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All Journal Dinamik (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Sarjana Teknik Informatika Indonesian Journal of Artificial Intelligence and Data Mining JurTI (JURNAL TEKNOLOGI INFORMASI) Jurnal ULTIMATICS METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Multitek Indonesia : Jurnal Ilmiah Jurnal Teknologi Terpadu Journal of Information System, Applied, Management, Accounting and Research Jurnal Sistem Informasi dan Informatika (SIMIKA) Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Business and Audit Information System (JBASE) Jurnal Sosial dan Teknologi Jurnal Manajemen Informatika Jayakarta HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Jurnal Vokasi Informatika (JAVIT) Journal Software, Hardware and Information Technology Journal of Technology and Informatics (JoTI) Simpatik: Jurnal sistem Informasi dan Informatika Indonesian Community Journal Blend Sains Jurnal Teknik Populer: Jurnal Penelitian Mahasiswa Jurnal Manajemen Informatika & Teknologi Jurnal Manajemen Informatika dan Bisnis Digital Jurnal Informatika dan Komputer (JIK) Jurnal Sistem Informasi dan Ilmu Komputer Jurnal Komputer Antartika Indonesian Journal of Education And Computer Science Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Journal Innovations Computer Science Repeater: Publikasi Teknik Informatika dan Jaringan Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer KETIK : Jurnal Informatika Sistematis Jurnal Sistem Informasi dan Aplikasi Nusantara Journal of Artificial Intelligence and Information Systems
Kaesmetan, Yampi R
STIKOM Uyelindo Kupang
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Sistem Pendukung Keputusan Pemberian Tunjangan Karyawan Menggunakan Metode Analytical Hierarchy Process (AHP): Studi Kasus: TVRI Nusa Tenggara Timur Yoman Berchmans; Linus Evrianus Ama Kean; Reynaldo Behar; Yampi R. Kaesmetan
Populer: Jurnal Penelitian Mahasiswa Vol. 3 No. 1 (2024): Maret : Jurnal Penelitian Mahasiswa
Publisher : Universitas Maritim AMNI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/populer.v3i1.1638

Abstract

This research aims to address the issues surrounding the allocation of employee benefits at TVRI Nusa Tenggara Timur. Currently, the decision-making process for benefits is solely based on recommendations from supervisors, without taking into consideration employee performance, potentially leading to social jealousy and suboptimal outcomes. In this study, we develop a Decision Support System (DSS) utilizing the Analytical Hierarchy Process (AHP) method to assess employee performance. AHP allows for a hierarchical and objective breakdown of multi-factor problems. The criteria used for evaluation include attendance, behavior, length of service, and dependents. It is expected that the implementation of this DSS will enhance transparency and objectivity in decision-making, minimize employee dissatisfaction, and provide a more robust basis for benefit allocation decisions. This research offers practical contributions to human resource management and decision-making at TVRI Nusa Tenggara Timur.
Menentukan Titik Rawan Malaria Di Provinsi Nusa Tenggara Timur Menggunakan Metode K-Means Clustering Yustina Bete Dos Santos; Rasti Lani; Atfandianus Ewal; Bastian Jumilton Lenggu; Yampi R Kaesmetan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 1 No. 4 (2023): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v1i4.1750

Abstract

Malaria is one of the diseases that is currently affected, but is still a threat and often causes unusual events in NTT province. Malaria in NTT province is the second highest malaria disease in Indonesia after Papua. The method used to analyze the vulnerability to malaria in NTT province is K-Means Clustering. The purpose of analyzing the level of malaria vulnerability is to find out which districts have the highest to lowest vulnerability in NTT province, which is carried out in a geographic information system. The results of the analysis showed tha 7 districts were classified as low malaria vulnerability, 1 district as medium, 12 districts as high and 2 districts as very high. The level of vulnerability can be understood as the level of malaria endemicity.
Sistem Pendukung Keputusan Seleksi Pemilihan Perguruan Tinggi Terbaik Menggunakan Metode Topsis La Beu, Dian Nurcahyani; Boling, Angel Agustina; Fua, Andreas Curtis Hopper; Kaesmetan, Yampi R
Dinamik Vol 29 No 2 (2024)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v29i2.9677

Abstract

Decision Support System (SPK) can be used to select the best college in this journal, the author uses the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method which is expected to be a solution for consideration for prospective new students who want to pursue higher education. From the calculation results, it is found that the highest result value from the calculation formula can be used to be the best choice in choosing a college for prospective students. With confusion matrix accuracy reaching 90%.
DETEKSI KEASLIAN UANG KERTAS BERDASARKAN WATERMARK DENGAN METODE SUPORT VEKTOR MACHINE (SVM) Kehi, Balthasar; Kaesmetan, Yampi R.; Saban, Aryandi
JIK : Jurnal Informatika dan Komputer Vol. 15 No. 1 (2024): Jurnal Informatika dan Komputer (JIK)
Publisher : Universitas Mahakarya Asia

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

Abstract

Money is a legal means of exchange or standard for measuring value (a unit of account), issued by the government of a country in the form of paper, gold, silver or other metals printed with certain shapes and images. Detection is a process of checking or examining something using certain methods and techniques. Along with advances in information technology, crimes that utilize technology are also developing. Currently, digital image processing has developed its usefulness to carry out a recognition system for possible criminal disturbances, especially for recognizing unique objects, watermarks on rupiah banknotes. In image segmentation there are also several methods, for example canny edge detection. Canny edge detection is a method that produces a different image display by displaying a relief effect in it. The aim of this research is to detect the authenticity of banknotes with watermarks using the canny edge detection method. The process of using the method above involves image acquisition,grayscale operations, morphology operations, then canny edge detection. There are 21 images used in this research consisting of nominal banknotes of 1,000, 2,000, 5,000, 10,000, 20,000, 50,000 and 100,000. The final result of the canny edge detection process is a collection of pixels that are used to determine whether the image has a watermark or not. From this research, the results of the accuracy of the watermark detection program on banknotes using the canny edge detection method to detect the authenticity of money were 85.71%. Keywords: canny, detection, image processing, money, watermark,
PENENTUAN PENERIMA BERAS RASKIN DI KELURAHAN OESAPA BARAT MENGGUNAKAN METODE K-NEAREST NEIGHBOR (KNN) kaesmetan, yampi
Jurnal Teknologi Terpadu Vol 2 No 2: Desember, 2016
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v2i2.54

Abstract

Rapid technological developments are currently very influential in all areas of work especially in the field ofmapping the location on maps online. Village of West Oesapa, District Kelapa Lima, Kupang is one of thevillages that aspires for the welfare of the community by way of distribution of poor rice aid to the poor in theeconomic field. Raskin rice distribution should be shared equitably and meets the criteria as a poor ricerecipient in the Village of West Oesapa. With KNN method (K-Nearest Neighbor) will count how many people ineach neighborhood would receive help poor rice in accordance with existing criteria, and to determine thepercentage can be seen in the form of a map.
Pemilihan Hotel Pada Kelurahan Oesapa Selatan Menggunakan Metode Weighted Product kaesmetan, yampi; Nawa, Yesaya Laga
Jurnal Teknologi Terpadu Vol 3 No 1: Juli, 2017
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v3i1.71

Abstract

Hotel is one of the supporting facilities of tourism in a city. The diversity of the hotel make tourists often faced difficulty in determining the choice of hotel that suits your needs and desired criteria. Through a computerized application, can help prioritize the selection of the hotel. The results of the election study with WP method can be used to perform perangkingan list of alternatives hotel in southern Oesapa village for visitors so that the hotel needs can be met based on the criteria of visitors. The output of this system in the form of priority Oesapa best hotel in the southern villages. With this application, people who want to stay at the hotel can be easier in choosing a hotel to suit the need. Keywords: Hotel, South Oesapa, Wighted Product.
SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN KUALITAS DEPOT AIR MINERAL ISI ULANG MENGGUNAKAN METODE TOPSIS (TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION) Febianus Asa; Elisabeth Kolastriwan Romanda; Jekonia Nelchika Titing; Maria Claris Salzano Nurak; Pua geno, Muhamad Nazhif Zuhri; Yampi R. Kaesmetan
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 10 No. 1 (2024): Volume 10 Nomor 1
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v10i1.2439

Abstract

The Decision Support System (DSS) for determining the quality of mineral water depots using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is an application designed to assist mineral water depot managers in selecting the best mineral water supplier based on certain criteria. The TOPSIS method is used to solve multi-criteria problems by considering the relative proximity to ideal solutions and anti-ideal solutions.First, relevant criteria for assessing the quality of mineral water are selected, including physical, chemical and microbiological parameters. Then, mineral water quality data from various suppliers is processed and normalized. Next, the normalized decision matrix is used to calculate the ideal solution and anti-ideal solution matrices. After that, a relative closeness score for each supplier is calculated based on the Euclidean distance to the ideal and anti-ideal solutions.The results of the TOPSIS analysis are used to provide recommendations for the best mineral water suppliers. By using this system, mineral water depot managers can optimize supplier selection based on predetermined quality criteria, thereby increasing customer satisfaction and maintaining the reputation of the mineral water depot in the market.
Pengenalan Plat Kendaraan Otomatis Berbasis Citra Menggunakan Metode Optical Character Recognition (OCR) Ginting, Rudolf F.A.; Djawas, Julaica F.; Kaesmetan, Yampi R.
Journal Software, Hardware and Information Technology Vol 4 No 2 (2024)
Publisher : Jurusan Sistem Informasi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/shift.v4i2.135

Abstract

Automatic parking registration has become a focal point in the research and development of modern urban transportation systems. In this context, image-based vehicle license plate recognition plays a vital role in facilitating efficient and accurate parking registration processes. This research aims to develop an image-based vehicle license plate recognition system for automatic parking registration applications using Optical Character Recognition (OCR) technology. The methods employed include vehicle image acquisition, image preprocessing, license plate segmentation, text extraction using OCR, and license plate character recognition. Testing was conducted using a dataset of vehicle images captured under various lighting conditions and angles. Experimental results demonstrate that the proposed system is capable of recognizing vehicle license plates with a high level of accuracy, even under varying lighting conditions and distorted license plates. Implementation of this system is expected to enhance efficiency in automatic parking registration and reduce manual involvement in the process.
Identifikasi Ekspresi Wajah Manusia dengan Metode Support Vector Machine Handul, Yohanes Janssen; Matulessy, Junus Yosia Eran Saktriawan; Kaesmetan, Yampi R
Jurnal Komputer Antartika Vol. 2 No. 2 (2024): Juni 2024
Publisher : Antartika Media Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70052/jka.v2i2.294

Abstract

Wajah adalah bagian tubuh manusia yang berfungsi sebagai pusat ekspresi, pengenalan dan juga komunikasi. Penciptaan teknik yang berguna untuk mengidentifikasi dan menganalisis ekspresi wajah sangat penting untuk penelitian ini. Support Vector Machine (SVM) merupakan teknik pembelajaran mesin yang digunakan untuk pengenalan pola klasifikasi ekspresi wajah Manusia. Support Vector Machine (SVM) adalah metode klasifikasi yang menggunakan konsep mencari hyperplane yang optimal dalam suatu ruang feature untuk memisahkan beberapa kelas. Dari keempat klasifikasi tersebut ternyata presentasi accuracy, precision dan recall tidak berbeda jauh untuk mendeteksi ekspresi wajah dari tiap kelas tersebut dengan menggunakan metode SVM. Berdasarkan uji ekstraksi  hasil rata-rata accuracy tertinggi yaitu  jenis ekspresi marah dengan accuracy paling tinggi. Tingkat rata-rata tertinggi accuracy yang kedua yaitu ekspresi senang. tingkat rata-rata tertinggi accuracy ketiga yaitu ekspresi netral, lalu tingkat rata-rata tertinggi accuracy keempat yaitu ekspresi senyum dan tingkat rata-rata terendah accuracy yaitu ekspresi sedih.   The face is a part of the human body that functions as a center of expression, recognition and communication. The creation of useful techniques for identifying and analyzing facial expressions was crucial for this study. Support Vector Machine (SVM) is a machine learning technique used for pattern recognition classification of Human facial expressions. Support Vector Machine (SVM) is a classification method that uses the concept of finding the optimal hyperplane in a feature space to separate classes. From the four classifications, it turns out that the presentation of accuracy, precision and recall is not much different to detect facial expressions from each class using the SVM method. Based on the extraction test, the highest average accuracy result is the type of angry expression with the highest accuracy. The second highest average level of accuracy is the expression of pleasure. The third highest average level of accuracy is neutral expression, then the fourth highest average level of accuracy is smile expression and the lowest average level of accuracy is sad expression.
Identifikasi Berat Badan Berdasarkan Citra Foto Menggunakan Metode Body Surface Area Sten Dofanky Mooy; Andrew Delfistian Dethan; Yampi R Kaesmetan
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 2 No. 3 (2024): Juli : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v2i3.1332

Abstract

Measurement of human body weight is an important process in various contexts, such as medical staffing administration, military recruitment, and individual health assessment, as body weight is a key parameter for determining one's body condition. Weight information is traditionally obtained using manual scales, which have been used for many years. However, manual weight measurement is quite time-consuming, especially when done for many people and repeatedly, such as in military recruitment or medical administration. A new approach using digital image technology offers improvements in this process. Therefore, this research aims to calculate human body weight based on digital photos using the Body Surface Area (BSA) method. The use of the BSA method in digital image-based weight measurement involves calculating the body surface area to estimate body mass. This method combines parameters such as height and body circumference taken from the photo image to calculate BSA. Furthermore, an investigation into calculation analysis and accuracy enhancement is conducted. The calculated weight results from the photos are then compared with the scale results to determine their accuracy. Based on the calculation results, an approximate value of 93.3% accuracy is obtained with an average conversion factor of 0.978 at a distance of 300 cm between the camera and the object.
Co-Authors Abraham Do Hina Abubakar, Muhammad A. Alfayet, Teofano E.D Andrew Delfistian Dethan Anindya, Fazha Safha Atfandianus Ewal Azahra Imran, Fatimah Azis, Mayang Fitrylia Babis, Arjen Yohanes Bajuri, Miftahul K Bastian Jumilton Lenggu Beda, Helena Bendi, Muhammad Indra Boboy, Vito Daniel Boling, Angel Agustina Delfince Toleu Desty A. Bekuliu Dinda Ayusma Tonael Djawas, Julaica F. Dominggus Mangngi Edwin Ariesto Umbu Malahina Elisabeth Kolastriwan Romanda Endang Oekolos Fahik, Ferdinandus Febianus Asa Frans, Harry Wolter Fryonanda, Harfebi Fua, Andreas Curtis Hopper Fuzy Yustika Manik, Fuzy Yustika Ginting, Rudolf F.A. Handul, Yohanes Janssen Helena dorothea Mbura Henakin, Yohanes Bala Jamung, Maria Susanti Jekonia Nelchika Titing Jusrianto A Johannis Kamirsa, Yota Putra Katihara, Gustaf Karel Kehi, Balthasar Kembo, Emanuel Kristiano Kolihar, Reflon Paskah Komba, Clarisa La Beu, Dian Nurcahyani Ladopurab, Yohana Uba Lae, Archangela Cornelia Laoe, Desly sabatini Latuan, Franklyn Priscian Leosae, Sepriono Linus Evrianus Ama Kean Maria Claris Salzano Nurak Maria Yohana Gabriela Sasi Marlinda Vasty Overbeek Marlinda Vasty Overbeek Martin Ch. Liufeto Matulessy, Junus Yosia Eran Saktriawan Melania Zemil Meliana O Meo Mone, Bintang Vieshe Mone, Gerry Moruk, Fransiskus Xaverius Mutty, Nanda Gracenda Christina naikteas, maria rosalinda Nawa, Yesaya Laga Ndun, Alfrend Nelci Non nenometa, elike adielwin Nesi, Maria Yunita Nimrot Doke Para Nindy Aulia Safirah Nono, Mariana Selvia Owa, Frederikus Mantolda Dede Penlaana, Vania Serafin Pua geno, Muhamad Nazhif Zuhri Putra Prawira Yohanes Puka Rafael, Simpati Gamalio Rasti Lani Rexion Alondeo Boimau Reynaldo Behar Rihi, Ivana Ristiana Betris Tosi Rosid, Achmat Saban, Aryandi Sanrina Natalia Evelin Tolan Saputri, Nur Azizah Indah Sayyid Ahmad Wisak Selan, Frederikus Wanforsan Reynaldy Sten Dofanky Mooy Tahuk, Wilhelmina Johana Tefa, Sepri Vito Daniel Boboy Vladimir Juino Jago Uko, Christianus Wole, Jernianti Susanti Wulansari Masan Yafet Balan Yesaya Laga Nawa Yoman Berchmans Yunita Luruk Ulu Yustina Bete Dos Santos Yusuf Elpontus Tanaem