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All Journal IJIBE (International Journal of Islamic Business Ethics) Dinamisia: Jurnal Pengabdian Kepada Masyarakat TIERS Information Technology Journal Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul)
Selvi Annisa
Lambung Mangkurat University
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Economics, Econometrics & Finance Education Energy Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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MACROECONOMICS EFFECT ON CONVENTIONAL AND SHARIA STOCKS DURING THE COVID-19 PANDEMIC Novia Nour Halisa; Selvi Annisa
IJIBE (International Journal of Islamic Business Ethics) Vol 7, No 1 (2022): March 2022
Publisher : UNISSULA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/ijibe.7.1.69-84

Abstract

This study aims to analyze the effect of macroeconomics on conventional and sharia stocks during the COVID-19 pandemic. The data collected for this study was obtained from monthly stock index data on the Indonesia Stock Exchange (IDX) as well as macroeconomic development reports from the Ministry of National Development Planning/Bappenas. The population in this study are all conventional and sharia stocks listed on the IDX. The sampling technique was carried out using a purposive sampling method with the criteria of conventional and sharia stocks listed on the IDX for the period March 2020 to June 2021. The macro variables used in researching the Jakarta Composite Index (JCI) and the Jakarta Islamic Index (JII) consisted of four variables, which are exports, imports, inflation rate, and foreign exchange reserves. The data analysis technique used in this research is multivariate multiple linear regression analysis accompanied by simultaneous and partial testing to determine the predictor variables that affect JCI and JII. The results shows that exports and foreign exchange reserves had a significant positive effect on JCI and JII, while imports and the inflation rate did not have a significant effect. The goodness of the model is 93%.
Peningkatan Kompetensi Peneliti Yayasan Kakikota Banajrmasin Dalam Melakukan Pre-Proccesing Data Hasil Survei, Analisis Data Kategorik, Dan Pembuatan Peta Tematik Yeni Rahkmawati; Selvi Annisa; Dewi Anggraini; Dewi Sri Susanti; Nur Salam; Yuana Sukmawaty; Fuad Muhajirin Farid
Jurnal Pengabdian ILUNG (Inovasi Lahan Basah Unggul) Vol 3, No 1 (2023)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ilung.v3i1.9334

Abstract

Banjarmasin KAKIKOTA Foundation is one of the NGOs based in South Kalimantan that works on urban issues in Banjarmasin City. Banjarmasin KAKIKOTA Foundation has conducted several social stuides on phenomena in Banjarmasin City through several surveys. However, due to the lack of knowledge about data processing, the researchers of the Banjarmasin KAKIKOTA Foundation experienced difficulties in analyzing survey results data. Therefore, Program Studi Statistika, FMIPA, Universitas Lambung Mangkurat (ULM) provides assistance in the form of statistical training to researcher of the Banjarmasin KAKIKOTA Foundation in order to improve the researcher’s competency and technical skills  in analyzing research data. The method used in this community service was training. The training was divided into three subthemes, namely: 1) Data preprocessing, 2) Categorical data analysis, and 3) Thematic map making. Based on the evaluation results, this training was very useful for the researcher of the Banjarmasin KAKIKOTA Foundation and is expected to carry out further training in 2023. Keywords: Statistical Training; NGO; Banjarmasin KAKIKOTA Foundation; Research
Product Development and Marketing Quality Improvement Training for Craftswomen of Purun Woven: Pelatihan Pengembangan Produk dan Peningkatan Kualitas Pemasaran bagi Pengrajin Anyaman Purun Dewi Sri Susanti; Selvi Annisa; Yeni Rahkmawati; Muhammad Fauzan Adzim; Angelina Ivanna Genardi; Viona Oktaviani
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 3 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i3.17063

Abstract

One of the villages in Banjarbaru has a unique handicraft product because it is made from Purun plants, a type of shrub that grows wild in swamp areas. The products made by the community around Palam Village are bags and accessories woven from Purun rat plant materials. So far, the handicraft is enough to provide additional income for housewives but has not provided optimal results because it has yet to implement a digital marketing strategy. The bag products produced are also relatively simple and have yet to be modified to gain more value in sales. This community service project aimed to train housewives in product development so they could produce Purun bag items more skillfully. Furthermore, instruction was provided on creating poster designs using the Canva software as a digital marketing tool. During the training, the artisans had the chance to try creating Purun bags by hand and creating advertising posters using their phones. The end training outcomes demonstrated that the artisans could incorporate the instruction into their creations. The assessment form revealed that the artisans were highly motivated to participate in the training and expressed hopes that conducting more of this kind of instruction in the future would be possible.
Resampling Techniques in Rainfall Classification of Banjarbaru using Decision Tree Method Selvi Annisa; Yeni Rahkmawati
TIERS Information Technology Journal Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i2.5069

Abstract

Continuous heavy rains, such as in 2021, can cause flood emergencies in various areas of Banjarbaru. Therefore, classification modeling is needed to predict rainfall classes based on climate parameters. The problem faced in the classification case is the unbalanced class distribution. Class imbalance occurs when the minority class is much smaller than the majority class. This research aims to compare three resampling techniques in handling imbalanced rainfall data in Banjarbaru using the Decision Tree model. The comparison methods used were sensitivity, specificity, and G-Mean values. In this research, the method used is a decision tree model with Random undersampling, Random Oversampling, and SMOTE. The result shows that the best model is the Decision tree model with the Random Undersampling technique because it provides the highest G-Mean value and sensitivity and specificity values above 70%. Based on this model, the variables that can separate the Rainy and Cloudy classes are Minimum temperature, Maximum temperature, and Sunshine duration, with the best separator being Maximum Temperature.
Clustering Time Series Using Dynamic Time Warping Distance in Provinces in Indonesia Based on Rice Prices Yeni Rahkmawati; Selvi Annisa
TIERS Information Technology Journal Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i2.5081

Abstract

Rice is a food commodity that is a basic need for Indonesian people. Since the end of 2022, average rice prices in Indonesia have been increasing, breaking the record for the highest price from August to October 2023. The price of rice in each province in Indonesia is different. This can happen because rice center provinces will distribute their rice production to other regions to meet rice needs. The grouping of provinces in Indonesia based on rice prices over time is an interesting thing to research. The analysis method used to group similar objects into groups for time series data is called clustering time series. The distance that can be used to measure the closeness of two-time series is the Dynamic Time Warping (DTW) distance. The clustering analysis used is the single, complete, average, Ward, and median linkage method. The results of the analysis show that time series clustering in provinces in Indonesia based on rice prices is best using median linkage hierarchical clustering. The median linkage method has a cophenetic correlation coefficient value of 0.899064, meaning that clustering using the DTW distance with the median difference is very good. The resulting clusters contained 3 clusters which had different characteristics between the clusters. There are 2 clusters that can be of concern to the government, because there are clusters that have rice prices that have always been high in the last period and there are provincial clusters that have rice prices that are very diverse or can be said to be unstable.
Co-Authors Angelina Ivanna Genardi Dewi Anggraini Dewi Sri Susanti Fuad Muhajirin Farid Muhammad Fauzan Adzim Novia Nour Halisa Nur Salam Viona Oktaviani Yeni Rahkmawati Yeni Rahkmawati Yuana Sukmawaty