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All Journal Jurnal Algoritma Jurnal Informatika Upgris JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Inotera Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Indonesian Journal of Applied Informatics Simtek : Jurnal Sistem Informasi dan Teknik Komputer STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Indonesian Journal of Community Services Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Manajemen Informatika dan Sistem Informasi Journal of Information Systems and Informatics bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) INFORMASI (Jurnal Informatika dan Sistem Informasi) G-Tech : Jurnal Teknologi Terapan Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Journal of Advanced in Information and Industrial Technology (JAIIT) Infotek : Jurnal Informatika dan Teknologi Infotech: Journal of Technology Information Idealis : Indonesia Journal Information System Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Infotech: Jurnal Informatika & Teknologi Jurnal Pendidikan dan Teknologi Indonesia Jurnal Mandiri IT Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Teknik Informatika Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Biner : Jurnal Ilmiah Informatika dan Komputer Proceeding of International Conference Health, Science And Technology (ICOHETECH) Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Informasi Kesehatan Nasional Bengawan :Jurnal Pengabdian Masyarakat SmartComp Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) ABDIKOM CSRID Jurnal ilmiah teknologi informasi Asia Teknologi : Jurnal Ilmiah Sistem Informasi
Atina, Vihi
Universitas Duta Bangsa Surakarta
Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Sistem Rekomendasi Pemilihan Produk UMKM Berbasis Hybrid Recommendation Adri Surya Kusuma; Dinita Christy Pratiwi; Vihi Atina
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

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Abstract

Smeska is one of the entrepreneurship programs belonging to the Solo Techno Incubator which is structurally related to Solo Technopark and is under the auspices of the Regional Research and Development Agency for the City of Surakarta. This program provides entrepreneurship training for non-digital startups or MSMEs with the hope that the output of the participants will be able to carry out end-to-end processes (production, branding, marketing, digitization & packaging) as well as setting the team's focus on the area of business achievement. With the special segmentation of MSME players, until the third year this program was running, it was still not far from the conventional scale even though digitization had become the point in the training. One solution that can accommodate this digitalization is to design a MSME product recommendation system that makes it easier for the client side, in this case buyers, to find what products they need. The purpose of this study is to make a Hybrid Recommendation model for the MSME Product Selection Recommendation System. The system development method used is Extreme Programming (XP) which consists of stages namely planning, design, implementation, as well as testing and integration. The Hybrid Recommendation modelling design used in this study is Pipelined Hybridization where the first recommender in this system is Content Based with naïve bayes techniques which will be input to the second recommender using Knowledge Based modelling with Case Based techniques. Modelling for this MSME product selection recommendation system can provide filtering of the search for conformity product items along with 5 choices of product search attributes, namely brand, price, material, variant and size. Based on the results of the Hybrid Recommendation modelling with 20 sample data, Adzkira chips get the highest similarity value of 0.99000 from the search input for MSME product types of chips. It is hoped that the results of this research can make a significant contribution to developing a recommendation system for selecting MSME products, as well as strengthening digitalization and business transformation efforts for Smeska program participants.
Sistem Pendukung Keputusan Pemilihan Supplier Pakaian Dengan Kombinasi Metode Fuzzy dan SAW Vihi Atina; Dwi Hartanti; Joni Maulindar
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

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Abstract

Pemilihan supplier merupakan salah satu faktor kritis dalam industri pakaian. Keputusan yang baik dalam memilih supplier akan berimbas pada kualitas produk, ketersediaan stok, dan kepuasan pelanggan. Simple Inc Store adalah toko besar di daerah pasar Klewer yang menjual berbagai produk pakaian skala besar (grosir) dan eceran. Dalam menjalankan proses bisnisnya, toko tersebut belum menerapkan manajemen resiko dalam menentukan supplier pakaian sehingga dijumpai beberapa permasalahan seperti kekurangan stok beberapa produk pakaian yang diminati pelanggan atau sebaliknya penumpukan produk pakaian yang kurang diminati oleh pelanggan. Tujuan dari penelitian ini adalah mengembangkan sistem pendukung keputusan (SPK) yang dapat membantu dalam pemilihan supplier pakaian dengan mengkobinasikan metode Fuzzy dan SAW. Tahapan dalam penelitian ini mengacu pada tahapan metode pengembangan Agile dalam mengembangkan sistem pendukung keputusan mulai dari perencanaan awal, analisis dan perancangan serta implementasi dan pengujian. Hasil sistem pendukung keputusan dapat mengelola kriteria, alternatif dan perhitungan fuzzy saw. Hasil perhitungan SAW menunjukkan bahwa nilai preferensi tertinggi 0,63 yaitu Supplier Three Second Store. Hasil pengujian fungsionalitas sistem menunjukkan bahwa fungsi-fungsi dalam sistem pendukung keputusan dapat berjalan sesuai dengan harapan.
IMPLEMENTASI KONTROL KIPAS ANGIN OTOMATIS MENGGUNAKAN SENSOR SUHU PADA KANDANG AYAM PEDAGING Bagus Muhammad Latif; Nurchim Nurchim; Vihi Atina
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 3 (2024): EDISI 21
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i3.4391

Abstract

Usaha beternak ayam broiler merupakan salah satu usaha yang menjanjikan perekonomiannya, namun terdapat kendala dalam beternak ayam broiler, yang paling sering ditemui adalah ayam mati karena stress akibat suhu dalam kandang yang meningkat akibat sistem pendingin kandang yang masih manual. dan bergantung pada mesin. kipas dengan kendali manusia. Penelitian ini bertujuan agar peternak dapat meminimalisir dampak kerugian akibat matinya ayam di kandang dengan mengandalkan sistem kendali sensor suhu pada kipas angin. Sistem ini menggunakan metode Prototype yang terdiri dari lima tahapan berupa analisis kebutuhan, perancangan, pengembangan, pengujian dan pemeliharaan. Dengan bahasa pemrograman Arduino dan mikrokontroler sebagai pusat kendali.Berdasarkan hasil penelitian, diperoleh sistem kendali sensor suhu kipas yang akan menyala secara otomatis jika suhu sangkar lebih dari 30oC dan kipas akan mati secara otomatis ketika suhu turun menjadi kurang. dari suhu 30oC, dimana alat telah teruji dan memenuhi harapan untuk menurunkan tingkat stres pada ayam broiler dan meningkatkan produks
Pengembangan E-Service Jasa Pernikahan Pada Marni Wedding Organizer Dengan Metode RAD Muhammad Alwan Nurdin; Vihi Atina; Faulinda Ely Nastiti
Computer Science Research and Its Development Journal Vol. 16 No. 2 (2024): June 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.16.2.2024.201-213

Abstract

In the digital era, Wedding Organizer (WO) services have become increasingly vital in facilitating wedding planning and execution. However, many WOs, including Marni Wedding Organizer, still grapple with inefficiencies stemming from manual operational systems. This research endeavors to address this issue by developing a web-based e-service system for Marni Wedding Organizer using the Rapid Application Development (RAD) method. RAD was chosen for its iterative approach and adaptability to evolving requirements. The system, developed using PHP, JavaScript, MySQL, and the Midtrans API, progresses through phases of requirements analysis, system design, coding, and testing. The study identifies operational inefficiencies as the primary problem, prompting the need for technological intervention. Through thorough testing, the system achieves a 100% testing level across all modules, ensuring robust functionality. However, limitations exist in the system's scope, focusing solely on booking and payment processes. Future research could explore expanding system features for enhanced service personalization. Ultimately, the developed e-service system enhances operational efficiency, customer satisfaction, and resource management for Marni Wedding Organizer.
PENERAPAN MODEL CRISP-DM PADA PREDIKSI NASABAH KREDIT MENGGUNAKAN ALGORITMA RANDOM FOREST Saputra, Dwi Bagus; Atina, Vihi; Nastiti, Faulinda Eli
IDEALIS : InDonEsiA journaL Information System Vol. 7 No. 2 (2024): Jurnal IDEALIS Juli 2024
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v7i2.3244

Abstract

Non-performing loans (NPLs) are one of the main challenges faced by Baitut Tamwil Tazakka Savings and Loan Cooperative, which can potentially threaten the financial stability and health of the institution. This study aims to evaluate the effectiveness of the Random Forest algorithm in predicting NPLs in the cooperative. The CRISP-DM method is applied in this study, encompassing the stages of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The data used consists of 14 attributes and 190 records that have been cleaned of missing values. The modeling results show that the Random Forest algorithm can provide very high prediction accuracy, with the best accuracy reaching 94.8% on a 90:10 dataset split. Performance metrics evaluation such as AUC, CA, F1 Score, Precision, Recall, and MCC indicate very good values, signifying strong predictive performance. Confusion matrix analysis also confirms high prediction accuracy with most correct predictions in the categories of non-performing, performing, and sub-performing loans. This study confirms that the Random Forest algorithm is effective in predicting NPLs, underscores the importance of applying machine learning in credit risk management, and contributes significantly to the financial stability of the cooperative through more accurate NPL predictions.
Teknik K-Fold Cross Validation untuk Mengevaluasi Kinerja Mahasiswa Wijiyanto, Wijiyanto; Pradana, Afu Ichsan; Sopingi, Sopingi; Atina, Vihi
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1618

Abstract

A student's ability to complete courses is influenced by various factors, including academic and non-academic aspects. Understanding the factors that influence it is very important to know in order to anticipate and prevent the possibility of failure in the study. It turns out that non-academic factors also have a big influence on student success, especially family factors, such as the level of education obtained by parents, the employment status of parents and the income of both parents. To be able to understand these factors, studies are needed to predict student performance based on family background factors using machine learning models, support vector machine algorithms, naïve Bayes, neural networks and decision trees. The data used was 365 records and 11 attributes, separated by 70% for train data and 30% for test data, which was then used by kfold cross validation to evaluate the results using the parameters n_split=10 and random_state=42. In the confusion matrix parameters, the average (mean) accuracy value for the support vector machine model was 87.68%, naïve Bayes was 90.97%, neural network was 87.95% and decision tree was 85.75%. Meanwhile, the best fold result for SVM is located at the 10th fold with an accuracy of 94.44%, for NB it is located at the 4th fold with an accuracy value of 97.29%, for NN it is located at the 4th fold with an accuracy value of 94.59% and for DT is located on the 5th fold with an accuracy value of 91.89%. Thus, evaluation using k-fold cross validation can be used to predict student performance based on family attributes using the 4th fold which has the highest accuracy of 97.29% in the naïve Bayes model algorithm in order to graduate on time.
Sistem Perencanaan Instalasi Listrik Rumah Tinggal Dengan Metode RAD Saputro, Andi; Permatasari, Hanifah; Atina, Vihi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.840

Abstract

This research aims to analyze, design, and develop a web-based information system to calculate the cost of electrical installation for simple residential homes using the Rapid Application Development (RAD) method. The research background is the need for a system that can facilitate users in planning and estimating electrical installation costs based on technical specifications and power requirements. The system is designed to provide accurate cost estimates, including the cost of installing electrical points, sockets, lights, and other electrical components, enabling users to make more informed decisions. The RAD method is employed to accelerate the development process and ensure the system meets user needs through rapid iterations and prototyping. The results indicate that the system can deliver precise and user-friendly cost calculations, making it an effective tool for planning electrical installations in simple residential homes.
PENERAPAN METODE CONTENT BASED FILTERING PADA SISTEM REKOMENDASI PEMILIHAN BUKU REFERENSI RUMAH BELAJAR PANCASILA Utomo, Dimas Cahyo; Atina, Vihi; Widyaningsih, Pipin
Infotech: Journal of Technology Information Vol 10, No 1 (2024): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v10i1.262

Abstract

Rumah Belajar Pancasila is a digital school facilitated by Barong Indonesia. Rumah Belajar Pancasila moves by using the application of the same name. In the Rumah Belajar Pancasila application there are many books that can be used by students in supporting students' insights. However, the number of books is a problem for students in finding books that suit student needs. Therefore, this research was conducted to overcome this problem, namely the construction of a recommendation system with the content-based filtering method and as a system development method using agile software development.  The agile software development method has several stages, namely planning, implementation, testing, documentation, deployment and maintenance. In the implementation of the research, the author used the observation method by looking at existing data on the Rumah Belajar Pancasila application. As for the features produced by themselves are book search, book list, book details, download and read books and also book recommendations. For testing the system itself using the recall and precision table method. And from these tests, the average percentage of recall value is 100% and the percentage of precision value is 90%. ABSTRAKRumah Belajar Pancasila adalah sebuah sekolah digital yang difasilitasi oleh Barong Indonesia. Rumah Belajar Pancasila bergerak dengan menggunakan aplikasi dengan nama yang sama. Didalam aplikasi Rumah belajar Pancasila terdapat banyak buku yang dapat digunakan oleh siswa dalam menunjang wawasan siswa. Akan tetapi banyaknya buku tersebut menjadi masalah bagi siswa dalam mencari buku yang sesuai dengan kebutuhan siswa. Oleh karena itu penelitian ini dilakukan untuk mengatasi masalah tersebut, yaitu dibangunnya sistem rekomendasi dengan metode content-based filtering dan sebagai metode pengembangan sistemnya menggunakan agile software development. Metode pengembangan sistem agile software development memiliki beberapa tahapan, yaitu planning, implementation, testing, documentation, deployment dan maintenance. Pada pelaksanaan penelitian, penulis menggunakan metode observasi dengan melihat data yang sudah ada pada aplikasi Rumah Belajar Pancasila. Sedangkan untuk fitur yang dihasilkan sendiri adalah pencarian buku, list buku, detail buku, unduh dan baca buku dan juga rekomendasi buku. Untuk pengujian sistemnya sendiri menggunakan metode tabel recall dan  precision. Dan dari pengujian tersebut didapatkan rata-rata prosentase nilai  recall yaitu 100% dan prosentase nilai precision yaitu 90%.
Product Stock Supply Analysis System with FP Growth Algorithm Hartanti, Dwi; Atina, Vihi
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.580

Abstract

This study explores the application of Data Mining in deciphering consumer purchasing patterns at Tani Heritage Shop, a retailer specializing in agricultural products. Facing the challenge of managing a high volume of daily sales transactions, the shop often encounters difficulties in tracking which products are frequently purchased together. This lack of insight leads to a critical issue: popular products running out of stock unexpectedly. To address this, the research focuses on developing a product stock supply analysis system, utilizing the FP Growth Algorithm. The FP Growth Algorithm, a powerful tool in Data Mining, is employed to analyze sales transaction data and identify consumer purchasing trends, particularly products bought simultaneously. This approach is designed to provide insights into optimal stocking strategies, ensuring the availability of in-demand products. The research methodology involves applying the FP Growth Algorithm to model the product stock supply system, using specific sales data attributes. The results of this study are significant. By setting parameters such as a minimum support value of 30%, a confidence value of 70%, and targeting the highest lift ratio value of 3.67, the research successfully derives several key association rules from the FP Growth algorithm. These rules are instrumental in optimizing the product stock supply analysis system.
Prototipe Sistem Rekomendasi Film Indonesia Menggunakan Pendekatan Content Based Filtering dan Metode Vector Space Model Theo Santoso, Daniel; Atina, Vihi; Hartanti, Dwi
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 2 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i2.26083

Abstract

Film represents a combination of narrative and cinematographic aspects in an audio-visual form. Films also provide an engaging visual, auditory, and emotional experience. The film industry in Indonesia has shown significant growth. In 2015, cinema audiences numbered 16.2 million, increasing to 51.2 million in 2019. The COVID-19 pandemic caused a drastic decline in the number of viewers, with only 4.5 million in 2021. However, the industry quickly recovered, reaching 54.07 million viewers in 2022 and 55 million in 2023, and is projected to reach 60 million in 2024. With the increasing availability of films and streaming platforms, finding movies that match user preferences often becomes a challenge. This study proposes a film recommendation system using the Content-Based Filtering method and the Vector Space Model to help users more easily find movies that match their preferences. Content-Based Filtering recommends films based on content similarity, while the Vector Space Model measures content similarity using metrics such as cosine similarity or euclidean distance. Based on experiments using 20 sample films, the results show that the designed system can provide accurate and precise movie recommendations based on keywords provided by users. The film "Pengabdi Setan 2: Communion" has the highest similarity score of 0.3018, followed by "Nana," "Menjelang Magrib," "Jailangkung: Sandekala," and "Qorin," with similarity scores of 0.0865, 0.0138, 0.0136, and 0.0125, respectively
Co-Authors Adri Surya Kusuma Agung Saputro Agustina Srirahayu Akbar Permana, Danny Aldi Wahyudi Arta Amad Tri Yanto Andi Saputro Andreas Sigit Andreas Anin Aliya Pahlevi, Khumaira Anisatul Farida Anjar Setiawan Aprilisa Arum Sari Ardi Lestari, Sofiana Arlin Govinda Putra Atmojo, Fernando Winantya Bagaskara, Ikrar Bagaskara, Mochammad Naufal Bagus Muhammad Latif Bambang Prasetyo Bawindra Surya, Lintang Chiva Olivia Bilah Dedi Nugroho Dimas Abimanyu Sutrisno Putro Dinita Christy Pratiwi Dwi Hartanti Dwi Hartanti Dwi Hartanti Eko Purwanto Eko Purwanto Ema Sagita Desylawati endra setiyawan Esti Suryani Fajrin Fadhilah, Dayinta Fajrin, Shoffia FAULINDA ELY NASTITI Faulinda Ely Nastiti Hafids Sidiq, Muhammad Hartanti , Dwi Hartanti, Dwi Hasanah, Herliyani Imaduddin, Mohamad Indrastata, Ilham Buyung Infantono, Ardian Intan Oktaviani Janah, Selvi Miftakhul Joni Maulidar Kurnia Sari, Vena Lufti Puspitasari Maulidar, Joni Maulindar, Joni Meraldy Fiko Rastio Ajie Mohd, Farahwahida Muhamad Ridwan Muhammad Alwan Nurdin Muhammad Dhafa Diar Ardhana Muhammad Fahmi Panwar Muhammad Frasha Candra Perdana Nailurrizqi, Adistya Nastiti, Faulinda Eli Niken Pratiwi, Niken Nugroho Arif Sudibyo Nur Arifin, Taufiq Nur Mahar Aji mahar Nurchim Nurchim Nurdin, Muhammad Alwan Nurlita, Catarina Ivanda Nurmalitasari Nurmalitasari Nurmalitasari Nurmalitasari Oktaviani, Intan Pegi Hasyim Rosidi Permatasari, Hanifah Pipin Widyaningsih Pradana, Afu Ichsan Pradityo Utomo Pramoedya Ananta Dzikri Pratiwi, Dinita Christy Purnama, Joel Adikurnia Purwanto, Eko Putra, Hasda Surya Putri, Della K. Putri, Desy Puspa Ragil Saputro, Abdullah Raharisti, Nur Arifah Ramadhan, Chandra Ratmini, Yuli Reza Pradana, Areta Ridwan, Alfian Junior Rifan Amirul H, Muhammad Rifdah Azizah, Hani Rizky Setiawan, Fadli Rudi Susanto Rusdiana Ekawati, Ratih Saputra, Dwi Bagus Saputri, Okta Ramma Saputro, Nurbagus Sejati, Ariya Putra Setiawati, Neha Poetri Sihwi, Sari W. Sopingi Sopingi, Sopingi SRI SUMARLINDA Srisuk, Prattana Sulami, Atik Sulistiyo, Galih Suwandi, Djatmiko Tanwal Hu, Wupiwulang Taufiq NurHidayat Theo Santoso, Daniel Umi Salamah Utomo, Dimas Cahyo Viona Putri Ardiana Vita Aryadi Wahyu Kurniawan, Christian Wibowo, Anita Carolina Wiharto Wiharto Wijiyanto Wijiyanto Wijiyanto, Wijiyanto Yommy Adhiwira Yudha