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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Jurnal CoreIT INOVTEK Polbeng - Seri Informatika Jurnal Teknologi Sistem Informasi dan Aplikasi Building of Informatics, Technology and Science Zonasi: Jurnal Sistem Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Information System Journal (INFOS) Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT) Malcom: Indonesian Journal of Machine Learning and Computer Science Scientific Journal of Informatics Jurnal Riset Pendidikan dan Karakter INOVTEK Polbeng - Seri Informatika
Fitri Insani
Bogor Agricultural University
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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UPAYA INDONESIA MEMBEBASKAN TENAGA KERJA INDONESIA TERPIDANA HUKUMAN MATI DI ARAB SAUDI (2011-2013) Insani, Fitri; Jamaan, Ahmad
Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Vol 2, No 1: WISUDA FEBRUARI 2015
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Riau

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Abstract

This research describes about effort of Indonesia to acquitted Indonesia labours who get death penalty in Saudi Arabia’s (2011-2013). There are some Indonesian labours that have been accused of committing a crime that drags them become a convict of the death penalty by a court of Saudi Arabia’s. There are three kind of the death penalty in Saudi Arabia’s, they are: Qishas, Rajam and Ta’zir. As for the allegations imposed on Indonesian labours that under sentence of death in Saudi Arabia’s are torture, murder, perform of magic and adultery.This research used the theory of diplomacy. As for the kind of diplomacy that used are bilateral diplomacy. Bilateral diplomacy is diplomacy carried out by between two countries. This research used nation-state analysis.This study applies qualitative research method with library. The data sources are from books, journal, and the internet.Finnaly, Indonesian government’s actions in providing protection for Indonesian labours who became convicted of the death penalty in 2011-2013 is considered to be the maximum. As for the efforts that has been made are: do moratorium policy, bilateral diplomacy, forming a special task force, appoint of retainer lawyer and assist in paying (diyat) to the families of victims. Those efforts can help the Indonesian labours who convicted of death penalty and get a lighter punishment like a forgiveness from the victim’s family or pay a fine.Keywords: Bilateral Diplomacy, Death Penalty, Effort, Indonesian Labours
KONSTRUKSI MAKNA “TAKKO BINOTO” BAGI PELAKU DI DESA MENAMING KECAMATAN RAMBAH KABUPATEN ROKAN HULU Insani, Fitri; Yohana, Nova
Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Vol. 6: Edisi II Juli - Desember 2019
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Riau

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Abstract

This research is motivated by the phenomenon of Takko binoto which has long been a fairly complex problem in which many male and female couples in realizing their desire to carry out a marriage contract by way of binoto takko. Because they felt that there was a conflict from parents about the relationship they had endured, Takko Binoto was chosen as a way out. Takko Binoto happened because it was influenced by economic aspects and low levels of education. The purpose of this research is to find out the motives behind the couple doing Takko Binoto, understanding the meaning of Takoto Binoto and knowing the communication experience for Takko Binoto actors in Menaming village, Rambah District, Rokan Hulu Regency.This study uses qualitative research methods with a phenomenological approach. Data collection techniques consist of in-depth interviews, observation and documentation. Data analysis techniques consist of data reduction, data presentation and drawing conclusions. The data validity checking technique uses triangulation. The gathering of informants in this study used the Snowball Technique with the number of informants as many as 5 pairs of Takoto Binoto actors.The results of this study show the first few motives of takoto binoto actors in the village menaming are divided into two motives because (because motive) and motives of hope (in order to motive). As for the motives because for Takoto binoto actors are economic factors, mutual love, free promiscuity and low education. Then in order to motive Takko Binoto's perpetrators are motives to provide a deterrent effect, happy motives for the world and the hereafter and motives to ease the burden on the family's economy. Second, the meaning of Takko Binoto for actors in the village of Menaming is the meaning of Takoto Binoto as the destiny of God, Takko Binoto as a result of past actions, and Takko Binoto as the last choice to be taken. Third, the Takko Binoto perpetrators' communication experience consists of pleasant (positive) communication experiences and unpleasant communication experiences. a pleasant (positive) communication experience for Takko Binoto's perpetrators, namely getting a life partner to feel extraordinary love from her husband. Then the unpleasant (negative) communication experience for Takko Binoto actors is getting negative comments, being ostracized from the family and the environment, and family conflicts. Keywords: Construction Meaning, Takko Binoto, Motives
Pembentukan Model Regresi Linier Menggunakan Algoritma Genetika untuk Prediksi Parameter Indeks Standar Pencemar Udara(ISPU) Insani, Fitri; Darlianti, Sri Indah
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 5, No 2 (2019): Desember 2019
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (568.836 KB) | DOI: 10.24014/coreit.v5i2.9157

Abstract

Prediksi merupakan upaya untuk mengetahui suatu peristiwa di masa yang akan datang. Pada kasus prediksi data yang dipelajari merupakan data historis, agar data tersebut dapat mengasilkan informasi berupa hasil prediksi maka digunakan suatu model yaitu regresi linier, dalam proses pembentukan model regresi linier digunakan pendekatan kecerdasan buatan algoritma genetika. Algoritma genetika digunakan untuk mendapatkan nilai koefisien terbaik pada persamaan regresi linier. Penelitian ini menggunakan data parameter Indeks Standar Pencemar Udara(ISPU), terdapat lima parameter ISPU meliputi Sulfur dioksida (SO2), Partikulat (PM10), Karbondioksida (CO), Ozon (O3), dan Nitrogen dioksida (NO2) sehingga dibangun lima model prediksi. Berdasarkan hasil pengujian menggunakan data harian bulan Januari 2016 sampai dengan Desember 2016, algoritma genetika mampu menentukan nilai koefisien yang digunakan pada model regresi linier dalam memprediksi parameter ISPU dengan kesalahan prediksi untuk parameter SO2 yaitu 2,33958%, kesalahan prediksi parameter PM10 6,623923%, kesalahan prediksi parameter CO 2,62279%, kesalahan prediksi parameter O3 6,34495%, dan kesalahan prediksi parameter NO2 2,927575%
Implementasi Metode Learning Vector Quantization (LVQ) Untuk Klasifikasi Keluarga Beresiko Stunting Aziz, Abdul; Insani, Fitri; Jasril, Jasril; Syafria, Fadhilah
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3478

Abstract

Stunting is a condition where a child's height is too short compared to children of the same age. This condition affects the health of toddlers in the short and long term, such as suboptimal body posture in adulthood, decreased reproductive health, and decreased learning capacity, resulting in suboptimal performance in school. One of the causes of stunting is a lack of nutrition, basic health facilities, and poor parenting practices. However, the current data collection and classification of families at risk of stunting still use Microsoft Excel, which is ineffective in processing large data. Therefore, the LVQ method, which is an improvement of the Vector Quantization method, is used to accelerate the classification process. In this study, 5 parameters were tested, and the optimal result was achieved by using 7 input neurons, Chebychev distance as the distance measure, a learning rate of 0.1, 7 epochs, and 30% of training data. With these parameters, an accuracy of 99.38% was obtained. Based on these results, the LVQ method can help improve accuracy in classifying families at risk of stunting
Penerapan Deep Learning Menggunakan Gated Recurrent Unit Untuk Memprediksi Harga Minyak Mentah Dunia Saputra, Nugroho Wahyu; Insani, Fitri; Agustian, Surya; Sanjaya, Suwanto
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3552

Abstract

Crude oil is a much-needed energy for the whole world. Each country is inseparable from the use of crude oil for use in various sectors, such as transportation, so that the price of world crude oil is the most important variable for the world. Fluctuations in oil prices will cause various problems, such as inflation, changes in market prices, and others. Therefore, the prediction of world crude oil prices is very important as a consideration for decision making. This study implements deep learning using the Gated Recurrent unit model. The data used is the price of Brent crude oil with a total of 5834 data, starting from January 4, 2000 to December 19, 2022. The parameters used are the number of GRU units, batch size, and lookback. The best model produced in this study is the GRU model with hyperparameters consisting of 30 lookbacks, 50 GRU units, and 256 batch sizes with the lowest MAPE value among the other models, which is 2.25%. The MAPE value states that predictions using the GRU model are said to be very good at predicting world crude oil prices
Analisis Pola Asosiasi Data Transaksi Penjualan Minuman Menggunakan Algoritma FP-Growth dan Eclat Najmi, Risna Lailatun; Irsyad, Muhammad; Insani, Fitri; Nazir, Alwis; ., Pizaini
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3592

Abstract

Every day transaction activities between companies and consumers continue to be carried out. This makes transaction data more and more and accumulate. This transaction data can be processed into more useful information using technology. Data mining is a technology that can work on a collection of transaction data into information that can be taken by companies as decision makers. The association rule method is used as a method to see the relationship between items in a transaction data. To analyze transaction data, researchers used the FP-Growth and Eclat algorithms. There are three stages of association in this study which are distinguished from the confidence value. The results in the first stage have a minimum confidence value of 0.4, the FP-Growth algorithm produces 41 association pattern rules, while the Eclat algorithm produces 32 association pattern rules. Then in the second stage the minimum trust value is 0.5, the FP-Growth algorithm produces 40 association pattern rules, for the Eclat algorithm it produces 32 association pattern rules. In the third stage, the minimum trust value is 0.6, the FP-Growth algorithm generates 32 association pattern rules, while the Eclat algorithm generates 30 association pattern rules. The results of the association pattern rules show that the Eclat algorithm is more efficient in determining the association pattern rules than the Fp-Growth algorithm
Sistem Klasifikasi Penyakit Jantung Menggunakan Teknik Pendekatan SMOTE Pada Algoritma Modified K-Nearest Neighbor Novitasari, Fitria; Haerani, Elin; Nazir, Alwis; Jasril, Jasril; Insani, Fitri
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3610

Abstract

The heart is a vital organ that plays a crucial role in pumping oxygenated blood and nutrients throughout the body. Heart disease refers to damage to the heart that can occur in various forms, caused by infections or congenital abnormalities. The World Health Organization (WHO) reports nearly 17.9 million deaths each year due to heart disease. In Indonesia, the prevalence of heart disease is around 1.5%, meaning that in 2018, approximately 15 out of 1,000 people, or nearly 2,784,060 individuals, were affected by this disease, according to the Basic Health Research data (Riskesdas) 2018. Many people have limited knowledge about heart health, leading to a lack of awareness of their heart conditions. This can be attributed to a lack of understanding regarding the importance of medical checkups related to heart health. Modified K-Nearest Neighbors (MKNN) is one of the data mining methods applied for classifying the risk of heart disease. The research utilized data obtained from the UCI dataset repository, which consists of 918 records with 12 attributes. To balance the imbalanced dataset with minority classes, the Synthetic Minority Over-sampling Technique (SMOTE) approach was used to generate new synthetic samples from the minority class. The objective of developing a web-based system for heart disease classification is to assist the public in assessing their risk of heart disease as early as possible, enabling them to take preventive actions sooner. The accuracy results of the MKNN algorithm with a 90:10 ratio are 80.37%, while with the MKNN+SMOTE approach, the accuracy increased to 84.00%. The use of the SMOTE approach improved the accuracy of low-performing data.
Diagnosis Dini Penyakit Gagal Ginjal Dengan Metode Dempster Fakhira, Adzra; Insani, Fitri; Irsyad, Muhammad; Vitriani, Yelfi; Kurnia, Fitra
Jurnal Inovtek Polbeng Seri Informatika Vol 8, No 2 (2023)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v8i2.3728

Abstract

Terlambatmendeteksipenyakitgagalginjalakanberakibatseriuskarenadiagnosisbiasanya terjadiketika masalah ginjal sudah mencapai tingkat parah. Seperti yang telah terjadi di Indonesia pada tahun 2022 lalu, terdapat 324 kasus terkonfirmasi dan 195 diantaranya meninggal dunia. Hal yang mempengaruhiketerlambatankesadaranpenderitaadalahpengetahuanyangkurangterhadapbahayapenyakit gagal ginjal. Penyakit gagal ginjal dapat disebabkan oleh dehidrasi, penyakit kronis seperti hypertensi dan diabetes, serta kekurangan banyak darah akibat  cedera atau operasi. Penggunaan teknologi dapat terwujud melalui pembuatan sistem pakardengan metode Dempster Shafer guna mendiagnosis penyakit gagal ginjal.Dalam sistem pakardiagnosis dini penyakit gagal ginjal ini penggunadiperintahkan agar mengisi data diri singkatdan gejala-gejala yang dialami. Selanjutnya sistem akan mengkombinasi gejala yang telahdipilih dengan metode Dempster Shafer menggunakan teori kepercayaan pakar sehingga mendapatkan hasil diagnosis berupa persentase pengguna mengidap penyakit gagal ginjal akut atau kronis, dan solusi untuk tindakan pengguna berikutnya. Penelitian ini telah menghasilkan sistem yang mampu mendiagnosis penyakit gagal ginjal dan dapat diterima dengan baik oleh pengguna
Perancangan VUI Pada Aplikasi Layanan Berita Kompas ID dengan Metode Human Centered Tri Prastio Nugroho; Mai Candra, Reski; Insani, Fitri; Iskandar, Iwan; Affandes, Muhammad
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6864

Abstract

Digital news has become an important breakthrough in current information development, replacing printed newspapers which are increasingly less popular in Indonesia. However, the majority of digital news readers, especially on Kompas.id, are elderly, who may face difficulties in using modern technology. This raises the question of whether sophisticated digital news products are enough to address issues of accessibility and convenience for seniors. This research aims to present innovative solutions by utilizing technology Voice User Interface (VUI) to help elderly and young digital news users. MethodHuman-Centered Design (HCD) was used in this study. Result ofUsability Testing (UT) on the prototype shows that users gave a positive assessment with a total score of 91.3, a high level of satisfaction. This became the basis for continuing development of this prototype.
Analisa sentimen terhadap kenaikan bbm di twitter (x) menggunakan naive bayes classifier Muhammad Abdillah; Fikry, Muhammad; Yusra; Nazir, Alwis; Insani, Fitri
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i1.6954

Abstract

In early September 2022, there was a shock from the news of the rise in fuel prices. The government decided to increase the price of fuel due to the surge in world oil prices. PT Pertamina (Persero) officially raised the price of Fuel Oil (BBM) one-third of September 2022, at 2:30 PM WIB (Western Indonesia Time). Since the decision, it has sparked opinions from the public. Many people expressed their responses through the social media platform Twitter, both in positive and negative ways. This resulted in both positive and negative sentiments from the public. The data used consisted of 3,000 tweets with the keyword "FUEL PRICE INCREASE," collected from November 1, 2022, to December 1, 2022. This research utilized the Naive Bayes Classifier method, conducted with three comparisons using thresholds ranging from 0.001 to 0.007. The experiment was conducted with three types of data testing: opinion data, mixed data (opinion-non-opinion), and balanced data. Here are the test results: for opinion data, the highest accuracy obtained was 80% with a ratio of 90:10, for mixed data, the accuracy obtained was 67.7% with a ratio of 70:30, and for balanced data, the accuracy obtained was 63.6% with a ratio of 90:10.
Co-Authors Abdul Aziz Afriyanti, Liza Ahmad Fauzan Al Fiqri, M. Faiz Ananda, Rahmadan Alam Ardan Aqilah, M Alfandri Baehaqi Damayanti, Elok Darlianti, Sri Indah Elin Haerani Elvia Budianita Fachry Abda El Rahman Fadhilah Syafria Fakhira, Adzra Febi Yanto Fitria Novitasari Gusti, Siska Kurnia Hasibuan, Aldiansyah Pramudia Iis Afrianty Jasril Jasril Jasril Jasril Kurnia Rahman, Fikri kurnia, fitra Lestari Handayani Miftah Farid Muhammad Abdillah Muhammad Affandes Muhammad Fikry Muhammad Irsyad Muhammad Ravil Mulyadi, Syahrul Najmi, Risna Lailatun Nazir, Alwis Nova Yohana Novriyanto Novriyanto Nurfadilah, Nova Siska Okfalisa Okfalisa Oktavia, Lola Pizaini Pizaini Pratama, Dandi Irwayunda Rahmad Abdillah Reni Susanti Reski Mai Candra Rossa, Rona Ruri Hartika Zain Saputra, Nugroho Wahyu Setiawan, Adil Subhi, Yazid Abdullah Surya Agustian Suwanto Sanjaya Syafira, Fadhilah Tri Prastio Nugroho Utari, Roid Fitrah Vernando, Julio Vitriani, Yelfi Vusuvangat, Imam Wiranti, Lusi Diah Yusra Zahri, Firman