classifier","authors":"Fakhrul Allaam, Barlian Henryranu Prasetio, Rizal Maulana","doi":"10.25126/jtiik.20241046908","DOIUrl":"https://doi.org/10.25126/jtiik.20241046908","url":null,"abstract":"Umumnya preeklamsia adalah penyakit komplikasi yang sering dialami pada ibu hamil.Penyakit ini terjadi dikarenakan adanya tekanan darah tinggi, tanpa edema atau bengkak dan disertai protein dalam urin (proteinuria).Kondisi ini kebanyakan dapat terjadi pada usia kehamilan timester 2 dan trimester 3 atau lebih dari 20 minggu. Ada beberapa teknik untuk mengetahui penyakit tersebut,salah satunya dengan dengan melihat kondisi urin. Namun, ketika penentuan status urin secara manual, sering mengalami kesalahan, karena proses diagnosis hanya menggunakan kasat mata sebagai indikator utama. Oleh karena itu, sistem diagnosa otomatis diperlukan untuk mengurangi kesalahan manusia dan memastikan bahwa pasien menerima perawatan yang mereka butuhkan. Informasi fitur warna diperoleh menggunakan sensor TCS 34725 untuk eksperimen ini. Ada tiga keadaan urin berbeda yang diidentifikasi dan diberi label sebagai Urine Normal, Urine Preeklampsia 1, dan Urine Preeklampsia 2. Titik referensi ditemukan sebagai Urine Normal. Proses klasifikasi menggunakan metode Naive Bayes yang merupakan salah bidang ilmu pengetahuan pola.Metode ini digunakan karena memberikan kemudahan implementasi dan komputasi yang cepat agar prediksi real-time dapat dilakukan.AbstractGenerally, preeclampsia is a complication disease that is often experienced by pregnant women. This disease occurs due to high blood pressure, without edema or swelling and accompanied by protein in the urine (proteinuria). This condition can usually occur in the 2nd and 3rd trimester of pregnancy or later 20 weeks. There are several ways to find out the disease, one of which is by looking at the condition of the urine. However, in the process of determining the condition of the urine manually, errors often occur because the analysis process only uses the naked eye as the main parameter. Therefore, a tool that can perform automatic analysis is needed to minimize errors in the process and take action on patients. This study uses a TCS 34725 sensor to perform feature extraction in the form of color. Urine conditions are divided into three classes, namely Normal Urine, Preeclampsia 1 Urine and Preeclampsia Urine 2. The classification process uses the Naive Bayes method which is one of the fields of pattern science. This method is used because it provides easy implementation and fast computation so that real-time predictions can be made.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42643028","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 Pendeteksi Sleep-Disordered Breathing Berdasarkan High dan Low Frequency Menggunakan Metode Naïve Bayes","authors":"A. Ghifari, E. R. Widasari","doi":"10.25126/jtiik.20241046913","DOIUrl":"https://doi.org/10.25126/jtiik.20241046913","url":null,"abstract":"Tidur merupakan aktivitas dimana otak memberikan tubuh waktu istirahat secara total. Kualitas tidur penting untuk menjaga kondisi fisik maupun mental seseorang. Buruknya kualitas tidur disebabkan oleh gangguan tidur. Gangguan tidur yang paling umum terjadi adalah Sleep-disordered Breathing (SDB) atau Sleep Apnea, dimana penderitanya akan mengalami henti napas secara berulang saat tertidur. Sleep Apnea dikategorikan menjadi 2, yaitu Obstructive Sleep Apnea (OSA) dan Central Sleep Apnea (CSA). Diagnosis gangguan tidur dilakukan dengan Polysomnography yang cenderung mahal dan kurang nyaman. Hasil Polysomnography juga tidak dapat langsung digunakan oleh dokter untuk evaluasi lebih lanjut. Oleh karena itu, pada penelitian ini dibuat sistem pendeteksi gangguan tidur ke dalam kelas Normal, OSA, atau CSA menggunakan sinyal Electrocardiography (ECG) yang diakuisisi dengan teknik 3-lead placement. Sistem ini menggunakan sensor AD8232 dalam mengakuisisi sinyal jantung yang akan diproses oleh Arduino Mega 2560 untuk mendapatkan fitur High dan Low Frequency dari sinyal yang kemudian digunakan untuk klasifikasi. Sistem ini memiliki akurasi sebesar 85% dalam melakukan klasifikasi SDB menggunakan metode Naïve Bayes dengan rata-rata waktu komputasi sebesar 12ms. Sistem ini dapat digunakan di rumah karena bersifat portable dan datanya dapat langsung diunduh melalui websiteuntuk evaluasi dokter, sehingga membuat pasien merasa lebih nyaman dan efisien dalam melakukan diagnosis dini. Abstract Sleep is an activity in which the brain gives the body total rest. The quality of sleep is important to maintain someone's physical and mental condition. Poor sleep quality is caused by sleep disorders. The most common sleep disorder is Sleep-Disordered Breathing (SDB) or Sleep Apnea, in which the sufferer will experience repeated pauses in breathing while asleep. Sleep Apnea is categorized into two, namely Obstructive Sleep Apnea (OSA) and Central Sleep Apnea (CSA). Sleep disorder diagnosis is done with Polysomnography which is expensive and uncomfortable. The result of Polysomnography can also not be directly used by doctors for further evaluation. Therefore, in this research, a system was created to detect sleep disorders into Normal, OSA, or CSA classes using Electrocardiography (ECG) signals acquired by the 3-lead placement technique. This system uses AD8232 sensors to acquire heart signals that are processed by Arduino Mega 2560 to obtain High and Low-frequency features of the signal, which are then used for classification. This system has an accuracy of 85% in classifying SDB using the Naive Bayes method with an average computation time of 12ms. This system can be used at home because it is portable and the data can be directly downloaded from the website for doctor evaluation, making the patient feel more comfortable and efficient in early diagnosis.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48858932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Penerimaan Learning Management System Institut Teknologi Garut Menggunakan Technology Acceptance Model","authors":"Asri Mulyani, Dede Kurniadi, Mita Hidayani Putri","doi":"10.25126/jtiik.20241046618","DOIUrl":"https://doi.org/10.25126/jtiik.20241046618","url":null,"abstract":"Kemajuan teknologi dari masa ke masa terus berkembang secara pesat dalam bermacam bidang salah satunya dalam bidang pendidikan. Pendidikan mempunyai kedudukan yang sangat berarti dalam upaya kenaikan mutu seseorang, tetapi dengan kemunculan wabah penyakit Corona Virus Disease 2019 (Covid-19) menyebabkan lahirnya tatanan gaya hidup baru secara global. Civitas akademika Institut Teknologi Garut selain mematuhi peraturan dari pemerintah juga mengikuti perkembangan pendidikan berbasis teknologi informasi yang bersifat interaktif dengan menggunakan aplikasi Learning Management System sebagai pendukung proses pembelajaran jarak jauh dimasa wabah penyakit Covid-19. Dikarenakan Learning Management System (LMS)  di Institut Teknologi Garut baru digunakan, maka penelitian ini bertujuan menganalisis penerimaan Learning Management System Institut Teknologi Garut menggunakan metode Technology Acceptance Model, untuk mengetahui pengukuran pengaruh antar konstruk sekaligus sebagai barometer adaptasi penerimaan pengguna terhadap sistem LMS yang digunakan. Dalam penelitian ini pengolahan data analisis memakai Structural Equation Modeling melalui tools Statistical Product and Service Solution dan Analysis of Moment Structures. Penelitian ini menghasilkan tingkat penerimaan pengguna terhadap Learning Management System dengan nilai probabilitas dibawah 5% yaitu 0,000 dan pengaruh antar konstruk Technology Acceptance Model dengan 3 hipotesis yang diterima ialah variabel Persepsi kemudahan memengaruhi Persepsi kegunaan, Persepsi kegunaan memengaruhi Niat penggunaan, dan Niat penggunaan memengaruhi Penggunaan nyata. AbstractTechnological advances from time to time continue to develop rapidly in various fields, one of which is in the field of education. Education has a very significant role in efforts to improve one's quality, but the emergence of the Corona Virus Disease 2019 outbreak has led to the birth of a new lifestyle order globally. In addition to complying with government regulations, the Garut Institute of Technology academic community also follows the development of interactive information technology-based education with the use of informative applications through electronic media in order to get efficient results, namely the Learning Management System. Because the Learning Management System at the Garut Institute of Technology has just been used, a study entitled Learning Management System Acceptance Analysis of the Garut Institute of Technology uses the Technology Acceptance Model Method, to determine the measurement of the influence between constructs as well as a benchmark for adapting user acceptance to the system used. In this research, data analysis is processed using Structural Equation Modeling through Statistical Product and Service Solution tools and Analysis of Moment Structures. This study resulted in the level of user acceptance of the Learning Management System with a probability value below 5%, namely 0.000 and the influence between the constr","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48005476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Faktor Transformasi Digital Pelayanan Publik Pemerintah Di Era Pandemi","authors":"Sari Sisilianingsih, Betty Purwandari, Imairi Eitiveni, Mardiana Purwaningsih","doi":"10.25126/jtiik.2024107059","DOIUrl":"https://doi.org/10.25126/jtiik.2024107059","url":null,"abstract":"Banyak perubahan yang terjadi dalam kehidupan masyarakat sebagai konsekuensi dari social distancing di era pandemi. Hal ini juga mempengaruhi cara pelayanan publik pemerintah kepada masyarakat yang ikut berubah akibat pembatasan sosial, di mana pelayanan tatap muka ditiadakan dan digantikan oleh layanan virtual dengan memanfaatkan teknologi informasi. Digital Government Transformation adalah teori yang digunakan dalam penelitian ini untuk melihat faktor pendorong dan penghambat proses transformasi digital khususnya pada pelayanan publik di masa pandemi. Penelitian ini bertujuan mengidentifikasi faktor-faktor yang mendukung dan menghambat serta tantangan yang dialami Indonesia selama pandemi dalam digitalisasi pelayanan publik. Penelitian ini dianalisa menggunakan Structural Equation Modelling dengan pengambilan data melalui cross sectional survey pada 208 responden. Hasil penelitian dapat disimpulkan bahwa faktor yang mendorong keberhasilan proses digitalisasi pelayanan publik di masa pandemi adalah profesionalisme dalam melayani yang tergambar dari inovasi pelayanan publik, kemampuan sumber daya manusia, dan pengalaman kerja. Sementara itu, faktor penghambat dari perspektif organisasi dan budaya seperti kurangnya panduan kepemimpinan, kurangnya koordinasi antar divisi, kurangnya dukungan operasional, budaya yang menolak perubahan, dan birokrasi yang rumit belum terbukti secara signifikan mempengaruhi proses transformasi karena hambatan tersebut tidak dapat membendung transformasi digital pelayanan masyarakat ketika dihadapkan pada kondisi pandemi Covid-19 yang membutuhkan perubahan.AbstractMany changes have occurred in people’s lives as a consequence of social distancing in pandemic era. This also affects the way government public services to the community have changed due to social restrictions, where face-to-face services are abolished and replaced by virtual services by utilizing information technology. Digital Government Transformation is the theory used in this research to see the driving and inhibiting factors of the digital transformation process. This research investigates the factors that support and hinder along with the challenges experienced in Indonesia during the pandemic in the digitalization of public services. This study used a questionnaire survey and managed to collect 208 respondents. The results of the study can be concluded that the factors that drive the successful practice of public service’s digitalization during the pandemic are professionalism in serving which is depicted from public service innovations, human resource capabilities, and work experience. Meanwhile, the inhibiting factors from the organizational and cultural perspective as lack of leadership guidance, lack of coordination between divisions, lack of operational support, a culture that resists change, and complicated bureaucracy have not proven to significantly affect the transformation process because these obstacles cannot stem the digital transformation","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136242314","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":"Pengembangan Sistem Manajemen Pelatihan Kerja di Kota Surakarta","authors":"Affriza Brilyan Relo Pambudi Agus Putra, Shelvie Nidya Neyman, Hendra Rahmawan","doi":"10.25126/jtiik.20241047167","DOIUrl":"https://doi.org/10.25126/jtiik.20241047167","url":null,"abstract":"Program pelatihan kerja di Pemerintah Kota Surakarta yang ditawarkan oleh Dinas Tenaga Kerja, Dinas Pendidikan, Dinas Perdagangan, Dinas Pemberdayaan Perempuan, Perlindungan Anak dan Pemberdayaan Masyarakat dan Dinas UMKM Koperasi & Industri. Saat ini beberapa instansi pemerintah yang memiliki program pelatihan kerja yang sama masih menggunakan sistem konvensional. Data pengangguran diambil melalui dari Dinas Sosial Kota Surakarta dikirim melalui media sosial WhatshApp sehingga terjadinya tumpang tindih data pengangguran dan pelaksanaan pelatihan kerja. Instansi yang terlibat dalam program pelatihan kerja belum memiliki rencana strategis dan beberapa proses bisnis dilakukan secara manual. Melihat kondisi permasalahan tersebut maka dibutuhkan suatu perencanaan pengembangan sistem pada instansi pemerintah (dalam hal ini Dinas terkait) sistem informasi dianalisis dan dirancang dengan metode prototyping, merupakan bagian proses untuk membagikan program pelatihan kerja di setiap dinas terkait merealisasikan tujuannya. Untuk dapat menerapkan perencanaan yang mengintegrasikan dan menyinkronkan data menjadi sarana Pemerintah Kota Surakarta dapat mengelola sistem manajemen pelatihan kerja. Dari hasil penelitian ini melalui pengujian dengan metode black box untuk mengukur efisiensi, akurasi, validitas data dan kegunaan sistem manajemen pelatihan kerja untuk memastikan tidak terjadinya kembali tumpang tindih data. AbstractJob training programs in the Surakarta City Government are offered by the Department of Manpower, the Office of Education, the Office of Commerce, the Office for Women's Empowerment, Child Protection and Community Empowerment, and the Office for MSME, Cooperatives, and Industry. Several government agencies with the same job training program are still using the conventional system. The response data was taken through the Surakarta City Social Service and sent via WhatsApp social media so that there was an overlapping of the response data and the implementation of job training. The agencies involved in the job training program do not yet have a strategic plan and some business processes are carried out manually. Seeing the condition of the problem, it is necessary to have a system development plan for government agencies (in this case the related Office). Information systems are analyzed and designed using the prototyping method, which is part of the process for distributing job training programs in each Service related to utilization. To be able to implement planning that integrates and synchronizes data becomes a means for the Surakarta City Government to manage a job training management system. the results of this study through testing with the black box method for efficiency, accuracy, data validity, and the use of job training management systems to ensure data overlap does not occur again.","PeriodicalId":32501,"journal":{"name":"Jurnal Teknologi Informasi dan Ilmu Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43904574","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}