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All Journal Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology Network Engineering Research Operation [NERO] Zeta - Math Journal JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal Informatika dan Rekayasa Perangkat Lunak Scientific Journal of Informatics Jurnal Nasional Teknologi Terapan KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Rinci Kembang Hapsari
Institut Teknologi Adhi Tama Surabaya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mathematics Other

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Sistem Rekomendasi Film Dengan Menggunakan Sentiment Analysis dan Collaborative Filtering Fikry, Muhamad Agus; Wardhana, Septiyawan Rosetya; Hapsari, Rinci Kembang
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 5, No 2 (2024)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2024.v5i2.7635

Abstract

Seiring pesatnya perkembangan digital pada saat ini, zaman semakin maju berbagai macam file bisa diakses dari internet. Begitu juga dengan film yang sering kita tonton dari TV sekarang bisa diakses dari internet dengan mudah. Banyak peminat film yang kadang masih bingung ketika ingin menonton film. Mengacu pada uraian tersebut, dalam penelitian ini, membangun sebuah sistem yang dapat memberikan rekomendasi film. Collaborative filtering adalah metode yang sering digunakan dalam hal rekomendasi dan Sentiment analysis digunakan untuk menentukan pola sentiment dari user serta menggunakan bahasa pemrograman python 3 untuk menghitung proses-proses pada sistem yang akan dibuat. Dari acuan dan juga metode tersebut tujuan dari penelitian ini adalah membangun sistem rekomendasi menggunakan metode Collaborative Filtering dan Sentiment Analysis terhadap ulasan pada film. Pengujian dilakukan sebanyak 5 kali uji coba, dimana hasil belum bisa memenuhi harapan dalam merekomendasikan, karena rata-rata nilai rekomendasi masih 32%.
Rancang Bangun Aplikasi Resto Berbasis Mobile Menggunakan Metode Personal Extreme Programming Hadad, Heksa Bustomi; Hapsari, Rinci Kembang; Hakim, Permana Faddyahsari
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2025: SNESTIK V
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2025.7623

Abstract

In the current era of globalization, technological developments are taking place very rapidly, including the development of information and communication technology; one of the steps in the development of information and communication technology is the development of telecommunications technology, especially smartphones. The development of smartphone technology has influenced various fields, including the culinary field. Kebon Kota Tropical Resto is a company in the culinary field. Currently, Kebon Kota Tropical Resto still uses a manual ordering method to order food and drinks, and it takes a long time to deliver consumer orders because of the long distance between kitchens, illegible handwritten orders, order slips, forgotten orders, and long queues. Therefore, an application is needed that makes it easier for customers to order food and drink menus. In developing this restaurant application, one of the agile development models has been used, namely the personal extreme programming model. In the personal extreme programming model, there are various stages: requirements, planning, iteration initialization, design, implementation, system testing, and retrospective. Based on the ISO 9126 evaluation with 50 respondents, the value of each criterion was obtained. Namely, the Usability value was 86.72%, the Functionality value was 86%, the Efficiency value was 86.53%, and the overall value of the application quality was 86.16%. Based on these values, the Kebon Kota Tropical Resto application is outstanding.
Implementasi Algoritma K-Nearest Neighbor Dalam Prediksi Penyakit Jantung Ardiansyah, Arif; Juan; Sirri, Latiful; Hapsari, Rinci Kembang; Santoso, Syahrul Riza Andi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 2 (2025): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Heart failure is a serious and pressing health problem that affects millions of people worldwide. Several factors influence the occurrence of heart failure, such as age, type of pain, blood pressure, cholesterol levels, and other risk factors associated with heart disease. With current technological developments, data mining and machine learning can be used to predict patient health conditions. Therefore, the problem of this research is how to implement data mining techniques for identifying heart disease. The goal of the study is to identify heart disease and prevent heart failure. This study utilises the K-Nearest Neighbour (k-NN) algorithm to estimate the likelihood of patients experiencing heart failure based on available data features. The data used is taken from the kaggle.com site, which includes information from patients diagnosed with heart failure and those who do not suffer from heart failure. The analysis process involves data processing steps, such as normalisation, feature grouping, and selecting the optimal K parameter for the k-NN algorithm. Evaluation is carried out by calculating the accuracy, precision, recall, and F1-score values. Testing is carried out on a dataset with 299 patient data, which is divided into training data and test data with a ratio of 80:20. The results of this study indicate that the k-NN algorithm has an accuracy of 87% in predicting kidney failure. This result indicates that the k-Nearest Neighbour algorithm can effectively predict heart failure.
Classification of Diabetes Mellitus using Decision Trees Hapsari, Rinci Kembang; Salim, Abdullah Harits; Oktavian, Leonardo Fahsi; Fitra, Aldy Ramadhan
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 9 No. 2 (2025)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v9i2.1461

Abstract

Diabetes Mellitus is a global health concern, with its prevalence and incidence rising sharply world-wide, including in Indonesia. Several factors contribute to the onset of diabetes mellitus, such as heredity, age, weight, and blood pressure. Managing blood sugar levels, maintaining a balanced diet, exercising regularly, and undergoing early screening when necessary are among the key measures to prevent and control this disease. Early diagnosis is essential to reduce both the number of cases and the associated risks. This study aims to detect diabetes mellitus using classification techniques. The method involves several subprocesses within the classification procedure. The first stage, data preprocessing, includes feature selection and data cleaning. The resulting preprocessed data are then used in the classification stage, specifically the learning subprocess, to generate a decision tree model. Model construction employs pruning, followed by training and performance evaluation. The study utilizes a diabetes dataset obtained from kaggle.com, consisting of 768 records. The dataset includes attributes such as Pregnancies, Glucose, Blood Pressure, Skin Thickness, Insulin, Body Mass Index (BMI), Diabetes Pedigree Function, Age, and the label Outcome. Testing was conducted using decision trees with maximum depths of 3, 5, 7, 10, and 15. The results show that the highest accuracy (88.56%) occurred at a maximum depth of 5, while the highest recall (100%) was achieved at a depth of 3. The highest precision (47.37%) and specificity (95.85%) were also obtained at a depth of 3.
Klasifikasi Penderita Penyakit Diabetes Berdasarkan Decision Tree Menggunakan Algoritma C4.5 Hapsari, Rinci Kembang; Wahyu, Bagas Aulifia Riski Putra; Farozi, Achmad Fayi; Mahendra, Caesario Putra
INTEGER: Journal of Information Technology Vol 8, No 1 (2023): Maret
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2023.v8i1.4423

Abstract

Diabetes is a metabolic disease characterized by high blood sugar levels (hyperglycemia) caused by a lack of insulin or the ineffectiveness of insulin in regulating glucose metabolism. In addition there are other factors that cause diabetes such as heredity, weight, age, blood pressure and so on. It is estimated that the death rate caused by diabetes will continue to increase every year. Treatment of diabetes can be done by controlling blood sugar levels, eating a healthy diet, exercising regularly, and if necessary, carrying out early checks to reduce the risk of developing diabetes. Therefore it is necessary to have an early diagnosis which is expected to reduce diabetes and reduce complications of diabetes in the future. One thing that can be done is to apply the method contained in data mining, namely utilizing the classification method using the C4.5 algorithm which can produce more accuracy. Classification can be used as early treatment of this disease. Algorithm C4.5 is an algorithm that is used to form a decision tree. From the test results, it produces a fairly large accuracy, namely 85% Precision of 92%, and Recall of 85%.
Pengembangan Sistem Kasir Berbasis Website Pada "Bang Aji Kebab" Menggunakan Model Agile Anshar, Moch Yusuf; Hapsari, Rinci Kembang; Sugiyanto, Sugiyanto
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 6, No 2 (2025)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2025.v6i2.8375

Abstract

The Bang Aji Kebab culinary business in Surabaya continues to experience growth in terms of branch expansion and transaction volume, thus requiring more effective operational management. However, the sales transaction recording process is still carried out manually, which often leads to issues such as recording errors, inaccurate sales data, and delays in preparing financial and stock reports. Based on these problems, a web-based cashier system was developed as a digital solution to support operational processes, transaction recording, and stock analysis automatically, in real time, and in an integrated manner. The development method used is the Agile Model through the timebox planning stage, implemented using the Laravel 11 framework and MySQL database, and tested using the Black-Box Testing method. System quality evaluation refers to the ISO 9126 standard, which includes Usability, Accessibility, Security, and Reliability aspects. The research results show that the system operates according to operational needs, with main features such as product management, cashier transactions, receipt printing, and sales analysis functioning optimally. Functional testing using Black-Box Testing produced results that met expectations, while software quality assessment based on ISO 9126 obtained an average score of 87.25% with a "very good" category. In conclusion, this web-based cashier system is capable of accelerating transaction processes, improving the accuracy of sales recording, and providing sales analysis reports that can support business decision-making more effectively.
Perancangan Sistem Kehadiran Berbasis Website Dengan Integrasi Geolokasi Untuk Karyawan MI Al- Amin Menggunakan Metode Agile Arinal, Fatahillah; Hapsari, Rinci Kembang
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 6, No 2 (2025)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2025.v6i2.8431

Abstract

This study develops a website-based attendance system with geolocation integration for MI Al-Amin employees using the Agile method. The system aims to replace manual attendance, which often leads to fraud and inefficiency. The development process involves the Agile model, which includes timebox planning, daily stand-up meetings, demonstrations, and retrospective meetings. Needs analysis was carried out through interviews, the system was designed using UML, and it was implemented as a web application that supports location-based attendance, employee management, leave management, and attendance reporting. Unit testing, integration testing, system testing, and user acceptance testing confirm that the application meets user needs, with black-box testing used throughout the process. System quality evaluation follows the ISO 9126 standard, focusing on reliability, accessibility, security, and usability. A total of 28 respondents assessed the system using a Likert scale, resulting in an average score of 82.14%, categorized as satisfactory. These results indicate that the attendance system is feasible for use, although it still requires enhancements to security and user interface comfort.
Penerapan Algoritma K-Medoids Clusetering Untuk Rekomendasi Menu dan Strategi Stok Bahan Baku Rinci Kembang Hapsari; M Safi Anwar Anas; Reza Zulkifli Ferdiansyah; Hanif Prasetyo; Mochamad Muhajir
Jurnal Ilmiah Informatika Vol. 9 No. 1 (2024): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v9i1.30-38

Abstract

Kedai kopi yang merupakan sebuah tempat yang menyediakan minuman kopi maupun minuman panas lainnya. Banyak pelanggan terutama anak muda yang berkunjung ke kedai kopi untuk menikmati makanan dan minuman sambil bersantai. Seiring pertumbuhan kedai kopi yang semakin meningkat dikarenakan tempat yang modern serta harga makanan dan minumannya yang terjangkau. Dalam berkompetisi service kedai kopi kepada pelanggan, banyak kedai kopi yang mengembangkan varian/ jenis minimum dan makanan yang dijual di kedai kopi. Banyaknya varian makanan dan minuman membuat pelanggan memerlukan waktu yang agak lama dalam memilih menu, dan juga membuat kesulitan bagian pembelian pada saat menyediakan stok bahan baku. Sehingga pada penelitian ini bertujuan untuk mengelompokkan menu yang ada di kedai kopi menjadi 2 cluster, yaitu cluster menu yang laku dan cluster menu cukup laku. Dalam penelitian ini dilakukan proses klasterisasi terhadap data penjualan menu kedai kopi dengan mengimplementasikan algoritma k-medoids. Dan dapat mengetahui setiap anggota dari cluster 1 dan setiap anggota dari cluster 2. Dari pengujian yang telah dilakukan, dapat membantu para pelanggan dan pengusaha kedai kopi untuk mendukung strategi pembelian. Dengan melihat menu cluster 1, dapat dijadikan sebagai informasi rekomendasi menu sehingga konsumen lebih mudah dalam memilih menu minuman dan makanan di kesai kopi. Selain itu juga dapat dijadikan sebagai dasar untuk melakukan pembelian bahan baku makanan dan minuman.
Co-Authors Adi, Danu Septi Aditya, Andre Fransisco Aji, Rega Wahyu Alamsyah, Mochamad Tegar Bagas Anshar, Moch Yusuf Ardiansyah, Arif Arinal, Fatahillah Arma Adzhana Mahran Audrey, Talitha Naifa Azmuri Wahyu Azinar Chanafi, Moch Irfan Dian Puspita Hapsari Farozi, Achmad Fayi Fikry, Muhamad Agus Fitra, Aldy Ramadhan Gutierres, Ego Prasetyo Ho H, Luky Agus Hadad, Heksa Bustomi Hakim, Permana Faddyahsari Hanif Prasetyo Hendro Nugroho Hendro Nugroho Hendro Nugroho, Hendro Irmayanti, Sivana Amelia Islamiyah, Mitha Juan Lande, Gamaliel Virani Fofid Limanjaya, Rafi Oktaviano Eka Luky Agus Hermanto Luky Agus Hermanto, Luky Agus M Safi Anwar Anas Maftahatul Hakimah Maftahatul Hakimah, Maftahatul Mahatma, Adhitya Arie Mahendra, Caesario Putra Mochamad Muhajir Navaro, Kamal Fauzan NUR SULAIMAN Nur Sulaiman Oktavian, Leonardo Fahsi Putri, Chatarina Natassya Rewina, Anggita Eka Reza Zulkifli Ferdiansyah Salim, Abdullah Harits Santoso, Syahrul Riza Andi Sirri, Latiful Siti Maimunah Siti Maimunah Sugiyanto - Sugiyanto, Sugiyanto Titus Kristanto Tukadi Tukadi, Tukadi Tutuk Indriyani Ubaidillah, M Ravi Vandaningtyas, Andriany Vinda Setia Nita Vinda Setia Nita, Vinda Setia Wahyu, Bagas Aulifia Riski Putra Wardana, Septiyawan Rosetya Wardhana, Septiyawan Rosetya Widodo, Muhammad Amiruddin Wijaya, Abdul Hamid