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Jurnal Informatika Teknologi dan Sains (Jinteks)
Published by Universitas Teknologi Sumbawa
ISSN : -     EISSN : 26863359     DOI : https://doi.org/10.51401/jinteks.v3i3.1260
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Jurnal Informatika Teknologi dan Sains (JINTEKS) merupakan media publikasi yang dikelola oleh Program Studi Informatika, Fakultas Teknik dengan ruang lingkup publikasi terkait dengan tema tema riset sesuai dengan bidang keilmuan Informatika yang meliputi Algoritm, Software Enginering, Network & Security serta Artificial Inteligence. disamping itu Jurnal Informatika Teknologi dan Sains (JINTEKS) juga mengelola publikasi yang terkait dengan ilmu Keteknikan / Engineering dan bidang sains yang meliputi matematika komputasi, Biomatematika serta Fisika terapan yang mengarah pada komputasi. Tujuan dan Lingkup Jurnal Jurnal Informatika Teknologi Dan Sains (JINTEKS) akan memuat hasil-hasil penelitian dan pengabdian masyarakat dalam bidang Teknologi Informasi, Komputer dan Sains yang belum pernah diterbitkan maupun sedang dikirim ke jurnal lain. Lingkup Jurnal Informatika Teknologi Dan Sains (JINTEKS) meliputi bidang Teknologi Informasi, Komputer dan Sains yang meliputi: Pemrograman Database Kecerdasan buatan Jaringan komputer Teknologi cloud Interfacing Sistem embedded Pengolahan citra E-commerce Sistem pengambilan keputusan Komputer Sains serta bidang-bidang lain yang relevan dengan teknologi informasi dan komputer
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 586 Documents
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OPTIMASI ALGORITMA NAIVE BAYES BERBASIS KERNEL UNTUK KLASIFIKASI PENYAKIT HATI Prasetyo, Muhammad A'an; Zyen, Akhmad Khanif; Kusumodestoni, R. Hadapiningradja
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 3 (2024): EDISI 21
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i3.4783

Abstract

Liver disease is a serious health problem that requires early and accurate diagnosis. This study develops and evaluates a kernel-based Naive Bayes algorithm for liver disease classification, comparing it with standard Naive Bayes. A dataset from Kaggle was used, covering a wide range of medical variables. After data preprocessing, both models are trained and evaluated using standard metrics. Results show significant improvements over the kernel-based model, with accuracy reaching 99% compared to 80% for the standard model. Feature importance and learning curves analysis is carried out for deeper understanding. This study demonstrates the great potential of using kernel-based Naive Bayes in improving liver disease diagnosis, which may contribute to improved clinical outcomes and quality of patient care.
TECHNO-ECONOMIC ANALYSIS PERHITUNGAN LCOE MESIN GASIFIKASI BIOMASSA SKALA MICRO-GRIDMENGGUNAKAN WOLFRAM MATHEMATICA Nuryadi, Halid; Sri Nuryani, Hanifa
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 3 (2024): EDISI 21
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i3.4854

Abstract

Perhitungan Levelized Cost of Electricity (LCOE) ini merupakan tindak lanjut dari Perancangan Mesin Gasifikasi Skala Micro-Grid yang bertujuan mengatasi minimnya distribusi energi listrik oleh jaringan PLN di daerah pedesaan dan bencana alam. Perancangan Mesin ini terkonsep modular menggunakan dua unit sistem utama, yaitu truck of feeding system (TFS) dan truck of power source (TPS). TFS berfungsi sebagai sistem pendistribusian feed stock biomassa menuju TPS. Sedangkan TPS berfungsi sebagai sistem penghasil distribusi energi listrik untuk user. Kedua unit sistem ini masing – masing diinstal terpisah pada sebuah container dan masing – masing unit sistem menggunakan sebuah kendaraan truck sebagai mobilty equipment. Secara umum beberapa variabel yang harus dipenuhi dalam perhitungan LCOE yaitu, antara lain: Capital Cost, Recurring Cost, dan Non-Recurring Cost. Perhitungan LCOE penulis jabarkan melalui metode Techno-Economic Analysis (TEA) menggunakan wolfram mathematica software. Hasil akhir dari penelitian ini adalah menentukan LCOE yaitu berapa nilai penjualan distribusi energi listrik per kWh kepada user. LCOE dari Mesin Gasifikasi Biomassa Skala Micro-Grid  ini diharapkan mampu mencapai harga standar pemerintah Indonesia dengan asumsi harga jual listrik pada tahun 2019 untuk PLTBM (Pembangkit Listrik Tenaga Biomassa) yaitu sebesar USD $Cent 8,41/kWh.
IMPLEMENTASI SISTEM INFORMASI DESA (SID) SEBAGAI UPAYA OPTIMALISASI LAYANAN ADMINISTRASI PUBLIK DI KANTOR DESA ROPANG Idham, Idham
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.2511

Abstract

Desa Ropang terletak di Kecamatan Ropang Kabupaten Sumbawa, Provinsi Nusa Tenggara Barat. Desa Ropang merupakan daerah terpencil yang jauh dari pusat kota, sehingga layanan administratif menjadi aspek yang sangat penting bagi masyarakat. Namun, terdapat beberapa masalah yang terkait dengan pengelolaan data kependudukan, khususnya dalam proses administratif. Pengelolaan data dilakukan sepenuhnya secara manual, menggunakan buku catatan fisik dan media cetak kantor. Selain itu, warga desa harus mengunjungi kantor desa secara langsung untuk meminta informasi dan menyelesaikan tugas administratif. Untuk mengatasi tantangan ini, penulis mengembangkan sistem informasi desa berbasis web yang mendukung konsep desa pintar. Sistem ini bertujuan untuk membantu pemerintah setempat dan masyarakat sekitar dalam memperlancar tugas administratif dan memastikan penyebaran informasi yang konsisten. Berdasarkan uji coba, sistem ini memperoleh indeks persetujuan sebesar 89%, dengan 30 responden menyatakan "SANGAT SETUJU" terhadap implementasi sistem informasi desa berbasis Web. Tujuan dari penelitian ini adalah untuk memanfaatkan kemajuan teknologi guna meningkatkan efisiensi administratif. Hasil uji coba menunjukkan bahwa sistem ini efektif dan dapat diterapkan dalam skenario dunia nyata
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN OBJEK WISATA DI PULAU LOMBOK DENGAN METODE PROFILE MATCHING
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4630

Abstract

Lombok Island, as a major tourist destination in Indonesia, offers various attractions including popular tourist villages. So far, there has been no proper guide or guideline for selecting tourist attractions in Lombok Island that match the preferences and needs of tourists, resulting in inaccuracies in choosing attractions that suit visitors' preferences, with added criteria from previous research including comfort, beauty, facilities, distance, cost, time, transportation, culinary, crowd levels, and limited available information. This study aims to develop a decision support system for selecting tourist attractions in Lombok Island using the Profile Matching method. The Profile Matching method is used with an analytic hierarchy approach to determine criteria weights, enabling the system to rank and recommend tourist attractions based on user preferences. The research will demonstrate which tourist villages have the highest values that tourists will choose. The research results indicate that the developed decision support system can assist tourists in selecting tourist attractions that match their desires.
PERENCANAAN STRATEGIS SISTEM INFORMASI MENGGUNAKAN METODE WARD DAN PEPPARD SERTA ANITA CASSIDY Tiawan, Tiawan; Fajari, Muhamad Soleh; Mawarseh, Mawarseh; Novarini, Retno; Harahap, Ahmad Karim; Syastra, Muhammad Taufik; Khaerullah, Akbar; Kurniawan, Rifky; Maulid, Elfina; Irfayanti, Yulia; Sutrisno, Sutrisno; Wijayanti, Elisabeth Kurnia
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4748

Abstract

Innovation is needed in the era of global competition. To continue to grow, PT. China Taiping Insurance Indonesia must develop existing technology and information systems. Strategic planning is needed to realize the company's vision and mission and compete with competitors. Proper planning can also save costs in purchasing technology and information systems and renting services. Effectiveness and efficiency are important foundations for companies to run their business processes. As a general insurance company, PT. China Taiping Insurance Indonesia faces problems such as long insurance policy making, long risk acceptance, slow claim handling, inefficient accounting and financial processes, and time-consuming reinsurance grouping. To solve this problem, SWOT analysis is used to determine the company's strategic position as a basis for making a business strategy. Information is obtained from internal and external information flows using the Ward and Peppard and Anita Cassidy methods, with Critical Success Factors analysis from a SWOT perspective. The result is an application portfolio consisting of 9 applications in various strategic quadrants. This study produces IS business strategies, IT strategies, IS/IT management strategies, as well as recommendations for application portfolios, costs required, and implementation schedules that can be implemented at PT. China Taiping Insurance Indonesia.
PENGEMBANGAN CHATBOT KONSULTASI KESEHATAN MENTAL KESEHATAN MENTAL BERBASIS OPEN AI MODEL GPT-3.5 TURBO MENGGUNAKAN MEDIA WHATSAPP
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4749

Abstract

This study aims to develop a WhatsApp-integrated chatbot utilizing OpenAI's GPT-3.5 Turbo model to assist in mental health contexts. Through this technological integration, the chatbot is capable of providing effective and empathetic responses to mental health-related inquiries and discussions. The methodology encompasses chatbot development, Black Box Testing, Usability Testing, and analysis of feedback from users and psychologists. The findings indicate that the chatbot successfully implements profound and relevant interactions in a mental health context. This chatbot offers an alternative approach to providing psychological support and mental health information. The study opens avenues for further development in the field of mental health chatbots, particularly in integrating the latest AI technology.
OPTIMISASI PARAMETER SUPPORT VECTOR MACHINE DENGAN PARTICLE SWARM OPTIMIZATION UNTUK PENINGKATAN KLASIFIKASI DIABETES Maulana, Muhammad Reza; Sucipto, Adi; Mulyo, Harminto Mulyo
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4784

Abstract

This research explores the effectiveness of using Particle Swarm Optimization (PSO) to optimize Support Vector Machine (SVM) parameters in diabetes diagnosis. Using Kaggle's "Diabetes Disease Data" dataset, this study compared the performance of SVM with default parameters and PSO-optimized SVM. Results showed small but consistent improvements in accuracy, precision, recall, and F1-score for the PSO-optimized model. Feature importance analysis identified glucose and BMI as the main predictors of diabetes. Learning curves showed both models were able to reduce overfitting as training data increased. Although the performance improvement is relatively small, this study illustrates the potential of optimization techniques in improving machine learning models for medical applications.
SISTEM INFORMASI GEOGRAFIS PEMETAAN FASILITAS KESEHATAN BPJS DI KABUPATEN JEPARA DENGAN ALGORITMA DIJKSTRA BERBASIS WEB Musyarraf, Fajrul Fahry; Sarwido, Sarwido; Kusumodestoni, R. Hadapiningradja
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4787

Abstract

Mapping BPJS health facilities in Jepara Regency is an important step to improve health accessibility. To support this effort, a web-based geographic information system was developed that is designed to map BPJS health facilities and determine the shortest route using Dijkstra's algorithm. This application was built with the Laravel 9 PHP framework and utilizes Leaflet for interactive map display. The results show that this system is effective in presenting complete information about BPJS health facilities in Jepara Regency. The main feature of this application is its ability to calculate and display the shortest route from the user's location to the selected health facility using Dijkstra's algorithm. With this feature, users can easily find the fastest path to the health facility, thus improving the efficiency and accessibility of health care in the region
PERBANDINGAN METODE OPTIMASI PENENTUAN SENTROID AWAL PADA ALGORITMA K-MEANS MENGGUNAKAN ELBOW PSO DAN SSE Muhamad Rodi; Hendrik, Hendrik; Amir Bagja; M Nurul Wathani; Zaenul Amri
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4803

Abstract

The increasing volume and complexity of data present challenges in big data processing, particularly in manually identifying data patterns and relationships. In data mining, clustering methods such as the K-Means algorithm are widely used to group data based on similar characteristics. However, K-Means’ reliance on random initial centroid selection can yield suboptimal clustering results. This study aims to compare the evaluation results and iteration time of three optimization methods—Elbow, Particle Swarm Optimization (PSO), and Sum of Square Error (SSE)—on the K-Means algorithm. The dataset used is the Online Retail II dataset from the UCI Machine Learning Repository. The Davies-Bouldin Index (DBI) method is used as an evaluation tool to assess the validity of the formed clusters. Based on the analysis results, the Elbow and SSE optimization methods achieved a DBI score of 0.8500 with faster iteration times compared to PSO. Meanwhile, the PSO method provided the best DBI score of 0.7376, although it required significantly longer iteration time. The results of this study are expected to serve as a reference for selecting an appropriate optimization method for the K-Means algorithm based on time requirements and clustering evaluation outcomes.
PENERAPAN SAW UNTUK MENENTUKAN PENERIMA BANTUAN PROGRAM KELUARGA HARAPAN PADA KELURAHAN RENTENG Septia, Laili; Zaen, Mohammad Taufan Asri; Mutawalli, Lalu
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4806

Abstract

The Family Hope Program (PKH) is a social assistance program from the government which aims to improve the welfare of underprivileged people. The process for receiving aid in this program requires an effective and objective method to ensure that aid is given to those who really need it. In this study, we applied the Simple Additive Weighting (SAW) method to determine the receipt of PKH assistance in Renteng Village. The SAW method was chosen because it is able to handle multi-criteria problems in a simple but efficient way. The criteria used include pregnant women, early childhood, school / education children, disabilities and the elderly. The research results show that the SAW method can be used effectively to determine receipt of assistance by providing a ranking based on the total score of each criterion. The implementation of this method is expected to increase transparency and accuracy in the distribution of social assistance in Renteng Village. The results of the calculations show Elderly V5= 0,6815 children are more deserving of PKH assistance in Renteng Village.

Page 37 of 59 | Total Record : 586

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