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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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Business Intelligence Dashboard Lokasi Rawan Bencana Alam Di Indonesia Menggunakan Tableau Faurika, F; Haris, M Syauqi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.721

Abstract

Natural disasters cause socio-economic damage in a country. Indonesia is one of the countries prone to being affected by natural disasters. This disaster was triggered by various factors, both natural factors and human factors themselves that did not protect the natural ecosystem. This research aims to visualize data on natural disaster cases in Indonesia that occurred in the period 2020 to 2023. This visualization of natural disasters in Indonesia applies Business Intelligence (BI) using Tableau Public to produce information from a dataset of natural disaster cases in Indonesia for the period 2020 to 2023 in the form of visuals to facilitate the process of analyzing natural disaster cases in Indonesia and with an attractive visual appearance. The results of the visualizations obtained in this research are combined to form an attractive dashboard and contains visual information on the distribution of disasters in various provinces in Indonesia, the number of disasters that occurred, the number of victims, the amount of damage, and disaster trends from 2020 to 2023. 
Implementasi Decision tree Untuk Prediksi Kanker Paru-Paru Faurika, F; Khudori, Ahsanun Naseh; Haris, M Syauqi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.717

Abstract

Lung cancer is a disorder of the lungs due to changes in respiratory tract epithelial cells which cause uncontrolled cell division and growth. Lung cancer is caused by several factors such as radiation exposure, smoking, heredity, gender, air pollution, and unhealthy lifestyles. Lung cancer can be detected when the cancer has entered an advanced stage. The large amount of lung cancer diagnosis data currently available can be used to predict lung cancer based on patterns in the data. One of the results of technological advances that can learn patterns in data is machine learning, which has currently made many positive contributions in the health sector. This research aims to predict lung cancer using a decision tree algorithm. This research produces rules based on decision trees which are built and then evaluated to produce the same accuracy, precision, recall, and F1-Score of 100%.
Perancangan Dashboard Vaksinasi dengan Kombinasi Design Sprint, Persona, Crazy 8’S, DAN MVP Anwar, David Saiful; Kusuma, Wahyu Teja; Haris, M. Syauqi
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.v9i2.789

Abstract

In carrying out the vaccination work program, the government is required to be able to take fast and appropriate policies while maintaining efficient use of funds in each work unit. One of the government work units that also focuses on vaccination is Kodam V/Brawijaya. The factors causing vaccination data to be uninformative in Kodam V/Brawijaya's ranks are that there are many 38 Kodam V/Brawijaya work units, Kodam V/Brawijaya does not yet have an integrated vaccination information system, the time and place for carrying out vaccination activities is short and moving. moving on, the presentation of data obtained from work units is still raw and uninformative data. Based on these problems, this research aims to design a vaccination dashboard application that suits the needs of users within the TNI Kodam V/Brawijaya area. The design of the vaccination application in this research used the design sprint method. The design sprint method was chosen because based on previous research it can be relied on to produce designs quickly and in accordance with user needs. In the stages of the design sprint method in this research, it will be combined with the persona, crazy 8's, and minimum viable product (MVP) methods. This research contributes to producing a new combination of methods to solve research problems in the field of application design. Finally, the combination of the design sprint method with persona, crazy 8's, and minimum viable product (MVP) is expected to produce a vaccination dashboard application design that meets the needs of Kodam V/Brawijaya.
Prediction Model for Diagnosing Heart Disease Using Classification Algorithm Pradini, Risqy Siwi; Anshori, Mochammad; Haris, M. Syauqi; Marilia, Busatto; Geraldo, Tostes
Journal of World Future Medicine, Health and Nursing Vol. 1 No. 2 (2023)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/health.v1i2.347

Abstract

Heart disease often causes death if not treated quickly and appropriately. Early diagnosis can prevent more serious complications and treat heart disease patients best. The existence of a disease prediction model can help health workers to diagnose diseases more quickly and accurately. The heart disease prediction model using a classification algorithm is a system built using machine learning techniques. The classification algorithm chosen is NN, Naive Bayes, Random Forest, and SVM because it is the best algorithm for predicting heart disease. This study makes a comparison of the four algorithms using a dataset of 918 instances with 11 features. The result is that the Random Forest algorithm produces the highest accuracy, with 86.8%, and has the best ability to distinguish classes based on the ROC curve.
Penerapan Teknik Cross-Validation untuk Menangani Overfitting pada Studi Kasus Implementasi Decision Tree untuk Prediksi Kanker Paru Faurika, Faurika; Naseh Khudori, Ahsanun; Haris, M. Syauqi
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 2 No. 2, Juli 2024
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v2i2.3631

Abstract

Lung cancer is a condition caused by cancer cells growing in the lungs. Lung cancer causes a weakened immune system, tumors, and other abnormalities that prevent the body from functioning properly. Lung cancer examination uses various technologies, namely CT Scan, X-ray, and others. However, the examination is relatively expensive and takes a long time. The use of machine learning makes it possible to support lung cancer diagnosis. With the large amount of medical data available today, machine learning can recognize patterns in the data so that it will help the process of diagnosing lung cancer more effectively. This study aims to correct overfitting in previous research which used the decision tree method to predict lung cancer with cross-validation techniques. In this research, we use a public dataset from Data World. This dataset consists of 25 data attributes and has 1000 data. The results of this research are rules obtained from decision trees which are then evaluated to produce 96.7% accuracy, 96.7% precision, 96.7% recall, and 96.7% f1-score. These results show that the decision tree method performs well in predicting lung cancer early and the cross-validation technique can overcome overfitting in decision trees with more general and stable results.
ANALISIS DAN VISUALISASI DATAPENDERITA PENYAKIT DBD DI SITUBONDO MENGGUNAKAN PLATFORM TABLEAU Basmalah Abirestu Maulisuriandhy; M. Syauqi Haris; Ahsanun naseh Khudori
Nusantara Hasana Journal Vol. 4 No. 2 (2024): Nusantara Hasana Journal, July 2024
Publisher : Yayasan Nusantara Hasana Berdikari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59003/nhj.v4i2.1159

Abstract

Cases of dengue fever in Situbondo are very fluctuating and unpredictable. This shows that dengue fever is still a problem that requires serious health attention. The infectious disease dengue fever is caused by the bite of the Aedes aegypti mosquito. Fluctuations in dengue fever cases are due to erratic rainfall. Sometimes rainfall is higher and the rainy season is longer. On the other hand, sometimes rainfall is relatively lower and the dry season is longer. This research aims to analyze and visualize data on dengue fever sufferers in Situbondo using the Tableau platform. The data used is map data per region or spatial data that has geographical references and historical data on dengue fever patients in Situbondo from 2016 to 2022. Data was obtained from the website Tanahair.indonesia.go.id and the Situbondo Community Health Center. The research results show that data visualization using Tableau can produce good, effective, interesting and efficient information. The results of data visualization of dengue fever sufferers in Situbondo showed that there were 2 cases of death. Cases of dengue fever sufferers are spread throughout all villages in Situbondo. It is hoped that the results of this research can help in adopting appropriate policies to control dengue fever in Situbondo.
Model Optimasi Model Optimasi Rute Transportasi Berbasis Pemrograman Linear Nazry, Hevlie Winda Nazry S; Ferdy Riza; Firahmi Rizky; Zuli Agustina Gultom; Muhammad Haris; Mika Debora Br Barus
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 4 No. 1 (2025): EDISI JANUARI 2025
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v4i1.10586

Abstract

Transportasi merupakan salah satu elemen penting dalam mendukung aktivitas logistik dan distribusi. Efisiensi dalam perencanaan rute transportasi dapat mengurangi biaya operasional, waktu tempuh, serta dampak lingkungan. Penelitian ini bertujuan untuk mengembangkan model optimasi rute transportasi berbasis pemrograman linear yang mampu memberikan solusi optimal dalam penentuan rute. Model ini mempertimbangkan berbagai parameter, seperti jarak, waktu, kapasitas kendaraan, dan batasan operasional. Pendekatan pemrograman linear untuk menemukan solusi optimal terkait penentuan rute pengiriman yang efisien, dengan memperhatikan berbagai kendala seperti kapasitas kendaraan, permintaan pelanggan, dan waktu pengiriman. Model ini terdiri dari fungsi objektif yang meminimalkan total biaya transportasi, sementara kendala yang diterapkan meliputi batasan kapasitas kendaraan, pemenuhan permintaan pelanggan, dan batasan waktu perjalanan. Hasil penelitian menunjukkan bahwa penerapan model ini berhasil menghasilkan solusi yang optimal, dengan mengurangi biaya total pengiriman secara signifikan, sekaligus memenuhi semua persyaratan dan batasan yang ada. Model ini memberikan kontribusi dalam peningkatan efisiensi pengelolaan rute transportasi dan dapat diadaptasi untuk berbagai jenis sistem distribusi yang lebih kompleks
Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering Haris, M Syauqi; Kurniawan, Tri Astoto; Ramdani, Fatwa
Journal of Information Technology and Computer Science Vol. 5 No. 3: Desember 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1330.912 KB) | DOI: 10.25126/jitecs.202053219

Abstract

Extractive Software Product Line Engineering (SPLE) puts features on the foremost aspect in domain analysis that needs to be extracted from the existing system's artifact. Feature in SPLE, which is closely related to system functionality, has been previously studied to be extracted from source code, models, and various text documents that exist along the software development process. Source code, with its concise and normative standard, has become the most focus target for feature extraction source on many kinds of research. However, in the software engineering principle, the Software Requirements Specification (SRS) document is the basis or main reference for system functionality conformance. Meanwhile, previous researches of feature extraction from text document are conducted on a list of functional requirement sentences that have been previously prepared, not literally SRS as a whole document. So, this research proposes direct processing on the SRS document that uses requirement boilerplates for requirement sentence statement. The proposed method uses Natural Language Processing (NLP) approach on the SRS document. Sequence Part-of-Speech (POS) tagging technique is used for automatic requirement sentence identification and extraction. The features are acquired afterward from extracted requirement sentences automatically using the word dependency parsing technique. Besides, mostly the previous researches about feature extraction were using non-public available SRS document that remains classified or not accessible, so this work uses selected SRS from publicly available SRS dataset to add reproducible research value. This research proves that requirement sentence extraction directly from the SRS document is viable with precision value from 64% to 100% and recall value from 64% to 89%. While features extraction from extracted requirement sentences has success rate from 65% to 88%.
MOBILE APPLICATION DEVELOPMENT FOR CHRONIC DISEASES RECORDING OF ARMY MEMBERS Haris, M Syauqi; Bagus Prasetyo Abdi , Benben; Teja Kusuma, Wahyu
Jurnal Mnemonic Vol 8 No 1 (2025): Mnemonic Vol. 8 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v8i1.13693

Abstract

Health services for army personnel play a crucial role in supporting military readiness and national defense. However, the current chronic disease data collection for army members is still conducted manually, causing inefficiencies in updating health information and hindering prompt promotive and preventive actions. This situation highlights the urgency for an integrated and accessible information system that allows health officers to monitor chronic illness cases more efficiently, especially in supporting early interventions and reducing curative and rehabilitative workloads. This research presents the development of a Mobile Device Application designed specifically for chronic disease data recording among army members, implemented in the Brawijaya Military Regional Health Unit (Kesdam V Brawijaya). The application, which is an expansion of the previously developed RAPI (Realtime Accountable Professional Integrative) system, utilizes Progressive Web App (PWA) technology to ensure accessibility and flexibility for users. The development followed the System Development Life Cycle (SDLC) methodology, with features tailored to stakeholder requirements, such as data grouping, diagnosis tracking, check-up history, and real-time reporting. The testing phase showed valid results for all system functionalities and confirmed compatibility across various smartphone types. The application successfully met all functional specifications and user needs, enabling faster access to health data, supporting preventive action planning, and reducing delays in chronic disease treatment monitoring. In conclusion, this application offers an effective, user-friendly, and scalable solution to improve health service delivery and chronic disease management for military personnel
ANALISIS KEBUTUHAN PENGGUNA APLIKASI MOBILE PEMESANAN LAYANAN KESEHATAN DI KLINIK PRATAMA MENGGUNAKAN USER PERSONA DAN USER JOURNEY Yaniar Ramdani, Dandi; Naseh Khudori, Ahsanun; Syauqi Haris, M
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.v9i4.13854

Abstract

Transformasi digital dalam pelayanan kesehatan menjadi prioritas untuk meningkatkan efisiensi dan aksesibilitas. Namun, banyak aplikasi kesehatan belum sepenuhnya memenuhi kebutuhan pengguna, dari sisi fungsionalitas maupun non-fungsionalitas. Berdasarkan data dari Kementerian Kesehatan, lebih dari 40% masyarakat masih belum memanfaatkan aplikasi kesehatan yang tersedia, termasuk untuk pemesanan layanan. Hal ini juga menjadi masalah bagi klinik pratama yang belum memiliki sistem digital, sehingga proses pendaftaran, pencatatan rekam medis, akses informasi manual menghambat pasien dan tenaga kesehatan dalam mengelola layanan kesehatan. Penelitian ini bertujuan untuk menganalisis kebutuhan pengguna dalam pengembangan aplikasi pemesanan layanan kesehatan di klinik pratama menggunakan pendekatan User Persona dan User Journey. Penelitian ini menggunakan mixed methods dengan pendekatan exploratory sequential design. Pendekatan ini bertujuan mengeksplorasi kebutuhan pengguna melalui wawancara mendalam dan observasi langsung sebelum divalidasi dengan data kuantitatif, hasilnya rekomendasi fitur akurat dan berbasis bukti. Analisis data kualitatif dilakukan secara tematik untuk menyusun user persona dan memetakan user journey dilanjutkan analisis data kuantitatif guna memperkuat temuan data kualitatif berupa prioritas fitur. Hasil analisis menunjukkan fitur dengan prioritas tertinggi adalah janji temu dengan dokter (skor 74), pendaftaran online (skor 72), Rekam Medis Elektronik (skor 72), pembayaran online (skor 71), fitur nomor antrian digital (skor 66), dan jadwal dokter (skor 64) menjadi bagian penting dalam meningkatkan efisiensi layanan. Dari aspek non-fungsionalitas, kebutuhan utama meliputi keamanan dan privasi data (skor 74), kecepatan dan performa aplikasi (skor 73), kemudahan penggunaan (skor 73). Temuan ini memberikan kontribusi signifikan dalam perancangan aplikasi mobile yang lebih responsif dan sesuai kebutuhan pengguna, baik dari sisi pasien maupun tenaga kesehatan.
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