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All Journal Sainteks Jurnal Teknologi dan Manajemen Informatika Jurnal Informatika Telematika SMATIKA Jurnal Ilmiah KOMPUTASI Jurnal Pendidikan Informatika dan Sains INTEGER: Journal of Information Technology Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Teknoinfo Martabe : Jurnal Pengabdian Kepada Masyarakat JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EDUMATIC: Jurnal Pendidikan Informatika JSAI (Journal Scientific and Applied Informatics) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Zonasi: Jurnal Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) Infotek : Jurnal Informatika dan Teknologi Indonesian Journal of Cultural and Community Development Community Empowerment Indonesian Journal of Innovation Studies Indonesian Journal of Public Policy Review Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) PELS (Procedia of Engineering and Life Science) Procedia of Social Sciences and Humanities Prosiding University Research Colloquium Malcom: Indonesian Journal of Machine Learning and Computer Science JOINCS (Journal of Informatics, Network, and Computer Science) SAGA: Journal of Technology and Information Systems Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Innovative Technologica: Methodical Research Journal Physical Sciences, Life Science and Engineering Indonesian Journal of Applied Technology Journal of Social Comunity Services Journal of Technology and System Information Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Journal for Technology and Science Jurnal Farmasi Galenika IJHCS Smatika Jurnal : STIKI Informatika Jurnal
Ade Eviyanti
Universitas Muhammadiyah Sidoarjo
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation

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Sistem Informasi Jabatan Fungsional Dosen Berbasis Web Studi Kasus Universitas Muhammadiyah Sidoarjo Bisri, Muhammad Anhar; Eviyanti, Ade; Hindarto, Hindarto
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 6 No. 1 (2022): PROSIDING SEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v6i1.2453

Abstract

Penelitian ini dilatarbelkangi dengan sistem pengajuan jabatan fungsional di Universitas Muhammadiyah Sidoarjo yang masih menggunakan cara manual, mulai dari pengajuan berkas, pemberitahuan status ajuan hingga penyimpanan, pemeriksaan dan pemindahan dokumen masih sangat bergantung dengan tenaga admin. Hal tersebut dikarenakan belum adanya sistem informasi yang terintegrasi yang dapat membantu dosen untuk mengajukan jabatan fungsional sehingga dosen harus melakukanya secara manual.Tujuan dari penelitian ini ialah mengembangkan sebuah sistem informasi jabatan fungsional yang dapat mempermudah dosen untuk mengajukan jabatan fungsional dengan menyediakan form pelampiran nilai dan file agar lebih teratur dan terkoordinir serta menyediakan informasi seputar status pengajuan yang telah diajukan, sehingga tidak perlu lagi menghubungi pihak admin untuk menanyakan status pengajuanya. Dan tentunya mengorganisir file yang telah dosen inputkan di sebuah sistem penyimpanan tersendiri. Hasil penelitian akan menghasilkan sebuah sistem informasi berbasis web yang akan memudahkan dosen untuk mengajukan jabatan fungsional.
Perhitungan Kalori Gizi Pada Ibu Hamil Berbasis Website Menggunakan Metode Cooper Sabilah, Hasya; Eviyanti, Ade
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 6 No. 3 (2022): PROSIDING SEMINAR NASIONAL INOVASI TEKNOLOGI TAHUN 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v6i3.2672

Abstract

Pada saat ini gizi pada ibu selama hamil sangat dapat mempengaruhi pertumbuhan janin yang sedang dikandung. Poliklinik KIA (Kesehatan Ibu dan Anak) merupakan salah satu dari beberapa pelayanan yang ada di Puskesmas yaitu tempat dimana mendapatkan pelayanan terkait dengan kesahatan ibu dan anak. Permasalahan yang saat ini semakin banyak dialami adalah ketika ibu hamil yang jarang sekali berkonsultasi kepada dokter atau ahli gizi tentang menu makanan yang harus dikonsumsi pada saat hamil yang dapat berakibat pada tambahnya angka kematian bayi khususnya di Indonesia. Karena pada kenyataannya banyak ibu hamil yang beranggapan bahwa makanan yang banyak itu sudah mencukupi kebutuhan gizi untuk janin yang dikandungnya. Tujuan dari penelitian adalah untuk membangun sebuah aplikasi berbasis web yang dapat digunakan sebagai media pemantauan gizi harian ibu hamil menggunakan metode Cooper. Dan pada pengujian dapat mengitung kebutuhan kalori dengan mengolah berat badan ideal, tinggi badan, aktifitas ibu hamil dan jumlah jam tidur ibu hamil. Hasil penelitian berupa aplikasi berbasis web yang dapat digunakan oleh ibu hamil untuk memperoleh informasi tentang kebutuhan gizi yang disarankan melalui perhitungan kalori dan menu makanan.
Analisis Sentimen Tingkat Kepuasan Aplikasi WordPress Menggunakan Metode K-Nearest Neighbor dan Naive Bayes Moch Siddiq Hamid; Ade Eviyanti; Hindarto Hindarto; Novia Ariyanti
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 01 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i01.1522

Abstract

User satisfaction reflects emotions when comparing services received with expectations, so understanding user satisfaction is important for app development. This research aims to evaluate user satisfaction with WordPress apps on the Google Play Store and identify areas for improvement. Sentiment analysis with KNN and Naïve bayes algorithms as the method used to extract information from 5,000 user reviews downloaded from Google Play Store,. The results showed the majority of reviews had positive sentiments, with Naïve Bayes providing better results than KNN, achieving 88% accuracy, 89.45% precision, 88% recall, and 83% F1-Score on a 90:10 data split. The word cloud of positive reviews featured words such as “great”, “good”, “helpful”, “app”, and “good”, reflecting user satisfaction with the ease and benefits of the app, while negative reviews featured words such as “difficult”, “try”, and “fail” indicating technical difficulties and user dissatisfaction. This study concludes that WordPress apps have provided a satisfactory experience for most users, but some technical areas need improvement. The results of this study will provide valuable information for app developers in efforts to improve service quality and the app's reputation
Klasifikasi Pola Peminjam Buku Bedarsarkan Profesi Menggunakan Algoritma Naïve Bayes Febri Rosita Dewi; Ade Eviyanti; Arif Senja Fitriani; Ika Ratna Indra Astutik
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1661

Abstract

As centers of literacy and learning, libraries face challenges in understanding book lending patterns to meet the needs of diverse users. The main problem faced is the lack of data-based analysis in optimizing library services and collections. This research aims to classify book borrowing patterns based on profession using the Naive Bayes algorithm, utilizing data from the Sidoarjo Library Service in 2023. The data consists of 4476 transactions with attributes such as profession, book category, and level of reading interest. This research was conducted in several phases, namely data collection preprocessing, processing using Gaussian and Multinomial Naive Bayes algorithms, and model evaluation. By testing on various data ratios (90:10, 80:20, 75:25, and 50:50), the results show that Gaussian Naive Bayes provides the highest accuracy of 97% in the random dataset scenario. The main findings show that students, university students and housewives dominate the high reading interest category, while doctors and researchers have lower reading interest. The unique value of this research is in its application of. data-based analysis to support library management. The research results provide strategic insight for developing more responsive data-based services, optimizing collections according to professional needs, and increasing the effectiveness of literacy programs. This research is anticipated to serve as the initial phase in utilizing data mining technology to overcome modern challenges in library management.
Penerapan K-Means dengan Evaluasi Davies-Bouldin Index untuk Pengelompokan Kelas Unggulan SMP Wijaya Sukodono Feny Anggraeny; Ade Eviyanti; Sumarno
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1689

Abstract

This research was conducted at Wijaya Sukodono Middle School, one of the largest schools in Sukodono District which seeks to improve the quality of education by utilizing student academic data. The main objective of this research is to group students based on academic scores using the K-Means Clustering method, which aims to divide students into two categories: Superior Class and Regular Class. The Flagship Class is defined as a group of students with high academic performance, while the Regular Class includes students with lower academic performance. The research method involves collecting report value data, processing, and data transformation, followed by the application of the K-Means algorithm. Evaluation was carried out using the Davies-Bouldin Index (DBI) to assess the quality of clustering. The analysis results show that of the 576 students, 488 students are included in the Superior Class and 88 students are in the Regular Class. The two cluster configuration provides optimal results with a DBI value of 0.337, indicating a good level of inter-cluster certification. This research concludes that the K-Means method is effective in grouping students based on academic performance. These results provide insight into strategies for schools in developing more targeted learning programs to improve the quality of education. Further development can be done by including non-academic variables or exploring other clustering methods for more comprehensive results
Analisis Sentimen Komentar YouTube MV K-Pop Menggunakan Naïve Bayes: Studi Kasus Jung Jaehyun ‘Horizon’ Addriana Fatma Putri Indah Sari; Ade Eviyanti; Ika Ratna Indra Astutik
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1691

Abstract

This research aims to analyze the sentiment of YouTube comments on the music video "Horizon" by Jung Jaehyun by applying the Naïve Bayes and Support Vector Machine (SVM). As a global phenomenon, K-pop serves as an intriguing subject for understanding interaction patterns and fan opinions on social media platforms, particularly YouTube. A total of 2,391 Indonesian-language comments were collected using the YouTube API and processed through preprocessing stages such as data cleaning, tokenization, normalization, and the removal of common stopwords. After manually labeling the comments for positive and negative sentiments, the data was analyzed using the Naïve Bayes algorithm, known for its simplicity, speed, and effectiveness with small datasets, and compared with SVM equipped with a linear kernel. The study found that while SVM with a linear kernel achieved the highest accuracy of 98% and excelled in handling imbalanced data, Naïve Bayes still delivered competitive results with an accuracy of 97%. The advantages of Naïve Bayes, including ease of implementation, computational efficiency, and performance on small datasets, make it an effective choice for similar sentiment analysis cases. Both algorithms demonstrated good performance in predicting sentiments, as shown in their confusion matrices, although challenges persisted with the negative class. This research contributes to sentiment analysis methodologies by highlighting that Naïve Bayes is an efficient and relevant algorithm for preliminary exploration, while SVM is more reliable for performance optimization on complex datasets. The findings are particularly relevant to the music industry in understanding fan sentiment as an indicator of success.
Analisis Sentimen Pengguna Aplikasi Tantan Perbandingan Kinerja Metode Naive Bayes dan SVM Serlindha Tri Andini; Ade Eviyanti; Hamza Setiawan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1692

Abstract

Tantan, as a popular dating application in Indonesia, has garnered various user reviews reflecting their experiences. This study aims to analyze user sentiment for the Tantan application by comparing the performance of Naive Bayes and Support Vector Machine (SVM) algorithms in sentiment classification. User reviews were collected from Google Play Store using web scraping techniques and processed through data cleaning, tokenization, and TF-IDF feature extraction. The dataset comprises 1,195 reviews, with 74.6% positive and 25.4% negative sentiments. The Naive Bayes model achieved an accuracy of 85.36%, excelling in detecting positive reviews (precision 86%, recall 97%). However, its performance on negative reviews was suboptimal, with a recall of only 44%. Conversely, the SVM model with a sigmoid kernel demonstrated superior overall performance, achieving an accuracy of 87.03%. It handled negative reviews better, with a recall of 67% and an F1-score of 69%, while maintaining excellent results for positive reviews (precision 91%, F1-score 92%). The results indicate that although both algorithms have their strengths, SVM with a sigmoid kernel is recommended for this dataset due to its balanced and stable performance. This model provides valuable insights for feature development and quality improvement strategies for the application.
Sistem Pakar Berbasis Web untuk Diagnosis Penyakit Paru Anak dengan Forward Chaining Mochammad Raflie Lazuardi; Ika Ratna Indra Astutik; Ade Eviyanti
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1738

Abstract

This research aims to design an expert system using the forward chaining method to facilitate the early diagnosis of lung diseases in children, such as tuberculosis, pneumonia, and bronchitis. The system is designed to help the community, especially in areas with limited access to healthcare services, in recognizing symptoms independently. The methodology uses the stages of the Expert System Development Life Cycle (ESDLC), including problem identification, knowledge acquisition from experts, design, and testing using black box techniques. This system is capable of detecting symptoms, matching them with a rule base, and providing an initial diagnosis along with recommended actions. The implementation results show that the system can support quick and accurate medical decision-making, as well as enhance public health awareness through internet-based access.
Pengelompokan Pelanggaran Lalu Lintas Menggunakan Algoritma K-Means pada Data CCTV Fitriah Fitriah; Ade Eviyanti; Hindarto Hindarto
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1739

Abstract

This study aims to cluster traffic violation data recorded by CCTV in the Sidoarjo area using the K-Means Clustering algorithm. The dataset used in this study was obtained from Sidoarjo Police, covering 43,055 traffic violation records in the period January 2023 to July 2024. The CRISP-DM approach is applied to ensure a systematic research flow, starting from problem understanding, data collection, to result evaluation. After the data selection and transformation stage, the dataset was processed into 14,386 data. Clustering was performed to divide violations into three categories based on severity, namely high, medium, and low. Evaluation of cluster quality using Silhouette Score showed the best result with a value of 0.9916 at k=9, indicating optimal cluster formation. The clustering results showed that the highest violation occurred in the category of “not using a seat belt” with 8,710 cases, while the moderate violation involved “not wearing a helmet” with 5,522 cases. This study confirms the effectiveness of the K-Means algorithm in clustering traffic violation data and provides valuable insights for the Sidoarjo Police Traffic Unit in designing more efficient traffic violation reduction programs.
Android-based Programming Language to Natural Language Translator App Aisyiyah, Rosydah Rihadhatu; Eviyanti, Ade
SAGA: Journal of Technology and Information System Vol. 3 No. 1 (2025): February 2025
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v3i1.476

Abstract

Translation between programming languages and natural languages is an important solution to improve the understanding of coding in informatics students who often have difficulty understanding the syntax rules of programming languages. This research develops a translator application that is integrated with OCR technology and uses GPT Chat API to automatically translate text. This application supports seven programming languages (Python, Kotlin, CSS, Dart, HTML, Javascript, and Java) and two natural languages (Indonesian and English). This research uses the Waterfall software development method, starting from requirements analysis, system design, implementation, to testing using the blackbox method. The results show that this application can help users understand coding more effectively and efficiently through translation features, interactive quizzes, and user activity history. Thus, this application has the potential to be an innovative learning media that improves the programming skills of informatics students.
Co-Authors Abdiansah, Lutfi Abror, M Abror, M. Achmad Alfian Fajriansyah Adam Putra Addriana Fatma Putri Indah Sari Adi Putra, Lutfi Agil Fajar Dwi Prasetyo Agustin, Erlina Ahmad Muflih Aisha Hanif Aisyiyah, Rosydah Rihadhatu Aliful Fatikh Pulunggono Suseta Alim, Kholqi Aminy, Ritzana Aisyah Andriani Eko Prihatiningrum, Andriani Eko Anggraeni, Anifah Warda Anjasmara, Dimas Bayu Arif Senja Fitrani Arif Senja Fitrani Arif Senja Fitriani Astutik, Ika Ratna Indra Ayu Anggilina Ayu Dwi Ratna Ningsih Azizah, Nurul Lutfi Bisri, Muhammad Anhar Busono, Suhendro Chulloh, Dafid Mizta Cornelius, Cornelius Damasta, Ifanda Reza Deby Kurniawan Armananda Dewanti, Irene Elvariani Diba, Naila Farah Dimas Sya’aldi Pasa Dini Aprilia Puspitasari Dini Yocta Prabayanti Dona Ardiansyah Dulkarnain, As’ad Dwi Cahyono, Qitfirul Erika Anjani Putri Eriyanto, Sandi Eko Faiqotul Himma Ramadhanti Fanani, Muchammad Ichsanuddin Fandy Rachmatulloh Febri Rosita Dewi Feny Anggraeny Fitrani, Arif Senja Fitriah Fitriah Fuad Azis Muslim Ghozali, M Fahruddin Ginanjar Agung Sudrajat Guko, William Yviis Hamid, Moch Siddiq Hamza Setiawan Hamzah Setiawan Hasan, Jamal Hazmi Ramadhan Al fatri Hendri Hermawan Hermawan, Tunggal Hibatullah Putra, Dimas Radito Hindarto Ika Ratna Indra Astutik Imanda, Almyra Gitta Indah Kurniawati Indra Astutik, Ika Ratna Indrawati, Marcella Intan Mauliana, Metatia khoirunnisa devita sari Lazuardi, Fajar Lola Herawati Luqmanul Hakiym Maulana M Fahruddin Ghozali Makhfudzoh, Fury Maulana, Mahardika Rafi Mauliana, Metatia Intan Ma’ruf , Mohammad Rizal Miftahurrohmat, A Miftakhurrohmat, A. Moch Alfan Rosyid Moch Siddiq Hamid Mochamad Alfan Rosid Mochammad Raflie Lazuardi Mohammad Fadli Zaka Mohammad Rizal Ma'ruf Muchammad Bagus Sasmita muchammad david mahendra Muhammad Alfin Firdiansyah Muhammad Arif Fa’i Muhammad Fajar Alfian Naufal Raihan naufal Nisa, Umi Khoirun Nouval Aulia Rachman Novia Ariyanti Novia Ariyanti Nuril Lutvi Azizah Octavia, Elga Padova Bima Maldini Pranatadityo, Billy Prasetyana, Dwi Gilang Ramadhan Pratama, Hepi Yoga Pratama, Robby Pratiwi, Rosa Machmuda Putra F, M. Bagus Putra, Fariq Abdillah Maulana Putri, Revanda Silva Astianto Ramdansyah, Adiffanani Reyhan Haqiqi Alif Fourniawan Rizki, M. Alvan Rohman Dijaya Rozzaq, Muhammad Rukhi Alfian, Muhammad Sabilah, Hasya Saiful Arifin Saiful Arifin Salsabil, Muhammad Saputra, Abhirama Senja Fitrani, Arif Serlindha Tri Andini Setiawan, Hamzah Shiddqy Hidayat, Syahril Shierly Mayco Angela Siti Nurjanah Ramadhany Suhendro Busno Suhendro Busono Sukma Aji Sumarno , Sumarno Sumarno . Sumarno Sumarno Syaifudin, Hilmi Fajar Sylfanie Sekar Mayang Tasya Gusti Amalia Taurusta, Cindy Teguh Hardianto Putra Uce Indahyanti Umi Khoirun Nisak Vevy Liansari via nabila banda Viarini, Dina Dwi Okta Wardani, Gita Wijayanto, Moch Eri Witno, Kasaifi Al Qurdhowi Bin Wulandari, Alidza Septiam Yanita Wardhani Yulian Findawati Yunianita Rahmawati, Yunianita Yuzefa, Hihaniza Lela Zahputra, Aldy Trisza Zaka, Mohammad Fadli