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All Journal Tekno : Jurnal Teknologi Elektro dan Kejuruan Techno.Com: Jurnal Teknologi Informasi Jurnal Sosioteknologi Jurnal Transformatika JUSIFO : Jurnal Sistem Informasi Jurnas Nasional Teknologi dan Sistem Informasi Sistemasi: Jurnal Sistem Informasi JMM (Jurnal Masyarakat Mandiri) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Tecnoscienza JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Advanced in Information and Industrial Technology (JAIIT) Sewagati Jurnal Informatika Polinema (JIP)
Endah Septa Sintiya
Politeknik Negeri Malang
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Systematic Literature Review: Implementation COBIT as a Best Practice of Electronic Based Government System Governance Puspitaningrum, Ari Cahaya; Fitrani, Laqma Dica; Sintiya, Endah Septa
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i1.3639

Abstract

Presidential Regulation of the Republic of Indonesia No. 95 of 2018 told that the implementation of SPBE is recommended to create clean, effective, transparent and accountable government governance as well as quality and trustworthy public services. This research use the systematic literature review (SLR) method by reviewed the implementation of COBIT best practices in various government organization in Indonesia in the last 5 years. This was done by analyzed each selected study and it can be concluded that there were 27 scientific journal studies and 3 conference studies. Analysis of 30 studies resulted in several groupings of studies, those are based on study objectives, frequently found focus areas, and frequently used domains. Based on the grouping of selected studies, it can be seen that there are 2 different objectives in using COBIT in government agencies, 1) the objective of measuring the level of maturity and capability of IT governance and 2) the objective of designing an IT governance system. The domains most frequently found in the selected studies are APO and DSS. Apart from that, this research also found a focus area that is often found, namely IT services and there are recommendations for further research based on being able to evaluate and design IT governance in the COBIT domain which is often found based on the focus area.
Analisis Efektivitas Algoritma K-Means Clustering dalam Pengelompokan Siswa Berdasarkan Kemampuan Multidimensi Rafandi, Hanif Naufal; Nurhasan, Usman; Sintiya, Endah Septa
Techno.Com Vol. 24 No. 4 (2025): November 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i4.14653

Abstract

Pengelompokan siswa berbasis data sangat penting untuk mendukung evaluasi yang adil dan menyeluruh, mengingat penilaian potensi selama ini cenderung terfokus pada aspek akademik saja. Penelitian ini mengembangkan sistem rekomendasi regu inti lomba kepramukaan menggunakan algoritma K-Means Clustering, dengan dataset berisi 120 siswa SMP yang dinilai berdasarkan parameter akademik, non-akademik, serta pencapaian SKU dan SKK. Jumlah cluster ditentukan sebanyak 24, sesuai dengan kategori lomba berdasarkan aturan Kwarnas mengenai lomba pramuka tingkat penggalang. Proses pengolahan data meliputi normalisasi dan reduksi dimensi menggunakan Principal Component Analysis (PCA). Evaluasi kualitas clustering dilakukan menggunakan metrik Silhouette Score dan Davies–Bouldin Index (DBI). Hasil terbaik diperoleh pada konfigurasi random_state = 42, n_init = 20, dan max_iter = 300, dengan Silhouette Score sebesar 0,1238 dan DBI sebesar 1,4418. Meskipun kualitas pengelompokan tergolong rendah dengan hasil Silhoutte Score = 0.102 dan DBI = 1.362, sistem ini tetap memberikan solusi objektif bagi pembina dalam memilih siswa berpotensi secara adil dan menyeluruh. Sistem ini juga menjawab keluhan orang tua terkait ketidakterlibatan anak dalam lomba, karena pemilihan dilakukan berdasarkan potensi keseluruhan kategori lomba, bukan hanya satu kategori untuk membentuk tim regu inti pramuka.   Kata kunci: K-Means Clustering, Principal Component Analysis (PCA), Silhouette Score, Davies–Bouldin Index, Regu Inti Pramuka.
Implementasi Machine Learning dalam Sistem Prediksi dan Rekomendasi Program Diet Terintegrasi LLM Endah Septa Sintiya; Sely Ruli Amanda; Candra Bella Vista; Agung Nugroho Pramudhita
Jurnal Nasional Teknologi dan Sistem Informasi Vol 11 No 2 (2025): Agustus 2025
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v11i2.2025.144-151

Abstract

Malnutrition, both in the form of overweight and underweight, remains a global health challenge. Unhealthy urban lifestyles and limited access to appropriate nutritional interventions exacerbate this problem. Technology-based approaches such as machine learning and Large Language Models (LLM) offer opportunities to improve the effectiveness of dietary management. This study proposes the development of a machine learning-based and LLM-integrated diet program prediction and recommendation system applied to Cafe NUT Castle. The system was developed to digitize body composition data recording, predict diet programs (weight loss, weight gain, and body fat loss) using the Random Forest algorithm, and generate personalized initial diet recommendations through the integration of the Gemini Flash-Lite API. Based on the test results, the prediction model achieved an accuracy of 93% on the test data and 84% on 50 new datasets. Evaluation of the diet recommendations generated by LLM showed a feasibility level of 86.6% which was categorized as very feasible. These results indicate that the developed system is not only accurate in predicting diet programs but also effective in providing initial recommendations that can support decision-making in digital nutrition consultation services.
Analyzing the Application of Optical Character Recognition: A Case Study in International Standard Book Number Detection Imam Fahrur Rozi; Ahmadi Yuli Ananta; Endah Septa Sintiya; Astrifidha Rahma Amalia; Yuri Ariyanto; Arin Kistia Nugraeni
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4367

Abstract

In the era of advanced education, assessing lecturer performance is crucial to maintaining educational quality. One aspect of this assessment involves evaluating the textbooks authored by lecturers. This study addresses the problem of efficiently detecting International Standard Book Numbers (ISBNs) within these textbooks using optical character recognition (OCR) as a potential solution. The objective is to determine the effectiveness of OCR, specifically the Tesseract platform, in facilitating ISBN detection to support lecturer performance assessments. The research method involves automated data collection and ISBN detection using Tesseract OCR on various sections of textbooks, including covers, tables of contents, and identity pages, across different file formats (JPG and PDF) and orientations. The study evaluates OCR performance concerning image quality, rotation, and file type. Results of this study indicate that Tesseract performs effectively on high-quality, low-noise JPG images, achieving an F1 score of 0.97 for JPG and 0.99 for PDF files. However, its performance decreases with rotated images and certain PDF conditions, highlighting specific limitations of OCR in ISBN detection. These findings suggest that OCR can be a valuable tool in enhancing lecturer performance assessments through efficient ISBN detection in textbooks.
Pengembangan Chatbot Berbasis Framework RASA pada Website Bank Sampah Sriwilis Vista, Candra Bella; Tundjung, Mellyana; Fatmawati, Triana; Sintiya, Endah Septa
Jurnal Informatika Polinema Vol. 12 No. 2 (2026): Vol. 12 No. 2 (2026)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i2.9569

Abstract

Perkembangan teknologi informasi dalam bidang Natural Language Processing (NLP) membuka peluang pemanfaatan chatbot sebagai solusi layanan informasi berbasis website yang interaktif dan responsive di tengah keterbatasan tenaga pelayanan dan waktu operasional. Chatbot memungkinkan pengguna memperoleh informasi secara real-time tanpa keterlibatan operator manusia secara langsung, sehingga dapat meningkatkan efisiensi dan ketersediaan layanan. Penelitian ini bertujuan mengembangkan chatbot berbasis Framework Really Awesome Software Automation (RASA) pada Website Bank Sampah Sriwilis serta menganalisis pengaruh konfigurasi pipeline Natural Language Understanding (NLU) terhadap performa klasifikasi intent. Metode pengembangan sistem menggunakan model Waterfall yang meliputi tahap analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Dataset disusun dalam bahasa Indonesia, terdiri dari 9 intent dengan total 250 kalimat. Eksperimen dilakukan terhadap tiga konfigurasi pipeline, yaitu DIETClassifier sebagai model baseline, DIETClassifier dengan penambahan fitur leksikal melalui RegexFeaturizer dan LexicalSyntacticFeaturizer, serta LogisticRegressionClassifier sebagai model pembanding. Evaluasi kinerja model dilakukan menggunakan metrik accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa model berbasis DIETClassifier memberikan peningkatan performa akurasi sebesar 5% dibandingkan Logistic Regression. Konfigurasi model dengan penambahan pipeline RegexFeaturizer dan LexicalSyntacticFeaturizer menghasilkan nilai accuracy terbaik sebesar 93%, precision 93%, recall 91%, dan F1-score 91%. Dengan demikian, pemilihan konfigurasi pipeline yang tepat serta penerapan fitur tambahan berpengaruh signifikan terhadap peningkatan performa chatbot berbasis RASA pada layanan informasi Bank Sampah Sriwilis.
Co-Authors Adevian Fairuz Pratama Affandi, Luqman Agung Nugroho Pramudhita Ahmadi Yuli Ananta Amalia, Astrifidha Rahma Amanda, Sely Ruli Ananta, Ahmadi Yuli Andhani, Yasmine Navisha Anugrah Nur Rahmanto Apol Pribadi Apol Pribadi Ari Cahaya Puspita Ningrum Ari Cahaya Puspitaningrum Ari Cahaya Puspitaningrum Ari Cahaya Puspitaningrum Ari Cahaya Puspitaningrum Ari Cahaya Puspitaningrum Arin Kistia Nugraeni Ashri Shabrina Afrah Astrifidha Rahma Amalia Bekti Cahyo Hidayanto Cahaya Puspitaningrum, Ari Candra Bella Vista Dhebys Suryani Hormansyah, Dhebys Suryani Dian Hanifudin Subhi Dimas Wahyu Wibowo Dodit Suprianto Eka Larasati Amalia Ekojono Ekojono Ekojono, Ekojono Erfan Rohadi Farida Ulfa Fayra, Syahla' Syafiqah Feby Artwodini Muqtadiroh Fitrani, Laqma Dica Furqon, Muhammad Ariful Hidayah, Hilda Khoirotul Ikawati, Deasy Sandhya Elya Imam Fahrur Rozi Imam Fahrur Rozi Irmasari Hafidz Irsyad Arif Mashudi Izzati, Afifah Nurul Khakim Ghozali Kusumawardana, Arya Latif, Ummi Khaira Luqman Affandi Luqman Affandi Mahfud Jiono Mohammad Al Hafidz Muhammad Afnan Habibi Najwa, Nina Fadilah Nugraeni, Arin Kistia Pramudhita, Agung Pratama, Adevian Fairuz Puspitaningrum, Ari Cahaya Rafandi, Hanif Naufal Riskitasari, Septyana Rita Sari Rita Sari Rizdania, Rizdania Sely Ruli Amanda Sely Ruli Amanda Sofyan Noor Arief Sulthon Fuad P., Aldhihamda Tony Dwi Susanto Triana Fatmawati Tundjung, Mellyana Ulfa, Farida Unggul Pamenang, Muhammad Usman Nurhasan Yuri Ariyanto Yuri Ariyanto