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All Journal TEKNIK INFORMATIKA Jurnal CoreIT JURNAL ILMIAH INFORMATIKA Journal Information System Development (ISD) METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Jurnal Saintek Lahan Kering JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JUSIM (Jurnal Sistem Informasi Musirawas) Jurnal Tekno Kompak Jurnal Generic Jurnal Abdimas Ilmiah Citra Bakti (JAICB) Journal Of Information And Technology Unimor (JITU) Jurnal Sains Teknologi dan Sistem Informasi Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Nababan, Darsono
Program Studi Teknologi Informasi, Universitas Timor
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Physics Public Health Social Sciences

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Penerapan Algoritma Genetika Pada Pengenalan Paragraf Erwin Saragih, Rejoice Iboy; Nababan, Darsono
Journal Information System Development (ISD) Vol 4, No 1 (2019): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (736.964 KB)

Abstract

Paragraph consists of sentences which has main idea. In this research, it applied the genetic algorithm to recognize a paragraph. It has several steps to do it, firstly on the alphabet forms word, then sentence, and finally paragraph. The process start from typing the paragraph and then the genetic algorithm will identify the paragraph accordingly by stages which are initial population, selection, crossover and mutation. Genetic algorithm is heuristic searching algorithm which based on nature selection of mechanism and nature genetics. Paragraph is a set of words or other characters with one or more languages are written especially if arranged in a customary order. The final result of this research is that showing the exact paragraph that is targeted.
SENTIMEN ANALISIS TERHADAP KEBIJAKAN PEMBELAJARAN JARAK JAUH SELAMA PANDEMI COVID-19 MENGGUNAKAN ALGORITMA NAÏVE BAYES Darsono Nababan
JURNAL TEKNIK INFORMATIKA Vol 14, No 1 (2021): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v14i1.17002

Abstract

Social media is a means to convey aspirations directly, but every aspiration is from social media users. Everyone who expresses opinions on social media contains positive, negative, and neutral sentiments. The implementation of the Ministry of Education and Culture's policy on the implementation of distance learning policies during the pandemic COVID-19 received various responses from the people of Indonesia. neutral as many as 894 comments, then 52 comments with negative sentiment, and 32 comments with positive sentiment with an accuracy value of 98.79%
SISTEM PENGONTROLAN PERSEDIAAN BARANG DENGAN METODE ECONOMIC ORDER QUANTITY (EOQ) MENGGUNAKAN ALGORITMA GENETIKA (Studi Kasus Gundaling Farm) Nababan, Darsono
Journal Information System Development (ISD) Vol 2, No 1 (2017): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

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Abstract

The problem of emphasis on the cost of spending on the need for ordering within a company is very complex where the company demands a very optimal achievement that will lead to a huge profit for the company. Gundaling Farm is a company engaged in the business of producing and selling cow's milk is always trying as much as possible to meet customer demand. In this research used Economic Order Quantity (EOQ) method with a genetic algorithm to solve supply problem on Pt.Gundaling Farm. This research is expected to help PT.Gundaling Farm to consider and determine the policy in inventory control activities in order to run more effectively and efficiently. EOQ is the quantity of goods that can be obtained with a minimal cost, or often said to be the optimal amount of purchases. So by applying EOQ method, PT.Gundaling Farm will know how many order (quantity order) goods and when PT.Gundaling Farm should re-order goods during the period 2015. Thus PT.Gundaling Farm can optimize the cost of inventory to be spent on goods.Keywords: inventory, goods, Economic Order Quantity (EOQ).algorithm, genetic
SISTEM PENDUKUNG KEPUTUSAN REWARD BONUS KARYAWAN DENGAN METODE TOPSIS Nababan, Darsono; Rahim, Robi
Journal Information System Development (ISD) Vol 3, No 1 (2018): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

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Abstract

ABSTRAKSistem pendukung keputusan atau dikenal dengan Decision Support System, pada tahun 1970-an sebagai pengganti istilah management Information System, Sistem pendukung keputusan penentuan bonus kedisiplinan, merupakan salah satu bentuk dari sistem pendukung keputusan biasa dipakai guna membantu memberikan keputusan sesuai kriteria-kriteria tertentu, Masalah yang terjadi banyaknya karyawan pada suatu instansi menyulitkan untuk menentukan karyawan yang berhak menerima bonus kedisiplinan.Penelitian ini bertujuan merancang dan membuat sistem untuk menentukan karywan yang berhak menerima bonus kedisiplinan yang lebih baik dari sistem sebelumnya dimana masih bersifat manual, untuk itu diperlukan suatu konsep pendukung keputusan yang memudahkan memberikan keputusan pemberian reward bonus, pada penelitian ini menggunakan metode Technique Order Preference By Similarity To Ideal Solution (TOPSIS) dimana akan memudahkan dalam proses pengambilan keputusan. Kata Kunci: TOPSIS, Reward , SPK TOPSIS 
ANALISIS FAKTOR -FAKTOR YANG MEMPENGARUHI MAHASISWA DALAM MENGAMBIL BEASISWA DENGAN MENGGUNAKAN ALGORITMA C4.5 Nababan, Darsono; Wijaya, Alvin; William, William
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 4 No 1 (2019): JUSIM (JURNAL SISTEM INFORMASI MUSIRAWAS) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v4i1.431

Abstract

Abstrak Pendidikan merupakan salah satu kebutuhan  yang sangat penting di dalam mansyarakat. Melalui Pendidikan pola pikir dan kualitas hidup seseorang akan meningkat. Untuk mendapatkan Pendidikan yang berkualitas maka dibutuhkan juga biaya yang sangat tinggi saat ini, untuk itu mahasiswa/mahasiswi banyak yang tertarik untuk mengambil beasiswa untuk dapat meringankan beban tersebut. Dengan memanfaatkan pengisian survei untuk mengukur  factor-faktor  apa saja yang mempengaruhi mahasiswa dalam mengambil beasiswa. Melalui hasil analisis tersebut diharapkan dapat menghasilkan faktor apa yang paling mendekati sehingga mahasiswa mengambil beasiswa. Pengolahan data mining  dilakukan dengan menggunakan Algoritma C4.5 untuk  untuk membentuk pohon keputusan. Adapun perangkat lunak yang menerapkan Algoritma C4.5 ini adalah Rapid Miner.   Kata kunci—Pendidikan, Beasiswa, Algoritma C4.5, Rapid Miner Abstract Education is one of the most important needs in society. Through Education the mindset and quality of one's life will increase. To get quality education, a very high cost is needed at this time, for students, many students are interested in taking scholarships to ease the burden. By utilizing filling surveys to measure what factors influence students in taking scholarships. Through the results of the analysis, it is expected to produce the closest factors so that students take scholarships. Data mining processing is done by using C4.5 Algorithm to form decision trees. The software that applies the C4.5 Algorithm is Rapid Miner. Keywords— Education, Scholarship, C4.5 Algorithms, Rapid Miner
IMPLEMENTASI METODE FUZZY TIME SERIES DENGAN MODEL ALGORITMA CHEN UNTUK MEMPREDIKSI HARGA EMAS Nababan, Darsono; Alexander, Eric
JURNAL TEKNIK INFORMATIKA Vol 13, No 1 (2020): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.092 KB) | DOI: 10.15408/jti.v13i1.15516

Abstract

Gold is one of the people's preferred forms of investment and is considered the safest (save -heaven). Gold risk which is considered small is the main attraction because in general Indonesian people are not yet familiar with capital market investments such as stocks and mutual funds. But the price of gold is very volatile as for the factors that affect the fluctuations of gold are consumption demand, volatility and market uncertainty, protection of low-interest rates, and the US dollar. Predicting the movement of the gold price and knowing where the direction of the exchange rate moves and determining the price of gold up or down cannot be done accurately and consistently. For this reason, in reducing the risk of loss, an application is needed to predict gold prices using the Fuzzy Time Series Chen algorithm using MATLAB software. In this study to obtain prediction results and comparison charts using actual data and prediction data for the 2015-2017 gold price. From the calculation results obtained by the prediction results with the Fuzzy Time Series method with the Chen algorithm where the average difference between the actual data and prediction data is not more than Rp. 2,850, - where predictions using the Fuzzy Time Series method Chen's algorithm is sufficient to use 1 data to predict the second data which makes this method accurate in predicting the price of gold.
Segmentasi Citra Tenun Menggunakan Metode Otsu Thresholding dengan Median Filter Budiman Baso; Darsono Nababan; Risald risald; Renaldi Yulvengki Kolloh
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 5 No. 1 (2022): Jutikomp Volume 5 Nomor 1 April 2022
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v5i1.2586

Abstract

Segmentasi citra tenun merupakan langkah yang dilakukan untuk memisahkan bagian area objek (foreground) dengan latar belakang (background) pada citra tenun, sehinggah objek tenun yang tersegmentasi berupa motif dapat diproses untuk keperluan lain seperti pengenalan pola. Hasil dari segmentasi harus akurat, jika tidak akurat dalam memisahkan objek yang ada pada citra maka akan mempengaruhi hasil proses selanjutnya. Pada penilitian ini segmentasi dilakukan menggunakan metode Otsu Thresholding pada citra tenun timor dengan terlebih dahulu melakukan preprocessing yaitu reduksi noise menggunakan Median Filter. Setelah mendapatkan citra hasil segmentasi menggunakan Otsu Thresholding dengan Median Filter, selanjutnya melakukan pengukuran performa, hasil segmentasi dari setiap pengujian dievaluasi dengan menggunakan RAE (relative foreground area error) dan ME (missclassification error). Terdapat dua skenario yang diimplementasikan dalam melakukan segmentasi citra tenun timor, skenario yang pertama yaitu melakukan segmentasi citra tenun timor dengan menggunakan metode Otsu Thresholding dan skenario kedua melakukan segmentasi citra tenun timor menggunakan metode Otsu Thresholding dengan penambahan Median Filter. Hasil segmentasi dari 16 citra tenun timor dari 8 motif yang ada menunjukkan bahwa, segmentasi citra tenun dengan menggunakan metode Otsu Thresholding dengan menambahkan Median Filter mendapatkan nilai rata-rata RAE terbaik yaitu 0.34 % dan nilai rata-rata ME sebesar 0.55 %.
ANALISIS PERSEDIAAN STOK BARANG MENGGUNAKAN ALGORITMA C 4.5 (STUDI KASUS CV HARAPAN RAYA) Darsono Nababan
JURNAL ILMIAH INFORMATIKA Vol 7 No 01 (2019): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (561.349 KB) | DOI: 10.33884/jif.v7i01.839

Abstract

In a distributor company, stock is one of the important factors that need to be considered by the company. The amount of stock in and out must be considered, the aim is to keep the stock available stable. A stable stock means that in a warehouse there is no excess stock or lack of stock. The problem is that each item has a different buying interest. Then a calculation is needed to be able to predict what items need to be added or reduced in the warehouse. C4.5 algorithm is a group of algorithms using decision trees. Decision trees are a very strong and well-known method of classification and prediction. The richer the information or knowledge contained by training data, the accuracy will increase. This algorithm is used to analyze the time of purchase of goods that have been depleted by classifying the items which are already in stock added or not, so that the availability of goods keep stable. The application of the C 4.5 algorithm can be used to predict stock availability at CV Harapan Raya. The results of calculating the entropy value in algorithm C 4.5 can predict the amount of stock provided by CV Harapan Raya.
PELATIHAN E-LEARNING DASAR BAGI GURU-GURU BIDANG STUDI IPS SE KOTA KEFAMENANU Darsono Nababan; Yasinta Rema
Jurnal Abdimas Ilmiah Citra Bakti Vol 2 No 2 (2021)
Publisher : STKIP Citra Bakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38048/jailcb.v2i2.385

Abstract

The COVID-19 emergency period changed the education system in Indonesia in a very short time, requiring every student to study remotely. Of course this encourages teachers to innovate and policy makers in this case the Ministry of Education and Culture of the Republic of Indonesia to make adjustments during the COVID-19 pandemic by changing some rules by issuing circular letter number 2 of 2020 regarding the prevention and handling of COVID-19 in the environment. Ministry of Education and Culture, as well as circular letter number 3 of 2020 regarding the prevention of COVID-19 in education units. The readiness of schools in implementing distance learning received various positive and negative responses from various elements of society. The readiness of teachers in the implementation of online education has not been maximized, this is due to the lack of knowledge in the field of Information Technology. Therefore, to support government policies in implementing distance learning and minimizing the spread of the COVID-19 virus, teachers need to be equipped with e-learning implementation. Teachers are expected to be able to compile learning materials using online e-learning using the Edmodo platform so that teachers are not only fixated on one learning model using conventional models
Klasifikasi Kepribadian Menggunakan Algoritma Decision Tree Berdasarkan Ten Item Personality Inventory Carissa Limantara; Darsono Nababan
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 5, No 1 (2019): Juni 2019
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v5i1.6236

Abstract

The Ten Item Personality Inventory (TIPI) dirancang sebagai alat pengukuran sederhana untuk menentukan lima kepribadian utama (Big Five Personality Domain) manusia: Openness, Conscientiousness, Extraversion, Agreeableness, dan Neuroticism (OCEAN). Dalam pengisian survey, responden cenderung merasa jenuh jika diminta untuk menjawab questionnaire yang panjang. Tes TIPI mengatasi hal tersebaut dengan memberikan solusi sepuluh pertanyaan. Menggunakan algoritma decision tree, spreadsheet yang terdiri dari data responden tes TIPI akan diubah menjadi file xls, yang akan diproses melalui program data mining, RapidMiner. Kumpulan data yang dimuat akan dipecahkan menggunakan metode klasifikasi pohon keputusan, di mana sifat kepribadian yang dominan akan diterapkan sebagai atribut target. Hasil yang diharapkan dari studi ini adalah simulasi tes TIPI yang bisa menelaah kepribadian dominan responden secara akurat. Kata Kunci – TIPI, OCEAN, data mining, pohon keputusan, RapidMiner
Co-Authors Alexander, Eric Budiman Baso Carissa Limantara Efrida_R Haumetan Erwin Saragih, Rejoice Iboy Fedelia Da Da Conceicao Florensia Seran Hevi Herlina Ullu Jeri Aurelianus Sede Krisantus J. Tey Seran Leonard Peter Gelu Maharani Cantika Cahyani Rahim, Robi Renaldi Yulvengki Kolloh Risald risald Septianmanek Septianmanek Wijaya, Alvin William William Yasinta Oktaviana Legu Rema Yasinta Rema Yoseph P.K Kelen Yoseph P.K Kelen Yoseph P.K. Kelen Yuliana Febriyanti Tefa