Lab-IS/filkom-research-papers huggingface dataset:
Penyusunan Standard Operating Procedure untuk Software Management dan Software Development pada Perusahaan XYZ berdasarkan Pedoman Information Technology Infrastructure Library
Authors: Dwi Cindy Herta Turnip, Admaja Dwi Herlambang, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2020
Topics: Software Engineering; IT Management
Abstract: Perusahaan XYZ adalah salah satu Badan Usaha Milik Negara (BUMN). Perusahaan XYZ dalam mengelola Teknologi Informasi-nya wajib mengikuti Peraturan Menteri BUMN nomor PER-03/MBU/02/2018. Menanggapi peraturan BUMN tesebut, Perusahaan XYZ membentuk RITI 2018-2022. Rencana tersebut menjelaskan bahwa Perusahaan XYZ akan menyusun Pedoman Tata Kelola TI yang berisi SOP (Standard Operating Procedure) dan juga Peraturan Direksi pada tahun 2018/2019. Pembentukan SOP TI tersebut berpedoman pada ITIL (Information Tecnology Infrastructure Library) domain Software Development and Management. Dalam menyusun SOP tersebut, pertama akan dilakukan wawancara dengan Departemen Pengembangan dan Pemeliharaan Sistem (PPS) sebagai peran yang bertanggung jawab pada proses Software Development dan Software Management. Lalu akan dilakukan analisis GAP untuk mengetahui kesenjangan antara kondisi saat ini dan kondisi ideal di perusahaan. Dari hasil kesenjangan tersebut akan muncul usulan untuk menyetarakannya. Usulan ini nantinya akan dimasukkan ke dalan aktivitas yang disusun dengan format flowchart pada Rancangan SOP yang dihasilkan nantinya. Hasil akhirnya adalah rancangan SOP untuk proses Software Development yang menghasilkan 6 aktivitas dan 16 sub-aktivitas. Selain itu juga menghasilkan SOP untuk proses Software Management yang menghasilkan 5 aktivitas dan 12 sub-aktivitas.
RAINFALL FORECASTING MODEL USING ADALINE AND REGRESSION ALGORITHM
Authors: Arief Andy Soebroto, Ery Suhartanto
Journal: HATHI 6th International Seminar on Advancement of Water Resources Management in a Global Challenge
Year: 2020
Topics: Machine Learning; Regression Analysis
Abstract: High rainfall intensity could cause flooding or inundation which needs to be forecasted to estimate the amount of rainfall that will come. Forecasting is the process of making future predictions based on past and present data and most commonly with trend analysis. Computational models can be used using artificial statistics and statistics. The advantage of forecasting using artificial intelligence is able to calculate with non-linear data and limited parameters while statistical forecasting is the opposite. Adaptive Linear Neuron (ADALINE) is one of the learning algorithms of the artificial neural network algorithm. The learning algorithm is able to recognize historical data patterns so that it can provide future pattern predictions. This study have compared the performance of computational models using ADALINE artificial intelligence with statistical computing models, namely regression. The rainfall data used was the rainfall …
Optimasi Analytic Hierarchy Process (AHP) dalam Penerimaan Siswa Baru pada Sekolah Menengah Kejuruan menggunakan Algoritme Evolution Strategies
Authors: Maya Febrianita, Edy Santoso, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2019
Topics: Decision Making; Optimization Algorithms
Abstract: Penerimaan siswa baru merupakan kegiatan yang dilakukan setiap memasuki awal masa sekolah. Salah satunya juga diterapkan pada Sekolah Menengah Kejuruan (SMK). Lulusan SMK ditujukan sebagai lulusan siap kerja yang memiliki potensi lebih dibandingkan dengan sekolah yang sederajat. Hal ini tentu dapat menimbulkan masalah jika seleksi yang dilakukan kurang maksimal. Untuk menyelesaikan masalah tersebut maka diterapkan metode Analytic Hyrarchy Process (AHP) dan algoritme Evolution Strategies (ES). Algoritme ES akan melakukan optimasi bobot dari proses AHP. Algoritme ini memiliki panjang kromosom sebanyak 6 gen, yang setiap gen mewakili nilai tiap elemen matrik bobot. Reproduksi yang dalam kasus ini hanya mutasi tanpa rekombinasi. Di dalam proses evaluasi terdapat proses AHP untuk menentukan hasil penerimaan yang kemudian akan dihitung nilai fitness dengan menggunakan rumus akurasi. Metode seleksi yang digunakan yaitu ellitsm selection. Berdasarkan penelitian yang telah dilakukan diperoleh hasil optimal dengan parameter ukuran populasi sebanyak 60, ukuran offspring sebanyak 50 dan banyak generasi 16 dengan nilai fitness 0, 8798 atau dengan akurasi 87, 98%. Hasil akhir yang akan ditampilkan kepada user adalah hasil penerimaan siswa baru.
Pembangunan Kakas Bantu Perhitungan Kualitas Kode (Quality Rate) menggunakan Metrik Perangkat Lunak
Authors: Odhia Yustika Putri, Bayu Priyambadha, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2019
Topics: Software Engineering; Software Development
Abstract: Perangkat lunak yang berkualitas adalah perangkat lunak yang tidak memiliki defisiensi kode. Sebelumnya Beranic dkk pada tahun 2018 melakukan penelitian berjudul â€ œTowards a Reliable Identification of Deficient Code with a Combination of Software Metricsâ€ mengenai penggunaan kombinasi 8 (delapan) jenis metrik perangkat lunak berorientasi objek untuk mendeteksi defisiensi kode pada perangkat lunak tersebut. Pendeteksian defisiensi kode ini dapat digunakan pada perhitungan kualitas kode (quality rate) yang dapat menjadi acuan baik buruknya perangkat lunak tersebut. Pada penelitian tersebut perhitungan metrik dilakukan dengan menggunakan kakas bantu terpisah untuk menghitung kualitas kode, sehingga membutuhkan waktu dan sumber daya yang banyak. Oleh karena itu, pada penelitian ini dibangunlah kakas bantu perhitungan kualitas kode menggunakan metrik perangkat lunak. Pembangunan kakas bantu dilakukan menggunakan metode siklus hidup perangkat lunak Waterfall dan dibangun dalam bahasa pemrograman Java. Kakas bantu dapat berjalan pada platform desktop dan menggunakan berkas proyek Java sebagai masukannya. Kakas bantu ini menghasilkan 3 kebutuhan fungsional dan 1 kebutuhan non-fungsional. Perancangan kakas bantu ini dilakukan dengan berorientasi objek dan menghasilkan 1 class diagram, 3 sequence diagram, 5 rancangan algoritme, dan 3 rancangan antarmuka. Implementasi kakas bantu ini dilakukan sesuai rancangan menggunakan library JavaFX dan ASTParser. Hasil pengujian white-box dan black-box yang telah dilakukan menunjukkan bahwa kakas bantu ini …
Sistem Pakar Deteksi Kenakalan Remaja di Sekolah Menggunakan Modified K-Nearest Neighbor (MKNN)
Authors: Asrul Syawal, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2019
Topics: Machine Learning; Expert Systems
Abstract: Kenakalan remaja salah satu permasalahan yang dihadapi orang tua dalam membimbing anak. Kenakalan remaja sering terjadi didunia pendidikan teruitama disekolah hal ini menjadi perhatian bagi orang tua, selain orang tua, guru sebagai pembimbing di sekolah ikut aktif dalam membimbing siswa di sekolah agar terhindar dari kenakalan remaja dan berprilaku baik dan positif dilingkungan sekolah maupun lingkungan luar sekolah. Untuk menghindari kenakalan di sekolah dilakukan pencegahan dengan melakukan deteksi kenakalan yang mungkin akan terjadi pada anak berdasarkan faktor atau gejala-gejala perilaku yang sering dilakukan oleh anak. Pada penelitian ini dibuat suatu sistem untuk mendeteksi kenakalan remaja khsusnya disekolah untuk mencegah kenakalan yang mungkin terjadi menggunakan metode Modified K-Nearest Neighbor (MKNN). Metode MKNN merupakan metode …
Pengembangan Sistem Aplikasi Penentuan Prioritas Kasus Uji Berbasis Lexicographical Ordering
Authors: Lailatul Rizqi Ramadhani, Bayu Priyambadha, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2019
Topics: Software Development; Lexicographical Ordering
Abstract: Penentuan prioritas kasus uji merupakan salah satu strategi yang dapat mengurangi biaya pengujian regresi. Teknik penentuan prioritas kasus uji berdasarkan lexicographical ordering merupakan suatu teknik yang dinilai paling unggul berdasarkan nilai rata-rata laju deteksi kesalahan (APFD). Untuk menentukan prioritas kasus uji, teknik ini menggunakan informasi coverage dari setiap kasus uji. Hingga saat ini belum ada penelitian yang mengimplementasikan teknik tersebut ke dalam sistem. Penelitian juga menunjukkan bahwa proses menentukan prioritas menggunakan code coverage membutuhkan biaya yang besar dari segi waktu dan resource. Karena semakin banyaknya jumlah kasus uji, maka semakin besar pula ukuran informasi coverage yang harus dibaca. Oleh karena itu, penelitian ini mengembangkan sistem aplikasi penentuan prioritas kasus uji berdasarkan lexicographical ordering tersebut. Sistem ini bertujuan untuk membantu proses membaca informasi coverage dan menentukan prioritas kasus uji secara otomatis. Sehingga adanya sistem ini diharapkan dapat mempercepat penentuan prioritas kasus uji. Hasil pengujian sistem menunjukkan bahwa sistem memiliki akurasi 100% dengan waktu membaca informasi coverage tiap kasus uji dan menghitung prioritas kasus uji dalam waktu kurang dari 8 detik. Makalah ini akan merangkum tahapan yang dilakukan peneliti dalam mengembangkan sistem aplikasi tersebut. Tahapan yang dijelaskan mulai dari tahap pendahuluan, metodologi penelitian, hasil dan pembahasan, serta penarikan kesimpulan dari penelitian.
Pengembangan Aplikasi Pemindaian Kode Pengujian Unit (Studi Kasus: PT Global Digital Niaga)
Authors: Ade Wija Nugraha, Bayu Priyambadha, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2019
Topics: Software Development; Quality Assurance
Abstract: Pengujian unit merupakan salah satu fase pada pengujian perangkat lunak, tetapi masih terdapat beberapa programmer yang enggan melakukan fase pengujian unit. Permasalahan tersebut juga terjadi pada perusahaan PT. Global Digital Niaga. Masih terdapat beberapa programmer pada perusahaan yang tidak memperhatikan kualitas dari kode pengujian unit yang dibuat dan hanya memperhatikan nilai dari cakupan kode pengujian unitnya saja. Maka dari itu, peneliti melakukan pengembangan aplikasi yang dapat digunakan untuk melakukan pemindaian kode pengujian unit dan dapat menampilkan kesalahan penulisan berdasarkan aturan yang telah dibuat oleh perusahaan. Proses pemindaian dimulai dengan mencari informasi dari proyek yang diunggah. Kemudian, aplikasi memindai kode produksi dan kode pengujian unit dengan menggunakan library JavaParser. Setelah itu, aplikasi menganalisa setiap kode pengujian unit yang dipindai apakah kode tersebut sesuai dengan aturan penulisan atau tidak. Kemudian, aplikasi menyimpan hasil pemindaian dan menampilkannya. Tahap pertama dari penelitian ini yaitu studi literatur. Kemudian, tahap rekayasa kebutuhan yang menghasilkan 25 kebutuhan fungsional dan 2 kebutuhan non-fungsional. Selanjutnya tahap perancangan dan diikuti tahap implementasi dengan membuat aplikasi berbasis website. Setelah itu, tahap pengujian dengan nilai 100% pass, 100% valid, dan 100% akurat untuk pengujian unit, validasi, dan akurasi. Aplikasi juga dapat dijalankan pada delapan browser berbeda untuk pengujian kompatibilitas.
Pembangunan Kakas Bantu Pembangkitan Kasus Uji Black-Box Berdasarkan Skenario Penggunaan Sistem
Authors: Laode Muhamad Fauzan, Bayu Priyambadha, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2019
Topics: Software Testing; Software Development
Abstract: Umumnya, pengujian perangkat lunak dibagi menjadi 3 fase, yaitu pembuatan kasus uji, eksekusi kasus uji dan evaluasi pengujian. Pengujian perangkat lunak adalah proses yang memakan waktu dan sumber daya yang banyak. Salah satu cara untuk mengurangi waktu dan usaha pada pengujian adalah dengan melakukan otomatisasi pada pembuatan kasus uji. Kasus uji dapat diturunkan dari skenario penggunaan sistem. Kasus uji ini disebut kasus uji black-box. Skenario penggunaan sistem yang akan dipakai adalah skenario dengan format Cockburn. Untuk mentransformasi skenario penggunaan sistem, penelitian ini menggunakan pemrosesan bahasa alami dan model EFSM (Extended Finite State Machine). Pemrosesan bahasa alami akan digunakan untuk membangun tabel aktivitas. Tabel aktivitas akan dimodelkan dengan EFSM dan kemudian ditelusuri untuk menghasilkan kasus uji. Kakas bantu dibangun dengan teknologi Java yang memungkinkan sistem dapat dijalankan pada platform yang mendukung JRE (Java Runtime Environment). Kakas bantu pembangkitan kasus uji diuji menggunakan pengujian unit, pengujian integrasi, dan pengujian validasi. Pengujian unit dan pengujian integrasi dilakukan dengan menggunakan metode whitebox dan pengujian validasi dengan menggunakan black-box. Sistem dapat mengenerasi kasus uji dari 20 use case scenario dalam waktu kurang dari 120 detik.
Pengembangan Sistem Aplikasi Penjadwalan Pendampingan Mahasiswa Disabilitas (Studi Kasus: Pusat Studi dan Layanan Disabilitas Universitas Brawijaya)
Authors: Dama Yuliana, Bayu Priyambadha, Arief Andy Soebroto
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2019
Topics: Software Development; Disability Services
Abstract: Penjadwalan merupakan proses yang untuk melakukan pembagian waktu secara terperinci sesuai dengan kegiatan yang direncanakan. Namun, apabila proses penjadwalan tidak dilakukan secara tepat maka akan menimbulkan masalah seperti yang terjadi di Pusat Studi dan Layanan Disabilitas Universitas Brawijaya (PSLD). Proses penyusunan jadwal yang saat ini dilakukan di PSLD adalah dengan cara menual sehingga seringkali ditemukan adanya jadwal yang bentrok karean faktor human error. Selain itu, sistem penjadwalan tersebut masih sulit untuk dilakukan pergantian volunteer apabila volunteer yang dijadwalkan tidak dapat melakukan pendampingan. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan sistem penjadwalan yang dapat meminimalisis adanya human error dan memudahkan dalam melakukan pergantian volunteer. Pengembangan sistem ini dilakukan melalui beberapa tahapan yaitu: analisis kebutuhan, perancangan, implementasi, dan pengujian sistem. Pengembangan sistem dilakukan dengan pendekatan berorientasi objek. Metode pengembangan perangkat lunak yang digunakan adalah prototype dengan 2 iterasi. Implementasi sistem dilakukan dengan menggunakan bahasa pemrograman PHP dengan bantuan framework CodeIgniter dan Bootstrap. Pengujian dilakukan dengan pendekatan white-box testing dengan pengujian unit menggunakan metode basis path testing dan pengujian black-box testing dengan pengujian validasi. Hasil dari penelitian ini menunjukan bahwa sistem diimplementasikan sesuai dengan kebutuhan pengguna yang telah didefinisikan, ditunjukan dari hasil …
DETEKSI BIOMETRIK UNIMODAL SEBAGAI IDENTITAS DAN KEAMANAN DATA SUMBER DAYA MANUSIA
Authors: Arief Andy Soebroto, Nurul Hidayat, Rekyan Regasari
Year: 2024
Topics: Biometrics; Human Resources
TRANSFORMER UNTUK KLASIFIKASI FUNGSI SENYAWA AKTIF BERDASARKAN STRUKTUR MOLEKUL
Authors: Dian Eka Ratnawati, Agus Wahyu Widodo, Rekyan Regasari
Year: 2023
Topics: Deep Learning; Chemistry
Analisis sentimen pemindahan ibu kota Indonesia pada media sosial Twitter menggunakan metode LSTM dan Word2Vec
Authors: Yunico Ardian Pradana, Imam Cholissodin, Diva Kurnianingtyas
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2023
Topics: Natural Language Processing; Deep Learning
Abstract: Pemindahan ibu kota negara dari DKI Jakarta ke Pulau Kalimantan telah menimbulkan perdebatan dan meningkatkan minat publik terhadap isu tersebut. Twitter menjadi media sosial yang populer untuk menyampaikan pendapat dan aspirasi masyarakat. Oleh karena itu, penelitian ini bertujuan untuk menganalisis sentimen masyarakat terkait pemindahan ibu kota menggunakan metode analisis sentimen. Dalam penelitian ini, metode Deep Learning, khususnya Long Short Term Memory (LSTM) dan word2vec yang digunakan untuk menganalisis sentimen tweet masyarakat. Dengan menerapkan metode LSTM dengan Word2Vec, diharapkan dapat diklasifikasikan apakah tweet masyarakat bersifat positif atau negatif terkait pemindahan ibu kota. Model LSTM yang dikembangkan dalam penelitian ini menghasilkan akurasi sebesar 95%, precision sebesar 93%, recall sebesar 93%, dan F1-measure sebesar 95%. Hasil tersebut menunjukkan bahwa metode ini efektif dalam menganalisis sentimen masyarakat terkait pemindahan ibu kota dan dapat memberikan pemahaman yang lebih baik mengenai pandangan publik terhadap perubahan tersebut.
Sentiment analysis model for klikindomaret android app during pandemic using vader and transformers NLTK library
Authors: Akhmad Ghiffary Budianto, Budisantoso Wirjodirdjo, Iffan Maflahah, Diva Kurnianingtyas
Year: 2022
Topics: Natural Language Processing; Machine Learning
Abstract: COVID-19 has changed the Indonesian people’s shopping habits for consumer goods. The online retail application came as a response to social distancing and stay-at-home advice. KlikIndomaret is an online retail application that uses the omnichannel concept. As the number of downloads increased, the number of various comments and sentiments on that application also increased. In this study, the researcher did a sentiment analysis aimed to improve the quality of application experiences and retail services. The result of the analysis reflected the services given to customers thus far. The data included reviews and star ratings derived from 4,066 reviews which went under the process of data pre-processing. The methods used in this study were VADER and NLTK, improved by Transformer, without pre-training data. These methods could filter the users’ reviews with sarcasm tone. The results were sentiment …
A hybrid symbiotic organisms and variable neighborhood searches to minimize response time
Authors: Diva Kurnianingtyas, Muhammad Isnaini Hadiyul Umam, Budi Santosa
Journal: AIP Conference Proceedings
Year: 2097
Topics: Optimization; Swarm Intelligence
Abstract: Medical Emergency Services (MES) are an important element in the modern healthcare system. MES become an important issue because it plays an essential role in saving lives and reducing mortality and disability. The ability of MES is to save lives depending on the time it takes for an ambulance to arrive on the scene after an emergency call received. The purpose of this study is to overcome the problems in the limitation of the number of ambulances required and the minimization of response time. This paper develops the hybrid of Symbiotic Organisms Search and Variable Neighbourhood Search to determine the location and amount of ambulance to be allocated. Our findings showed that for the current system, the ideal limit time is 15 minutes, considering the amount of demand that can be covered. This scenario is able to produce a response time of around 13 minutes and is able to meet the entire demand …
Synthesis of batik motifs using a diffusion-generative adversarial network
Authors: One Octadion, Novanto Yudistira, Diva Kurnianingtyas
Journal: Multimedia Tools and Applications
Year: 2025
Topics: Deep Learning; Computer Vision
Abstract: This paper presents a novel approach for generating intricate Batik motifs using a modified Diffusion-Generative Adversarial Network (Diffusion-GAN) augmented with StyleGAN2-Ada. Motivated by the rich cultural heritage of Indonesian Batik, our research addresses the challenge of synthesizing high-quality, diverse patterns that capture the artistry and complexity of traditional designs. Traditional generative models often struggle with stability and fidelity in artistic synthesis. We integrate StyleGAN2-Ada and Diffusion techniques to overcome these limitations, optimizing model architecture and employing a curated Batik dataset. Evaluation metrics including Frechet Inception Distance (FID), Kernel Inception Distance (KID), precision, recall, and non-redundancy assess the quality and diversity of generated motifs. Our results demonstrate significant advancements in the realism and authenticity of synthesized Batik …
Machine Learning
Authors: Lailil Muflikhah, Wayan Firdaus Mahmudy, Diva Kurnianingtyas
Year: 2023
Topics: Machine Learning
Abstract: Machine Learning merupakan cabang dari kecerdasan buatan yang memungkinkan komputer untuk mempelajari pola-pola yang terdapat dalam data agar dapat melakukan prediksi setelah melalui proses pembelajaran. Banyak permasalahan nyata dalam kehidupan sehari-hari dapat diselesaiksan dengan metode pembelajaran, meliputi: prediksi, klasifikasi, rekomendasi, ataupun pengelompokan suatu obyek benda atau kasus tertentu. Buku Ajar Machine Learning ini dimulai dari konsep dasar metode pembelajaran mesin, representasi data, dan pemrosesan awal data. Kemudian dilanjutkan dengan pendekatan secara statistik dalam metode pembelajaran, metode supervised learning, unsupervised learning (clustering), Semi-supervised learning (Reinforcement Learning), serta pengembangan metode pembelajaran mesin (ensemble machine learning). Terakhir, disajikan metode evaluasi pengukuran tingkat performansi kualitas model. Buku ajar ini dilengkapi berbagai contoh soal sehingga mahasiswa dapat mudah memahami dengan belajar secara mandiri dan interaktif. Harapan dari penulis, pembaca bisa memahami dan menganalisis secara tepat dalam pemecahan permasalahan berbasis machine learning serta mengimplementasikan dalam berbagai bidang dalam kehidupan sehari-hari.
A system dynamics for financial strategy model assessment in national health insurance system
Authors: Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto
Year: 2020
Topics: System Dynamics; Healthcare
Abstract: The National Health Insurance System (NHIS) was established by the government to provide health insurance to its people. However, some obstacles will be faced by NHIS. For example, when not having proper financial management, the fiscal budget sector will experience a deficit. The issue is happening in Indonesia. The purpose of this research is to develop and evaluate problem models so it can be used for consideration in determining relevant proposed policies. This research uses NHIS data in Indonesia from 2014 to 2018. The method used is a system dynamics approach. The validation of the SD model uses the mean comparison test and t statistic. Next, the model is tested for sensitivity under extreme conditions of low, basic, and high. Patient variables generate low and high states of 34.34% and 33.24%, respectively, which affect the variable fund inventory about 49.3 trillion and -93.46 trillion …
Structural and Behavioral Validity using a System Dynamic Simulation Approach: The Indonesian National Health Insurance System Problem
Authors: Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto
Journal: Proceedings of the 1st International Conference on Industrial Technology - ICONIT
Year: 2020
Topics: System Dynamics; Healthcare
Abstract: The dynamic system simulation model (SD) is increasingly favored by researchers in analyzing problems to find policy solutions, particularly in the health sector. The advantage of this approach is that it can predict the system in the long term at the macro level by looking at the interrelationship of behavior between subsystems in the observed system. The purpose of this study is to provide an overview of structural and behavioral validation testing in order to build reliability in the model being built. In this paper, the model developed is the Indonesian National Health Insurance System Problem (INHIS). Here we use structural validation test boundary adequacy and structure verification. Meanwhile, testing the validation of behavior used an average comparison of actual data and data from simulation results. The results obtained are the variables in the INHIS model and are declared valid and accurate because the value of the error ratio obtained (E)< 0.1. The importance of conducting validation has been proven in this study, which produces a valid INHIS model. This causes an increase in the reliability and attractiveness of the INHIS model.
Financial Strategy Model for Social Health Insurance in Indonesia using Simulation
Authors: D Kurnianingtyas, B Santosa, N Siswanto
Journal: IOP Conference Series: Materials Science and Engineering
Year: 2019
Topics: System Dynamics; Healthcare
Abstract: Social Health Insurance (SHI) in Indonesia is still facing many obstacles, especially the financial aspects from 2014 to 2017 due to the SHI financial losses that has received more attention from the public and the government in Indonesia. Therefore, this study intends to provide financial strategy recommendations that will get a stability revenue over cost. Dynamic system simulation approaches are used to obtain optimal financial strategies that take into account variable costs and income decisions. The parameter of the load variable is medical costs while the income variable is obtained from the participant premium rate factor. The data come from 2016 and 2017 related data to membership, especially PBPU (Participants Not Wage Recipients). Then, the equation used to find the right strategy is Income≥ Expenditures. In conducting simulations, scenarios are designed to reduce the level of financial losses that occur …
System dynamics simulation to determine financial strategy for social health insurance in Indonesia
Authors: Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto
Journal: Journal of Physics: Conference Series
Year: 2019
Topics: System Dynamics; Healthcare
Abstract: Social Health Insurance (SHI) in Indonesia is still experiencing financial constraints because the financial condition of the SHI has continued to be a loss since it was established in 2014 until present so it becomes special attention needed to get achieving the Universal Health Coverage (UHC) target by the government. Therefore, this study intends to provide an appropriate SHI financial strategy recommendation by considering the stability of the balance of income and expense. In addition, a system dynamics simulation approach is needed to find optimal SHI financial strategies with variables including participant premium rates, average cost of benefits, number of health cases, and number of insurance participants. The data used came from BPJS Health data for 2016 and 2017. Afterwards, the equation used was Income≥ Expenditures. In addition, there are several scenarios designed to reduce the level of …
Optimization of healthcare problem using swarm intelligence: a review
Authors: Agus Wahyu Widodo, Diva Kurnianingtyas, Wayan Firdaus Mahmudy
Year: 2022
Topics: Swarm Intelligence; Optimization
Abstract: Advances in information technology cause research to focus on involving smart technology to find optimal healthcare. The aim of this study is to provide a brief survey of the latest literature. This study can be used by researchers as basic for development related to healthcare and swarm intelligence (SI). SI optimization algorithm is proven to be able to solve problems from disease diagnosis, scheduling, routing, and service satisfaction. However, the results obtained have not been integrated, accordingly, effective and efficient healthcare services. This study also presents the potential and trends of future healthcare problems that can be solved by the SI.
Reforming premium amount in the Indonesian National Health Insurance System program using system dynamics
Authors: Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto
Journal: Cogent Engineering
Year: 2021
Topics: System Dynamics; Healthcare
Abstract: The National Health Insurance System (NHIS) is a government program to help the health needs of its population such as in Indonesia (INHIS). However, there are obstacles to implementing it, which is shown by the results of program evaluations every year that there is a deficit problem, starting in 2014 until 2019 to and even expected to increase in the following years. One of the possible deficits is due to inefficient patient behavior and referral system which will affect the premium amount. The goal is to evaluate and plan further policies with efficient premiums amount. System dynamics is used to simulate the effects of ability-to-pay, willingness-to-pay, salary, age, health cost each customer, and fund inventory. The historical data are used from INHIS from 2014 to 2019, then projected until 2030. The simulation results show that the health costs considered for determining the premiums are critical to the financial …
Application of Artificial Intelligence for Maternal and Child Disorders in Indonesia: A Review
Authors: Diva Kurnianingtyas, Lailil Muflikhah
Year: 2024
Topics: Artificial Intelligence; Healthcare
Abstract: The development of Artificial Intelligence (AI) technology is used to minimize the risk of maternal disorders during pregnancy. Maternal health needs to be monitored so as not to cause problems during the baby's birth. The purpose of this study is to provide a literature review from 2017 to 2023. The method used is Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study is a basis for researchers to help solve maternal health problems using AI. This technology is proven to detect and predict problems during pregnancy, thereby reducing maternal and infant mortality and preventing abnormalities in the development process. In addition, AI can help improve medical personnel's performance by minimizing human error. This study also presents trends in AI problems and methods used. However, the rapid development of AI methods has not provided novelty in solving maternal …
Solving Deficit Funding Issues in Indonesian Health Insurance Systems
Authors: Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto
Year: 2019
Topics: Healthcare; System Dynamics
Abstract: Indonesian National Health Insurance System (INHIS) is a government program that aims to provide health insurance to citizens by guaranteeing their health services. However, INHIS finances continued to experience a deficit since 2014. The purpose of this study was to find a solution so that the stock of funds remained stable. This is done by changing the patient's referral mechanism in INHIS. This is one solution so that the total health care costs do not increase. In this case the dynamic system simulation model is needed to find the relationship pattern between variables so that it can estimate the condition of INHIS funds. The decision variables in this study are the total health care costs and the stock of funds. From the simulation process, the results show that the proposed model can reduce the total health care costs by 44% and be able to maintain a stable supply of funds up to 40% of the sudden increase.
Comprehensive Review of Meta-Learning Methods for Cold-Start Issue in Recommendation Systems
Authors: Jamallah M Zawia, Maizatul Akmar Binti Ismail, Mohammad Imran, Buce Trias Hanggara, Diva Kurnianingtyas, Silvi Asna, Quang Tran Minh
Year: 2025
Topics: Machine Learning; Recommendation Systems
Abstract: The cold-start issue in recommendation systems refers to the challenge of recommending items or users when minimal or no prior data is available. Meta-learning methods have emerged as a response to this challenge due to their ability to transfer prior knowledge to recommendation tasks. However, meta-learning techniques are still new, and a general literature review is missing. This paper reviews the existing literature on meta-learning techniques specifically designed to solve the cold-start issue in recommender systems. A systematic review of the literature published between 2018 and June 2024 was conducted, identifying only experimental papers that use meta-learning methods to solve the cold-start issue. Advances, strengths, and weaknesses of such methods were analyzed, and possible research directions for the future were identified. The results demonstrate the application of model-independent meta …
Comparison Genetics Algorithm and Particle Swarm Optimization in Dietary Recommendations for Maternal Nutritional Fulfillment
Authors: Diva Kurnianingtyas, Nathan Daud, Indriati Indriati, Lailil Muflikhah
Journal: SITEKIN: Jurnal Sains, Teknologi dan Industri
Year: 2024
Topics: Optimization; Swarm Intelligence
Abstract: Fulfilling maternal nutrition is an NP-hard problem. Optimization techniques are required to solve its complexity. This issue is crucial as it affects the number of stunted toddlers in Indonesia. Stunting begins in the womb due to inadequate maternal nutrition during pregnancy. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are optimization methods applied to NP-hard problems, including medicine. Their performance has not been compared in this field. This study aims to identify an alternative method for recommending daily menus based on maternal nutritional needs. There are 55 food ingredients used to fulfill five menu parts: staple food (SF), vegetables (VG), plant source food (PS), animal source food (AS), and complementary (CP). Nutritional adequacy for prenatal is determined by Total Energy Expenditure (TEE) based on basal energy, daily activity, and stress levels. Results show PSO …
The necessity of implementing AI for enhancing safety in the Indonesian passenger shipping fleet
Authors: Shinta JA Rahadi, Dhimas F Prasetya, Muhammad Luqman Hakim, Dian Purnama Sari, Cakra WK Rahadi, Putri Virliani, RD Yulfani, Luthfansyah Mohammad, Diva Kurnianingtyas
Journal: Kapal: Jurnal Ilmu Pengetahuan dan Teknologi Kelautan
Year: 2023
Topics: Artificial Intelligence
Knowledge-enriched domain specific chatbot on low-resource language
Authors: Rizal Setya Perdana, Putra Pandu Adikara, Diva Kurnianingtyas
Year: 2022
Topics: Natural Language Processing
Abstract: This study presents architecture in learning human-machine conversation using a human language known as chatbots. Given an utterance, a chatbot attempt to reply using human language by mimicking human intelligence in communication. Previous works in this domain were mostly implemented in English, thus it remains a problem when bringing to a low-resource language, e.g., Indonesian. The limited availability of human-to-human dialog history led to difficulty in the learning process of machine learning algorithms. Therefore, this study proposed a Knowledgeable Chatbot (KC), an enhanced pipeline that enables to receiving of transferred knowledge from another task. A data augmentation pipeline is proposed to handle the limited number of available. To deal with the low-resource language, this study proposed to incorporate a pre-trained language model to gain contextualized language understanding. As …
A system dynamic to reforming of the healthcare sector in the Indonesian National Health Insurance System Program
Authors: Diva Kurnianingtyas, Budi Santosa, Nurhadi Siswanto
Journal: International Journal of Industrial and Systems Engineering
Year: 2022
Topics: Healthcare Systems
Abstract: National Health Insurance System (NHIS) was established by the Indonesian Government to ensure the health needs of its people. However, the programme encountered many obstacles due to inefficiencies caused by changes in people's behaviour. The aim is to identify key factors, evaluate and plan further policies using Indonesian data from 2014 to 2018. The system's dynamics approach is used to build a model for determining policy alternatives that only focuses on referral reform and limiting health service coverage. The proposed model was proven correct and then implemented in 2019 to plan a policy solution. The result was limiting healthcare coverage as a short-term strategy, whereas changing tiered referrals to combined referrals could be considered a long-term strategy. However, the success of this strategy will only occur if there is good collaboration between health services and regulations. In …
Cost-Effective Job Sequence Optimization for Minimizing Downtime in Flexographic Printing With Puma Optimizer Algorithm
Authors: Haidar Hanif, Nathan Daud, Diva Kurnianingtyas, Ivan Keane Hutomo, Ivan Gunawan
Year: 2024
Topics: Optimization Algorithms
Abstract: This paper presents the Puma Optimizer (PO), a recent novel metaheuristic algorithm inspired by the hunting behaviors of pumas. The sequence of the color printing jobs in flexography industry play a significant role since downtime occurs every color changes. Therefore, this study focuses on optimizing printing job sequences to minimize cost, downtime, and maximize revenue. Three experiments of PO algorithm were conducted with varying population sizes and iteration sizes, all resulting in a total revenue of IDR265,434,000 (approximately ${\$}$17,426). Demonstrating the algorithm’s consistency despite different iteration paths. The exploration phase of the PO facilitates diverse solution generation through random searches, while the exploitation phase refines solutions by simulating puma hunting strategies, including ambush and sprinting.
Analisis Faktor-Faktor yang Memengaruhi Niat Penggunaan Sistem Pembayaran Digital
Authors: Aliya Faradila, Riswan Septriayadi Sianturi, Diva Kurnianingtyas
Journal: Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi
Year: 2024
Topics: Digital Payments
Abstract: Based on observations and interviews with passengers of Trans Jatim Corridor I Bus, found that most of them still pay tickets in cash. Digital payment system considered less efficient, because conductors have to walk around and difficulty using phones when the bus is crowded, making cash payments more preferable. This study aims to analyze the factors influencing the use of the digital payment system in the Trans Jatim Corridor I bus based on the UTAUT model and using SEM-PLS analysis techniques. The results show that the intention to use the system is influenced by facilitating conditions, while performance expectancy, effort expectancy, and social influence variables have no effect. Gender, age, and experience do not moderate the relationship between these variables and behavioral intention to use the system. It can be concluded that if Trans Jatim Corridor I bus passengers have adequate facilities to use digital payments, they will have a high intention to use the system.
Application of Data Augmentation on SSD Mobilenet for Detection of Kenaf Plant Disease and Pest
Authors: Agus Wahyu Widodo, Alfita Rakhmandasari, Wayan Firdaus Mahmudy, Muh Arif Rahman, Diva Kurnianingtyas
Year: 2023
Topics: Computer Vision; Data Augmentation
Abstract: The Kenaf plant is a source of natural fibre and can potentially be a source of bioenergy, biopharmaceuticals, bioremediation, and others. The need for Kenaf plant fibre is increasing due to the variety of plant uses. This high demand is different from a high production level as well. One of the main production barriers is pests and diseases in plants. Rapid detection of pests and diseases is needed to carry out appropriate actions. Pest and disease detection can be assisted with deep learning methods such as Single-Shot Multibox Detection (SSD) Mobilenet. Data augmentation is carried out to improve the accuracy of the results. Although the Mobilenet SSD gets an accuracy of only 54%, using data augmentation can increase the accuracy of the Mobilenet SSD by 14.02% to 72.02%. This result is better than using Faster Region-based Convolutional Neural Network (RCNN), which is used as a comparison method.
Opportunities of Artificial Intelligence for Authentication and Assurance of Halal Products
Authors: Wayan Mahmudy, Diva Kurnianingtyas
Journal: Journal of Information Technology and Computer Science
Year: 2025
Topics: Artificial Intelligence
Abstract: The need for Muslims to obtain halal food encourages the development of systems that can assist in the authentication and assurance of halal products. Various Artificial Intelligence (AI) based systems have been developed to meet these needs. AI is a technology that enables computers to understand, learn, and perform tasks that would typically require human intelligence and reasoning to act and make decisions. With the help of high-speed computers, AI algorithms learn patterns in available data and perform assigned tasks with high accuracy and efficiency. This study focusses on the application of AI for the identification, monitoring, verification and validation of halal products. Also, this paper limits the discussion to food products with the topics of (1) Inspection of raw materials and detection of contamination to ensure the halalness of raw materials (2) Market monitoring and recommendation of halal restaurants to help Muslim consumers. The consumers were looking for a restaurant that suits their needs and preferences (3) Verification of halal certification to ensure that the certification given to the product comes from a competent and trustworthy authority.
Performance Evaluation of Different Classification Algorithms Applied for Identifying Maternal Nutritional Status by Anthropometric Measurements
Authors: Diva Kurnianingtyas, Nathan Daud, Agus Wahyu Widodo, Tutut Herawan
Journal: International Journal of Integrated Engineering
Year: 2025
Topics: Machine Learning
Abstract: Pregnancy significantly influences infant quality and development. Maternal monitoring, indicated by body mass index (BMI) and mid-upper arm circumference (MUAC) measurements, reflects a country's socioeconomic development. Improper measurements heighten the risk of chronic energy deficiency (CED) in pregnant women and low birth weight (LBW) in infants. This study leverages artificial intelligence (AI) to enhance the detection process. Specifically, it evaluates the prediction performance of various classification methods: Decision Tree (DT), K-Nearest Neighbors (KNN), Logistic Regression (LR), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM). Using interviews in Jombang District, Indonesia, these methods were expected to identify maternal nutritional status. The model design was divided into two stages: MUAC estimation generated binary classes, and BMI estimation generated multiple classes. The evaluation of these methods included various performance metrics: Accuracy (Acc), G-means, Sensitivity (Sens), Specificity (Spec), Positive Predictive Value (PPV), and Negative Predictive Value (NPV). Based on the results, all methods are proposed for both classifications, except KNN on multiple classification. KNN achieved significant scores in all matrices with p<0.01. KNN's performance is impacted by data imbalance. The study revealed a strong correlation (0.92 coefficient) between BMI and MUAC variables. The application of ML algorithms in detecting maternal nutritional status can significantly enhance the effectiveness and efficiency of health facilities, especially in areas with inadequate resources …
Chest X-Ray Images Clustering Using Convolutional Autoencoder for Lung Disease Detection
Authors: Putri Amanda Syafira, Novanto Yudistira, Diva Kurnianingtyas
Journal: JOIV: International Journal on Informatics Visualization
Year: 2025
Topics: Deep Learning
Abstract: In healthcare, medical imaging is commonly used for health assessments. One of the most commonly used types of medical imaging is X-ray imaging. One area that often undergoes examination using this modality is the lungs, where healthcare professionals use X-ray images to interpret the results. However, prolonged interpretation of X-ray results by healthcare professionals and other work activities can lead to errors and potentially result in invalid disease identification. There is a need for a system that can classify the detection results from these images to assist healthcare professionals in their tasks. Various methods can be used for this purpose, such as classification, clustering, segmentation, etc. However, data labeling requires significant resources and costs, especially with large-scale datasets. One possible solution is to use an unsupervised learning approach to address this. One method under unsupervised learning is clustering, which allows the system to process and understand data patterns without needing external annotations or manual labeling. This research uses an autoencoder as a subcategory of unsupervised learning. This is because autoencoders can automatically extract relevant features from the data without needing external label guidance. The research utilizes a dataset consisting of 700 X-ray images of the chest, including 500 images showing disease and 200 normal X-ray images. This research aims to determine the effectiveness of clustering methods using an autoencoder model in grouping X-ray image results. The research conducted two experiments. In the first experiment, an autoencoder with 18 Layers was …
Deteksi Tingkat Resiko Kanker Serviks pada Wanita Usia Subur dengan Metode Modified K-Nearest Neighbor
Authors: Dillah Lyra Mukhrodi, Lailil Muflikhah, Diva Kurnianingtyas
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2025
Topics: Machine Learning
Abstract: Kanker serviks merupakan kanker kedua yang paling banyak diderita oleh wanita di Indonesia. Penyebab utama kanker serviks 99, 7% berkaitan erat dengan infeksi virus Human Papilloma. Salah satu metode yang digunakan untuk skrining kanker serviks adalah IVA (Inspeksi Visual dengan Asam Asetat), yang berfungsi mendeteksi keberadaan sel-sel abnormal sejak dini. Namun, metode IVA memiliki kekurangan, yakni tingkat sensitivitas dan spesifitas yang rendah. Maka, penelitian ini dilakukan dengan tujuan untuk mendeteksi tingkat resiko kanker serviks dengen menerapkan metode Modified K-Nearest Neighbor (MKNN). Metode tersebut dipilih karena mampu menangani data outlier dan tidak seimbang. Metode ini bekerja dengan menghitung jarak antar data sambil menyesuaikan bobot tetangga berdasarkan jaraknya sehingga menghasilkan klasifikasi yang lebih representatif. Dataset penelitian mencakup 314 pasien kanker serviks. Setelah melalui tahapan data preprocessing, pembagian
Eksplorasi Skema Reproduksi Algoritma Genetika untuk Vehicle Routing Problem dengan Time Windows (Studi Kasus: Anekapay)
Authors: Haidar Hanif, Diva Kurnianingtyas, Agus Wahyu Widodo
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2025
Topics: Genetic Algorithms
Abstract: Eksplorasi Skema Reproduksi Algoritma Genetika untuk Vehicle Routing Problem dengan Time Windows (Studi Kasus: Anekapay) | Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer j-ptiik logo Beranda Terkini Arsip Tentang Kami Tentang Jurnal Ini Penyerahan Naskah Dewan Editor Kontak Bahasa Indonesia Register Login Eksplorasi Skema Reproduksi Algoritma Genetika untuk Vehicle Routing Problem dengan Time Windows (Studi Kasus: Anekapay) 1.Beranda / 2.Arsip / 3.Vol 9 No 13 (2025): Publikasi Khusus Tahun 2025 / 4.Artikel Eksplorasi Skema Reproduksi Algoritma Genetika untuk Vehicle Routing Problem dengan Time Windows (Studi Kasus: Anekapay) Penulis Haidar Hanif Universitas Brawijaya Diva Kurnianingtyas Universitas Brawijaya Agus Wahyu Widodo Universitas Brawijaya Abstrak Naskah ini akan diterbitkan di Engineering Optimization Journal Diterbitkan 15 Jan 2025 Cara …
Penjadwalan Makan Otomatis untuk Ibu Hamil Menggunakan Algoritma Genetika pada Aplikasi Mobile Berbasis Jetpack Compose
Authors: I Gusti Ngurah Mayun Suryatama Giri, Diva Kurnianingtyas, Fais Al Huda
Journal: Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Year: 2025
Topics: Genetic Algorithms
Abstract: Penjadwalan Makan Otomatis untuk Ibu Hamil Menggunakan Algoritma Genetika pada Aplikasi Mobile Berbasis Jetpack Compose | Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer j-ptiik logo Beranda Terkini Arsip Tentang Kami Tentang Jurnal Ini Penyerahan Naskah Dewan Editor Kontak Bahasa Indonesia Register Login Penjadwalan Makan Otomatis untuk Ibu Hamil Menggunakan Algoritma Genetika pada Aplikasi Mobile Berbasis Jetpack Compose 1.Beranda / 2.Arsip / 3.Vol 9 No 13 (2025): Publikasi Khusus Tahun 2025 / 4.Artikel Penjadwalan Makan Otomatis untuk Ibu Hamil Menggunakan Algoritma Genetika pada Aplikasi Mobile Berbasis Jetpack Compose Penulis I Gusti Ngurah Mayun Suryatama Giri Putra Universitas Brawijaya Diva Fais Kata Kunci: Algoritma Genetika, jadwal makan otomatis, Kekurangan Energi Kronis, Jetpack Compose. Abstrak Naskah ini akan diterbitkan di e-…