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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan Journal of Information Technology and Computer Science Knowledge Engineering and Data Science JOURNAL OF APPLIED INFORMATICS AND COMPUTING TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Jurnal Ilmu Komputer dan Desain Komunikasi Visual Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknologi Informatika dan Komputer Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal Restikom : Riset Teknik Informatika dan Komputer Nusantara Hasana Journal Jurnal Informatika Terpadu Jurnal Janitra Informatika dan Sistem Informasi International Journal Software Engineering and Computer Science (IJSECS) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Pengabdian Masyarakat Bhinneka Prosiding Seminar Nasional Pengabdian Kepada Masyarakat ROUTERS: Jurnal Sistem dan Teknologi Informasi Journal of World Future Medicine, Health and Nursing The Journal of Enhanced Studies in Informatics and Computer Applications Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health
M. Syauqi Haris
Institut Teknologi, Sains, Dan Kesehatan RS Dr Soepraoen Kesdam V/Brw, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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ANALISIS PENERIMAAN SISTEM PENDAFTARAN ONLINE PASIEN RAWAT JALAN DI RS RADJIMAN WEDIODININGRAT MENGGUNAKAN TEKNOLOGY ACCEPTANCE MODEL Wisam Syahputra, Kelvin; Haris, M. Syauqi; Siwi Pradini, Risqy
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 4 (2025): JATI Vol. 9 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i4.13917

Abstract

Perkembangan teknologi informasi dalam layanan kesehatan telah mendorong digitalisasi sistem pendaftaran pasien untuk meningkatkan efisiensi dan kenyamanan. Penelitian ini menganalisis penerimaan sistem pendaftaran online pasien rawat jalan di RS Radjiman Wediodiningrat menggunakan Technology Acceptance Model (TAM) dengan menambahkan aksesibilitas sebagai variabel eksternal. Metode kuantitatif dengan desain cross-sectional diterapkan pada 100 responden. Hasil pengujian hipotesis menunjukkan bahwa enam variabel yang diuji Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Toward Using (ATU), dan Behavioral Intention (BI), Actual System Use (ASU), dan Accessibility (AC) berpengaruh signifikan terhadap penerimaan sistem (nilai sig. < 0,05). Aksesibilitas juga terbukti berpengaruh positif terhadap PU (koefisien 0,646) dan PEOU (koefisien 0,759). Temuan ini menunjukkan bahwa peningkatan kemudahan akses dan antarmuka pengguna yang baik dapat mendorong adopsi teknologi oleh pasien. Implikasi praktis dari penelitian ini menyarankan RS Radjiman Wediodiningrat untuk memperbaiki infrastruktur sistem guna meningkatkan pengalaman pengguna dan efisiensi layanan.
PENINGKATAN KOMPETENSI PELAKU UMKM KOTA BATU DALAM BRAND AWARENESS MELALUI PELATIHAN BERBASIS ARTIFICIAL INTELLIGENCE Pradini, Risqy Siwi; Haris, M. Syauqi; Anshori, Mochammad
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 6 No. 3 (2025): Volume 6 No 3 Tahun 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v6i3.44159

Abstract

Program Pengabdian kepada Masyarakat ini bertujuan untuk meningkatkan kompetensi pelaku UMKM di Kota Batu dalam memperkuat brand awareness produk melalui pelatihan berbasis Artificial Intelligence. Pelatihan ini dilakukan dengan menggunakan metode Participatory Learning and Action yang mengedepankan interaksi aktif dan praktik langsung dari para peserta pelatihan. Materi pelatihan mencakup konsep dasar branding, pemanfaatan media sosial, serta aplikasi teknologi AI seperti Canva dan ChatGPT dalam pembuatan desain visual untuk meningkatkan brand awareness produk UMKM. Evaluasi yang dilakukan melalui pre-test dan post-test menunjukkan peningkatan signifikan rata-rata pemahaman peserta, dari skor awal 63 menjadi 90,33. Hasil ini membuktikan bahwa metode pelatihan yang digunakan efektif dalam meningkatkan kompetensi para peserta. Pelatihan ini juga mendorong peserta untuk lebih percaya diri dalam memanfaatkan teknologi untuk pemasaran digital, sehingga mampu bersaing di pasar yang semakin kompetitif.
UI/UX Design of Pratama Clinic Mobile Application Based on User Cultural Dimensions with User-Centered Design (UCD) Approach Iqbal, Ahmad; Khudori, Ahsanun Naseh; Haris, M. Syauqi
Jurnal Teknologi Informatika dan Komputer Vol. 11 No. 2 (2025): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v11i2.2645

Abstract

Digital transformation has brought significant changes to various sectors, including healthcare. Digital technology, particularly mobile applications, enables increased efficiency, accessibility, and service quality. In the context of digital healthcare, effective user interface (UI) and user experience (UX) design are key factors in increasing application adoption by users. This study aims to design a mobile application for Klinik Pratama using a User-Centered Design (UCD) approach and integrating local cultural values in Malang City to improve accessibility and user satisfaction. This study uses quantitative methods. Data collection techniques include in-depth interviews with respondents, participant observation, and prototype evaluation using the System Usability Scale (SUS). The cultural dimensions used include Power Distance, Collectivism, Uncertainty Avoidance, Masculinity vs. Femininity, and Long-Term Orientation, which are then implemented in UI design elements. The evaluation results show that the integration of UCD with a culture-based approach can significantly increase the application's usability value, with an average SUS score of 86.75 for patients, 87.5 for doctors, and 85.83 for administrative staff. All scores are included in the 'Good' category with a letter grade of 'B' based on the interpretation of the SUS standard. These findings confirm that a user-oriented design approach to culture can promote the inclusivity and effectiveness of primary digital health services through design strategies that are adaptive to local culture.
KOMPARASI ALGORITMA BOOSTING UNTUK PREDIKSI GANGGUAN TIDUR Mawardi, Ade Bagus; Pradini, Risqy Siwi; Haris, M. Syauqi
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.7281

Abstract

Gangguan tidur merupakan salah satu permasalahan kesehatan yang dapat berdampak pada kualitas hidup seseorang. Dalam upaya meningkatkan akurasi prediksi gangguan tidur, teknologi kecerdasan buatan telah banyak dimanfaatkan, khususnya melalui pendekatan algoritma machine learning. Penelitian ini bertujuan untuk melakukan komparasi terhadap lima algoritma boosting, yaitu AdaBoost, CatBoost, LightGBM, Gradient Boosting, dan XGBoost menggunakan dataset Sleep Health and Lifestyle. Adapun tahap penelitian yang dilakukan meliputi pengumpulan data, prapemrosesan data, normalisasi, serta evaluasi model. Berdasarkan hasil evaluasi, algoritma CatBoost menunjukkan performa paling unggul dibandingkan dengan algoritma lainnya. Hasil evaluasi menunjukkan bahwa algoritma CatBoost memberikan performa terbaik dengan akurasi sebesar 97,37%, presisi 96,29%, recall 95,83%, dan F1-score 95,82%. Hasil analisis menunjukkan bahwa keunggulan CatBoost berasal dari kemampuannya dalam menangani fitur kategorikal secara langsung tanpa memerlukan encoding tambahan, serta kemampuannya dalam mengurangi overfitting dibandingkan dengan metode boosting lainnya. Temuan ini menunjukkan bahwa model prediksi berbasis boosting khususnya CatBoost dapat dijadikan alat bantu yang efektif dalam deteksi gangguan tidur secara lebih akurat.
Application of Internet of Things in the Field of Staple Food Commodity Agriculture: Literature Review Khofida, Nisa; M. Syauqi Haris; Mochammad Anshori
Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer Vol 7 No 2 (2025): Agustus
Publisher : Program Studi Teknik Informatika Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/restikom.v7i2.436

Abstract

Kebutuhan akan pertanian yang efisien, produktif, dan berkelanjutan di Indonesia menuntut penerapan teknologi modern. Salah satu teknologi The need for efficient, productive, and sustainable agriculture in Indonesia demands the application of modern technology. One technology that offers significant solutions is the Internet of Things (IoT). This study presents a systematic literature review on the application of IoT to staple food commodity agriculture in Indonesia, with a focus on the use of soil sensors, automatic irrigation systems, and real-time data integration. The Systematic Literature Review (SLR) method was used to analyze 44 selected articles published between 2019 and 2024. The results of the study show that IoT technology contributes greatly to increasing water use efficiency, reducing operational costs, and increasing crop yields. In addition, the integration of this technology also has positive implications for the social and economic aspects of local agriculture. This study aims to provide an in-depth understanding of technology trends and development methods used, as well as identifying implementation challenges in the field. These findings are expected to be an important reference for academics, practitioners, and policy makers in formulating IoT-based agricultural development strategies in the future.
Comparing Different KNN Parameters Based on Woman Risk Factors to Predict the Cervical Cancer Saletia, Maria Claudia; Anshori, Mochammad; Haris, M Syauqi
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10746

Abstract

Cervical cancer remains a major cause of mortality among women, particularly in low-resource regions where access to conventional screening is limited. Early detection through predictive modeling offers a low-cost and non-invasive alternative to clinical diagnostics. This study aims to evaluate the effectiveness of the k-Nearest Neighbors algorithm for predicting cervical cancer risk using behavioral and psychosocial attributes. The research utilized the publicly available Sobar cervical cancer behavioral dataset comprising 72 instances with 18 input features and a binary target label. Data preprocessing included removal of incomplete records, encoding of categorical variables, and normalization. The algorithm was tested across varying numbers of neighbors and distance metrics, with performance evaluated using 10-fold cross-validation and multiple classification metrics. The optimal configuration was achieved with three neighbors and the Manhattan distance metric, yielding an accuracy of 93.06%, sensitivity of 93.10%, specificity of 85.90%, precision of 93.10%, F1-score of 92.90%, and an area under the curve of 0.8952. This performance surpassed the reported baseline of a probabilistic classifier and demonstrated the algorithm’s capability to capture complex behavioral patterns associated with cervical cancer risk. These findings confirm the feasibility of applying optimized instance-based learning to behavioral data for early cancer risk assessment. The approach offers potential for integration into community health programs to support early detection and prevention strategies.
Analisis Penerimaan Byond By BSI Menggunakan Technology Acceptance Model (TAM) (Studi Kasus: Super Apps Byond By BSI) Wilayah Kota Malang Wicaksana, Gigih; Haris, M. Syauqi; Khudori, Ahsanun Naseh
Jurnal Janitra Informatika dan Sistem Informasi Vol. 5 No. 2 (2025): Oktober - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/nb3dtf03

Abstract

Penelitian ini bertujuan untuk menganalisis penerimaan pengguna terhadap aplikasi Byond by BSI di Kota Malang dengan menggunakan kerangka Technology Acceptance Model (TAM) yang berfokus pada variabel Perceived Ease of Use (PEOU), Perceived Usefulness (PU), dan Attitude Toward Using (ATU). Metode penelitian yang digunakan adalah kuantitatif dengan survei terhadap 145 responden, di mana instrumen penelitian telah diuji validitas dan reliabilitasnya serta memenuhi kriteria yang dipersyaratkan. Hasil penelitian menunjukkan bahwa kemudahan penggunaan meningkatkan persepsi kegunaan dan secara langsung mendorong sikap positif terhadap aplikasi, sementara manfaat yang dirasakan juga memperkuat sikap positif pengguna. Temuan ini menegaskan relevansi TAM dalam konteks perbankan syariah Indonesia, yang masih terbatas dieksplorasi, sekaligus memberikan implikasi praktis bagi pengembang mobile banking untuk merancang fitur yang sederhana, fungsional, dan berorientasi pada pengalaman pengguna guna meningkatkan kepuasan serta loyalitas.
Challenges in Implementing Digital Medical Records in Indonesian Hospitals: Perspectives on Technology, Regulation, and Data Security Fita Rusdian Ikawati; M. Syauqi Haris
Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Vol. 4 No. 2 (2024): Proceeding of The International Conference of Inovation, Science, Technology, E
Publisher : Program Studi DIII Rekam Medis dan Informasi Kesehatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/icistech.v4i2.70

Abstract

The implementation of digital medical records in Indonesian hospitals faces various challenges, especially in terms of technological readiness, inadequate regulations, and data security threats that need to be addressed to ensure efficient and safe healthcare services. This study aims to identify the challenges in Digital Medical Record Implementation from the perspective of technology, regulation, and data security. This study used a systematic literature review research approach guided by the Preferred Reposrting Items for Systematic Review and Meta-Analysis (PRISMA). The results showed that the implementation of digital medical records in Indonesian hospitals faces considerable challenges from three main perspectives, namely technology, regulation, and data security. The technology perspective includes several challenges such as 1) System Interoperability, 2) Privacy, 3) IT Infrastructure Limitations, 4) Implementation Costs and 5) Maintenance and Technology Adoption by Medical Staff. The regulatory perspective includes challenges such as 1) Regulatory Compliance, 2) Patient Data Protection, 3) Validity of Medical Records, 4) Long-term Data Retention and 5) System Interoperability. The data security perspective includes challenges such as 1) Infrastructure Security, 2) Data Encryption, 3) Access Control, 4) Incident Response and 5) Regular Security Audits. Thus, collaborative efforts between the government, hospitals and technology providers are needed to address these challenges and drive safe and effective digital transformation in Indonesia's healthcare sector.
Teknik Identifikasi Fitur Berdasarkan Kalimat Pernyataan Kebutuhan dalam Konteks Pengembangan Software Product Line Haris, M Syauqi; Kurniawan, Tri Astoto
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 3: Juni 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022935732

Abstract

Software product line (SPL) adalah konsep software reuse di bidang industri perangkat lunak yang memiliki fase awal berupa domain engineering untuk mengidentifikasi dan memetakan fitur-fitur dari sekumpulan produk perangkat lunak yang akan dikembangkan. Fitur perangkat lunak sering kali diekspresikan secara eksplisit dalam kalimat pernyataan kebutuhan yang ada pada dokumen spesifikasi kebutuhan perangkat lunak (SRS). Saat ini, penelitian tentang otomatisasi identifikasi fitur perangkat lunak berdasarkan dokumen spesifikasi kebutuhan telah banyak diusulkan dengan berbagai metode, namun hasil yang diperoleh kebanyakan adalah kata benda yang dianggap sebagai kandidat fitur. Representasi fitur dengan kata benda dianggap masih terlalu abstrak dan tidak mewakili konsep fitur sebagai kemampuan atau fungsionalitas suatu perangkat lunak. Dalam penelitian ini, identifikasi fitur yang direpresentasikan dengan frasa gabungan kata kerja dan kata benda diusulkan karena dianggap lebih menjelaskan kemampuan  dan fungsionalitas dari suatu perangkat lunak. Pola penulisan kalimat pernyataan kebutuhan dengan requirement boilerplate dimanfaatkan sebagai dasar identifikasi fitur perangkat lunak secara otomatis dengan menggunakan alat bantu pemrosesan bahasa natural atau NLP (natural language processing). Dalam penelitian ini diusulkan 4 (empat) aturan dependency parser, yang merupakan salah satu pipeline dalam NLP. Tingkat keberhasilan metode pada penelitian ini adalah antara 65% sampai dengan 88% untuk 5 kelompok kalimat pernyataan kebutuhan yang diujikan. Hasil tersebut menunjukkan bahwa metode yang diusulkan pada penelitian ini bisa mengautomasi proses identifikasi fitur pada tahapan domain engineering dalam pengembangan software product line khususnya yang menggunakan metode ekstraktif.AbstractSoftware product line (SPL) is a software reuse concept in the software industry that has an initial phase of domain engineering to identify and map the features of a set of software products to be developed. Software features are often expressed explicitly in the requirement sentences contained in the software requirements specification (SRS) document. Currently, research on the automation of software feature identification based on requirements specification documents has been proposed by various methods, but the results obtained are mostly nouns that are considered feature candidates. Representation of features with nouns is considered too abstract and does not represent the concept of features as capabilities or functionality of the software. In this study, the identification of features represented by combined phrases of verbs and nouns is proposed because it is considered to better explain the capabilities and functionality of software. The pattern of writing a requirement sentence with boilerplate requirements is used as the basis for automatically identifying software features using natural language processing (NLP) tools. In this research, 4 (four) dependency parser rules are proposed, which is one of the pipelines in NLP. The success rate of the method in this study is between 65% to 88% for the 5 groups of sentences that were tested. These results indicate that the method proposed in this study can automate the feature identification process at the domain engineering stage in product line software development, especially those using extractive methods.
Perbandingan Metode Supervised Machine Learning untuk Prediksi Prevalensi Stunting di Provinsi Jawa Timur Haris, M Syauqi; Khudori, Ahsanun Naseh; Kusuma, Wahyu Teja
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 7: Spesial Issue Seminar Nasional Teknologi dan Rekayasa Informasi (SENTRIN) 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022976744

Abstract

Stunting atau kasus balita kerdil/pendek adalah salah satu masalah di bidang kesehatan yang saat ini sedang dihadapi oleh masyarakat Indonesia. Provinsi Jawa Timur memiliki nilai prevalensi stunting sebesar 26,8% berdasarkan integrasi data Kementerian Kesehatan dan Badan Pusat Statistik. Nilai tersebut masih tergolong tinggi karena standar minimal yang ditetapkan oleh World Health Organization (WHO) adalah sebesar 20%. Oleh karena itu, penelitian ini bertujuan untuk memberikan kontribusi dalam penyelesaian permasalahan stunting di Provinsi Jawa Timur dengan cara menganalisis faktor-faktor yang diprediksi bisa memengaruhi tingkat prevalensi stunting berdasarkan data sekunder hasil survei dari beberapa lembaga resmi dan terpercaya di bidang kesehatan yang telah dipublikasikan. Supervised machine learning merupakan pendekatan dalam pembuatan kecerdasan buatan (artificial intelligence) yang menggunakan data-data berlabel sebagai data latihnya. Pendekatan ini dirasa sangat sesuai digunakan dalam prediksi nilai prevalensi stunting pada suatu wilayah berdasarkan data-data lain yang relevan.  Penelitian-penelitian sebelumnya tentang prediksi prevalensi stunting rata-rata hanya menggunakan salah satu metode supervised machine learning saja dan data sekunder yang digunakan hanya bersumber dari salah satu sumber survei saja. Hasil penelitian menunjukkan bahwa faktor-faktor penyebab yang memiliki korelasi tinggi terhadap nilai prevalensi stunting bukan hanya Berat Badan Lahir Rendah (BBLR) saja, namun juga Indeks Pembangunan Manusia, sanitasi, dan Indeks Penduduk Miskin. Selain itu, beberapa metode dalam supervised machine learning juga dibandingkan yaitu, linier regression, support vector regression, dan random forest regression.Metode support vector regression dalam penelitian ini memiliki nilai galat yang lebih rendah yaitu 0,91 untuk MAE dan 1,30 untuk MSE.AbstractStunting or the case of stunted/short toddlers is one of the problems in the health sector that is currently being faced by the people of Indonesia. East Java Province has a stunting prevalence value of 26.8% based on data integration from the Ministry of Health and the Central Statistics Agency. This value is still relatively high because the minimum standard set by the World Health Organization (WHO) is 20%. Therefore, this study aims to contribute to solving the stunting problem in East Java Province by analyzing the factors that are predicted to affect the stunting prevalence rate based on published secondary data from surveys from several official and trusted institutions in the health sector. Supervised machine learning is an approach in making artificial intelligence that uses labeled data as training data. This approach is considered very suitable to be used in predicting the value of stunting prevalence in an area based on other relevant data. Previous studies on predicting the prevalence of stunting on average only used one supervised machine learning method and the secondary data used was only sourced from one survey source. The results showed that the causative factors that have a high correlation to the prevalence of stunting are not only low birth weight (BBLR), but also the Human Development Index, sanitation, and the Poor Population Index. In addition, several methods in supervised machine learning are also compared, namely, linear regression, support vector regression, and random forest regression. The support vector regression method in this study has a lower error value, namely 0.91 for MAE and 1.30 for MSE.
Co-Authors Abda Abda Ahsanun N. Khudori Ahsanun Naseh Khudori Anwar, David Saiful Arif Wahyudi Bagus Prasetyo Abdi , Benben Basmalah Abirestu Maulisuriandhy Fatwa Ramdani, Fatwa Faurika Faurika, F Faurika, Faurika Ferdy Riza Firahmi Rizky Fita Rusdian Ikawati Geraldo, Tostes Herry Prasetyo Wibowo Hevlie Winda Nazry S Khofida, Nisa Marilia, Busatto Mawardi, Ade Bagus Mika Debora Br Barus Mochamad Anshori Mourryn Galuh Erawati Nindynar Rikatsih Nindynar Rikatsih Nugroho Teguh Yuono Pradini, Risqy Siwi Putriana, Rena Risqy Siwi Pradini Risqy Siwi Pradini Saletia, Maria Claudia Siwi Pradini, Risqy Tri Astoto Kurniawan, Tri Astoto Wahyu Tejakusuma, Wahyu Wicaksana, Gigih Wisam Syahputra, Kelvin Yaniar Ramdani, Dandi Zuli Agustina Gultom