Article Per Year (5 Year)
p-Index From 2020 - 2025
0.778
P-Index
This Author published in this journals
All Journal Jurnal Teknologi dan Informasi Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Teknologika Jurnal Sains dan Teknologi
Teguh Iman Hermanto
Program Studi Teknik Informatika, Sekolah Tinggi Teknologi Wastukancana Purwakarta
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary Other

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
PENJADWALAN MATA KULIAH MENGGUNAKAN ALGORITMA GENETIKA DI STT WASTUKANCANA PURWAKARTA Umar Hasan; Teguh Iman Hermanto; M. Rafi Muttaqin
Jurnal Teknologi dan Informasi (JATI) Vol 8 No 2 (2018): Jurnal Teknologi dan Informasi (JATI)
Publisher : Program Studi Sistem Informasi, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (469.921 KB) | DOI: 10.34010/jati.v8i2.1040

Abstract

Generating a study at STT Wastukancana Purwakarta is strongly important to get an effective way to study. As the allocation of rooms to the schedule made is still manual, it is possible there are some room service clashes. To solve that problem, a study scheduling using computerization is needed in order to make no clash of room service. The use of genetic algorithm to solve the problem is able to get the optimal solution in generating the schedule with chromosome representative as an integer from each of data primary key, the beginning of population initialization, the selection with rank-selection method, two-points crossover method, and mutation. From the test, the result points out that the optimal schedule with 416 pengampu data is generated when a number of population are 30, a number of generations are 150, the crossover probability value (Pc) is 0.4, and the mutation probability value (Pm) is 0.37.
Penerapan K-Means Clustering dan Cross-Industry Standard Process For Data Mining (CRISP-DM) untuk Mengelompokan Penjualan Kue Muhammad Rafi Muttaqin; Teguh Iman Hermanto; Muhamad Agus Sunandar
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 19, No 1 (2022): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v19i1.3976

Abstract

Cake is a food that doesn’t have long durability. This will cause the cake producer to suffer a losses if the product is not sold out at the expiration date. With the availability of cake sales data, the sales potential will be clustered according to the date of sale using K-Means method. The data mining process used in this study is Cross-Industry Standard Process for Data Mining (CRISP-DM). The results obtained are the formation of agroup of cake sales that man consumers buy on each date. This grouping is divided into three, namely low, medium, and high sales. This will help producers to prepare their products more effectively and efficiently so as to reduce wasteful production. If the cake is in the low sales group, the number of cake products is small. On the contrary, if there is a cake that goes into high sales group, then the producer will produce the cake in large quantities.
RANCANG BANGUN TEMPAT SAMPAH PINTAR (SMARTBIN) Minarto Minarto; Lise Sri Andar Muni; Candra Dewi Lestari; Teguh Iman Hermanto
Jurnal Teknologika Vol 11 No 2 (2021): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.738 KB) | DOI: 10.51132/teknologika.v11i2.137

Abstract

Semakin meningkatnya jumlah penduduk di suatu wilayah, maka semakin banyak pula sampah yang akan dihasilkan. Jika kita mendengar kotak sampah yang penuh dan didiamkan maka pasti terlintas dibenak kita masalah berupa sekumpulan dari berbagai macam benda yang telah di buang dan sejenisnya yang akan menimbulkan bau busuk dan berbagai macam penyakit seperti gatal-gatal, diare, flu, DBD, dan lain-lain Masalah sampah bukanlah hal yang baru bagi kota-kota besar. Dari permasalahan tersebut penulis melakukan penelitian untuk dapat merancang dan membangun tempat sampah pintar (Smartbin) dengan notifikasi menggunakan metode pengembangan prototype. Adapun beberapa komponen yang digunakan yaitu NodeMCU, motor servo, sensor ultrasonic, modul GPS, speaker, modul mp3 dan lain-lain. Hasil dari penelitian ini adalah perangkat tempat sampah pintar (Smartbin) dengan notifikasi yang dapat memudahkan dalam membuang sampah, dimana tempat sampah akan terbuka secara otomatis ketika sampah akan dibuang. Selain itu juga memudahkan pihak dinas lingkungan hidup dalam mendapatkan informasi ketika tempat sampah sudah terisi penuh yang akan mengirimkan notifikasi melalui telegram. Kata kunci: Tempat Sampah, Prototype, NodeMCU, Motor Servo, Ultrasonic
Analisis Sentimen Opini Masyarakat Terhadap Film Pada Platform Twitter Menggunakan Algoritma Naive Bayes Yuni Nurtikasari; Syariful Alam; Teguh Iman Hermanto
INSOLOGI: Jurnal Sains dan Teknologi Vol. 1 No. 4 (2022): Agustus 2022
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v1i4.770

Abstract

Film is one of the most interesting topics to talk about. When someone writes an opinion on a film, all the elements in the film will be written down. Film opinion data in this study were taken from film comments written on twitter. The number of opinions written on Twitter requires classification according to the sentiments they have so that it is easy to get the tendency of the opinion towards the film whether it tends to have a positive, negative or neutral opinion. Recently, the spotlight on twitter media in Indonesia is a film with the title Horror-Ngeri Sedap. Ngeri-Ngeri Sedap is a 2022 Indonesian comedy-drama film directed and written by Bene Dion Rajagukguk. The film is set in the Batak Tribe, starring Arswendy Beningswara Nasution, Tika Panggabean, Boris Bokir Manullang, Gita Bhebhita Butar-butar, Lolox, and Indra Jegel. This causes differences in the views and opinions of twitter users towards the Horror Sedap film. So it is necessary to have a sentiment classification for the opinion. The use of the Naïve Bayes Algorithm was chosen in the analysis because it has the highest probability or opportunity value for data classification. Labeling on Twitter data is done manually by giving positive, negative, neutral sentiments to the raw dataset in Microsoft excel then the data enters the preprocessing transformation, tokenization and filtering stages. The tf-idf weighting is carried out when the data is complete in the transformation process, tf-idf is used to determine the number of occurrences of words, then the data classification is carried out using the Naïve Bayes Algorithm. confusion matrix testing is done after the data classification is complete using the orange tools. Based on the test results with the confusion matrix with orange tools, the average accuracy value is 0.65% and the precision value is 0.67%, and recall is 0.65%, and the percentage is neutral 0.83% in its classification. This proves that the public sentiment on the twitter platform towards the case of the film Horror Sedap is neutral and the Naïve Bayes Algorithm is considered reliable and valid in data processing.
Co-Authors Candra Dewi Lestari Lise Sri Andar Muni M. Rafi Muttaqin Minarto Minarto Muhamad Agus Sunandar Muhammad Rafi Muttaqin Syariful Alam Umar Hasan Yuni Nurtikasari