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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 KETIK : Jurnal Informatika Sistematis Jurnal Sistem Informasi dan Aplikasi Nusantara Journal of Artificial Intelligence and Information Systems
Kaesmetan, Yampi R
STIKOM Uyelindo Kupang
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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PENENTUAN PENERIMA BERAS RASKIN DI KELURAHAN OESAPA BARAT MENGGUNAKAN METODE K-NEAREST NEIGHBOR (KNN) yampi kaesmetan
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 yampi kaesmetan; Yesaya Laga Nawa
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.
Digital Image Processing using Texture Features Extraction of Local Seeds in Nekbaun Village with Color Moment, Gray Level Co Occurance Matrix, and k-Nearest Neighbor Yampi R Kaesmetan; Marlinda Vasty Overbeek
Ultimatics : Jurnal Teknik Informatika Vol 13 No 2 (2021): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v13i2.2038

Abstract

The problem in determining the selection of corn seeds for replanting, especially maize in East Nusa Tenggara is still an important issue. Things that affect the quality of corn seeds are damaged seeds, dull seeds, dirty seeds, and broken seeds due to the drying and shelling process, which during the process of shelling corn with a machine, many damaged and broken seeds are found. So far, quality evaluation in the process of classification of the quality of corn seeds is still done manually through visible observations. Manual systems take a long time and produce products of inconsistent quality due to visual limitations, fatigue, and differences in the perceptions of each observer. The selection of local maize seeds in Timor Island, East Nusa Tenggara Province, especially in Nekbaun Village, West Amarasi District with feature extraction with a color moment shows that the mean, standard deviation and skewness features have an average validation of 88% and use the GLCM method which shows the neighbor relationship. Between the two pixels that form a co-occurrence matrix of the image data, namely GLCM, it shows that the features of homogeneity, correlation, contrast and energy have an average validation of 70.93%. The k-Nearest Neighbor (k-NN) algorithm is used in research to classify the image object to be studied. The results of this study were successfully carried out using k-Nearest Neighbor (k-NN) with the euclidean distance and k = 1 with the highest extraction yield of 88% and the results of GLCM feature extraction for homogeneity of 75.5%, correlation of 78.67%, contrast of 65.75 % and energy of 63.83% with an average accuracy of 70.93%.
Ant Colony Optimization for Traveling Tourism Problem on Timor Island East Nusa Tenggara Yampi R Kaesmetan; Marlinda Vasty Overbeek
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 1 (2020): March 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i1.9274

Abstract

Timor island consists of five districts and one city, namely Kupang District, South Central Timor District, North Central Timor, Belu District, Malaka District, and Kupang City. On the Timor island, it has natural tourist destinations, culinary tours, cultural and historical attractions most on the island of Timor. The Ant Colony Optimization (ACO) Algorithm is very unique compared to the other nearby search algorithm, this algorithm adopted because of Ant Colony who were looking for food from the nest to food sources by leaving a footprint called Pheromone. Mapping system algorithm using ant, tourist sites can show the shortest route between two points is desired. Ants algorithm proved to be applied in determining the optimum route, but still has the disadvantage of dependence on the parameter value is not maximized. From the test results based on parameters of the cycle and the number of ants affects the simulation time, for ant algorithm parameters. From the test results based on the parameters, α and β affects, number of node, the simulation time and the shortest distance varying toward the destination even if the starting location and ending on the same location.
Selection of Superior Rice Seed Features Using Deep Learning Method Dinda Ayusma Tonael; Yampi R Kaesmetan; Marinus I. J. Lamabelawa
Indonesian Journal of Artificial Intelligence and Data Mining Vol 4, No 2 (2021): September 2021
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v4i2.13947

Abstract

Indonesia is a tropical country known as an agricultural country, where 88.57% of the population works in the agricultural sector (BPS Indonesia, 2020). Indonesia is rich in agricultural products such as rice, soybeans, corn, peanuts, cassava and sweet potatoes. Rice (Oryza sativia L) is one of the most dominant food commodities for the people of Indonesia. The carbohydrate content per 100 grams of rice reaches 79.34 grams. The main benefit of rice is as a source of carbohydrates and a source of energy for the body. Seed is one of the factors that play a role as a carrier of technology in advanced agriculture, therefore the seeds used must be of good quality. Farmers tend to equate rice seeds from previous harvests, the rice seed classification process is carried out manually through visual observation and soaking rice seeds in a container filled with water, submerged and floating rice seeds are selected for use, and those that float are discarded. But in reality it still produces less than optimal results, for example rice that is less dense and cracked. This study uses a color moment to be extracted using GLCM (gray level co-occurence matrix) then classified with k-NN to determine the class, then uses the SVM model to display the best hyperplane line to separate the two classes, namely superior and non-superior classes after that system tested with confusion matrix. With a continuous and more intense work process, the research entitled Selection of Superior Rice Seed Features Using Deep Learning Methods. The output of this research leads to a conclusion which rice seeds are superior and which are not superior, aiming to optimize the yield of rice with better quality. The research was successfully carried out using the deep learning method with the highest accuracy of 92.85%.
Data Train Reduction on Data Image With K Support Vector Nearest Neighbor (Case Study : Maize Leaf Image) Marlinda Vasty Overbeek; Yampi R Kaesmetan
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 2 (2020): Spetember 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i2.10451

Abstract

In this study, we applied the K Support Vector Nearest Neighbor algorithm to reduce data train on data image. The data image that we used is the maize leaves image infected with fungi and healthy maize leave. The aim of data train reduction in this study is to get faster and more accurate prediction results. This because by using the K Support Vector Nearest Neighbor algorithm, a support vector that is formed from the algorithm really characterize the objective function of the problem. The accuracy obtained from this study is 0.20 or 20% mean error for the value of nearest neighbor K  = 3 and using K Nearest Neighbor as a model construction algorithm. The error value is smaller than when we compared to the construction of the model without performing data train reduction. The error value if not doing any reduction is 0.209 or 20.9%. Whereas in terms of time efficiency, working with the K Support Vector Nearest algorithm is 24 seconds faster than without performing data train reduction 
KLASIFIKASI STATUS GIZI BALITA DI KELURAHAN OESAPA BARAT MENGGUNAKAN METODE K-NEAREST NEIGBOR Yampi R Kaesmitan; Jusrianto A Johannis
MULTITEK INDONESIA Vol 11, No 1 (2017): Juni
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (458.108 KB) | DOI: 10.24269/mtkind.v11i1.506

Abstract

Nutritional status is a state of the body as a result of food consumption patterns and the use of nutritional substances. Determination of the nutritional status of children is useful to know the circumstances of infant nutritional based BB / U (Weight by Age), TB / U (Height by Age), BB / TB (Weight by Height). The system designed is a system of determining the nutritional status of children using the K-NN (K-Nearest Neighbor), where the method of K-NN (K-Nearest Neighbor) is a method of classifying or grouping of test data that is unknown class to several nearest neighbors using distance calculation formula. The variables used in this system is based on data Anthropometri or measurements of the human body, namely U (Age), BB (Weight), TB (Height), LK (Head Circumference).
Simulasi Pengukuran Kadar Air, Ph Tanah, Kelembaban Dan Suhu Udara Menggunakan Mikrokontroler (Arduino-Uno R3) Melania Zemil; Yampi R. Kaesmetan; Edwin A. U. Malahina
(JurTI) Jurnal Teknologi Informasi Vol 6, No 2 (2022): DESEMBER 2022
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36294/jurti.v6i2.2618

Abstract

Pada kantor Instalasi Penelitian dan Pengembangan Teknologi Pertanian (IPPTP)  Naibonat memiliki sebuah masalah yaitu sulit dalam mengetahui kesuburan tanah ini dikarenakan hanya memiliki 12 orang petugas lapangan yang mengontrol lahan tanam yang luas. Berdasarkan masalah yang ada maka dibuatlah sebuah alat dimana alat ini dapat membantu petugas lapangan dalam mengetahui apakah lahan yang akan ditanami subur atau tidak dengan memperhatikan faktor-faktor yang mempengaruhi kesuburn tanah yaitu kelembaban tanah, suhu dan kelembaban udara, serta pH tanah. Rangcangan alat yang akan dibuat ini menggunakan capacitive soil moisture sensor v1.2 sebagai sensor yang berfungsi mengukur kelembaban tanah, sensor pH tanah yang digunakan untuk mengukur tingkat acid (keasaman) dan alkali (kebasaan) tanah,sensor DHT11 untuk mengukur suhu dan kelembaban udara. Dengan di buatnya alat ini diharapkan dapat membantu petugas lapangan di Instalasi Penelitian dan Pengkajian Teknologi Pertanian (IPPTP) Naibonat dalam menngontrol kesuburan tanah pada lahan tanam.
Workshop Manajemen Pembelajaran Berbasis Digital di SMP Negeri 1 Amfoang Tengah Desty A. Bekuliu; Yusuf Elpontus Tanaem; Nimrot Doke Para; Martin Ch. Liufeto; Nelci Non; Yampi R. Kaesmetan; Delfince Toleu; Endang Oekolos; Yafet Balan
I-Com: Indonesian Community Journal Vol 3 No 4 (2023): I-Com: Indonesian Community Journal (Desember 2023)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v3i4.3593

Abstract

Community service activities are wrapped in the form of workshops based on digital learning and evaluation which is utilizing applications connected to the internet network. The purpose of this Community Service Activity (CSA) is to provide training and enhance teachers' understanding of learning management, specifically digital-based learning evaluation, at Junior High School (JSC) 1 Amfoang Center. The activity spans 2 days, involving 3 speakers who deliver materials and training to 14 teachers. The CSA implementation method includes presenting content on learning management, digital-based learning management, and digital-based learning evaluation. It also includes practical exercises in digital-based learning evaluation using the Slido platform, a website that facilitates interactive online discussions. The outcome of this workshop indicates that teachers gain knowledge and skills in conducting digital-based evaluations for mid-term exams and final semester exams using the Slido application.
Citra Digital Voice Recognition Menggunakan SVD Dominggus Mangngi; Putra Prawira Yohanes Puka; Yampi R. Kaesmetan
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 4 (2024): JELIKU Volume 12 No 4, May 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2024.v12.i04.p21

Abstract

Pengenalan suara merupakan area penting dalam pemrosesan sinyal digital dan kecerdasan buatan. Dalam penelitian ini, kami mengusulkan sebuah metode pengenalan suara yang inovatif menggunakan Singular Value Decomposition (SVD) pada citra digital. Pendekatan ini bertujuan untuk meningkatkan akurasi dan efisiensi dalam pengenalan suara dengan memanfaatkan representasi citra suara yang dihasilkan melalui proses SVD. Kami mengintegrasikan teknik-teknik pemrosesan citra dengan model pengenalan suara berbasis mesin learning untuk menghasilkan sistem yang dapat mengidentifikasi dan membedakan pola suara dengan tepat. Metode yang diusulkan diuji menggunakan berbagai dataset suara yang mencakup berbagai variasi dan kondisi, dan hasil eksperimen menunjukkan peningkatan yang signifikan dalam akurasi pengenalan suara dibandingkan dengan metode-metode konvensional. Dengan demikian, pendekatan ini menjanjikan sebagai kontribusi penting dalam pengembangan sistem pengenalan suara yang handal dan efisien. Keywords: Pengenalan suara, Citra digital, Singular Value Decomposition (SVD), Mesin pembelajaran, Akurasi pengenalan suara
Co-Authors 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 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 Safirah, Nindy Aulia Saputri, Nur Azizah Indah Selan, Frederikus Wanforsan Reynaldy Sten Dofanky Mooy Tahuk, Wilhelmina Johana Tefa, Sepri Vito Daniel Boboy Vladimir Juino Jago Uko, Christianus Wisak, Sayyid Ahmad Wole, Jernianti Susanti Wulansari Masan Yafet Balan Yesaya Laga Nawa Yoman Berchmans Yunita Luruk Ulu Yustina Bete Dos Santos Yusuf Elpontus Tanaem