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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) JURNAL SISTEM INFORMASI BISNIS TEKMAPRO Journal of Industrial Engineering and Management Infotech Journal UNEJ e-Proceeding NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Jurnal Inotera INTECOMS: Journal of Information Technology and Computer Science Jurnal Teknologi Informasi dan Multimedia International Journal of Economics, Business and Accounting Research (IJEBAR) JATI (Jurnal Mahasiswa Teknik Informatika) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Journal of Intelligent Decision Support System (IDSS) Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Tematik : Jurnal Teknologi Informasi Komunikasi Infotech: Journal of Technology Information Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan Idealis : Indonesia Journal Information System Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Multicience INTELEKTIVA TIERS Information Technology Journal Journal of Dinda : Data Science, Information Technology, and Data Analytics Journal Computer Science and Informatic Systems : J-Cosys International Journal Software Engineering and Computer Science (IJSECS) Jurnal Teknik Informatika Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Duta Abdimas: Jurnal Pengabdian Masyarakat Proceeding of International Conference Health, Science And Technology (ICOHETECH) Prosiding Seminar Nasional Teknologi Informasi dan Bisnis SATIN - Sains dan Teknologi Informasi SmartComp Jurnal Informatika Polinema (JIP) Teknologi : Jurnal Ilmiah Sistem Informasi Jurnal Informatika Dan Tekonologi Komputer
SRI SUMARLINDA
Universitas Duta Bangsa Surakarta
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Studi Komparatif Model Klasifikasi Kerentanan Penyakit Jantung Menggunakan Algoritma Machine Learning Wiji Lestari; Sri Sumarlinda
SATIN - Sains dan Teknologi Informasi Vol 9 No 1 (2023): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (567.024 KB) | DOI: 10.33372/stn.v9i1.918

Abstract

Penyakit jantung merupakan salah satu penyebab kematian baik di dunia maupun Indonesia. Perhatian awal dari penyakit jantung akan memudahkan pencegahan dan penyembuhanya. Tujuan penelitian ini adalah melakukan analisis komapratif model klasifikasi dengan berbagai algoritma machine learning untuk kerentanan penyakit jantung. Dataset diambil dari UCI machine Learning Resipatory dengan 300 data training dan 100 data testing. Parameter klasifikasi terdiri dari age, sex, systolic blood pressure, cholesterol, thalach, oldpeak dan slope, serta labelnya cardio. Model klasifikasi dibangun dengan algoritma Naïve Bayes, K-Nearest Neighbor (KNN), Decision Tree, random Forest, Backpropagation, Logistic Regression dan Support Vector machine (SVM). Hasil model klasifikasi dari pengukuran accuracy didapatkan Naïve Bayes (79,00%), KNN (63,00%), Decision Tree (66,00%), Random Forest (77,00%), Backpropagation (80,00%), Logistic Regression (81,00%) dan SVM (80,00%). Dari analisis komparatif pegukuran parameter accuracy, precision, recall dan F1 score maka model klasifikasi dengan algoritma Logistic Regression dan backpropagation menghasilkan performa terbaik.
Perancangan Sistem Pakar Diagnosis Penyakit Flu Kucing Dan Feline Lower Urinary Tract Disease Pada Kucing Ras Persia Menggunakan Metode Certainty Factor Faiz Mu’ammar Hadi; Moh Muhtarom; Sri Sumarlinda
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kucing merupakan salah satu hewan yang populer dan disukai di kalangan masyarakat, karena tingkah laku maupun fisiknya yang lucu serta mudah dalam pemeliharaannya menjadi alasan yang membuat banyak orang menyukai untuk memelihara hewan peliharaan ini. Jika tidak diimbangi dengan pengetahuan dalam pemeliharaan dan perawatannya, kucing rentan terhadap suatu penyakit, penyakit yang sering kali terjadi disebabkan oleh virus, parasit, dan bakteri yang berkembang dalam tubuh kucing tanpa sepengetahuan pemilik kucing. Metode certainty factor memiliki kemampuan menentukan tingkat akurasi dan metode ini cocok dalam proses penentuan identifikasi hama dan penyakit, dan hasil dari penerapan metode ini adalah persentase. Dengan adanya sistem pakar diagnosis penyakit flu kucing dan feline lower urinary tract disease pada kucing ras persia diharap dapat membantu untuk mendiagnosis penyakit yang menyerang kucing kesayangannya sedini mungkin serta dapat memberi solusi cara pengobatan dan pencegahannya dengan bantuan dokter hewan. Hasil perhitungan manual yang dilakukan pada penelitian ini sebesar 82.39%.
THE USER SATISFACTION LEVEL OF ELEARNING FOR BUSINESS AND MANAGEMENT SUBJECTS BASED ON TECHNOLOGY ACCEPTANCE MODEL Indra Hastuti; Wijiyanto Wijiyanto; Wiji Lestari; Sri Sumarlinda
International Journal of Economics, Business and Accounting Research (IJEBAR) Vol 3, No 03 (2019): IJEBAR, VOL. 03 ISSUE 03, SEPTEMBER 2019
Publisher : LPPM ITB AAS INDONESIA (d.h STIE AAS Surakarta)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijebar.v3i03.491

Abstract

Elearning is the implementation of information technology in learning. Elearning was used in courses in Introduction to Business and Management, Business Process Management and Ebusiness. This study aims to use the Technology Acceptance model (TAM) to measure the level of user satisfaction. TAM method is used to determine the relationship between content, accuracy, format, ease of use, timelines, organizational support, user attitudes towards the information system (user attitude towards information). system) and perceived attitude of top management on the level of satisfaction of using e-learning on learning business courses and management at the Faculty of Computer Science, Duta Bangsa University Surakarta. This research is a descriptive study using the modified End User Computing Satisfaction (EUCS) approach method. The results of the evaluation study show that the 5 variables (content), the level of accuracy of the system, format, easy of use, and timeliness significantly influence user satisfaction. While organizational support variables have a significant effect on user satifaction but variable usser attitude toward information system and perceived attitude of top management has an effect but not significant to the support organization. Key words : elearning, user satisfaction, technology acceptance model, end user computing satisfaction.
Marvel Movie Recommendation System Using Hybrid Item-Based and Content-Based Filtering Methods Daffa Rizki Putra Noordi; Herliyani Hasanah; Sri Sumarlinda
TIERS Information Technology Journal Vol. 5 No. 1 (2024)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v5i1.5209

Abstract

Currently, there are so many movie genres available to the general public, making it difficult for viewers to choose a movie. One of the most popular movies is the “Marvel Movies” or MCU (Marvel Cinematic Universe), which has become the highest grossing franchise of all time with 90 movies released. The large number of movie titles makes it difficult for people to choose which movie to watch. Therefore, a Marvel movie recommendation system is needed using a hybrid item-based and content-based filtering method. The content-based method calculates the similarity between movies by identifying similar Marvel movies based on content such as genre, actor, director, and synopsis. Meanwhile, item-based completes content-based recommendations by considering user preferences. The reason for using the hybrid item-based and content-based filtering method is to be able to produce more accurate recommendations than a single method. The types and sources of data used are secondary data from journals and the internet (Imdb and Movielens), as well as datasets about Marvel movies. From the results of testing the hybrid model, the precision value is 0.8 or 80% which indicates that the model is accurate. In item-based filtering testing, the similarity result of 0.68 shows good item similarity. In the content-based filtering test, the highest similarity is 0.14 and the lowest similarity is 0.10 which shows that the similarity between the searched content and the generated content is relevant.
FORECASTING CENTRAL BANK DIGITAL CURRENCY TERHADAP RUPIAH DIGITAL Mumu, Raul Galvin Rudolf; Nurchim, N; Sumarlinda, Sri
IDEALIS : InDonEsiA journaL Information System Vol 6 No 2 (2023): Jurnal IDEALIS Juli 2023
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v6i2.3027

Abstract

Munculnya mata uang digital sebagai hasil dari inovasi teknologi untuk mengurangi penggunaan uang tunai menghadirkan tantangan baru bagi pelaku ekonomi, termasuk bank sentral. Menyusul fenomena digitalisasi yang berkembang pesat, Bank Indonesia mengumumkanrencananya untuk segera menerbitkan Rupiah Digital sebagai Central Bank Digital Currency (CBDC). Pengembangan bank sentral ini bertujuan untuk menciptakan sistem pembayaran digital di Indonesia. Untuk mengatasi permasalahan tersebut, dilakukan penelitian menggunakan teknik data mining guna menemukan prediksi yang berguna. Proses data mining dilakukan dengan menerapkan metode Cross-Industry Standard Process for Data Mining (CRISP-DM) dan menggunakan algoritma regresi linear berganda. Data dikumpulkan selamaperiode 4tahun, mulai dari Januari 2019 hingga Februari 2023, yang diperoleh melalui website resmi dengan akses internet. Teknik regresi linear berganda digunakan untuk memprediksi hubungan antara 4 variabel, yaitu jumlah uang kartal yang diedarkan, nilai transaksi ATMcard and credit card, nilai transaksi uang elektronik, nilai transaksi SMS/mobile banking terhadap variabel Y yaitu analytical accounts of the central bank. Dari hasil penelitian, ditemukan bahwa keempat variabel tersebut memberikan kontribusi sebesar 79,8% terhadap variabel Y (analytical accounts of the central bank)
Sistem Pakar Diagnosis Penyakit ISPA Pada Anak Tasya Mutiara Diva; Joni Maulindar; Sri Sumarlinda
TEMATIK Vol. 11 No. 1 (2024): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2024
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v11i1.1916

Abstract

Acute Respiratory Tract Infections (ARTIs) in children are often challenging to diagnose due to their similar and varied symptoms. Hence, the development of an expert system for diagnosing ARTIs in children is crucial. The aim of this research is to develop an expert system that can assist in the rapid and accurate diagnosis of ARTIs in children. The method employed is the forward chaining approach, where observed symptoms are linked to specific ARTIs through inference rules. Initially, the symptoms of ARTIs and related diseases are identified, forming the knowledge base. Subsequently, the forward chaining algorithm is implemented in the system to facilitate the dissemination of information from observed symptoms to the correct diagnosis. The user interface is designed to facilitate input from users, whether doctors or parents, regarding their child's symptoms. Internal testing is conducted to validate the system's accuracy, involving medical professionals to evaluate and provide feedback on the generated diagnoses. The results indicate that bronchitis is the most likely disease in children based on the total scores of observed symptoms. Treatment recommendations focus on symptomatic care and complication prevention. Thus, the use of an expert system with a forward chaining approach positively contributes to supporting the diagnosis of ARTIs in children by providing faster and more accurate diagnoses and appropriate treatment recommendations.
Sistem Rekomendasi Pemilihan Paket Rakitan Komputer Menggunakan Metode Knowledge Base Di Cv Innovision Saputra, Rizal Dwi; Sumarlinda, Sri; Sopingi, Sopingi
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 4 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i4.10980

Abstract

Penelitian ini dilatarbelakangi karena CV Innovision memiliki masalah dalam memberikan rekomendasi produk paket rakitan komputer yang sesuai kebutuhan pelanggan. Maka peneliti melakukan observasi serta wawancara kepada pemilik CV Innovision untuk mengetahui cara yang paling tepat dalam menyelesaikan masalah tersebut. Sistem rekomendasi yang digunakan peneliti adalah metode Knowledge Base Filtering tujuan metode ini untuk membantu pelanggan mendapatkan paket rakitan komputer yang dibutuhkan. Atribut yang digunakan untuk memfilter produk antara lain ; spare part , harga , dan instalasi software. Produk rakitan komputer yang digunakan sebagai objek penelitian sejumlah 30 produk, dari produk tersebut terdapat spefikasi yang beragam seperti processor, RAM, motherboard, harddisk, dan case. Hal ini juga yang mempengaruhi minat pelanggan untuk memilih serta membeli produk rakitan komputer. Kata Kunci : Komputer, Sistem Rekomendasi, Kebutuhan
Sistem Rekomendasi Pemilihan Nutrisi Hewan dengan Metode Content Based Filtering Andrian Setya Putra; Pipin Widyaningsih; Sri Sumarlinda
Jurnal Inotera Vol. 9 No. 2 (2024): July - December 2024
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol9.Iss2.2024.ID378

Abstract

In this digital age, technology can make everyday life easier, including finding and providing food for livestock and pets. Hilda Pakan Supplier is a business that provides various types of nutrition, such as feed, vitamins, and veterinary medicine. At the time of observation, some customers were often confused in determining the right feed, vitamins, or medicine for their animals due to the lack of information they had. Customers usually have to ask the shopkeeper, which can take a long time especially when the shop is crowded. To overcome these problems, the purpose of this project is to use the content-based filtering method to create a recommendation system for animal nutrition choices. This method was chosen because the recommendation process is simpler and does not require rating data from other users. The system can provide recommendations in accordance with the needs and preferences of animals. In its application, the cosine similarity algorithm is used to measure product similarity based on text descriptions. The results show that this recommendation system is able to produce 10 products with the highest similarity value, which is 0.331060048. In the future, this system can be further developed by adding more products to provide more accurate insurance results.
Sistem Informasi Pemesanan Genteng Berbasis Website di Dusun Kebak Supriyanto, Kukuh; Wijiyanto, Wijiyanto; Sumarlinda, Sri
Journal Computer Science and Information Systems : J-Cosys Vol 4, No 2 (2024): J-Cosys - September
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53514/jco.v4i2.530

Abstract

Dusun Kebak merupakan sentral tempat pengrajin genteng. Disana terdapat 10 pengrajin genteng yang masih melakukan produksi genteng setiap hari nya. Dusun Kebak menjadi satu-satu nya dusun pengrajin genteng terbanyak se-Desa Wirun. Permasalahan yang dihadapi para pengrajin genteng di Dusun Kebak adalah kurangnya perluasan jaringan pelanggan dikarenakan pelanggan yang ingin melakukan pemesanan harus datang bertemu dengan pengrajin secara langsung sehingga pelanggan yang memiliki waktu dan jarak yang terbatas kesulitan dalam melakukan pemesanan. Sebagai upaya untuk mengatasi permasalahan tersebut, maka para pengrajin genteng di Dusun Kebak memerlukan sistem informasi pemesanan yang dapat memudahkan calon pelanggan untuk melakukan pemesanan produk genteng tanpa harus datang menemui pengrajin genteng secara langsung.Sistem yang akan di buat akan menampilkan informasi terkait produk produk yang akan dijual dan memproses pesanan pelanggan. Untuk pengembangan sistem menggunakkan metode Waterfall dan bahasa pemrograman. PHP. Sistem pemesanan yang dibuat memiliki 2 hak akses antara lain : pelanggan dan admin
Decision Support System for Internship Acceptance at Digital Connection Using the Simple Additive Weighting Method Saputra, Bintang Pratama Yuarna; Sumarlinda, Sri; Sari, Aprilisa Arum
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.2996

Abstract

The internship program serves as a bridge for students into the professional world. At Digital Connection, the current manual selection process for internship candidates leads to inefficiency and potential errors. This study aims to implement a Decision Support System using the Simple Additive Weighting (SAW) method to improve the efficiency of the internship selection process. The SAW method is selected for its capability to provide accurate assessments based on predefined criteria and preference weights, as well as to rank the best alternatives. The system is developed as a web-based application with full access for HR (Admin), including tests as evaluation criteria. This research has resulted in the creation of a decision support system utilizing the Simple Additive Weighting (SAW) calculation method. System testing, conducted using black-box testing, shows that all primary functions and buttons of the system, such as adding, editing, deleting, searching, logging in, managing criteria and sub-criteria data, managing alternative data, calculating scores, exporting, and logging out, function properly and as expected. Furthermore, user testing with 6 criteria and 10 alternative input data points revealed the highest rank of 100% for Wahyu, followed by Noelino in second place with 76%, Hana in third place with 74%, and the lowest rank for Sanjaya with 58%. These results confirm that the calculation system operates effectively according to the researched method and provides clear ranking evaluations to assist HR (Admin) in determining the most suitable internship candidates. The system was implemented on a website using the waterfall model approach as the development method for the research system.
Co-Authors Abidarin Rosidi Aditya Prasetyo Wibowo Afu Ichsan Pradana Agustina Srirahayu Andrian Setya Putra Aprilisa Arum Sari Awang Long, Zalizah binti Azizah Binti Rahmat AzizahBinti Rahmat Bintang Pratama Yuarna Saputra binti Rahmat, Azizah Budi Suryono, Arif Daffa Rizki Putra Noordi Dedy Hariyadi Desi Mandasari Dewangga Ranggi Wiku Dwi Hartanti Eko Purwanto endra setiyawan Fadhillah, Dian Agil Faiz Mu’ammar Hadi FAULINDA ELY NASTITI Ghoffar Pangestya Prabowo Hanif Al Fatta Hasanah, Herliyani Humam Rosadi Indra Hastuti INDRA HASTUTI Intan Oktaviani Jayawarsa, A.A. Ketut Joko Endriyanto Junaidi, Iqbal Hanan Khotimah, Agil Husnul Maulana Saputra, Ridlo Maulindar, Joni Moh Muhtarom Muhammad Dhito Maulidan Muhammad Mujib Al Khafid Mumu, Raul Galvin Rudolf Nafaria Rohmandani Nibras Fa'id Muhammad Nibras Fa’id Muhammad Nugroho, Ledjar Nugroho Nugroho, Robby Gusti Nurchim Nurmalitasari Nurmalitasari Oktaviani, Intan Permatasari, Hanifah Pipin Widyaningsih Puput Yulianto Purnama, Joel Adikurnia Ridwan, Avin Nolis Rifal Bayu Ardi Rina Arum Prastyanti Rina Arum Prastyantia Rizqi Saputra Robby Gusti Nugroho Rohmat Eko Prasetyo Ryan Arya Pramudya Saputra, Bintang Pratama Yuarna Saputra, Rizal Dwi Sholeh Abdul Irfan Torodipo Sopingi Sopingi Sopingi Sopingi Sopingi Sopingi, Sopingi Sri Rejeki Supriyanto, Kukuh Tasya Mutiara Diva Udhata Swardana, Avila Vihi Atina Wiji Lestari Wiji Lestari Wiji Lestari Wiji Lestari WIJI LESTARI Wijiyanto Wijiyanto Wijiyanto, Wijiyanto Yeremia Dhimas Abiyoso Yoga Prasetiawan, Ardhian Yuliyanto, Rico Dwi Yuwono, Adhi Zalizah Awang Long Zalizah Binti Awang Long