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All Journal snimed Jurnal Teknoin Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Telematika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Teknoinfo IJID (International Journal on Informatics for Development) Jurnal Pendidikan dan Konseling JITU : Journal Informatic Technology And Communication Automata Journal of Education Informatic Technology and Science JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Jurnal Teknik Informatika (JUTIF) Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi
Lizda Iswari
Fakultas Teknologi Industri, Universitas Islam Indonesia
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
IDENTIFYING AREA HOTSPOTS AND TAXI PICKUP TIMES USING SPATIAL DENSITY-BASED CLUSTERING Lestari, Mulia Dea; Iswari, Lizda
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.992

Abstract

Taxis are one of the competitive sectors of transportation and are recognized as convenient and easy means of transportation to meet individual needs. However, in the operation of a taxi there are some problems that would make the taxi service less optimal, such as the difficulty with finding a taxi at specific hours, the imbalance between demand and taxi supplies, and the length of passengers waiting for a taxi. Therefore, to optimize taxi service, a knowledge base is needed for strategic management decision making. In the study, data of exploration taxis uses a DBSCAN algorithm aimed at identifying and clustering pickup hotspots based on time during weekday and weekend time from Queens, New York City. As for the features used which are pickup latitude and pickup longitude. Accuracy scores for modeling use coefficients to achieve accuracy scores of 0.80 on weekdays and 0.77 on weekends where the accuracy score falls into the accurate category in modeling. Results show that there are three areas of taxi pickup centers based on high taxi demand in January 2016, where they are at LaGuardia airport, John f. Kennedy international, and the area around Steinway Street.
TEMPORAL SPATIAL PROPERTY PROFILING AND IDENTIFICATION OF EARTHQUAKE PRONE AREAS USING ST-DBSCAN AND K-MEANS CLUSTERING Samsudin, Angga Radlisa; Fudholi, Dhomas Hatta; Iswari, Lizda
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.3.1293

Abstract

Indonesia is a country located at the confluence of three major tectonic plates, namely Indo-Australia, Eurasia, and the Pacific so that earthquakes often occur, one of which is in West Nusa Tenggara Province. One way to accelerate the disaster mitigation process is to analyze earthquake occurrence based on spatial temporal aspects. This study uses data from BMKG NTB Province during 2018 with a total of 3,699 earthquake events which are then analyzed using ST-DBSCAN and K-Means. ST-DBSCAN analysis was used to determine earthquake prone areas based on the date and location of the event, while k-means used the depth and magnitude of the earthquake. The results show that the distribution pattern of earthquakes in the NTB region has a stationary pattern and there are similar prone areas based on the location and time of occurrence as well as the strength and depth of the earthquake. The ST-DBSCAN method using latitude and longitude attributes produces one cluster that covers 96.33% of the total data. Meanwhile, K-Means using the depth and magnitude attributes produced four clusters. The four clusters were obtained from the cluster density using the silhouette score value between -1 and 1. The K-means analysis used a silhouette score result of 18.527 which was found in cluster 1. Earthquake prone areas in the distribution of earthquakes or types of earthquakes are located in Gangga and Bayan sub-districts of North Lombok and in Sambelia and Sembalun sub-districts of East Lombok. The sub-district with the most frequent earthquakes is Sambelia sub-district with 112 earthquakes. Then the strength of the largest earthquakes on average occurred in Gangga sub-district with magnitudes of 4 to 6.2 SR with shallow earthquake types. The prone area is located at the foot of the mountain and directly adjacent to the ocean.ith shallow earthquake types. The Prone area is at the foot of a mountain and directly adjacent to the ocean.
Co-Authors Ahmad Raf'ie Pratama Alan Chandra Darmawan Dadang Heksaputra Dhomas Hatta Fudholi Dina Febriana Elyza Gustri Wahyuni Ervina Gita Ayu Fathul Wahid Fudholi, Dhomas Hatta Gunanto Gunanto Izzan Yattaqi Nugraha Izzati Muhimmah Khoiruzzidan, Ilma Kusumawati, Anggara Jatu Lestari, Mulia Dea Moch. Fathi Siddiqi Muhammad Daffa Muafa Muhammad Zufar Al Rafif Muhd Humam Rhamadhani Nasution - Nielza Atthina Nurul Mega Saraswati Rio Rizki Aryanto Risca Naquitasia Riyanto, Didik Sabella, Billy Salsabila, Anisa Sigit Nugroho Sri Kusumadewi Wijaya Kusuma Yopi Azani Zumrotun Naimah